Aniform Prepreg Forming

arXiv:2112.11591v1 [cond-mat.mtrl-sci] 22 Dec 2021 Effects of Out Time on the Mechanical and Fracture Properties of Chopped Fiber Composites Made From Repurposed Aerospace

Prepreg Scrap And Waste

Troy Nakagawaa, Seunghyun Koa, Cory Slaughtera, Talal Abdullahb, Guy Houserc, Marco

Washington 98195-2400, Usa

cComposite Recycling Technology Center, 2220 W 18th St, Port Angeles, Washington 98363-1521, USA

Abstract

In this study, the effects of prepreg out time on the mechanical and fracture properties of Discontinuous Fiber Composites (DFCs) are investigated. Carbon fiber prepregs are aged at 0×, 1×, 2×, and 3× the out life in an environmental chamber at constant temperature and humidity. Degree of cure is measured via Differential Scanning Calorimetry (DSC) while tension, compression, and shear tests are performed to investigate the effects that aging has on these mechanical properties. For the first time, Mode I intra-laminar fracture and its size effect are also investigated by means of fracture tests on geometrically-scaled Single Edge Notch Tension (SENT) specimens.

From the tension, compression, and shear experiments it is seen that the out time has no effect on the elastic moduli. However, the strength increases with increasing age of the specimens for all the loading conditions. The percent increase compared to the non-aged material ranges from 15% to 33%. This is likely caused by plasticization of the matrix with age, allowing for higher energy absorption.

More complex trends are reported for the SENT specimens for all the sizes. It is found that the fracture energy and characteristic length initially decrease with age, and then finally increase for the longest out time. This trend is owed to two factors with countering effects on the fracture behavior: 1) the increase of the average number of platelets with increasing aging due to increase in resin viscosity, and 2) the plasticization of the matrix with aging.

The results from this study suggest that Discontinuous Fiber Composites (DFCs) made from reused materials can have equal, if not better, performance than non-aged DFCs. The experimental data presented in this work can be used as a baseline to design DFC composite components made from repurposed prepreg scrap and waste.

Aging, Strand, Recycling, Fracture

Preprint submitted to Sustainable Materials and Technologies

Ntroduction

The use of polymer composites in the aerospace, automotive, and energy sectors has seen a tremendous increase in the last few decades . To give an idea, the U.S. composite end products market was valued at $26.7 billion in 2019 and is forecast to grow to $33.4 billion by 2025 [4, 5]. Similar trends are reported worldwide.

While these numbers give an idea of the key role that composites are playing in the global economic growth, they also show that sustainability is becoming an increasingly important issue considering that hard-to-recycle thermosetting composites represented 82% of the U.S.

composite market in 2019 [4, 5]. Fostering sustainable practices and finding ways to reuse and recycle thermoset composite prepreg waste is imperative to mitigate the environmental impact of this industry and enable the expected growth of the market across the wind, aerospace, automotive, and construction industries.

Following , thermoset composite prepreg waste can be broadly classified into uncrosslinked waste produced during manufacturing and crosslinked waste from components reaching end of life. Efforts to handle the former material stream can be defined as “reuse” while efforts to handle the latter are commonly defined as “recycle”. The overarching goal of recycling is to reclaim fibers from cured waste by getting rid of the matrix. Through the years, several interesting techniques for recycling have been developed including pyrolisis (see e.g. ), matrix digestion (see e.g.

), and depolymerization (see e.g. ).

Typically, Depending On The Technique,

reclaimed fibers can have comparable mechanical properties to virgin fibers. However, this is often achieved at the expenses of fiber continuity. In fact, reclaimed fibers often take the form of tangled, discontinuous arrays which undermines the manufacturing of high-quality composite laminates requiring long, continuous fibers to achieve high mechanical performance .

Different from recycling, reusing aims at repurposing both the fibers and the uncured matrix in their original configuration to manufacture new composite parts . In this case, the material sources include e.g.

ply cutter waste, end-of-roll material, and out-of-spec material beyond out-life or storage life. For instance, the aerospace industry follows very strict requirements on material certification and the costs of re-certifying an out-of-spec material would be prohibitive, leading to significant amounts of prepreg waste.

Except For Few Cases In Which Out-Of-Spec

material is used internally for R&D or donated to research institutions, most prepreg scrap and waste ends in landfills, posing an environmental challenge. It is clear that this situation will not be sustainable with the future growth of the composite market unless prepreg waste reuse becomes common practice.

Developing technologies for the reuse of prepreg scrap and waste is one of the core mis- sions of the Composite Recycling Technology Center (CRTC) located in Port Angeles, WA, USA. Since its establishment the CRTC has developed unique products made from repurposed aerospace carbon fiber prepreg with applications ranging from the sport goods industry to con- struction and even defense. Figure 1a, for instance, shows a corrosion-resistant bench made using a combination of reused scrap roll form and Discontinuous Fiber Composites (DFCs). Figure 1b shows SwiftnetTM a lightweight, portable pickle-ball net while Figure 1c shows a novel Ad- vanced Cross Laminated Timber Panel (ACLT) featuring natural wood and 85% in weight of repurposed aerospace carbon fibers.

Among the several technologies utilized by the CRTC, using prepreg scrap and waste to manufacture discontinuous fiber composites (also known as chopped fiber composites) is one that has shown great promise. As Figures 2a-c show, Discontinuous Fiber Composites (DFCs) are made by cutting rectangular platelets from scrap prepregs. The size and aspect ratio of the platelets depend on the particular part to manufacture but platelet widths range from hundreds to few millimetre. The platelets can then be used to fill a mold and can be compression molded to make very complex shape parts.

Figures 2b,c show an example of a ball joint made by CRTC using repurposed prepreg. It is worth noting that, thanks to the unique characteristics of DFCs, even a complex part such as the one shown in the figure can be manufactured without additional machining. This characteristic alone might enable DFCs made from reused prepregs to reach markets that are not easily accessible by advanced unidirectional composites due to the manufacturing costs.

DFC parts made from virgin prepregs have already been shown to have outstanding me- chanical properties, comparable to aluminum and quasi-isotropic carbon fiber laminates [14, 15]. However, it is possible that some of the properties of DFCs made from reused materials might be degraded by the aging of the prepregs. Hence, considering how difficult it would be to control the ageing of this material stream, the question to answer is: how much does ageing affect the mechanical performance of DFCs made from repurposed prepregs? Answering this question is the goal of the present study which presents one of the most comprehensive investigations into the effects of aging on the tensile, compression, and shear strength, and global mode I fracture energy of DFCs made from reused material. Understanding the link between aging and mechan- ical performance is quintessential to formulate design guidelines which can pave the way for the use of DFCs made from repurposed prepregs also in secondary structural applications.

Fc Manufacturing Procedure

In this study, Toray T700G-12k/2510 prepreg was aged and used to manufacture DFC lam- inates. To follow the standard conditioning atmosphere stated in ASTM D4332 , an in- house environmental chamber was made to keep the temperature and humidity at 23 ± 2◦C and 50±5%RH respectively. An indoor grow tent was used to isolate the prepreg, and an off-the-shelf temperature and humidity controller was used to control a system composed of an Air Condi- tioner (AC), heater, humidifier, and dehumidifier. The prepreg was aged to 0×, 1×, 2×, and 3× the out life of the prepreg (0, 28, 56, and 84 days). The manufacturing method detailed by Ko et al. [14, 17] was used to make the DFC laminates. Platelets were cut using a fabric cutter to the desired size of 50 × 8 mm. The weight was controlled to attain the desired thickness of 3.3 mm. In addition to the DFC specimens, a quasi-isotropic laminate using [45/90/ −45/0]3s was made using non-aged material to serve as an additional benchmark to evaluate the performance of the aged DFCs.

Analysis Of Crosslinking Degree

To quantify the progression of cure while the prepreg ages, Differential Scanning Calorimetry (DSC) was used to obtain the enthalpy of the prepreg. These tests were done following ASTM D3418 using a Mettler Toledo DSC 3+. For the first week of aging DSC tests were performed daily. After the first week, DSC was performed once a week for 28 days (which corresponds to one out life). Then, DSC was performed every other week until 3× the out life was reached after which DSC testing was not performed until 7× out life. After this, DSC was performed at 9× the out life and at every n× out-lives until 16× out-lives (448 days) was reached. This time is longer than any previous study found by the authors in the open literature.

For each DSC analysis, four samples of 10 mg were tested in aluminum pans. A ramp rate of 10◦C/min was used to sweep from 23 to 280◦C. Nitrogen was used as the purge gas and had a flow rate of 10 mL/min. To calculate the enthalpy, a MATLAB code was developed to calculate the area under the specific heat flow vs time curve. During the later parts of the tests,

Glass Transition Temperature (T◦

g) could also be calculated from these scans. To calculate the

T◦

g Mettler Toledo’s STARe software was used which follows ASTM E1356 .

Esostructure

An investigation into the mesostructure of aged DFCs was also performed. To this end, small sections of 25 mm were cut from the laminates. For out times 0× and 2×, 6 specimens were investigated, for out time 1×, 5 specimens were investigated, and for out time 3×, 4 specimens were investigated. The samples were encased into epoxy pucks made using Allied High Tech’s QuickCure Acrylic to be used in a Struers RotoPol 21 and a RotoFoce 3 auto-polisher. Once polished, an Olympus BX50 microscope was used to inspect the mesostructure. A magnification of 5× was used to find the constituent content, thickness of platelets, and the number of platelets through the thickness. Stitching of the images was done using ImageJ which was also used to find the constituent content.

To find the number of platelets though the thickness and the thickness of the platelets, 7 evenly spaced sections within the 25 mm length were investigated. The first and last sections were 1 mm away from the ends of the specimen. A MATLAB code was developed to find the thickness of platelets, and the number of platelets through the thickness .

Ata Acquisition

Tests were performed using an Instron 5585H 250 kN electro-mechanical load frame with an Interface 1210ACK-50kN-B load cell, and with the 250kN Instron load cell for the largest size tested for the size effect testing. The load cells recorded with a sampling frequency of 10 Hz while Digital Image Correlation (DIC) was used to obtain the strain values needed. Images were captured using a Nikon D5600 DSLR camera with Nikon AF micro 200 mm and Sigma 135 mm DG HSM lenses with a sampling rate of 1 Hz. GOM Correlate was used to process the photos and obtain the strain values. The number of specimens tested for each loading case can be found in Tables 2-5.

Tension

Tensile data for the quasi-isotropic and non-aged DFCs made from the same material system tested in this work was taken from tests performed by Ko et al. . For the aged samples, tensile tests were performed based on ASTM D3039 . Specimens were made to have a width of 25.5 mm, which corresponds to about three times the width of a platelet, and a gauge length of 140 mm. The tabs were made with 1/8 in. thick garolite and JB-Weld Cold Weld Steel Reinforced Epoxy and had a length of 55 mm with a bevel of 8◦. A displacement rate of 2 mm/min was maintained for all the tests.

Ompression

Compression tests were performed following ASTM D3410 . The samples were made to were performed using the Instron load frame and a Wyoming Modified IITRI Compression test fixture. A displacement rate of 1.5 mm/min was used.

Shear

Shear tests were performed according to ASTM D5379 . An Omax 2652 water jet cutter was used to cut the specimens to the required geometry. Specimens were tabbed using 1/8 in thick garolite and Solvay FM 94k adhesive film. During the tests, the specimens were clamped in the tab area to prevent crushing and twisting and tested using the Instron load frame and a Wyoming Iosipescu test fixture. A displacement rate of 1 mm/min was used. A study was performed on the quasi-isotropic shear specimen to find the optimum width to average the shear strain obtained from DIC. This width was found to be 1 mm.

Size Effect Tests

For the aged coupons, the experimental procedures used in this study followed . This source also provided size effect test data for quasi-isotropic and non-aged DFCs. The smallest size effect specimen had a base dimension of 20 × 44.5 mm (D × Lg) and a target thickness of 3.3 mm. The gauge areas of the specimens were geometrically scaled following a 2D scaling of 1 : 2 : 4. Tabs were made with 1/8 in. thick garolite and JB-Weld Cold Weld Steel Reinforced Epoxy with a length of 38 mm for all specimens. To create the notch, a diamond-coated razor blade saw was used. The blade thickness was 0.2 mm. The initial notch length, a◦, was kept at a constant ratio of D/5. A constant strain rate of 0.2%/min was used for all specimens.

Rosslinking Evolution With Aging

In fig. 3, two representative heat flow curves from DSC testing are shown. The red stars on the plot indicate the bounds used to calculate the enthalpy of the prepreg. Here, the bounds were selected manually by finding the transition points of the exothermic cure peak. It can be seen in fig. 3b that the first bound can be hard to determine due to the bump in the heat flow caused by the glass transition temperature. A good way to determine the location of the first bounds is by looking at previous out times where the glass transition temperature does not appear on the curve, as well as interpolating from the straight parts of the curve at the beginning and end of the curve.

In fig. 4a and b, the results from the enthalpy calculations are shown from which it can be seen that the variation in enthalpy found was very small. On average, the variation in enthalpy at one out time was 3.38%. There were two outliers where the variation were large. These were day 0 (0× out life) and day 392 (14× out life) with a variation of 10.62% and 7.07% respectively.

If the outliers are taken out, the average variation drops to 2.86%. This low variability validates the low sample count used in this study. It can be seen in fig. 4b, that at the beginning there is an increase in enthalpy from day 0 to day 4. This is because the initial samples were taken from the edge of the prepreg roll and each day was a little closer to the center of the roll. Starting from day 4 the samples for DSC analysis were taken from the center of the roll. For this reason, when calculating the percent decrease of enthalpy in fig. 5 and when performing the linear fit, the initial enthalpy is taken to be the one calculated on day 4.

The data in fig. 4 and 5 were fit using the following equation:

(1)

where A is the horizontal asymptote, the initial slope is −AB/H, and the y-intercept is A(1+B). At the early stages of aging the decrease in enthalpy is approximately linear. Then the enthalpy starts to asymptotically approach a value of 84 J/g, indicating a saturation of crosslinking. It can be seen in the figures, that more crosslinking can occur, but the time required to complete the curing would be extremely large. The final enthalpy measured has about a 7% difference from the asymptote, and to get to a difference of 1%, an additional 358 days of aging is needed.

This would correspond to the percent enthalpy decrease to go from 49.4% to 52.6%. At this point the evolution of crosslinking is marginal. A similar saturation can also be seen in the glass transition temperature (Tg) in fig. 6. From 10× the out life (280 days) the Tg can be seen in the heat flow curves. The Tg appears to be saturating at about 63◦C. This shows that if the prepreg is left out past this time there should be no further progression of ambient curing. It should be noted that the exact degree of cure cannot be obtained because of the unknown initial enthalpy or degree of cure of the epoxy. Thus the percent decrease stated here is related to a progression of cure since the “as purchased” state rather than the degree of cure of the prepreg.

Esostructure

Figure 7 shows the laminate thickness measured from all the tested specimens. It can be seen that there was an increase in the specimen thickness with out time. The increase from the non-aged to the aged specimen was between 23% and 33% while there was much less change in thickness between the aged specimens.

To understand the thickness increase, microscope images were taken and analysed to observe any changes in the mesostructure. With reference to Figure 8 and table 1, it can be noted that the number of platelets through the thickness increased with the out time. This can be explained by looking at the thickness of the platelets reported in Figure 9 and table 1. In fact, it can be noted that the platelets in the DFC specimens are slightly thinner than those of the plies in the quasi-isotropic laminate. However, the platelet thickness does not change with the increase in out time. Figure 10 shows the probability density of the platelet thicknesses constructed leveraging 800 −1160 platelet observations for each out time. As can be noted, there are only slight changes in the peaks of the probability distributions with a change in out time, confirming that the mesostructure does not change significantly with increasing out time.

Figure 11 shows areas where the platelet thickness is significantly different from the average value due to defects. Fig. 11a, for instance, shows fibers rearranging around a void causing an increase in thickness of the platelet. On the other hand, fig. 11b shows an area where there are fewer platelets compared to the average number of platelets and the remaining volume must be filled with resin or voids. Due to the resin filling the volume where there are no platelets, the thickness of the platelet that is in the volume increases.

Figure 12 and table 1 provide information on the fiber and void area fractions. It can be seen from fig. 12a, that the fiber area fraction does not change with age, and that the fiber area fractions of the DFC specimens are equal to those of the quasi-isotropic laminate. Moreover, fig.

12b, shows that the non-aged DFCs have a void area fraction similar to that of the quasi-isotropic layup, and that the void area fraction of DFCs increases with age. In fact, the quasi-isotropic and non-aged DFCs have a void volume fraction of 0.29% and 0.24% respectively while all the aged DFCs have a void area fraction of about 1%.

The void volume fraction does not change between out times, and the maximum and min- imum void content also do not change between the aged DFCs. The minimum void content observed was 0.13%, 0.16%, and 0.11% for out times 1×, 2×, and 3× respectively while the max- imum void content observed was 2.98%, 3.12%, and 2.63%. The variation of the aged specimens is much higher than the quasi-isotropic and non-aged specimens.

Tension

Figure 13 shows examples of fracture surfaces of tensile coupons of out times 1×, 2×, and 3×. Similar to non-aged specimens seen in previous papers , the failure path can be seen to go around platelets or within a platelet. Fiber breakage still occurs, however its frequency is much lower in comparison to delamination and matrix damage since the failure attempts to take the path of least resistance thus avoiding fiber breakage. There was no perceivable difference in failure mechanisms between out times.

Figure 14 shows the stress vs strain curves for out time 1×, 2×, and 3× DFC specimens. It can be seen that the behavior was linear up to the peak and that there was progressive damage for all the specimens. For the lowest modulus specimens shown in fig. 14c, it can be seen that at about 50% the ultimate strength there was damage, however the specimen was still able to carry load. This is a property of DFCs: where there is an area with less favorable fiber orientation there will be damage, however the areas with favorable orientation can carry more load.

Figure 15 and table 2 provide information on the tensile modulus and strength for the quasi-isotropic and DFC specimens. It can be seen in fig.

A That The Modulus Does Not

change significantly with age and there is little difference when compared to the quasi-isotropic value. The modulus for the DFC specimens remains at 92 −97% that of the quasi-isotropic modulus. The largest difference in modulus occurs at out time 2×, which is 91.6% that of the quasi-isotropic modulus. However, this modulus still falls within one standard deviation of the non-aged DFC specimens.

In fig. 15b, it can be seen that the strength of the DFC specimens can be from 39% to 52% that of the quasi-isotropic laminate. It is interesting to note that there is an increase in tensile strength of the DFC specimens when the prepreg is aged. After aging for one out time, the aged DFCs exhibit a strength 28% higher than the non-aged sample. After the initial increase, little change in strength can be noted past for longer aging times.

Ompression

Figure 16 shows examples of fracture surfaces of quasi-isotropic, and DFC compression spec- imens for out times 0×, 1×, 2×, and 3×. It can be seen that the failure of DFC specimens is much less brittle when compared to the quasi-isotropic specimens. There is still fiber failure at the outer surfaces of the DFC specimen at various out times, however most of the damage is through the thickness. In fact, similar to the tension specimens, the majority of the damage is from the matrix and platelet debonding. There was no perceivable difference in failure mecha- nisms between out times and it is worth mentioning that similar failure for non-aged compression specimens were seen in previous papers [25, 26, 28].

Figure 17 shows the stress vs strain curves for quasi-isotropic, and out time 0×, 1×, 2×, and 3× DFC specimens. It can be seen that when the nominal stress was at about 200 MPa, that there could be unloading, this is caused by the fact that the compression fixture grips are wedges and must readjust at this point. It can be seen from the curves that the compression specimens exhibit varying degrees of non-linearity. The out time 0× specimen exhibited the most non-linear behavior and as the out time increased the non-linear behavior decreased.

Figure 18 and table 3 provide the compression modulus and strength for the quasi-isotropic and DFC specimens. It can be seen in fig. 18a that the modulus does not change significantly with age. There is also little difference in the modulus when compared to the quasi-isotropic value, but there is more of a difference between the DFC and quasi-isotropic modulus than what was seen with the tensile modulus. The modulus for the DFC specimens remain at 83−92% that of the quasi-isotropic modulus with the largest difference in modulus occurring at out time 2×, which is 82.9% that of the quasi-isotropic modulus. In any case, this modulus still falls within one standard deviation of the non-aged DFC specimens confirming a minor effect of aging on the elastic behavior of DFCs.

In fig. 18b, it can be seen that the strength of the DFC specimens is from 42% to 58% that of the quasi-isotropic laminate. It can also be seen that, there is an increase in compressive strength of the DFC specimens when the prepreg is aged with a difference as high as a 33% between aged and non-aged DFCs. This is similar to what is seen for the tension specimen.

Shear

Figure 19 shows examples of fracture surfaces of quasi-isotropic, and DFC shear specimens for out times 0×, 1×, 2×, and 3×. It can be noted that the quasi-isotropic samples had fiber breakage at the surface 45◦ply. However, initiation of failure occurred at the notch and propagated along the fibers. For DFC specimens, the majority of the failure occurred at the platelet boundaries, similar to the tension and compression specimens. There was no perceivable difference in failure mechanisms between out times and it is worth mentioning that similar failures of non-aged shear specimen were reported previously by Selezneva et al. .

For the calculation of the shear strains during the tests, a thorough investigation was per- formed to identify the area of analysis providing the most consistent and accurate results. Figures 20a,b show the effect of the size of the area used for the calculation of the shear modulus. It can be seen in fig. 20a that the shear modulus does not change much when the box width is less than 1 mm. But, after this point the modulus starts to increase rapidly. At 1 mm, the percent increase of the shear modulus calculated is only 0.68%. The increase after 1 mm is from the fact that only the center of the specimen is in pure shear. When looking at a DFC specimen, fig. 20b, a similar trend can be seen. At 1 mm the percent increase in modulus is only 0.87%. Even though the area of pure shear will be the same for the DFC and quasi-isotropic specimen, the modulus change within that width will look different for DFC specimens, since DFCs’ mesostructure is inhomogeneous. This is confirmed by the fact that the shear modulus increase within the 1 mm box is different when compared to the quasi-isotropic layup. Another observation showing the inhomogeneous mesostructure of DFCs’ is that, when the box width is between about 4 −5 mm, the modulus decreases which does not happen for the quasi-isotropic specimen. From the quasi-isotropic layup the shear strain does not change within the 1 mm area at the center, thus it can be assumed that this area is in pure shear and is a good area to average shear strain over for all the specimens. This size was used for the analysis of all the shear specimens investigated in this work.

Figure 21 shows the stress vs strain curves for quasi-isotropic, and DFC samples made from aged prepregs with out time 0×, 1×, 2×, and 3×. The post peak behavior is not captured here because after the peak is reached, the DIC becomes too distorted to give accurate results.

However it should be noted that most of the specimens exhibited progressive damage and did not fail when the ultimate strength was reached. This is because when one ply or platelet fails there are still others that are able to carry load. There were many specimens that were linear up to the peak, however for the quasi-isotropic specimen and all the DFC specimens, there were 3 out of 12 that exhibited non-linearity prior to the peak. The nonlinear behavior can be ascribed to sub-critical damage dissipating energy before reaching the ultimate load.

Figure 22 and table 4 show the shear modulus and strength for the quasi-isotropic and aged DFC specimens. As for the case of tension and compression, fig. 22a shows that also the shear modulus does not change significantly with age. There is also little difference in the modulus when compared to the quasi-isotropic value, but the difference between the DFC and quasi- isotropic modulus is larger than what was seen with the tensile modulus. The modulus for the DFC specimens remains at 81 −89% that of the quasi-isotropic modulus. The largest difference in modulus occurs at out time 3×, which is 81.06% that of the quasi-isotropic modulus although this modulus still falls within one standard deviation of the non-aged DFC specimens.

In fig. 22b, it can be seen that the strength of the DFC specimens is 66 −89% that of the quasi-isotropic laminate. This is higher than that of the tension and compressive strengths. In fact, for tension and compression the strength on non-aged DFC was about 40% that of the quasi-isotropic specimen, but it is 66% for shear. However the increase in strength of the aged specimens compared to the non-aged ones is similar to the one reported for the tension and compression specimens. There was as high as a 30% difference for the non-aged to aged DFC specimen. Similar to the tension and compression tests there was little change in strength past out time 1×.

Size Effect Tests

Figures 23a-c show the three types of fracture surfaces of SENT Discontinuous Fiber Com- posite specimens. Figure 23a shows a fracture that occurred at the notch. Similar to three mechanical tests, matrix damage and debonding were much more common than fiber breakage.

Figure 23b shows a fracture that happened at the notch, but not at the tip. This type of failure occurred in two specimens, one in out time 1×, size 3, and one in out time 2×, size 2. There was initial damage at the notch tip, however due to the size of the fracture process zone (FPZ), damage happened to platelets not directly touching the notch tip. Thus when the platelet failed, the fracture path was not connected to the notch tip.

Figure 23c shows fracture that occurred away from the notch. It can be seen that there was damage at the notch before ultimate failure, however the ultimate failure occurred away from the notch. It was seen for out time 1×, 1 out of 8 specimen failed away from the notch, and for out time 2× and 3×, 2 out of 8 specimens failed away from the notch. For the two larger sizes all the specimen failed at the notch. The specimens that failed away from the notch or at the notch but not at the tip, showed no difference in nominal strength when compared to specimen that failed at the notch. Previous studies [14, 15, 17, 30, 31] have seen similar fracture behaviors presented here in non-aged DFCs.

Figure 24 shows the load vs displacement curves for out time 1×, 2×, and 3× DFC specimens. The displacements used for the load vs displacement curves were found using DIC. The nominal displacement was calculated by averaging the relative displacement between two horizontal lines spanning the width of the specimen. The distance between the lines and the notch was taken to be 1.2D. This was done to remove the effects of the compliance of the machine. The stiffness of each specimen was seen to be relatively the same. Most of the specimens had a linear behavior up to the peak, however, some specimens in out time 3× size 3 exhibited minor non-linearity.

This nonlinear behavior comes from damage in the FPZ. Following e.g. [14, 15, 32], the nominal strengths of the specimens were defined as σNc = Pc/tD, where Pc is the peak load found during tests, t is the specimen thickness, and D is the specimen width. Figure 25 and table 5 report the nominal strength for the DFC and quasi- isotropic specimens. It can be seen that there was an increase in strength with aging, similar to the mechanical tests. In this case, the aged DFC specimens have a nominal strength similar to that of the quasi-isotropic specimens. At the same time a size effect can be seen where the strength of the SENT specimen increases with a decrease in specimen width.

Size Effect Analysis

In this study, Type 2 size effect of aged DFCs is investigated. This is quintessential to obtain an accurate estimation of the fracture energy of the material, which is an important measure of the capability of the material of resisting crack propagation by dissipating energy.

Type 2 size effect deals with structures featuring a stress-free crack or notch [33, 34]. Due to the complex mesostructure of DFCs, significant stress redistribution occurs during the damage process [14, 15]. This redistribution is characterized by a nonlinear Fracture Process Zone (FPZ) whose size is proportional to the size of the largest inhomogeneity of the material. For increasing structure sizes, the percentage of the structure subject to the stress redistribution occurring in the FPZ gets smaller and smaller, leading to significant size effects. Typically, large quasibrittle structures experience limited stress redistribution prior to failure and they behave in a rather brittle manner. In contrast, small structures compared to the characteristic size of the FPZ incur significant nonlinear stress redistribution which reduce the severity of the notch and generally lead to a more quasiductile behavior. These size effects have been confirmed for a number of quasibrittle materials including e.g. fiber and 2D/3D textile composites [32, 35–37], polymers , nanocomposites [39, 40], concrete [41, 42], metals , and many other materials .

Equivalent fracture mechanics, which was pioneered by Irwin and extended to quasibrit- tle materials , can be used to account for these effects provided that the FPZ is still not too large compared to the structure size. Towards this goal, an additional effective FPZ length, cf, is added to the original crack length, a0. The additional length is added such that the resultant stress of the effective crack equals the ones related to the cohesive stresses in the FPZ.

The effective FPZ size, cf, depends on how the elastic energy in the FPZ is being dissipated. In DFCs, some mechanisms for energy dissipation are fiber fracture, platelet pullout, platelet delamination, and matrix microcracking [14, 15]. These mechanisms are all influenced by the platelet geometry, orientation, and the number of platelets through the thickness. Thus, the mesostructure must be properly accounted for to capture the fracture behavior and the effects of the nonlinear FPZ.

If the mesostructure and quasibrittle softening laws are calibrated properly, the progressive damage in a structure can be modeled explicitly and the cf can be predicted. However, with so means the progressive damage does not need to be modeled explicitly, but the effects of the mesostructure still needs to be captured. Through finite element modeling, the effects of the mesostructure on the elastic strain energy can be captured. By combining the size effect experiments and finite element modeling the fracture behavior of DFCs can be characterized.

The following sections provide an explanation of the analytical and computational framework used.

Size Effect Law (Sel)

As stated previously, to account for the nonlinear Fracture Process Zone (FPZ), an equivalent

(2)

where a0 is the original crack length, and cf is the effective FPZ length, which is treated as a material property. From Linear Elastic Fracture Mechanics (LEFM), the energy release rate as a function of

(3)

with α = a/D being the dimensionless crack length, σN = P/(tD) being the nominal stress, E∗ being the effective elastic tensile modulus, and g(α) being the dimensionless energy release rate. The dimensionless energy release rate accounts for the effects of geometry on the energy release rate. For structures that are homogeneous, g depends only on the geometry of the structure and is constant for geometrically-scaled specimens. However, DFC inhomogeneities, which depend on the platelet’s geometry and are not geometrically scaled, can be comparable with the size of the structures. Thus different structure sizes may lead to significantly different energy release rates potentially making g dependent on the structure size, D, and the thickness, t. We can write eq. 3 to account for the inhomogeneity of DFCs as follows:

(4)

where g is now considered a function of both the dimensionless crack length and the characteristic length of the structure. At the onset of fracture, the energy release rate, G, must be equal to the fracture energy, Gf, assumed to be a material property. By substituting eq. 2 into eq. 3, Gf can be expressed

(5)

Performing a Taylor expansion around α0 for a constant D we get:

(6)

By rearranging eq. 6, Baˇzant’s Size Effect Law (SEL) is obtained :

Where, G′

D = [∂g/∂α]D. Here, the subscript D denotes that the partial differentiation is taken for a constant structure size. It should be noted that, in contrast to the traditional SEL , the dimensionless energy release rate in eq. 7 is a function of the structure size and can be calculated via stochastic finite element analysis. Unlike LEFM, eq. 7 depends both on the structure size and the material characteristic length. This is needed to capture the transition of the fracture behavior from quasi-ductile to brittle. It is worth noting that Eq. 7 can also be written as

(Α0, D)/G(Α0, D) Are The Size Effect Constants

depending on the structure geometry and FPZ size. As discussed in following (Section 4.4.2), extensive computational studies were performed to investigate the dependence of the dimensionless energy release rate on the structure size D. It was found that, for the particular DFC systems investigated in this work the structure size, D, has no significant effect on the dimensionless energy release functions. This result agrees with previous work done by Ko et al. [14, 15, 17] which showed that, when the average number of platelets through the thickness of the structure is sufficiently large, the mesostructure becomes statistically homogeneous and the energy release rate has no dependence on structure size.

Therefore, the dimensionless energy release rates were considered to be size independent in this

Work And The Average G And G′

D values of all specimen sizes for a given out time were used in eq. 7. However, it should be noted that for another platelet geometry or specimen thickness, g and

G′

D may become dependent on the structure size and the dimensionless functions calculated for each size should be used instead of the averaged values.

Fitting Of The Experimental Data Using Sel

To obtain the size effect constants from experiments, linear regression analysis was performed as shown in fig. 9. In fact, Eq. 8 can be written in a linear form [33, 45]:

(10)

As can be noted from fig. 26 and eq. 10, the size effect constants are obtained from the slope and the y-intercept providing the input for the construction of the size effect curves using eq. 8.

Figure 27 shows the normalized size effect curves found using eq. 8 and 10. Here, the log of the nominal stress normalized to the size effect constant σ0 is plotted against the log of the structural width D normalized to the size effect constant D0. As can be noted, all out times exhibit a deviation from LEFM. It can be seen that the specimens tested are in the transition between the horizontal asymptote, which dictates stress driven failure, and the asymptote with a slope of −1/2, where failure is fully energy driven and LEFM is valid. This can be attributed to the size of the Fracture Process Zone (FPZ) compared to the structure size. When the structure size is sufficiently small, the FPZ impacts the structural behavior and causes deviation from LEFM. As the structure size increases, the FPZ has less impact on the structural behavior and size effect can be captured using LEFM. It is interesting to note that out time 1× and 2× are closer to the LEFM region and are comparable to the quasi-isotropic specimen. Then once out time 3× is reached, the specimen becomes comparable to out time 0× and becomes more quasi-ductile.

Brittleness Number

To compare the structural behavior of aged DFCs, non-aged DFCs, and traditional com- posites, a non-dimensional parameter called the brittleness number, β, can be used . This number compares the brittleness of structures with similar geometry and size and is defined as the ratio between the characteristic size of the structure, D, and the size effect constant D0.

When β is greater than 10, then the behavior is brittle and LEFM is suitable to capture the fracture behavior. When β is less than 0.1, the behavior is quasi-ductile or perfectly plastic and a strength based failure criteria can predict the behavior. If β is between these two points, the structure is quasi-brittle. Figure 28 shows β for a quasi-isotropic laminate and DFC laminates at the various out times (the quasi-isotropic and non-aged DFC data is taken from Ko et al.

). It can be seen that as aging increases the brittleness of DFCs increase up to a certain point. Once this point is met, the brittleness decreases and becomes comparable to the non-aged DFC. It can be seen that for out time 2×, β is larger than the quasi-isotropic specimen, and for the largest size tested, the brittleness number leaves the quasi-brittle zone. This change in brittleness will change the damage tolerance of DFC material.

Stochastic Finite Element Model

In order to obtain the fracture energy, Gf, and the FPZ length, cf, the dimensionless energy

(Α0, D), Must Be Found. These Values Are Highly

dependent on the platelet constitutive properties and the random distribution of the platelets. To capture this, a stochastic finite element model is used.

Esostructure Generation

The mesostructure generation used in this work is an extension of the stochastic laminate analogy method proposed in . A brief summary of the generation algorithm is provided here, and more details on the algorithm and its implementation can be found in [14, 15, 50, 51].

In this study platelets are partitioned into grids of 1 × 1 mm. The platelet generation algorithm can be divided into two parts. The first is a platelet distri- bution algorithm and the second is a thickness adjustment algorithm. In this study, the platelets are assumed to be perfectly randomly distributed and planar. This means that a uniform prob- ability distribution is used for both the spacial component and orientation of the platelet, and the out-of-plane orientation is assumed to be zero. From the mesostructure investigation we have the average number of platelets through the thickness and the CoV of the laminates for the different out times which are used as inputs to the platelet generation algorithm. To achieve these parameters, saturation points and platelet limits are used to guide generation. Saturation points are set to be every three layers. The average number of platelets through the thickness must equal the current saturation point before moving on to the next saturation point. The platelet limits are used to prevent a higher concentration of platelets in certain areas. A higher concentration would lead to the average number of platelets to equal the saturation point, but there would be large areas of little to no platelets. These limits are taken to be the saturation points times the CoV.

Once the average number of platelets generated meets the one found from the mesostructure study, a thickness adjustment is performed. This is done to simulate the effects of resin flow, without modeling it explicitly. If the number of platelets through the thickness is greater than or equal to the average number of platelets found experimentally, then the thickness of the platelet will be evenly distributed to all the platelets. If the number of platelets though the thickness is less than the one found experimentally, then resin will fill the additional thickness needed. This is done to mimic resin flow. For more information about the platelet generation algorithm the reader is referred to previous articles published by the authors [14, 15, 50, 51].

Omputation Of G(Α) And G’(Α)

The mesostructure that is generated from section 4.4.1 is imported into Abaqus/Standard . Each partition in the mesostructure is homogenised into an 8-node, quadrilateral Belytschko- Tsay shell element (S8R). The platelets and resin are assumed to be linear elastic, with properties shown in table 7. At one end a uniform uni-axial displacement is applied and the other end is fixed in all directions. For homogeneous geometrically scaled specimens, g(α) and g′(α) do not change with the structure size . However, this is not generally true for DFCs since they have an inhomogeneous mesostructure. For this reason, 5 −8 specimens for every size and out time are simulated to verify if any size effects on g(α) and g′(α) are present.

Generally, a method to obtain the energy release rate is by using the J-integral [32, 53]. This can not be done with DFCs because of their inhomogeneous mesostructure. To calculate G(α),

(11)

with u being the applied displacement, a being the crack length, b the thickness, and Π being the potential energy of the whole specimen. The subscript u denotes that the potential energy is taken for a constant applied displacement. Figure 29a shows the potential energy of a typical DFC SENT specimen. To approximate G(u, a) the central finite difference method is used to get the partial derivative of the potential energy as a function of the normalized crack length α = a/D. Then, the dimensionless energy release rate, g(α), is found using eq. 3 and g′(α) can be found through linear regression as can be seen in fig. 29.

Figure 30 and table 6 show the dimensionless energy release rate and its derivative at various out times for various sizes. It can be seen that g and g′ do not change significantly with age or with structure size. In fact, the values of g and g′ are about the same as the values for a quasi-isotropic laminate and for the non-aged DFC specimen. Since there is little change with respect to structure size, the average value of g and g′ using results from all sizes are used for the fracture energy and characteristic length calculations. It is worth noting though that the average is not taken across out times since the mesostructure was not consistent through the various out times.

Fracture Energy And Characteristic Length

With g(α0) and g′(α0) obtained from the previous section, the fracture energy Gf and the FPZ length, cf can be calculated. By utilizing eq. 7 and 9 we get that:

(12)

where E∗is the equivalent elastic tensile modulus for the DFC specimen at the specific out time, and A and C are the slope and intercept found from the linear regression analysis. Figure 31 and table 6 show the fracture properties. It can be seen that there is little change in the fracture energy when going from out time 0× to 1×. When increasing the out time to 2× there is a decrease in the fracture energy, and when increasing to 3× the out life, there is a large increase in the fracture energy. The fracture energy of out time 2× becomes close to the fracture energy of a quasi-isotropic layup, but then increases by 1.7× when going to out time 3×. A similar trend found in the fracture energy can be seen for the characteristic length in out times 2× and 3×. In addition to these trends, the characteristic length also decreases when going from out time 0× to out time 1×. The characteristic length of out time 1× and 2× becomes about the same as a quasi-isotropic laminate.

Iscussion

The present study investigated the effect of the age of repurposed prepregs on the mechanical performance of chopped fiber composites.

As Described In The Previous Sections, The Study

included the analysis of the remaining crosslinking degree via Differential Scanning Calorimetry (DSC) for different age times along with the investigation of the mechanical performance of the DFCs in tension, compression, shear, and nominal mode I fracture. To the best of the authors’ knowledge, this investigation on aging covers the most extensive set of properties ever reported for DFCs.

In regard to the DSC results, the initial linear decrease of enthalpy with age reported in this work has been shown in many previous studies . However, the horizontal asymptote for large age times as the one shown in fig. 4 has only been reported in the study done by Blass et al. . One of the two prepreg tested by Blass et al. showed this plateau at 4× the out life, while the other did not reach this plateau even after 12× the out life. Both of these prepregs were aged to 120 days which is less than half the aging times investigated in the present work. Thanks to the extensive duration, probably among the largest ever reported in the literature, the tests performed in this work clearly show a saturation of crosslinking occurring at ambient temperature for sufficient out times. In the context of repurposing the material to make chopped fiber composites, this observation is of utmost importance. In fact, tracking the out time of various material streams might not be practical or even possible. However, the results clearly suggest that while crosslinking occurs continuously during the aging of the material, it would take a significant amount of time to reach a state in which further curing is not possible.

Simple DSC sampling of the repurposed material every e.g. 4 −5 out times might be enough to make sure the material can still be used. Of course, the extensive usability over large aging times makes the use of scrap prepregs from other composite manufacturing processes very attractive and convenient provided that the mechanical properties are not significantly affected by aging.

From the morphological point of view, an increase in Discontinuous Fiber Composite (DFC) plate thickness with increasing age times was noted. After thorough mesostructure studies, it is hypothesized that the increase in thickness could be from an increase in viscosity of the prepreg caused by aging. It has been found in previous studies that with the increase in prepreg out time, there is an increase in the viscosity of epoxy [57, 59, 60]. This increase in viscosity would decrease the platelet flow during the curing process leading to less platelet reorientation during curing and causing the number of platelets through the thickness to increase for the same hot press temperature and pressure. This decrease in flow is also supported by the fact that there is an increase in void area fraction with age as shown in fig. 12. If there was flow during curing, platelets and resin can fill the volume where there are less platelets, which would lead to a lower void area fraction. This can be seen in the lower void area fraction in the non-aged DFCs compared to the aged ones.

Another important morphological observation obtained in this work is that the fiber area fraction of the DFC specimens is all the same as the quasi-isotropic specimens, about 60%. This is different from typical short fiber composites who has a fiber area fraction of about 25 −40% . When looking at the application of recycling, this is a huge improvement. Typically when recycling prepreg, the resin is removed from the fiber and the fiber is milled into powder, chopped into short fiber, or made into mats. The option most comparable to DFCs would be short fibers, which would have a much lower fiber area fraction than DFCs. If DFCs are used for recycling there would be no decrease in fiber area fraction. The void area fraction increases with age for DFCs. This is also seen in previous studies . Even with the increase in void area fraction, the fiber volume fraction remains still very high. At the high end, void content was about 3% for most of the samples investigated in this work, and at the low end it was comparable to the void content in the non-aged DFC and quasi-isotropic laminate. With changes in the curing process to account for the increase in viscosity with age and with extra care to evenly distribute platelets, it may be possible to decrease the void content to be comparable with the non-aged specimens. However, decreasing void content may not be necessary. Voids have less impact on the structural behavior of DFCs than with continuous fiber laminates and, different from continuous fiber composites, void content of 3% may be acceptable for DFCs. Also, it was seen that even with the increase in void content, the modulus of aged specimen did not change and the strength increased. This shows the impact of voids on the mechanical properties of aged DFCs to be minimal.

From the mechanical point of view, it can be seen that the out time of the prepreg does not effect the various moduli of DFC specimens, even when aged to three times the out life. Figure 32 shows the DFCs’ modulus normalized to their respective quasi-isotropic values. The figure shows how the modulus does not change with age and that the modulus of DFCs are about the same as a quasi-isotropic layup. The lowest moduli found was for the shear modulus at out time 3× and is 81% that of the quasi-isotropic shear modulus. For other test, the moduli are between 82 −97% that of their respective quasi-isotropic values and this does not change with age. This consistent modulus with age has also been seen in continuous fiber composites [54, 59, 62–65] and by Nilakantan et al. in DFC tension specimens. However, unlike with the modulus, an increase in strength with the aged specimens can be seen. This is different to what has been seen in previous studies done on continuous fiber composites [54, 59, 62–65]. In fact, in these studies it was shown that if the mechanical property had more dependence on the matrix, such as 90◦tension, then there would be a decrease in strength, and if it had more dependence on the fibers, such as 0◦tension, then the strength would not change with age. Figure 32 shows the strength of all tests normalized to their respective quasi-isotropic values and a clear aging effect can be seen. Non-aged specimen can be as low as 39% that of the quasi-isotropic value. Then with age, the strength increases by 15% on average, and has a maximum percent increase of 27% for size 3 out time 2× specimen. It is worth mentioning that an increase in tensile strength with prepreg age for DFCs was also seen by Nilakantan et al. . However, to the best of the authors’ knowledge, the present work is the first to ever investigate the effect of aging also on the compression and shear strengths and to confirm that such strengths increase with age. This is a very important result since recycled DFC components can be subject to a large variety of loading conditions, not only uniaxial tension. Thanks to the results presented in this work, it is possible to conclude with confidence that the structural capacity of a recycled DFC component is not affected by age. On the contrary, the structural capacity might slightly increase.

By looking at work done on aging of cured epoxy and composites we can gain insight on what could be the reason for the strength increase. Work by Zhou et al. has shown that there are two types of bonding that can occur when cured epoxy is aged in distilled water. The first type of bond corresponds to one hydrogen bond between the water molecule and the resin network. This breaks the initial interchain Van der Waals forces resulting in increased mobility of the chains and plasticization of the epoxy. The second type of bonding happens when the water molecules form multiple hydrogen bonds and act as a pseudo-crosslink. This plasticization effect can be seen in aging of a cured laminate and aging of prepregs. Asp found that when composites were aged in high humidity and temperature, mode I fracture toughness increased when testing at room temperature and at 100◦C. Sharp allowed the prepreg used for the center plies of the laminate to absorb 0.5% of its weight in water before curing. This resulted in an increase in mode I and mode II fracture toughness, similar to what was found to happen when cured laminates absorbed water. Blass et al. aged two prepregs in a standard ambient temperature and humidity and performed Double Cantilever Beam (DCB) tests to find mode I fracture toughness. Here one of the prepregs tested showed no changed in fracture toughness after 120 days (12× out life), while the other prepreg tested had an increase in fracture toughness.

The increases in fracture toughness seen in previous works can be linked to the plasticization of the epoxy. In DFCs, the failure is due to a combination of fiber and matrix damage mechanisms, so the plasticization allows the epoxy to absorb more energy before failure and the fibers can carry more load, resulting in a higher strength which is not seen in continuous fiber composites.

The present study also provided the first ever investigation on the effects of aging on the nominal mode I fracture energy of DFCs. This is an important property measuring the capability of the material of dissipating energy upon fracture. From the size effect analysis performed in this study it can be seen that the characteristic size of the Fracture Process Zone (FPZ) decreases when going from out time 0× to out time 1× and 2×, but it increases when going from out time 2× to out time 3×. On the other hand, the fracture energy has little change for the first out time, decreases for the second, and increases for the final out time.

There are two phenomena with contrasting effects at play that are causing the decrease and increase in these properties. The first phenomenon is the increase in thickness of the specimen with increasing age. Ko et al. reported that the fracture energy and characteristic length are strongly effected by the thickness. It was seen that the fracture properties will increase up to a certain thickness and then hit a plateau. At the plateau it is possible that the increase in thickness will cause a decrease in the fracture properties. saw that when the thickness increased from 2.2 mm to 3.3 mm the fracture energy increased, but when the thickness increased from 3.3 mm to 4.1 mm the fracture energy decreased. This phenomenon is exactly what is happening for out time 1× and 2×.

The second phenomenon affecting the fracture properties is the plasticization of the matrix with aging which leads to an increase of the fracture energy. The effect of plasticization can be seen in the fact that for even though there is a thickness increase from out time 0× to out time 1× there is no change in the fracture energy. It was seen by Blass et al. , that with increase in prepreg out time, the mode I fracture toughness would increase or remain constant.

It is believed that this retention or increase is caused by the plasticization of the matrix that happens with aging. The thickness change and plasticization are fighting each other to change the fracture properties. This can also been seen in the fact that the rate at which the fracture properties change when going from out time 0× to 1× and out time 1× to 2× changes. The rate of decrease in properties becomes lower which indicates the plasticization taking effect and then when out time 3× is reached, the plasticization is developed enough to increase the fracture properties.

Onclusions

This work investigated the effects of out time on the mechanical and fracture properties of Discontinuous Fiber Composites (DFCs) for the use in recycling of thermoset prepreg material. Prepreg was aged to 1×, 2×, and 3× the out life of the prepreg (28, 56, and 84 days) and compared with non-aged DFC and quasi-isotropic specimens. Based on this study the following

Conclusions Can Be Drawn:

1. As the out time of the prepreg increases, the prepreg is ambient curing and the degree of cure increases up to a an asymptotic value at around 9× the out life of the prepreg (252 days). The effects of this ambient curing can be seen in the change in the mesostructure of the DFC specimen. With an increase in out time, there was an increase in the number of platelets through the thickness of the laminate and an increase in the laminate thickness.

This is caused by the decrease in resin flow from the viscosity increase of the resin caused by aging. At the same time there was no change in the fiber content, but there was an increase in the void content of the aged specimens. However, voids do not impact the mechanical properties of DFCs when at the level void content seen here the same way it would for continuous fiber composites.

2. The experimental results on tensile, compression, and shear specimens showed for the first time that prepreg out time has no effect on the moduli of DFCs, even when the out time reached 3× the out life of the prepreg. Figure 32 shows the moduli found normalized to their respective quasi-isotropic values. Here it can be seen that the moduli of DFC specimens remain at 81 −97% that of the quasi-isotropic values, and with age this does not change. This is similar to what happens with continuous fiber composites.

3. The experimental results on tensile, compression, shear, and geometrically-scaled Single Edge Notch Tension (SENT) specimens showed for the first time that prepreg out time had a strengthening effect on DFCs. Figure 32 shows the mechanical strength and notched strength found normalized to their respective quasi-isotropic values. It can be seen that the non-aged strength could drop to be as low as 39% that of the quasi-isotropic strength.

However, with age the strength increased, and for the notched strength, could be larger than the quasi-isotropic strength. This is contrary to what happens with continuous fiber composites, where aging has no effect on fiber dominated strength (i.e. 0◦tension), but decreases matrix-dominated properties (i.e. 90◦tension). The strengthening is suspected to be caused by plasticization of the matrix which allows for more energy absorption before failure. Since DFCs’ properties depend on both fiber and matrix, this leads to an increase in strength which is not seen with continuous fiber composites.

Authors:

Peder EZ Larson 1, 2,* , Jenna ML Bernard1, James A Bankson 3, Nikolaj Bøgh 4, Robert A Bok1, Albert P. Chen 5, Charles H Cunningham 6,7, Jeremy Gordon1, Jan-Bernd Hövener 8, Christoffer Laustsen 4, Dirk Mayer 9,10, Mary A McLean11 12, Franz Schilling13, James Slater1, Jean-Luc Vanderheyden5, 14, Cornelius von Morze 15, Daniel B Vigneron1, 2, Duan Xu1, 2, and the HP 13C

94143, Usa.

Denmark. 5 GE Healthcare, Menlo Park, California, USA. 6 Physical Sciences, Sunnybrook Research Institute, Toronto, Ontario, Canada.

8 Section Biomedical Imaging, Molecular Imaging North Competence Center (MOIN CC), Medicine, Baltimore, MD, USA. Cambridge, United Kingdom.

14Jlvmi Consulting Llc, Dousman, Wi, Usa

#See Acknowledgements for a list of all HP 13C MRI Consensus Group Members This work was supported by the ISMRM Hyperpolarized Media MR Study Group, the ISMRM Hyperpolarization Methods & Equipment Study Group, and the Hyperpolarized MRI Technology Resource Center (NIH/NIBIB grant P41EB013598).

Abstract

MRI with hyperpolarized (HP) 13C agents, also known as HP 13C MRI, can measure processes such as localized metabolism that is altered in numerous cancers, liver, heart, kidney diseases, and more. It has been translated into human studies during the past 10 years, with recent rapid growth in studies largely based on increasing availability of hyperpolarized agent preparation methods suitable for use in humans. This paper aims to capture the current successful practices for HP MRI human studies with [1-13C]pyruvate - by far the most commonly used agent, which sits at a key metabolic junction in glycolysis. The paper is divided into four major topic areas: (1) HP 13C-pyruvate preparation, (2) MRI system setup and calibrations, (3) data acquisition and image reconstruction, and (4) data analysis and quantification. In each area, we identified the key components for a successful study, summarized both published studies and current practices, and discuss evidence gaps, strengths, and limitations. This paper is the output of the “HP 13C MRI Consensus Group” as well as the ISMRM Hyperpolarized Media MR and Hyperpolarized Methods & Equipment study groups. It further aims to provide a comprehensive reference for future consensus building as the field continues to advance human studies with this metabolic imaging modality.

Keywords: Hyperpolarized MRI, metabolic imaging, carbon-13, pyruvate, dissolution dynamic

Introduction

MRI with hyperpolarized 13C agents, also known as hyperpolarized (HP) 13C MRI, has shown great potential as a novel imaging modality, particularly for its ability to probe metabolic processes in real time. The first human studies with HP [1-13C]pyruvate were performed in 2011 in prostate cancer patients (1).

Since then, there have been over 60 papers published with imaging results of human subjects from 13 different sites, with applications including prostate cancer, brain tumors, breast cancer, kidney cancer, pancreatic cancer, metastatic disease, liver disease, ischemic heart disease, diabetes and cardiomyopathies. The vast majority of these studies used [1-13C]pyruvate (1–63), where [2-13C]pyruvate (64) and 13C-urea (56) have been demonstrated too.

As clinical HP 13C MRI advances, there is a growing need to build consensus for best practices, which are critical for comparing data across sites, performing multi-site trials,deploying methods to new sites, partnering with vendors, and potentially for obtaining broader regulatory approvals.

In March 2022, we initiated an effort to build consensus within the HP 13C MRI community with this opportunity in mind, and it was greeted with strong enthusiasm. The “HP 13C MRI Consensus Group”, containing over 55 members from 27 sites, identified the area of greatest need and opportunity for consensus building to be HP [1-13C]pyruvate human

●

Pyruvate is the most mature and widely used HP agent and has the most significant translational evidence emphasizing the potential clinical impact.

●

Clinical trials, particularly multi-site trials, have the strongest need for consensus methods to ensure that data can be combined across sites. This work is a Position Paper for which the goal is to describe current successful practices and study methods for HP [1-13C]pyruvate human studies along with justification to support those practices. This is divided into four major topic areas: (1) HP 13C-pyruvate preparation, (2) MRI system setup and calibrations, (3) data acquisition and image reconstruction, and (4) data analysis and quantification (Fig. 1). The current successful practices and study methods include a literature review of published peer-reviewed journal papers showing human HP [1-13C]pyruvate study data, up to September 2022 (1–63), as well as new unpublished information from surveys of HP 13C study sites. Based on this information, we also highlight the evidence gaps, strengths, and limitations of current practices which are summarized at the end of each section.

Figure 1: Illustration of the HP 13C MRI human study process, including the 4 major areas covered in this paper: Hyperpolarized 13C-pyruvate preparation, MRI system setup and calibration, Acquisition and Reconstruction, and Data Analysis and Quantification.

Figure 2: Anatomical targets of HP [1-13C]pyruvate MRI human studies published up to September 2022.

Hyperpolarized 13C-Pyruvate Preparation

This section covers the processes for creating the HP agent, 13C pyruvate, and will include many aspects and considerations that are needed to safely and effectively prepare doses for metabolic imaging studies in human subjects. These include material, personnel, equipment and facility, fluid path preparation, quality control, and release.

It is helpful to understand that the specifications of a dose of 13C pyruvate suitable for in vivo MR HP metabolic imaging were shaped in part by early preclinical studies performed by GE HealthCare summarized in Ref. (65). In short, the safety of the two novel drug components, 13C pyruvate and the electron paramagnetic agent (EPA) AH111501, were demonstrated in those studies. The more precise formulation of the dose suitable for human use was then determined from clinical studies (66) that included two Phase 1 clinical trials in young and elderly healthy volunteers without hyperpolarization of the 13C nuclei and another Phase 1/2a dose escalation and imaging feasibility study with HP 13C pyruvate in 31 prostate cancer patients at the With the exception of the first HP 13C imaging clinical trial, which utilized a prototype device in a cleanroom (1), all HP 13C studies performed in humans to date have utilized the SPINlab polarizer (manufactured by GE HealthCare). Consequently all doses of the HP 13C pyruvate delivered by SPINlab have been produced using the “SPINlab Pharmacy Kit” that serves as the container-closure system for the various drug components (13C pyruvic acid and EPA mixture, dissolution medium, and neutralization and dilution medium) during sample polarization, dissolution and quality control (QC) processes. Thus many aspects of the HP sample preparation considerations discussed below are related to the SPINlab instrument and the consumables designed to be used with it (67).

General Considerations

While more than 860 patients or healthy subjects having been injected with HP 13C pyruvate as of January 2022 without reports of any serious adverse events (68), HP 13C pyruvate injection remains an investigational MR contrast agent and can only be administered by those with Investigational New Drug (IND) exemption from the Food and Drug Administration (FDA) in the USA, a Clinical Trial Application (CTA) in Canada, approval from National Research Ethics Committee Services in the UK, or approval from the relevant local regulatory body. Thus, methods and processes involved to produce a dose should have patient safety as the first priority. Since utilizing dissolution dynamic nuclear polarization (dissolution-DNP) for human use is still a relatively new development, there are no existing published regulatory guidelines specifically for this method.

There are two major production styles that determine how various sites approach the agent preparation. In the US, the most common approach is to rely on a sterilizing filter (“Terminal Sterilization”) to ensure sterility of the final product, akin to PET tracer production, where a starting molecule with a radioisotope is processed using various other ingredients to make the final, desired and injectable contrast agent within a necessarily short amount of time (69). For these sites, sterilization of the components and accessories upstream of this filter are not required, although many of them were manufactured and tested following Good Manufacturing Practice (GMP) or Good Laboratory Practice (GLP) requirements. The filling process is usually performed under an ISO 5 laminar flow hood, but a clean room or an isolator is not required.

This approach is typically accompanied by testing the integrity of the sterilizing filter prior to release of the dose for injection. Typically, post release endotoxin and sterility tests are performed using an aliquot reserved from each released dose.

In the UK and EU, the most common approach is to more-closely follow sterile pharmaceutical compounding guidelines (70), where all components and ingredients are required to be sterile or manufactured under GMP guidelines and are assembled and filled within a clean room environment or an isolator system (“Sterile Preparation”). Typically a batch of Pharmacy Kits for HP 13C pyruvate injection are prepared together. The sterility of the final dose is also ensured by batch validation testing, in addition to the sterility of the ingredients and the sterile compounding process. The endotoxin and sterility testing are performed for the process validation but are not performed for each injected dose.

Some institutions fill and assemble the Pharmacy Kit required for a specific study on the same day or the day prior to polarization, dissolution, and patient administration, but others have also demonstrated the feasibility of preparing a batch of kits, keeping them in a -20ºC freezer and using them over a period of a few months.

Beyond the obvious requirements that the process and the facility has to ultimately produce a dose that is safe to inject into a human, regulatory authorities will also focus on the question “Are you in control of your processes?”. To be in control of your process requires an in-depth and broad understanding of all processes involved in pre, post, and during the production process.

Personnel

It is typical and may be required to have licensed personnel involved in the production process depending on local regulations.Typically a pharmacist, radiopharmacist or other similarly qualified person (QP), in charge of the facility where the Pharmacy Kit filling and preparation is taking place, is responsible for the overall process and the release of the injectable dose.

Qualified cleanroom technicians are often involved in the Pharmacy Kit filling under the supervision of the pharmacist or QP. As is required for pharmaceutical compounding or PET tracer production, training requirements and training records for all personnel need to be maintained and available for audit by the FDA or equivalent.

Equipment And Facility

The facility and all equipment need to have standard operating procedures (SOPs) that describe how equipment is used, maintained, and calibrated to comply with relevant legislation. Currently, almost all the filling of the Pharmacy Kit takes place within a compounding laminar flow hood or isolator (typically ISO 5). At some sites, the filling is conducted within a cleanroom, while at others, it is conducted in a dedicated non-cleanroom space, reflecting differences in cleanroom approach and specifications between regulators worldwide (71). Some equipment or facilities, such as the compounding hood or cleanroom, may require external certified laboratories for testing.

Material Handling

Material handling guidelines (69,70) require SOPs detailing a system to track all of the materials involved in the HP production process for a particular patient dose, similar to current good manufacturing practice (cGMP) requirements for material handling for drug compounding. This includes acceptance standards, storage conditions, amount used in the patient dose for each ingredient and materials used in the assembly of the fluid path and Pharmacy Kit. Currently some users choose to open and inspect and sometimes modify the Pharmacy Kits upon arrival, but some users keep them in the sealed packaging until they are required for dose preparation.

Pharmacy Kit Filling And Assembling

As required by an IND or its equivalent, the preparation of the doses of HP 13C agent are detailed in the Chemistry, Manufacturing, and Control (CMC) section of an applicable regulatory submission; an example of this has been made available (72). It describes the processes of filling the Pharmacy Kit with the different components that make up the final drug product, and of assembling the final kit for either storage or immediate use in the polarizer. Special attention should be given to the laser welding process in order to satisfy installation qualification (IQ) and operational qualification (OQ). Typically, the final developed process is validated by process qualification (PQ) runs, during which 3 or more Pharmacy Kits are filled and used and the final HP 13C products are tested for endotoxin and sterility and to confirm that they meet the dose specifications for injections (usually including pyruvate concentration, residual EPA concentration, pH, liquid state polarization level and dose temperature). The data from 3 consecutive PQ runs are submitted as part of the IND submission (or its equivalent), and are often also reviewed by the Institutional Review Board (IRB) where the studies are conducted.

Quality Control And Dose Release

The quality control (QC) and dose release can be separated into two aspects: one is the QC and release of the filled Pharmacy Kit, and second is the QC and release of the HP 13C agent for injection, after polarization and dissolution. For institutions filling a batch of kits and storing them to use over a period of time, typically the batch can be released based on initial validation, environmental monitoring data from the day of kit production, and if filters are used during preparation of any of the components, filter integrity testing. But in some cases one or more kits are used for validation before the batch of kits are released for future use. For institutions that fill only the kits required for specific studies shortly before the experiment, the filled kits often do not go through separate release tests before they are used.

The quality control of the HP 13C pyruvate solution post dissolution is primarily performed to ensure that the agent meets the dose specifications (Table 1) before it is administered to the subject. These specifications target both safety (pH, residual EPA, temperature) and efficacy (pyruvate concentration, polarization, volume). Typically, the pyruvate concentration, residual EPA concentration, pH, dose temperature, dose volume, and liquid state polarization are measured by the QC accessory associated with the SPINlab polarizer. Some users perform a secondary measurement for one of the parameters, such as pH, using a different instrument or pH paper. For sites that do not go through a separate release testing process for batch filled kits, the integrity of the sterilization assurance filter, a part of the Pharmacy Kit, is typically tested as a part of the dose release. It is also common for these users to preserve an aliquot of the final HP 13C pyruvate solution for post-release endotoxin and sterility testing. This testing cannot be completed fast enough to test an individual dose prior to injection, but this is why other processes such as PQ runs and validation testing are done to minimize the chance a subject could be injected with a contaminated dose.

The Final Dose Release And Injection

should be done under the supervision of a licensed professional, based on local regulations.

Some Key Challenges

Many of the challenges associated with HP 13C pyruvate preparation can be attributed to the conditions required for the dissolution-DNP method of high magnetic field (~3-7 T) and very low temperature (~1 K) during polarization, with pressurized and superheated water necessary for the rapid dissolution event. These extreme conditions are quite challenging for the design of the container-closure and fluid path system. In particular, the cryogenic temperature in the polarizer requires special attention to any moisture or ambient (moist) air introduced into that portion of the fluid path, which can form an ice block at ~1 K. This ice can lead to flow restriction during the dissolution event and reduce the strength of the laser welded bond between the cryovial and its cap. This can ultimately produce failures in the dissolution step, including variations in final pyruvate concentration and pH that may fail to meet QC release criteria as well as fluid path ruptures that provide no available dose and result in polarizer down-time.

The polarization of the HP 13C pyruvate sample decays quickly over the span of a few minutes after dissolution, and thus the process of dissolution, QC for release, and injection should be completed as fast as possible to preserve the high polarization level achieved. Any delays in the preparation process, such as transportation time or equipment malfunction, can significantly reduce the final polarization and result in lower quality imaging data.

Current Practices

A summary of data collected from all sites performing clinical trials with HP 13C-pyruvate is shown in Fig. 3 and Table 1, including the specification of the final dose and how the quality control and release of the final dose are performed. There is a split in the Production Style, described in the General Considerations section above, with 8/13 sites using Sterile Preparation versus 5/13 using Terminal Sterilization. While many of the dose specifications show notable differences in acceptable ranges, all of these variations listed in tables have been successfully and safely been used to perform HP 13C pyruvate studies in humans. Their differences depend on the institutions’ preferences, resources and their particular regulatory situation. There is high similarity in pyruvate ranges, temperature ranges, EPA limits, and volume limits. There is modest variability in pH ranges and large variability in the endotoxin test limit. There is a 3-fold difference in acceptable polarization levels, which are measured to ensure a futile dose is not injected since the polarization is directly proportional to SNR. This reflects the decision by several sites to believe that useful data can be still be obtained with suboptimal polarizations.

Figure 3: Hyperpolarized agent preparation methods reported by sites currently performing HP

In House

Table 1: HP 13C-pyruvate preparation parameters, methods, and dose specifications used for quality control testing and release as well as validation. These were obtained from a survey of all sites performing clinical trials with HP [1-13C]pyruvate. The parameters used for product release are noted in bold text, otherwise these parameters are measured for batch validation or other QC measurements. The endotoxin and sterility testing are performed during process validation of the batch and/or post-injection, and largely depends on the agent production approach.

Summary

The overall safety record of HP 13C-pyruvate has been very strong, and the SPINlab hyperpolarizer has proven to provide high polarizations at human sized doses while meeting numerous QC and release criteria. A weakness remains the failure modes of the SPINlab Phamacy Kits (e.g. ice blocks, path ruptures), which are placed under extreme requirements particularly during dissolution. The preparation process still requires a high degree of expertise.

Therefore, there is a significant need to improve the reliability, robustness, and ease of operation for generating HP 13C-pyruvate doses for human studies. Furthermore, there is a divide between manufacturing and sterile compounding style preparation as well as other site-specific practices, resulting in variations in SOPs and justification required to relevant regulatory bodies. There have also been no comparisons between these approaches. It is also unclear what release criteria and QC parameters are truly required to ensure patient safety.

However, all of the reported methods are acceptable and approved by the appropriate regulatory authorities, and have led to the rapid expansion of successful human studies in recent years.

Mri System Setup And Calibrations

This section covers the MRI system setup, including the imaging system, RF coils, phantoms, and prescan calibration methods.

Imaging System

The main prerequisite for a given MRI scanner to be capable of supporting studies with HP 13C is its “broadband” capability to transmit and receive radiofrequency (RF) signal at the frequency of 13C, which is around 4 times lower than 1H. This does not come as a default on clinical MR devices. The transmit power of the broadband amplifier should also be sufficient to support the intended flip angle and RF pulse shape with the employed transmission RF coil(s) for 13C. Most studies to date use relatively low flip angles (< 90 degrees) for HP 13C in order to preserve polarization for time-resolved imaging. The capability to receive 13C signal on multiple channels is also desirable to increase SNR, as discussed further in the “RF coils” section.

The choice of magnetic field strength is primarily dependent on the metabolites’ frequency separation due to chemical shift dispersion and 1H imaging. High field strengths do not enhance hyperpolarized 13C signal as they do for 1H because the signal strength in a HP experiment relies on manipulating the population of quantum energy states outside of the MRI scanner.

However, the injected HP 13C-pyruvate and its metabolic products have greater frequency separation at higher fields, and it may thus be easier to separate and quantify these resonances at higher fields. This comes at the cost of a reduction in the achievable T2* and often reduced T1. As the initial polarization is independent of the imaging field strength it has been proposed that the increased T2* at 1.5T can potentially be exploited to increase SNR by adapting the acquisition bandwidth or reduce off-resonance imaging effects in cases when the decay of the transverse magnetization is dominated by T2* (73). In practice, 3T has been used in all published human 13C-pyruvate studies surveyed (Supporting Table S1), and comprises the majority of scanners currently in use for human studies (Table 3). A field strength of 3T is well-suited for 1H MRI anatomical reference and correlative imaging.

Stronger and more rapidly slewing magnetic field gradients support more rapid spatial encoding, particularly for metabolite-specific single-shot imaging using echo-planar imaging (EPI) or spiral imaging (See “Acquisition and Reconstruction”). Although the spatial resolution acquired for HP 13C imaging is typically much coarser than for 1H MRI, the factor of ~4 in gyromagnetic ratio leads to the same reduction factor in performance of the gradient system, so 13C experiments are potentially more limited by gradient hardware performance. To date, all human studies have used the commercially-available integrated gradient systems provided in clinical MRI scanners.

Optimization of scanner design has understandably focused on minimization of artifacts in 1H MRI, where devices such as room lights, the gradient amplifiers, and the motors driving the patient bed are checked to ensure that they do not produce RF interference at the 1H frequency, but artifacts may arise at other frequencies. Eddy current compensation is also not always appropriately adjusted for nuclei at other frequencies (74). In order to optimize for 13C, many sites have performed checks on phantoms for RF interference, gradient artifacts, and eddy currents (74), including the use of post-hoc gradient impulse response function characterisation and correction, and some vendors have fixed these issues as well.

Rf Coils

For HP 13C imaging studies in humans, RF coils for both 1H and 13C nuclei are needed, with 1H MRI providing an anatomical reference for registration and optional additional multiparametric MRI readouts. At the Larmor frequency of 13C nuclei, the relative contributions from coil noise compared to sample noise increase compared to 1H (73,75), although sample noise still is likely the dominant contributor for human-sized coils at 32.1MHz - the resonance frequency of 13C nuclei at 3T.

The key requirement for human 13C-pyruvate RF coils are that the coil geometry and sensitive volume must cover the volume of interest in the subject. Table 2 and Figure 4 shows coil configurations that have been used and optimized for applications in different anatomic regions.

Volume resonators are most commonly used for transmit, as they surround the subject to

Provide B1 Transmit Across The Fov (B1

+). While 1H relies on a large birdcage (“body”) coil built into the scanner, 13C transmit coils must be placed inside the bore. This takes up valuable space within the magnet, and also has led to the use of designs with relatively inhomogeneous

B1

+. Many human studies have used Helmholz pair resonators for transmit, including the “clamshell coil”, which has a notably inhomogeneous B1

+ Profile But Has Been Used Because Of

relatively easy integration into the scanner bore. B1

+ Variation Results In Variations In The Flip

angles that control the use of the hyperpolarized magnetization and creates errors in common HP metrics (9,76). The exception are head coils, where birdcage designs with highly

Homogeneous B1

+ can be placed around the head while easily fitting inside the bore. As with 1H MRI, higher SNR can typically be achieved by smaller receive coil elements, such as surface coils or phased arrays, and the majority of 13C receive coils used have layouts similar to 1H phased arrays.

RF coil quality control is important to ensure proper functioning of the coils to provide consistent imaging quality, especially with limited natural abundance 13C signal in vivo. It typically involves 1) a physical integrity check of the coil cables and connectors and 2) phantom SNR tests to check the coil’s performance and to monitor it over time (see Phantoms below). An useful reference for RF coil quality control is outlined in the MRI accreditation program of the American College of Radiology (77) and can be adapted for 13C coils.

Notably, configurations for brain and prostate studies used dual-tuned 1H/13C coil designs, which greatly simplify workflow and registration of 1H and 13C images, as no switching of coils is needed.

(1)

Table 2: RF coil configurations reported for human HP [1-13C]pyruvate studies.

Tx = Transmit

coil, RX = receive coil. The commonly used “clamshell” TX coil is a Helmholz pair design. For 1H RF configurations, all used the Body coil for TX unless otherwise noted, and “repositioned” indicates the 13C coil was removed for 1H imaging. One representative reference is listed for each configuration. The RF coil configurations reported in the reviewed papers are shown in Supporting Table S1.

Figure 4: Examples of RF coil configurations used for human HP [1-13C]pyruvate brain studies. (A,B) 13C Clamshell TX (Helmholz pair) and 2× 4-channel paddle RX arrays. (C) 13C Birdcage volume TX and 32-channel RX array (RX array slides into TX coil). (D) 13C Birdcage volume TX and 24-channel RX array, combined with a 1H 8-channel RX array. Image reproduced with permission from Ref (16).

Phantoms

Since hyperpolarized magnetization is non-renewable, phantoms containing 13C nuclei are important to: 1) test the multi-nuclear capabilities of the imaging system, including all parts of the signal excitation and receive chain; 2) perform calibration measurements before a scan with hyperpolarized nuclei; and 3) perform necessary pre-scan adjustments (see “Prescan Calibration” section). The phantoms currently in use are listed in Table 3. Their composition must provide sufficient 13C signal, with additional considerations of conductivity, stability, chemical shift(s) present, potential for dynamic imaging, and cost. The phantom geometries are typically either compact, in order to be used alongside the subject during a HP scan, or large enough to mimic the inner volume of a RF coil for system testing.

One popular compact design contains enriched 13C-urea at high concentration, typically 8 M, which provides a single resonance, placed inside a small container ~1 mL. The most common recipe mixes 13C-urea in a 90% water/10% glycerol solution, with glycerol used to increase the urea solubility and doping with a Gd-based contrast agent to shorten T1 which increases the potential SNR per unit time. For example, when Dotarem is added at a 3:1000 volume ratio the 13C-urea T1 is around 500 ms and T2 is around 100 ms. However, when testing pulse sequences influenced by T1 and T2, doping should be used carefully. This phantom is suitable for frequency calibration, transmit gain calibration, sequence testing, and as a fiducial marker when placed next to a patient. However, enriched 13C-urea has a relatively high cost compared to natural abundance compounds.

For larger volumes (>100 ml), the phantoms most often used contain undiluted ethylene glycol, glycerol, or dimethyl silicone. These compounds have sufficiently high carbon concentrations to provide sufficient 13C signal even with the 1.1% natural abundance of 13C. These larger phantoms matching the inner volume of an RF coil are useful for coil testing, including transmit

+) And Receive (B1

-) coil profile mapping, as well as to mimic acquisitions using in vivo FOV requirements. In this case, size and conductivity should match the expected subject size in order to mimic coil loading and get a realistic estimation of B1+. Large-volume natural abundance urea phantoms have also been used by some sites, but suffer from higher conductivity compared to biological tissues. Typically, it is easier to increase the conductivity and hence coil loading of the non-conductive phantom by adding NaCl to match physiological loading (16,78).

Dynamic phantoms that aim to mimic metabolite kinetics have also been developed (79–81), and have the potential to more closely mimic the HP experiment, but so far these are not widely used.

Prescan Calibration

Prior to performing an MRI acquisition, the so-called prescan procedure is used to set the shim parameters to maximize B0 homogeneity over the field of view (FOV) or a specific region of interest (ROI), the scanner center frequency (CF), the RF transmit gain, and the receiver gain.

While this calibration procedure is usually automated for 1H, the lack of sufficient natural abundance 13C signal prevents use of automated methods. (Although natural abundance 13C lipid signal has been detected, there are so far no reports on using this signal for prescan.) Table 3 shows current practices across sites.

Maximizing B0 homogeneity is independent of the nucleus and is therefore performed prior to 13C imaging using the 1H water signal and existing shimming tools, such as by a standard automated process (“Auto Shimming”) or using high order shimming routines. Similarly, the 13C CF can be calculated from the 1H CF using a predetermined scaling factor that depends on the target chemical shift (82). Another common approach used is to have a small, high-concentration 13C phantom, e.g. 8M 13C-urea, integrated in the RF coil or placed next to the scan subject (1). The reference frequency can also be based on real-time measurements after the HP injection but prior to imaging (83). Both the CF and B0 shimming are critical when using spectrally-selective RF pulses, as inmetabolite-specific imaging methods, where the desired excitation bandwidths are typically very narrow and frequency offsets can lead to a failure mode that is only apparent after injection.

The calibration of the RF transmit power is typically performed on a small, high-concentration 13C phantom placed near the region of interest during the scan or on a large 13C phantom of similar size and coil loading as the subject, prior to the subject scan. Reference power is often done by sweeping the power in a pulse-acquire sequence (53,62), or the Bloch-Siegert method (52,84). When using a small phantom, the location of the phantom, B1

+ Inhomogeneity As Well

as any shielding effects, e.g., when the phantom is integrated into a coil (1), may degrade the accuracy. Other methods include real-time Bloch-Siegert method measurements after the HP injection (83), and using the stronger natural abundance 23Na signal that is close enough to the 13C resonance frequency to be detected by 13C coils (82).

The receiver gain is predetermined, either systematically based on independent phantom measurements and assuming the dose and polarization of the HP compound is known prior to injection, or based on past HP imaging studies.

Power [Kw]

Phantom(s) - during study Phantom(s) - before study 13C Frequency

8

13C-bicarbonate doped with dimethyl silicone, various

Power [Kw]

Phantom(s) - during study Phantom(s) - before study 13C Frequency

Maximum Values

Table 3: Summary of the imaging systems, phantoms, and prescan procedures used at sites currently performing HP 13C-pyruvate human studies. These were obtained from a survey of all sites performing clinical trials with HP [1-13C]pyruvate. *Previously performed studies with a Siemens 3T Tim Trio. The imaging systems, phantoms, and prescan procedures reported in the reviewed papers are shown in Supporting Table S1.

Summary

Commercially available 3T MRI systems are by far the most commonly used for human HP 13C-pyruvate studies, although a systematic investigation of the impact of B0 has only recently been investigated (73). The multi-nuclear RF transmit and receive chain has proven sufficient for current acquisition strategies, although many sites have observed artifacts due to RF interference, gradient interference, and residual eddy currents when operating at the 13C frequency. A variety of 13C RF coils, tailored for numerous anatomical targets, have been successfully demonstrated, with the main limitation that most transmit coils take up a lot of additional space inside the bore and provide relatively inhomogeneous B1

+ Profiles. The

phantoms used have converged into generally 2 categories - small phantoms containing 13C-enriched compounds that can be used during the study and human-sized phantoms containing compounds with high carbon concentrations but without 13C enrichment that are used to test and calibrate the coils. There are no standardized compositions or geometry, and dynamic phantoms that recapitulate in vivo kinetics would be desirable but are still an emerging area. Prescan calibration procedures were not well defined in most publications, so we surveyed individual sites to determine current practices. Calibration procedures for the B0 field (13C CF and shimming) for most sites take advantage of 1H signal and methods, while methods

For Calibration Of B1

+ is more variable across sites, likely a reflection of remaining challenges in how to perform this calibration. Standardization of both phantoms and calibration procedures would synergistically improve the robustness and reproducibility of HP 13C studies.

Acquisition And Reconstruction

Data acquisition strategies in human HP [1-13C]pyruvate MRI studies must account for multiple chemical shifts, efficiently utilize the non-renewable HP magnetization, and acquire data quickly relative to metabolism and relaxation decay processes. These studies require spectral encoding to separate metabolites, necessitating pulse sequences that efficiently encode up to 5D data (3 spatial + 1 spectral + 1 temporal dimension). RF pulses must efficiently sample without immediately saturating the non-renewable HP magnetization, and sequences must acquire data quickly and be robust to both experimental and physiologic variation (e.g. B1

+ Inhomogeneity,

variation in perfusion) to ensure reproducibility and minimize scan-to-scan variability. This section covers current successful practices for data acquisition in human [1-13C]pyruvate studies, and accompanying 1H imaging, from different anatomic regions, including scan parameters and image reconstruction.

Acquisition And Reconstruction Methods

The acquisition methods used in human [1-13C]pyruvate studies can be classified into 3 categories: 1) MR spectroscopy or MR spectroscopic imaging (“MRS/I”), 2) chemical shift encoding methods, and 3) metabolite-specific imaging (Fig. 5).

Mrs/I Methods Specifically

resolve a spectrum that can be analyzed to extract expected as well as unexpected resonances, making this approach very robust. It was used in many initial studies (1).

Chemical Shift

encoding methods, most commonly the Iterative Decomposition of water and fat with Echo Asymmetry and Least-squares estimation (IDEAL) method, use imaging sequences acquired with multiple TEs and rely on a model-based separation of expected chemical shifts (85).

Metabolite-specific imaging methods use specialized RF pulses that are spatially and spectrally selective to excite individual metabolites which are then typically imaged with fast k-space trajectories such as echo planar imaging (EPI) or spirals (86).

Their Application To Different

organ systems is described below. The image reconstruction methods used in human [1-13C]pyruvate studies have typically been conventional methods (e.g. FFT, non-uniform FFT, or equivalent). The incorporation of accelerated imaging and advanced reconstruction methods including parallel imaging (4,57,87) and compressed sensing (7) has also been applied in human studies for improved spatial resolution, temporal resolution and coverage, but have the potential for additional artifacts as well as SNR losses due to ill-conditioning of the reconstruction (e.g. g-factor).

The Majority Of

published studies do not use accelerated imaging indicating the resolution and coverage achievable without acceleration is currently adequate for successful data collection. Performing coil combination, even with fully sampled data has also been shown to have specific challenges for HP human images: using naive sum-of-squares methods suffer from high noise amplification in the relatively low SNR regime of HP [1-13C]pyruvate (compared to 1H), motivating several HP 13C-specific methods that include data-driven coil sensitivity estimation which have shown obvious improvements over sum-of-squares (11).

More recently denoising techniques have been applied as post-processing of human HP data(41,42,44). The techniques applied are based on spatial-temporal singular value decomposition for unsupervised estimation of signal and noise components. They have shown improvements in apparent SNR in the brain and liver, while care must be taken to choose parameters such as the rank threshold to avoid oversmoothing and overfitting to the estimated signal components.

Prostate Studies

Prostate cancer was the first human application of HP [1-13C]pyruvate (1), and data was acquired with MRS/I methods: 1D dynamic MRS, single-slice 2D dynamic echo-planar spectroscopic imaging (EPSI), and single time point 3D EPSI. Advances in imaging strategies led to the development and application of new acquisition schemes, including undersampled 3D EPSI with compressed-sensing (7), model-based chemical shift encoding methods that use a priori information (47,59), and metabolite-specific EPI (10), all of which can provide volumetric whole-organ coverage and dynamic acquisitions.

The pyruvate bolus arrival in the prostate can vary by ± 10 s between patients, necessitating dynamic imaging to reliably and consistently capture the pyruvate bolus (18). For this reason, all currently ongoing studies acquire dynamic data. While MRS/I, chemical shift encoding, and metabolite-specific imaging can all achieve dynamic imaging, chemical shift encoding and metabolite-specific imaging provide greater dynamic and volumetric coverage (85). For scan prescriptions, the FOV is designed to provide full prostate coverage and typically to match the orientation of the anatomic imaging used for registration. Flip angles used in current studies are constant through time, as quantification with a variable-through-time flip scheme is highly sensitive to bolus timing (8) and errors in the RF transmit (B1 +) field (76).

Heart Studies

Data acquisition methods for 13C imaging in the heart must be designed to meet the demands of significant cardiac motion and blood flow. To cope with the periodic cardiac motion, most human heart studies to date used gating to the diastolic window, the longest cardiac cycle interval, which has reduced motion (2,22,28,30,35,36,38,45,52). The duration of the diastolic window limits the available data sampling time, making cardiac acquisitions the most time-constrained of the HP 13C MRI applications. The most common acquisition approach is metabolite-specific imaging with spiral k-space trajectories (2). Their single-shot imaging capability makes these methods particularly robust to motion effects. Furthermore, spiral k-space trajectories provide rapid k-space coverage and relatively benign flow and motion artifacts. The majority of studies have used 2D multi-slice acquisitions, but 3D encoding has also been used successfully (35).

Brain Studies

For HP 13C MRI of the human brain, the majority of studies have also used 2D (slice selective) acquisitions (10–12,14,16,28,33,40,41,44,51,53,60), with a trend toward volumetric coverage using 2D multi-slice metabolite-specific imaging. 3D metabolite-specific imaging of the whole brain, with phase encoding of the slice direction (34,57), has been shown to provide similar SNR efficiency (88) compared with multislice imaging. A number of studies have employed MRS/I (5,6,29,31–33,50,55) resulting in a spectrum from each voxel, which has the advantage of not requiring a priori information about which peaks to encode. This was important in early brain studies when it was not known which peaks would be detectable. Chemical shift encoding, using a set of images with different echo times and an iterative reconstruction of the individual resonances (i.e. the IDEAL approach (85)), has also been used (12,49,54), with the drawback that coverage in the slice direction was limited due to the time required to acquire multiple echo time images.

Abdomen And Breast Studies

The fundamental approaches to data acquisition and reconstruction in the abdomen and breast are largely similar to the aforementioned applications, but demand attention to particular challenges associated with these anatomic regions, especially relating to respiratory motion.

Although it has been shown that a basic 2D MRSI approach based on phase encoding and FID readout can be successfully applied for HP 13C imaging in breast (15) and kidney (13), major advantages in terms of spatiotemporal resolution and coverage have been realized using tailored approaches based on metabolite-specific imaging (43,62) and chemical shift encoding (43), which have facilitated multi-slice or 3D dynamic acquisitions over large FOVs in the abdomen (4,37,46).

The significant respiratory motion encountered in these regions can directly blur 13C images, and has further favored these rapid acquisition strategies. Motion also degrades B0 homogeneity, which can shift frequency-selective excitation profiles and introduce artifacts into rapid imaging readouts. This makes accurate determination of the acquisition center frequency and shimming essential in these regions which often cover large FOVs. (See “Prescan Calibration” section for more information). In some studies, breath-holding was used to minimize motion effects and enforce frame-to-frame data consistency (42). A pragmatic and reasonably effective approach for dealing with respiratory motion during 13C data acquisition is an initial breath-hold (as long as can be tolerated), followed by free-breathing (46,62).

1H Imaging

Collection of 1H imaging data is essential both for prescribing the 13C acquisition and for interpretation of the resulting 13C data. Multi-planar 1H scouts are acquired prior to 13C acquisition to enable graphical prescription of the 13C imaging region. All human HP 13C-pyruvate imaging studies acquire conventional MRI scans (e.g. T1- and T2-weighted volumes) for anatomic reference, aiming to cover at least the full 13C FOV. Acquiring these anatomic scans as close as possible to the time of 13C imaging (immediately before or after) minimizes potential misregistration between the data sets. Depending on the application, other advanced 1H sequences are also acquired (e.g. diffusion-weighted imaging for cancer imaging).

When contrast-enhanced data is acquired, it is done after 13C imaging, as paramagnetic contrast agents will accelerate 13C relaxation.

Reported Study Parameters

Figures 5 and 6, and Supporting Table S2 shows the reported acquisition study parameters for human HP [1-13C]pyruvate studies published as of September 2022. Figure 5 shows a mixture of MRS/I, metabolite-specific imaging, and chemical shift encoding methods have been successfully used, where spectroscopy-based methods have become less prevalent in recent studies. Figure 6 shows the acquisition timing, including the important start time and interval/temporal resolution, is quite variable across studies.

Figure 5: Acquisition methods used in published HP [1-13C]pyruvate human studies published up to September 2022, classified into: MR spectroscopy and spectroscopy imaging (MRS/I); chemical shift encoding methods, such as IDEAL, that use multiple TEs and model-based reconstructions; and metabolite-specific imaging methods that use spectrally-selective excitation to image a single resonance at a time.

Figure 6: Temporal acquisition characteristics reported in HP [1-13C]pyruvate human studies published up to September 2022. (a) Reported referencing of acquisition start times.

(B)

Acquisition start times reported when using dynamic imaging and when timing was reported relative to the end of the injection. (c) Temporal resolutions. “Not Applicable” indicates dynamic imaging was not used.

Summary

Three general categories of acquisition strategies have been used successfully for human HP 13C-pyruvate studies: MRS/I, model-based chemical shift encoding (e.g. IDEAL) methods, and metabolite-specific imaging methods. These have enabled successful studies in the prostate, heart, brain, abdomen, and breast. Recent studies increasingly have used the imaging-based strategies of metabolite-specific imaging and chemical shift encoding which are the fastest methods, although a heads-to–head comparison between techniques has not been performed.

Metabolite-specific imaging is quite popular because of its speed and compatibility with single-shot imaging, but is sensitive to B0 field variations and thus requires careful calibrations. Nearly all studies surveyed acquired data dynamically, allowing measurement of the bolus and metabolite kinetics. The exact timings and associated flip angles vary quite widely across reported studies, with no consensus yet as to how to choose these parameters. Image reconstruction is typically done directly using Fourier Transform methods, and accelerated imaging strategies are uncommon.

Data Analysis And Quantification

This section covers the analysis of data from human HP [1-13C]pyruvate studies, including modeling and metrics, visualization, as well as considerations for how to store data and metadata. Depending on study design, the analysis may need to give quantitative or semi-quantitative output reflecting a biological process or may just reflect a contrast between different regions of interest for quantitative evaluation.

Metrics

Figure 7: HP [1-13C]pyruvate raw data (A) have typically been quantified using four categories of metrics depending on the acquisition. Data acquired as a single time point are often quantified using normalized metabolite images or metabolite ratios (B). Dynamic data can be quantified using normalized metabolite images or metabolite ratios (B), or with metabolite timings such as time-to-peak (TTP) or pharmacokinetic (PK) models (C). The latter two require the data to be time-resolved. [1-13C]alanine and 13C-bicarbonate are analyzed similarly to [1-13C]lactate but omitted here for display.

Metabolite images are commonly used as summary metrics for HP MRI data, often including some form of normalization as well as summed over time as an area under the time curve (AUC) (17). These are analogous to the visual evaluation that is most used for routine clinical work (89,90). In these metabolite images, we expect that the [1-13C]pyruvate AUC signal is predominantly weighted towards perfusion and uptake, while [1-13C]lactate, [1-13C]alanine and 13C-bicarbonate AUCs represent metabolic conversion. The strength of this approach lies in its simplicity and relatively few underlying assumptions. Limitations to the use of single-metabolite images or AUCs include sensitivity to inhomogeneous coil profiles (57,87,91), the acquisition strategy and acquisition parameters, pyruvate polarization and concentration level, and signal relaxation rates (92). Further, the reader must be careful to interpret all the images in conjunction to better understand the underlying biology; for example, increased [1-13C]lactate in the presence of decreased [1-13C]pyruvate delivery can have a very different meaning compared to increased [1-13C]lactate with increased [1-13C]pyruvate delivery.

In an attempt to address variations in coil sensitivity, polarization level, and pyruvate delivery, AUC images are often computed by normalizing to a specified parameter, such as the maximum pyruvate or average lactate signals, or presented as a ratio such as lactate/pyruvate or divided by “total Carbon” - the sum total of HP 13C signal observed across all metabolites. The AUC ratios between metabolites and pyruvate are proportional to the corresponding forward kinetic rates (81,93), but are not directly comparable to rate constants when magnetization loss rates (e.g. relaxation and losses due to signal excitation) differ between studies. Similarly, the ratios between the produced metabolites (e.g. bicarbonate/lactate) can reflect the balance between downstream metabolic pathways (12,55). Care must be taken to consider how AUC images are calculated and normalized before comparing values between studies.

To further quantify the interpretation, pharmacokinetic (PK) modeling approaches were developed to compute the apparent kinetics of pyruvate-to-metabolite exchange (92,94–99). These yield semi-quantitative to quantitative apparent rate constants, given in s-1. Some models require a vascular input function, while others avoid this requirement (95). PK models can explicitly account for acquisition-specific details such as excitation angle and repetition time, and thus may reduce the effects of these details on quantification. An input-less model, provided in the Hyperpolarized-MRI-Toolbox (https://github.com/LarsonLab/hyperpolarized-mri-toolbox) (100) and thus frequently employed for human data, has been shown to fit well and robustly to prostate and brain data (8,20). PK models are quantitative in nature, arguably provide more relevant biological information (8,20), and appear to be reproducible across sites (51). However, rate constants derived from PK models are still apparent rates, and likely do not reflect a single biological characteristic.

Some additional considerations include whether complex or magnitude data is used, as the noise behaviors will impact the analysis differently. Additionally, cut-off thresholds or other criteria may be used to identify and avoid voxels with insufficient SNR before analysis to improve robustness (20,41).

Regardless of the analysis approach, the underlying biology is not always clearly represented by the data; instead, the metrics may be influenced by perfusion, barrier permeability, intercellular shuttles, enzyme activities, co-substrate concentrations, or combinations thereof, depending on the organ and disease of interest (19,43,94,101–103). This may be addressed by incorporating complementary information. As an example, HP 13C pyruvate data is influenced by perfusion, and thus addition of perfusion MRI could be important for interpretation (98,104,105).

All the methods outlined above have been explored in clinical studies, described in Supporting Table 3 and summarized in Figure 8. As of September 2022, approximately 52% of studies involving human subjects report rate constants derived from a PK model with a few different models reported. A nearly equal fraction (51%) of the studies report AUC ratio values.

Approximately 66% of these studies report metabolite-specific images or AUC values. About 40% report SNR values; this metric is particularly frequent in manuscripts that describe technical developments for clinical HP MRI. Approximately 16% of these studies summarize model-free metrics, and 10% report measurements from a single timepoint. Most studies report a combination of quantities.

Figure 8: Reported metrics used for analysis in HP [1-13C]pyruvate human studies published up to September 2022.

Visualization

A wide variety of approaches have been used for visualizing data from human HP 13C-MRI studies. The challenges and practical considerations are: 1) choosing the appropriate metrics to display, 2) how to encode the parameters (e.g. the colormap), and 3) choosing how to provide anatomical context and other multi-parametric data. The choice of visualization also depends on the goal which could be for diagnostic interpretation, but also quality control, reproducibility among readers and publication.

Metrics

The choice of HP 13C metrics is described in detail above. At this stage in HP 13C development where there is no standardized metric, often a combination of metabolite images and ratios or PK model parameters are shown.

Parameter Encoding

The mapping function chosen should provide an adequate, often quantitative, impression of the parameter mapped. There is a consensus in the visualization field that perceptually uniform maps are best suited to visualize continuous parameters, like the greyscale typically used by radiologists as well as other monochrome (black to blue) and color ranges (fire-type, rainbow-type) (106,107). Multi-color heatmaps have been the most frequently employed method for HP 13C data, while greyscale has infrequently been used but it ensures there is no coloring-based bias as well as facilitating later reuse (Fig. 9a). Among the color schemes employed in the clinical HP 13C literature, fire-type scheme seems to be the most common [similar to “Plasma” or “Inferno” in matplotlib.org]. Next most commonly employed is the rainbow-type scheme [similar to “Rainbow” in matplotlib.org].

Anatomical Context

HP MRI faces the challenge that it does not necessarily depict the anatomical features, similar to PET, and thus requires an anatomical reference. Most often, a grayscale anatomical image is overlaid with a HP colormap (Fig. 9c,d). This approach is very intuitive, but can skew perception as the grey-scale anatomical reference may affect the brightness of the HP data (e.g. signal in the skull). This bias does not occur when showing adjacent maps (Fig. 9a, b). Here, anatomical outlines may help to provide reference (Fig. 9b).

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