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DOE OSTI2024

Anode Upcycling via Tailored Solvent Treatment

To achieve a truly closed-loop direct recycling process for lithium-ion batteries, all component materials must be recovered. To date, direct recycling method development has primarily focused on the high-value transition-metal cathode materials, while the inherently lower-value graphite has been challenging to recover in a cost-effective manner. However, end-of-life graphite contains a unique engineered value due to the presence of the solid electrolyte interphase (SEI). Growth of the SEI during the cell's active lifetime stabilizes the electronically reactive graphite surface through an irreversible consumption of Li, and thus necessitates both excess lithiation of the cathode and a costly and time-intensive formation procedure during manufacturing. An optimized pre-formed SEI that capitalizes on existing SEI components from end-of-life batteries has the potential to significantly reduce cathode lithiation requirements and eliminate the critical bottleneck of formation cycling during cell remanufacturing. Further, retaining Li at the anode obviates the need for a separate Li leaching and recovery step, improving the overall efficiency of the direct recycling line. In this work, we present a novel approach to "upcycling" spent graphite through use of tailored chemical treatment to remove adverse (i.e., highly resistive and/or poorly passivating) SEI species while retaining beneficially passivating components. We have explored a rational set of solvents spanning a range of polarity, proticity, and molecular size to evaluate structure-property-performance relationships between applied solvent(s), removed and remaining SEI species, and electrochemical response of the resulting graphite product. Further, we have developed and optimized a robust and holistic analysis procedure that couples symmetric-cell electrochemical testing, multi-modal materials characterization, and advanced electrochemical modeling. These analysis results inform a set of correlative metrics for graphite performance relative to both solvent properties and upcycled SEI composition. We demonstrate effective tunability in the residual SEI composition by varying solvent identity and concentration, and report on several promising solvent systems that achieve comparable or performance to pristine graphite.

anode recycling↗

DOE OSTI2025

A machine learning approach to quantify degradation of nuclear fuels and the effects of fission products

Nuclear fuel performance is critically dependent on understanding the evolution of fuel properties under operational conditions, a complex challenge driven by chemical changes and substantial radiation damage during fission. Traditionally, property evolution has been determined via empirical data collected following irradiation. However, these empirical correlations are limited in their applicability beyond the specific conditions in which they were obtained. This study explores a novel approach to address this challenge by applying materials informatics to develop a machine learning random forest (ML-RF) model that captures the effects of fission products on fuel compounds. The model predicts formation enthalpy (ΔH f ) by leveraging extensive quantum materials property data and correlating it with material descriptors such as composition, atomic and site features, and crystal lattice properties. This ML-RF model enables rapid interpolation across the compositional and structural spaces covered by the training data, thus supporting high-throughput screening and energetic ranking of candidate phases. The model demonstrates the ability to predict ΔH f with a mean absolute error (MAE) of approximately 0.1 to 0.2 eV/atom across a wide range of compounds, including key nuclear fuel systems (U-O, U-N, U-C, U-Si, and U-Mo). For example, it was used to assess shifts in stoichiometry for UO 2 (O/M) and UN (N/M) fuels, revealing their distinct tendencies in chemical potential variation and enabling preliminary convex hull analyses. Furthermore, the model provides insights into how individual fission products affect fuel properties. Results indicate that larger fission products (e.g., Nd, Pu, Ce) have a more pronounced impact on UO 2 , while lighter ones (e.g., Zr) strongly influence UN. Here, the model developed in this work can be used to support the Accelerated Fuel Qualification approach by facilitating preliminary evaluations prior to extensive materials modeling and experimentation. To this end, the trained model has been made available to the fuel community to support ongoing fuel development efforts.

Accelerated fuel qualification↗

DOE OSTI2023

Probabilistic Failure Criterion of SiC/SiC Composites Under Multiaxial Loading

Owing to its excellent mechanical properties and stability under high temperature and neutron irradiation conditions, SiC/SiC composites have emerged as a promising material for light water reactors (LWRs) in the development of accident-tolerant fuel (ATF) systems. Structural integrity and retention of hermeticity are two crucial requirements for SiC/SiC claddings during normal operations, and both of them are closely related to the proportional limit stress (PLS) of the material. Understanding the behavior of SiC/SiC composites under multiaxial stress states and developing a probabilistic approach for evaluating the structural vulnerability are of paramount importance for reliability-based analysis and design of SiC/SiC composite claddings. So far, there has been very limited effort towards experimental and analytical investigations of probabilistic failure of SiC/SiC claddings. This critical knowledge gap motivates this research. A probabilistic failure criterion for SiC/SiC composites under multi-axial loading is developed, and this criterion is incorporated into reliability analysis of the structural integrity of SiC/SiC fuel cladding. The research consists of two parts: 1) experimental investigation of multiaxial failure behavior of SiC/SiC composites, and 2) theoretical modeling of time-dependent probabilistic failure of SiC/SiC cladding. In the experimental investigation, the PLS is determined through the examination of stress-strain response, the acoustic emission measurement, as well as the X-ray computed tomography. The theoretical framework is derived by combin- ing the finite weakest-link statistical model and the subcritical damage growth model. This theoretical model captures the time-dependent failure mechanism of the material, which has a major consequence for predicting the lifetime distribution of the cladding. Meanwhile, the model also predicts that the failure statistics of the cladding depends strongly on the cladding length. The results of the multiaxial experiments reveal the level of statistical variation of the PLS of SiC/SiC materials under different stress states. The theoretical model provides a robust analytical tool for extrapolation of small-scale laboratory test results to the behavior of full-scale claddings. These findings establish a scientific foundation for the development of reliability-based design of SiC/SiC fuel claddings, which will play an essential role in improving the structural safety and integrity of LWRs.

42 ENGINEERING↗

DOE OSTI2020

Capacitive deionization using carbon derived from an array of zeolitic-imidazolate frameworks

Capacitive deionization (CDI) represents one of the most thermodynamically efficient technologies for brackish water desalination. Its performance is highly reliant on the surface properties of carbon-based electrodes. Zeolitic-imidazolate framework (ZIF)-derived carbon materials have emerged among the most promising candidates owing to their high structural and compositional tuneability. However, the impacts of the precursory ZIF structure on the properties of the final carbon, and therefore, CDI capacity and efficiency remain to be further explored. In this work, four Zn-based ZIFs with different side-chain substitutions on the imidazolates were synthesized on a gram scale with high yields to produce N-doped carbons by pyrolysis. Next, the resulting carbons along with four commercial carbon blacks were characterized physically and electrochemically to explore the structure-performance relationship. We demonstrated that the imidazole side-chain substitution alters the ZIF's decomposition during pyrolysis, influencing the elemental compositions, surface properties, wettability and graphitization levels. The diverse carbon properties result in variable double layer capacitance and charge-transfer resistance, ultimately impacting the CDI performance. Among these carbons, Zn (4abIm)2-C afforded the greatest salt adsorption capacity of 14.19 mg NaCl $·g_C^{–1}$, while Zn (mIm) 2 -C showed the highest overall salt adsorption capacity and rate; both exceeded the performance of the commercial carbon blacks.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Mechanical Characterization of Stacked Single-Crystal of Polyethylene and Monolayer MoSe 2

Polymer single crystal (SC) is a key building block of semicrystalline polymers. However, direct experimental measurement of freestanding mono-lamella polymer SC has not been demonstrated. This is, in large part, due to the difficulties associated with manipulating freestanding individual mono-lamella SC because of its extremely low rigidity and low robustness. Here, we demonstrate a new strategy to successfully suspend and test a polymer SC by using a 2D material as backing. In particular, mono-lamella polyethylene (PE) SC is stacked on monolayer MoSe 2 , and the hybrid stacks can be suspended over microholes. Nanoindentation is used to probe the suspended PE-SC/MoSe2 stacks and MoSe 2 monolayers. The results suggest the first experimentally-measured in-plane moduli of PE-SC and 2D MoSe 2 as 32 ± 3 and 237 ± 15 GPa, respectively. Such a stacked unit represents an ultrathin structure of polymer-ceramic laminate and the idea can be applied to other laminated composite systems. Therefore, this research will pave the way to accurately measure the mechanical properties of polymer SCs and their composites, as well as provide a key insight on designing composite structures.

36 MATERIALS SCIENCE↗

DOE OSTI2023

High-throughput printing of combinatorial materials from aerosols

The development of new materials and their compositional and microstructural optimization are essential in regard to next-generation technologies such as clean energy and environmental sustainability. However, materials discovery and optimization have been a frustratingly slow process. The Edisonian trial-and-error process is time consuming and resource inefficient, particularly when contrasted with vast materials design spaces 1 . Whereas traditional combinatorial deposition methods can generate material libraries 2,3 , these suffer from limited material options and inability to leverage major breakthroughs in nanomaterial synthesis. Here we report a high-throughput combinatorial printing method capable of fabricating materials with compositional gradients at microscale spatial resolution. In situ mixing and printing in the aerosol phase allows instantaneous tuning of the mixing ratio of a broad range of materials on the fly, which is an important feature unobtainable in conventional multimaterials printing using feedstocks in liquid–liquid or solid–solid phases 4–6 . We demonstrate a variety of high-throughput printing strategies and applications in combinatorial doping, functional grading and chemical reaction, enabling materials exploration of doped chalcogenides and compositionally graded materials with gradient properties. The ability to combine the top-down design freedom of additive manufacturing with bottom-up control over local material compositions promises the development of compositionally complex materials inaccessible via conventional manufacturing approaches.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Magnetic and Optical Properties of Au–Co Solid Solution and Phase-Separated Thin Films and Nanoparticles

The chemical composition and morphology of Au x Co 1–x thin films and nanoparticles are controlled via a combination of cosputtering, pulsed laser-induced dewetting (PLiD), and annealing, leading to tunable magnetic and optical properties. Regardless of chemical composition, the as-deposited thin films and as-PLiD nanoparticles are found to possess a face-centered cubic (FCC) Au x Co 1–x solid-solution crystal structure. Annealing results in large phase-separated grains of Au and Co in both the thin films and nanostructures for all chemical compositions. The magnetic and optical properties are characterized via vibrating sample magnetometry (VSM), ellipsometry, optical transmission spectroscopy, and electron energy loss spectroscopy (EELS). Despite the exceptionally high magnetic anisotropy inherent to Co, the presence of sufficient Au (72 atom %) in the Au x Co 1–x solid solution results in superparamagnetic thin films. Among the as-PLiD nanoparticle samples, an increased Co composition leads to a departure from traditional ferromagnetism in favor of wasp-waisted hysteresis caused by magnetic vortices. Phase separation resulting from annealing leads to ferromagnetism for all compositions in both the thin films and nanoparticles. The optical properties of Au x Co 1–x nanostructures are also largely influenced by the chemical morphology, where the Au x Co 1–x intermixed solid solution has significantly damped plasmonic performance relative to pure Au and comparable to pure Co. Phase separation greatly enhances the quality factor, optical absorption, and electron energy loss spectroscopy (EELS) signatures. The enhancement of the localized surface plasmon resonances (LSPRs) scales with the reduction in Co composition, despite EELS evidence that excitation of the Co portions of a nanoparticle can provide a similar, and in some instances enhanced, LSPR resonance compared to Au. This behavior, however, is seemingly limited to the LSPR dipole mode, while higher-order modes are greatly damped by a Co aloof position. As a result, this observed magneto-plasmonic functionality and tunability could be applicable in biomedicine, namely, cancer therapeutics.

annealing (metallurgy)↗

DOE OSTI2021

Large-scale continuous carbon/glass fiber additive-compression molded composites

Additive Manufacturing (AM) or 3-D printing has advanced from small-scale desktop printers to large-scale printers. Most of the present large-scale printers utilize feedstock materials in the form of pellets to create composite structures. To create structurally robust composite parts, reinforcements in the form of short fibers (carbon or glass) are often used to impart mechanical properties to the printed parts. However, poor mechanical properties in Z-direction and high porosity of pellets-based printed composites compared to composite manufactured using traditional methods are serious concerns. The authors report a combined approach in the present work, where fiber reinforced composites are printed with a high-throughput continuous fiber deposition method followed by a secondary compression molding process. A specially designed end-effector mounted on a robotic arm is used to print composite preforms. Continuous comingled fibers (Thermofiber 12K CF-PA12, Thermofiber 12K S2-PA12, and Hybrid Thermofiber 12K CF-PA12+PEEK PA6) embedded in the thermoplastic nylon matrix are printed to create composite preform plaques. The printed preforms were further compression molded (CM) using a hydraulic hot-press to create highly consolidated composite parts. The mechanical properties of the continuous fiber composites produced by this combined approach are improved significantly due to the highly aligned continuous fibers and reduced porosity. Flexural strength, flexural modulus, and tensile modulus of AM-CM Thermofiber 12K CF-PA12 UD sample were 615.37 MPa, 75.65 GPa, and 122.23 GPa, respectively.

Kumar, Vipin↗

DOE OSTI2020

Molecular and Topographical Organization: Influence on Cicada Wing Wettability and Bactericidal Properties

Numerous natural surfaces have micro/nanostructures that result in extraordinary functionality, such as superhydrophobicity, self-cleaning, antifogging, and antimicrobial properties. One such example is the cicada wing, where differences in nanopillar geometry and composition among species can impact and influence the degree of exhibited properties. To understand the relationships between surface topography and chemical composition with multifunctionality, the wing properties of Neotibicen pruinosus (superhydrophobic) and Magicicada cassinii (hydrophobic) cicadas are investigated at time points after microwave-assisted extraction of surface molecules to characterize the chemical contribution to nanopillar functionality. Electron microscopy of the wings throughout the extraction process illustrates nanoscale topographical changes, while concomitant changes in hydrophobicity, bacterial fouling, and bactericidal properties are also measured. Extract analysis reveals the major components of the nanostructures to be fatty acids and saturated hydrocarbons ranging from C17 to C44. Effects on the antimicrobial character of a wing surface with respect to the extracted chemicals suggest that the molecular composition of the nanopillars plays both a direct and an indirect role in concert with nanopillar geometry. The data presented not only correlates the nanopillar molecular organization to macroscale functional properties, but it also presents design guidelines to consider during the replication of natural nanostructures onto engineered substrates to induce desired properties.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Performance analysis of functionally graded multifunctional piezoelectric energy harvesting microgyroscopes

Functionally graded materials (FGMs) are composite materials with varying material properties in one or more directions. These materials possess distinct characteristics compared to their constituent components. The ability to control material distribution and compositions in FGMs offers improved constraints over the natural frequencies of the system, making them highly suitable for energy harvesting applications. In this study, we focus on a piezoelectric FGM composed of Platinum (Pt) and Lead Titanate Zirconate (PZT). By utilizing FGMs for energy harvesting, we simplify the system from a multilayer structure to a single-layer system, thereby increasing power density by reducing volume. In this work, a power law distribution is used to model the material variation throughout the thickness of the single-layered beam. The governing equations of motion and boundary conditions for FG energy harvesting microgyroscope are derived using Euler-Bernoulli beam theory, the constitutive piezoelectric principle, and the extended Hamilton's principle. To simulate the nonlinear motion of the FG energy harvester, we employ the differential quadrature method (DQM). Subsequently, an investigation is carried out to examine the effects of various factors including material distribution, platinum percentage, base rotation, DC voltage, and electrical load resistance on the energy harvesting microgyroscope with functionally graded materials. Here, the findings suggest that functionally graded energy harvesting gyroscopes can be adjusted to obtain effective energy harvesting and sensing capabilities by carefully selecting the material distribution, input voltage, and electrical load resistance.

42 ENGINEERING↗

DOE OSTI2025

Predicting multi-nodal in-nozzle particle interactions in high-viscosity fluid mediums for acoustophoretic direct-ink writing of line-patterned composites

Patterned functional materials offer improved properties (electrical, thermal, etc.) over their bulk counterparts in many applications, including energy storage, flexible electronics, and sensors. However, manufacturing approaches for patterning materials over large areas with features on the order of hundreds of microns or less are limited. Acoustophoresis, which uses acoustic forces to control particle arrangement in a fluid medium, is a pathway to address this challenge. This process is dependent on particle and fluid properties and enables patterning of a broad range of materials. Herein, a model with experimental validation is presented to demonstrate that acoustophoresis can be combined with direct-ink writing (DIW) to fabricate line patterns over large cm-scale areas. An in-nozzle particle interaction model was developed to investigate the impact of processing conditions on multi-nodal acoustophoretic DIW. The model predicts patterned line widths within a factor of two relative to experimental results for a high viscosity case study. Here, the model was used to investigate the impact of frequency, particle loading, particle radius, and acoustic pressure on line width and patterning time, providing critical feedback regarding the processing conditions suitable for a target application. Model results illustrate that frequency has the greatest impact on line patterns: increasing from 1 to 3 MHz resulted in a greater than 65% reduction in line width and a greater than 85% reduction in patterning time. Additionally, experiments were conducted with an alumina-epoxy ink and a ~21 cm 2 area pattern was rastered in ~5.5 minutes, demonstrating a path towards large-area line-patterned composite fabrication.

25 ENERGY STORAGE↗

DOE OSTI2020

Disorder effects in nitride semiconductors: impact on fundamental and device properties

Abstract Semiconductor structures used for fundamental or device applications most often incorporate alloy materials. In “usual” or “common” III–V alloys, based on the InGaAsP or InGaAlAs material systems, the effects of compositional disorder on the electronic properties can be treated in a perturbative approach. This is not the case in the more recent nitride-based GaInAlN alloys, where the potential changes associated with the various atoms induce strong localization effects, which cannot be described perturbatively. Since the early studies of these materials and devices, disorder effects have indeed been identified to play a major role in their properties. Although many studies have been performed on the structural characterization of materials, on intrinsic electronic localization properties, and on the impact of disorder on device operation, there are still many open questions on all these topics. Taking disorder into account also leads to unmanageable problems in simulations. As a prerequisite to address material and device simulations, a critical examination of experiments must be considered to ensure that one measures intrinsic parameters as these materials are difficult to grow with low defect densities. A specific property of nitride semiconductors that can obscure intrinsic properties is the strong spontaneous and piezoelectric fields. We outline in this review the remaining challenges faced when attempting to fully describe nitride-based material systems, taking the examples of LEDs. The objectives of a better understanding of disorder phenomena are to explain the hidden phenomena often forcing one to use ad hoc parameters, or additional poorly defined concepts, to make simulations agree with experiments. Finally, we describe a novel simulation tool based on a mathematical breakthrough to solve the Schrödinger equation in disordered potentials that facilitates 3D simulations that include alloy disorder.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2022

Identification of Distribution of Elastic Constants of SiC/SiC Braided Tubes

There has been considerable interest in chemical vapor infiltration (CVI) manufactured silicon carbide fiber and silicon carbide matrix (SiCf/SiCm) composite tubes due to their superior mechanical properties. There are many parameters in the manufacturing of SiCf/SiCm composite tubes such as elastic constants of constituent SiC fiber and SiC matrix, braiding angle, porosity, and others whose values vary over a range. A sensitivity analysis will be carried out to determine the dominant parameters among the abovementioned ones. We intend to determine the variability in elastic constants of SiCf/SiCm composite tubes considering the variability in dominant parameters. A chosen number of combinations of dominant variables will be sampled through Latin hypercube sampling (LHS) method. The elastic constants of composite tube namely Young's moduli in circumferential and longitudinal direction, Poisson's ratio and shear modulus will be calculated at sampled points through finite element (FE) analysis. A polynomial response surface (PRS) will be built for each of the elastic constants to be used a surrogate to FE analysis. once the predictive accuracy of PRS is verified at the validation set of data points, the PRS will be invoked 105 times in Monte Carlo simulations (MCS). The variability can be calculated based on MCS-generated data which will be presented at the conference.

42 ENGINEERING↗

DOE OSTI2022

A machine learning approach to determine the elastic properties of printed fiber-reinforced polymers

This work focuses on the simultaneous determination of the elastic constants and the fiber orientation state for a short fiber-reinforced polymer composite by performing a minimum of experimental tests. Here we introduce a methodology that enables the inverse determination of fiber orientation state and the in-situ polymer properties by performing tensile tests at the composite coupon level. We demonstrate the approach for the extrusion deposition additive manufacturing (EDAM) process to illustrate one application of the methodology, but the development is such that it can be applied to short fiber-reinforced polymer (SFRP) systems processed via other methods. Currently, developing composites additive manufacturing digital twins require extensive material characterization. In particular, the mechanical characterization of the orthotropic elastic properties of a composite involves extensive sample preparation and testing, therefore the elasticity tensor is generally populated using a micromechanics model. This, however, requires measuring the fiber orientation state in addition to knowing the constituent material properties. Experimentally measuring the fiber orientation state can be tedious and time consuming. Further, optical methods are limited to resolving the orientation of cylindrical fibers or cluster of non-cylindrical fibers, and computed tomography (CT) methods scan regions of volume that are much smaller than a full printed bead. Therefore, we propose a methodology, accelerated by machine learning, to identify the anisotropic mechanical properties and fiber orientation state at the same time. Early results show that inference of the fiber orientation and composite properties is possible with as few as three tensile tests. Our results show that a combination of the choice of the micromechanics model and reliable set of experiments can yield the nine elastic constants, as well as, the fiber orientation state.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Exploring the impact of nucleotide length on lipid nanoparticle structure and properties

Lipid nanoparticles (LNPs) are versatile carriers for nucleic acid (NA) therapeutics, including ASOs, siRNA, mRNA, and poly-IC. While lipid composition is known to influence LNP properties, the impact of NA length on morphology and internal structure is less understood, particularly during the stages of carrier–cargo assembly. Here, we examine NA length and lipid composition immediately after mixing using high-throughput SAXS, dynamic light scattering, and cryogenic electron microscopy. All LNPs form ordered NA/lipid compartments, with longer NAs promoting inverse hexagonal (H II ) phases and larger intercompartment distances. In contrast, short NAs, especially in formulations with SM102 ionizable lipid, favor lamellar phases. SAXS peak deconvolution quantifies ordered versus disordered phases via a Robustness of Ordered Phase factor, which correlates with particle size and encapsulation efficiency. Formulations with MC3 ionizable and DOPE helper lipids exhibit the most stable H II -phase packing, highlighting the role of helper-lipid curvature in compartment stabilization. Variations in NA compartmentalization indicate differences in payload capacity, offering a framework for rational LNP design across diverse nucleic acid cargos.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2025

Repurposing Post-Consumer Polyethylene to Access Cross-Linked Polyethylene with Reprocessabilty, Recyclability, and Tunable Properties

Polyethylene (PE) is the most widely produced plastic but accumulation and resistance to degradation has significantly contributed to the plastic waste crisis. Upcycling has presented promising solutions to transform PE waste into value-added products. In this study, mixed post-consumer PE was successfully repurposed into reprocessable and chemically recyclable cross-linked polyethylene (XLPE). This process involved converting PE into telechelic oligomers, followed by repolymerization using a hybrid cross-linking system consisting of a dynamic cross-linker 2,4,6-triethoxy-1,3,5-triazine (TETA) and non-dynamic cross-linker tris(6-isocyanatohexyl)isocyanurate (Tri-HDI). In the resulting XLPE, TETA facilitated iterative reprocessing with minimal property degradation across cycles, whereas Tri-HDI helped preserve functional performance throughout service life. Compared to PE, XLPE exhibited enhanced mechanical properties, reduced creep deformation under application-relevant temperatures, and high temperature structural stability. Notably, copolymerizing PE oligomers with commercial macrodiols was employed to create composite XLPEs, enabling tuning material properties. After use, XLPE can be efficiently and selectively depolymerized under mild conditions, even when mixed with commercial insulator cables. This depolymerization allows for the recovery of the constituent building blocks, enabling purification and subsequent repolymerization for reuse. This approach demonstrates the potential of repurposing plastic waste into sustainable materials and fostering the development of a circular economy.

INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMI↗

DOE OSTI2025

Predicting Thermoset Resin Cure Kinetics for Composite Processing

Predicting a material’s thermal properties is not only useful for designing parts but also for defining processing parameters. This is especially applicable to wet-filament winding operations and the production of composite parts using thermoset res ins. For these, the formation of cross-linking bonds is affected by time and temperature, but the degree of cross-linking can be modeled using phenomenological methods. In the current study, the Kissinger and Flynn/Wall/Ozawa methods were both used to calculate kinetic parameters and produced values that were in agreement with each other. The kinetic parameters activation energy ( E a ) and pre-exponential factor (𝐴) calculated from exothermic peak data increased between an epoxy and resole phenol resin system, with a cyanate ester having the highest. The successful application of both methods suggests applicability to future studies for developing cure recipes.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Investigation of the effects of ternary deep eutectic solvent composition on pretreatment of sorghum stover

Biomass‐derived deep eutectic solvents (DESs) have been introduced as promising pretreatment and fractionation solvents because of their mild processing conditions, easy synthesis, and green solvent components from biomass. In recent DES studies, solvent‐based third constituents like water, ethanol, and others improve the processibility of typical binary DESs. However, the impacts of these components are not well understood. Here, two solvent‐based constituents, including water and ethylene glycol, were applied to 3,4‐dihydroxybenzoic acid (DHBA)‐based DES system for improving the conversion efficiency of cellulose‐rich fraction and the properties of lignin fraction. Chemical composition, enzymatic digestibility, degree of polymerization of cellulose and physicochemical properties of lignin were used to evaluate the impact of each third constituent on biomass processing. Ternary ChCl‐DHBA DESs exhibited better performances in delignification, fermentable sugar production, and preservation of β‐O‐4 ether linkage in lignin compared with binary ChCl‐DHBA DES.

09 BIOMASS FUELS↗