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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Solvent Transport in Disordered and Dynamic Membrane Pores: Implications for Reverse Osmosis and Nanofiltration Membranes

Pressure-driven separations with nanoporous membranes, such as reverse osmosis and nanofiltration, play a vital role in addressing water scarcity and enabling resource recovery. Understanding water or solvent transport in membrane pores is essential for advancing membrane separation technologies. A key question in transport modeling is to establish a relationship between solvent permeability and membrane porous structure properties, such as porosity or pore size. The nano- and subnanometer pores in polymeric membranes such as reverse osmosis and nanofiltration membranes are highly tortuous and dynamically connected, which challenges the conventional methods of transport modeling. This study addresses this challenge by developing a theoretical framework to describe solvent transport through membranes with dynamic and disordered porous structure. Specifically, we propose a lattice model to describe the pore network, while preserving the viscous nature of solvent permeation. We further establish a relationship between solvent permeability and membrane porosity or pore size, which is validated by molecular dynamics simulations and experimental data. By integrating this relationship into the solution-friction model, we define pore connectivity and local friction coefficient to quantify the impact of pore structure on solvent permeability. Our analysis highlights the dominant influence of pore connectivity on the permeability of reverse osmosis and nanofiltration membranes, particularly when the pore size approaches the dimensions of solvent molecules. Overall, this study provides critical insights into water and solvent transport mechanisms in nanoporous membranes, opening the door for strategies to substantially enhance membrane performance.

membranes↗
DOE OSTI2025

Advanced Materials & Manufacturing Technology (AMMT): Process understanding for qualifying LPBF 316H SS

Investigations were conducted in fiscal years (FY) 2023 and 2024 to gather relevant data sets addressing challenges related to qualifying 316H stainless steel (SS) for use in future nuclear reactors. This work was a collaborative effort involving researchers from Idaho National Laboratory (INL), Argonne National Laboratory (ANL), and Oak Ridge National Laboratory (ORNL). Key outcomes included: • Development of process-structure-property data sets to better understand the relationships between manufacturing processes, material structure, and performance characteristics. • Establishment of an in-situ monitoring system to link these various data sets together. • Detailed characterization of the raw material feedstock to further strengthen the understanding of process-structure and process-property relationships. Building on this foundation, in FY25 there was interest in exploring the behavior of additively manufactured 316H SS under different test conditions to support the overall material qualification process. Los Alamos National Laboratory (LANL) was tasked with providing specimen samples to the collaborating labs, who then conducted a round-robin study examining factors like selective heat treatment, low-cycle fatigue (LCF), and tensile-creep (T-C) properties. Additionally, high-temperature differential scanning calorimetry (DSC) was performed by LANL to better understand how the material's thermal characteristics change as it is heated up to the melting point. This provided a more comprehensive understanding of the material's behavior. The combined results from these investigations could potentially be used to support the inclusion of 316H stainless steel in Section III, Division 5 of the relevant codes and standards, allowing its use in future nuclear reactor applications.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Kinetic control of phase evolution and defect-mediated recombination in AACVD-grown copper antimony sulphide thin films

Copper antimony sulphide (CAS) is a multinary chalcogenide semiconductor in which small deviations from stoichiometry can drive phase competition and strong defect-mediated modulation of optoelectronic properties. However, the systematic roles of copper precursor fraction and deposition time in governing phase evolution, off-stoichiometry, and recombination dynamics in aerosol-assisted chemical vapour deposition (AACVD)-grown undoped CAS thin films remain insufficiently understood. In this work, undoped CAS thin films were deposited by AACVD using Cu(dedtc)2 and Sb(dedtc)3 single-source precursors at 550 °C and a carrier gas flow rate of 150 sccm, while the Cu(dedtc)2 mole fraction (x = 0.15 – 0.55) and deposition time (1 – 2 hours) were systematically varied to probe how growth kinetics influence phase composition, microstructure, and defect-mediated optical properties without post-deposition annealing or extrinsic doping. Increasing copper precursor content drives phase evolution toward tetrahedrite-dominant CAS films at intermediate Cu(dedtc)2 mole fractions, with the film deposited at x = 0.35 exhibiting the strongest tetrahedrite character within the parameter space examined. The films are also copper-rich, antimony-poor, and sulphur-deficient, consistent with off-stoichiometric growth and intrinsic defect formation, plausibly including copper interstitials, Cu-on-Sb antisites, and sulphur vacancies. These growth-dependent compositional deviations are accompanied by tunable indirect optical bandgaps of approximately 1.60 – 2.18 eV and weak visible photoluminescence governed by defect-mediated recombination. Time-resolved photoluminescence reveals bi-exponential decay behaviour with lifetimes of approximately 0.1 – 3.6 ns, with emission dominated by slower donor–acceptor pair recombination and a smaller contribution from faster trap-assisted pathways. Collectively, these results establish an explicit kinetic process–structure–defect–property relationship for AACVD-grown CAS thin films and provide a growth–structure–property framework relevant to future optimization of CAS-based optoelectronic and energy materials.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Machine Learning‐Guided Discovery of High‐Entropy Perovskite Oxide Electrocatalysts via Oxygen Vacancy Engineering

Abstract High‐entropy perovskite oxides (HEPOs) have recently emerged as multifunctional catalysts. However, the HEPOs’ structural and compositional complexity hinders the easy and accurate extrapolation of activity indicators, which are essential for establishing structure‐property correlations. Here, OxiGraphX, is introduced as a novel graph neural network (GNN) model designed to capture the complex relationships among structure, composition, and atomic chemical environments for accurate prediction of oxygen vacancy formation energies (OVFEs) in HEPOs. By integrating machine learning (ML), density functional theory (DFT), and experimental validation, this work demonstrates an efficient framework for rapidly and accurately screening HEPO electrocatalysts for oxygen evolution reaction (OER). The OxiGraphX predicts OVFEs with a precision exceeding existing data, enabling the identification of compositions of higher oxygen vacancy content (OVC) and, thus, higher catalytic activity. Furthermore, the model explores latent spaces that translate effectively into experimental domains, bridging computational predictions with real‐world applications. This approach accelerates the discovery of high‐performance HEPO catalysts while providing deeper insights into their catalytic mechanisms.

Chemistry↗
NASA NTRS1996

Differences in Femoral Geometry and Structure Due to Immobilization

Reduction in bone mass of the lower extremity is well documented in individuals with paralysis resulting from spinal cord injury (SCI). The consequent osteopenia leads to elevated fracture risk with fractures occurring more commonly in the femoral shaft and supracondylar regions than the hip. A model has recently been described to estimate geometry and structure of the femoral midshaft from whole body scans by dual X-ray absorptiometry (DXA). Increases in femoral geometric and structural properties during growth were primarily related to mechanical loading as reflected by body mass. In this study, we investigate the relationship between body mass and femoral geometry and structure in adults with normal habitual mechanical loading patterns and those with severely reduced loading. The subjects were 78 ambulatory men (aged 20-72 yrs) and 113 men with complete paralysis from SCI of more than 4 years duration (aged 21 73 yrs). Subregional analysis was performed on DXA whole body scans to obtain bone mineral content (BMC, g), cortical thickness (cm), crosssectional moment of inertia (CSMI, cm4), and section modulus (cm3) of the femoral midshaft. All measured bone variables were significantly lower in SCI compared with ambulatory subjects: -29% (BMC), -33% (cortical thickness), -23% (CSMI), and -22% (section modulus) while body mass was not significantly different. However, the associations between body mass and bone properties were notably different; r2 values were higher for ambulatory than SCI subjects in regressions of body mass on BMC (0.48 vs 0.20), CSMI (0.59 vs 0.32), and section modulus (0.59 vs 0.31). No association was seen between body mass and cortical thickness for either group. The greatest difference between groups is in the femoral cortex, consistent with reduced bone mass via endosteal expansion. The relatively lesser difference in geometric and structural properties implies that there is less effect on mechanical integrity than would be expected from bone mass results alone. The reduced association in SCI subjects between body mass and bone properties is not unexpected. Although mean body mass differs little between ambulatory and SCI individuals, the association between body mass and in vivo skeletal loading is no longer present, as mechanical influences are removed except for transfer activities. The residual association is probably attributable to the strength of this influence during growth. These results highlight the importance of examining geometry and structure in conjunction with bone mass.

Kiratli, Beatrice Jenny↗
DOE OSTI2025

Simultaneous prediction of structural properties in epitaxially–grown GaN with quantum and conventional multi–output learning algorithms

Hundreds of GaN thin film crystal plasma–assisted molecular beam epitaxy synthesis experiment records spanning two decades were organized into a dataset correlating the growth experiment design parameters with discrete, binary determinations of crystallinity and surface morphology. Conventional data science techniques as well as both quantum and classical multi–output supervised machine learning algorithms were implemented to investigate the relationships between the operating parameter data and the structural figures of merit. Correlation coefficients, decision tree nodes, p–values, and SHAP values all support substrate temperature and gallium effusion cell conditions as being statistically significant for simultaneously influencing GaN crystallinity and surface morphology. Here, a conventional deep neural network learned best from the data, followed by a quantum–classical hybrid gradient boosting algorithm. When combined with calculations of uncertainty intervals based on VennAbers predictors, machine learning predictions of both structural properties show good agreement with results reported in published experimental literature.

36 MATERIALS SCIENCE↗
NASA NTRS1995

Investigation of Strain Aging in the Ordered Intermetallic Compound beta-NiAl

The phenomenon of strain aging has been investigated in polycrystalline and single crystal NiAl alloys at temperatures between 300 and 1200 K. Static strain aging studies revealed that after annealing at 1100 K for 7200 s (i.e., 2h) followed by furnace cooling, high purity, nitrogen-doped and titanium-doped polycrystalline alloys exhibited continuous yielding, while conventional-purity and carbon-doped alloys exhibited distinct yield points and Luders strains. Prestraining by hydrostatic pressurization removed the yield points, but they could be reintroduced by further annealing treatments. Yield points could be reintroduced more rapidly if the specimens were prestrained uniaxially rather than hydrostatically, owing to the arrangement of dislocations into cell structures during uniaxial deformation. The time dependence of the strain aging events followed at t(exp 2/3) relationship suggesting that the yield points observed in polycrystalline NiAl were the result of the pinning of mobile dislocations by interstitials, specifically carbon. Between 700 and 800 K, yield stress plateaus, yield stress transients upon a ten-fold increase in strain rate, work hardening peaks, and dips in the strain rate sensitivity (SRS) have been observed in conventional-purity and carbon-doped polycrystals. In single crystals, similar behavior was observed; in conventional-purity single crystals, however, the strain rate sensitivity became negative resulting in serrated yielding, whereas, the strain rate sensitivity stayed positive in high purity and in molybdenum-doped NiAl. These observations are indicative of dynamic strain aging (DSA) and are discussed in terms of conventional strain aging theories. The impact of these phenomena on the composition-structure-property relations are discerned. Finally, a good correlation has been demonstrated between the properties of NiAl alloys and a recently developed model for strain aging in metals and alloys developed by Reed-Hill et al.

Weaver, Mark Lovell↗
DOE OSTI2025

Pressure-induced irreversible volume collapse in a high-entropy alloy

At ambient conditions, the high-entropy alloy superconductor R⁢e 0.6⁢ (NbTiZrHf) 0.4 exhibits exceptional mechanical properties among high-entropy alloys, with its hexagonal phase achieving nanoindentation hardness of 18.5 GPa. We report on a unique pressure-induced structural transformation from a hexagonal phase to a body-centered cubic (BCC) phase, revealed by synchrotron x-ray diffraction measurements up to 70 GPa. This first-order transition, accompanied by a 6.1% volume collapse, occurs at 44 GPa and results in a BCC structure with random site occupancy by the five constituent elements, which is remarkably retained upon decompression to ambient conditions. The transformation proceeds via a martensiticlike, diffusionless mechanism without elemental segregation, enabled by pressure-induced electronic redistribution and atomic-scale disorder. These findings demonstrate a rare case of metastable phase retention in a chemically complex alloy and offer new insights into structure-stability relationships under pressure.

Alloys↗
DOE OSTI2025

Additive manufacturing of metal matrix composites

Although Metal matrix composites (MMCs) are superior to most sought-after metallic alloys, their challenging fabricability has limited their widespread use in bulk-form applications. Among the many advanced fabrication techniques, Additive Manufacturing (AM), owing to its unique capabilities to produce near-net shapes, has drawn significant traction in the past two decades, especially for materials that are difficult to process using traditional methods. However, unlike pure metal/alloy systems, MMCs are highly sensitive to the processing conditions prevailing in AM techniques due to factors such as the high melting point of reinforcement particles and the potential for in-situ reactions. Therefore, it may be a while before metal matrix composites are commercially produced via AM. This review will discuss the current state-of-the-art design, fabricability, and performance of various additively manufactured MMCs. A particular focus will be on microstructural evolution and microstructure-property relationships. The most employed AM techniques, such as directed energy deposition, powder bed fusion, binder jetting, sheet lamination, and solid-state friction stir processing, are fundamentally different in terms of thermo-kinetics, forming the perspective for this review. A detailed comparison of microstructural evolution and process parameter optimization, including feedstock preparation methods and the role of machine learning and modeling among the different AM processes, is also presented. Finally, a critical evaluation of emerging AM technologies for MMCs is also provided, highlighting their potential advantages and challenges.

36 - MATERIALS SCIENCE↗
DOE OSTI2025

Understanding the Active Site Structures and Achieving Catalytic Activity Tuning of Atomically Dispersed FeN 4 Sites for Oxygen Reduction Reaction

Atomically dispersed Fe–—N—C catalysts with high oxygen reduction reaction (ORR) activity have attracted great attention since the last decade. Due to comparable ORR activity and low material cost, they are promising platinum group metal (PGM)-free catalysts that can replace the commercialized Pt/C materials; furthermore, it can facilitate the efficiency of the fuel cell technologies and mitigate dependence on fossil fuels. Great advancements have been made to experimentally optimize the synthesis approach of the Fe–—N—C catalysts, enhance the ORR activity, and improve the catalyst stability. Similarly, recent theoretical studies also provide enriched understanding of the active site structures, properties, and reaction mechanisms. In this review, discussions are made upon utilizing combined experimental and computational spectroscopy to reveal the active site structures, employing mechanistic studies to investigate reaction thermodynamics and kinetics, as well as developing scaling relationships to assist the design and development of future PGM-free catalyst materials. Furthermore, recent advances in studying Fe–—N—C catalysts utilizing electrified surface models and explicit solvation models are also discussed. Not only can these aspects improve the accuracy of theoretical simulation and predictions but also deepen the understanding of the catalyst properties and reaction mechanisms under the effect of surface charges and solvent molecules.

Fe single-atom catalysts↗
DOE OSTI2026

Electron beam irradiation effects on bulk metals: a comparative study of polycrystalline versus single-crystalline structures

This study investigates the effects of electron beam (e-beam) irradiation on the mechanical and structural properties of eight bulk metallic samples, comprising both polycrystalline (PC) and single-crystalline (SC) forms of Ni, Cr, V, and Ti. These metals were evaluated as potential candidates for beam exit windows in high-power (MW-class) particle accelerators. The primary objective is to identify metals capable of withstanding the conditions of high-power/MW-class e-beam accelerators and serve effectively as exit windows. Selection criteria were based on each metal’s intrinsic properties, power dissipation capability, and irradiation-induced changes in mechanical behavior, including hardness, elastic modulus, and defect density. Comprehensive characterization was conducted using field-emission scanning electron microscopy (FESEM), atomic force microscopy (AFM), scanning electron microscopy with energy-dispersive X-ray spectroscopy (SEM–EDS), X-ray diffraction (XRD), high-resolution transmission electron microscopy (HRTEM), selected area electron diffraction (SAED), and nanoindentation, performed both before and after exposure to a ~¿66 kGy dose from a 10 MeV e-beam accelerator. Results revealed that e-beam irradiation induced hardening in PC Ni, whereas PC Ti, commonly used in beam exit windows, exhibited softening. The observed softening in PC Ti is attributed to grain coarsening, elongation, and the formation of twins and twin boundaries, in contrast to the smaller, compressed grains in the pristine (Pr) PC Ti samples, consistent with the Hall–Petch relationship. The stresses due to twinning are small and insignificant in influencing the overall hardening of the PC Ti irradiated sample when compared to the stresses due to the dislocation density. Conversely, SC Ti samples exhibited irradiation-induced hardening. The SC Ti irradiated samples developed additional irradiation-induced modifications in crystallographic texture of (100), (101), (110), (200), (112), (004), and (211) as evidenced from the XRD results, which could probably explain the hardening effect that is caused by irradiation.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Ligand-Driven Electrochemical Tuning of Co 6 Se 8 Chevrel Clusters

Molecular “Chevrel-type” clusters of the formula Co 6 Se 8 L 6 (L = neutral ligand) are a well-studied class of clusters due to their utility as molecular analogues to the Chevrel extended solid phase and their application as subunits in hierarchical materials. However, their solution and optical properties remain relatively underexplored. Aiming to develop the fundamental relationships between the molecular and electronic structures of these clusters and their electrochemical and photophysical properties, this work reports the preparation of a series of Co 6 Se 8 (P­(C 6 H 4 R) 3 ) 6 -type clusters with R = Cl (1), F (2), H (3), CH 3 (4), and OCH 3 (5) via a stepwise synthetic approach. Solution and solid-state experimental characterization and density functional theory calculations reveal that the Co 6 Se 8 cores of 1–5 maintain consistent electronic and structural properties despite the variation of the triarylphosphine ligand para-substituent Hammett parameters (σ p ). However, cyclic voltammetry measurements indicate that the electron transfer energetics of 1–5 are strongly influenced by ligand substitution, with the E 1/2 of a given redox event spanning ∼0.5 V depending on the triarylphosphine ligand’s σ p . In conclusion, these findings support the characterization of Co 6 Se 8 clusters as atomically precise nanoclusters with both the structural robustness and the electrochemical tunability needed to act as components in larger charge transfer assemblies.

Wheaton, Amelia M. [Argonne National Laboratory (A↗
DOE OSTI2025

Amino Acid Sequence Controls Enhanced Electron Transport in Heme-Binding Peptide Monolayers

Metal-binding proteins have the exceptional ability to facilitate long-range electron transport in nature. Despite recent progress, the sequence-structure–function relationships governing electron transport in heme-binding peptides and protein assemblies are not yet fully understood. In this work, the electronic properties of a series of heme-binding peptides inspired by cytochrome bc1 are studied using a combination of molecular electronics experiments, molecular modeling, and simulation. Self-assembled monolayers (SAMs) are prepared using sequence-defined heme-binding peptides capable of forming helical secondary structures. Following monolayer formation, the structural properties and chemical composition of assembled peptides are determined using atomic force microscopy and X-ray photoelectron spectroscopy, and the electronic properties (current density–voltage response) are characterized using a soft contact liquid metal electrode method based on eutectic gallium–indium alloys (EGaIn). Our results show a substantial 1000-fold increase in current density across SAM junctions upon addition of heme compared to identical peptide sequences in the absence of heme, while maintaining a constant junction thickness. These findings show that amino acid composition and sequence directly control enhancements in electron transport in heme-binding peptides. Overall, this study demonstrates the potential of using sequence-defined synthetic peptides inspired by nature as functional bioelectronic materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Era of entropy: Synthesis, structure, properties, and applications of high-entropy materials

The field of high-entropy materials (HEMs) has emerged as a dynamic area of scientific exploration, driven by the exceptional properties arising from their compositional complexity. Encompassing both high-entropy alloys (HEAs) and high-entropy ceramics (HECs), these materials have garnered significant attention across diverse research domains. From investigations into phase evolution and mechanical characteristics to studies of ionic, electronic, and magnetic behaviors, HEMs demonstrate remarkable potential for a wide array of applications. These range from catalysis and tribology to energy storage and superconductivity. Fundamental research has shed light on crucial phenomena such as configurational entropy, lattice distortion, and sluggish diffusion. These discoveries are paving the way for materials design strategies that enable new functional tunability and resistance to application-specific harsh environments. This burgeoning field promises to revolutionize material design and performance across numerous technological sectors. Here, this special collection between Applied Physics Letters and the Journal of Applied Physics provides a timely overview of the latest research in this area. It highlights the growing interest in understanding the impact of high compositional complexity on conventional structure–process–property–performance relationships in HEMs.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Statistical generic design of glass and optimization: Selective review on oxide glasses

Designing a single glass composition for a multidimensional property space is challenging, and the difficulty increases with the number of design criteria. Traditionally, the task is accomplished using multiple statistical models that describe the relationships between composition (C) and property (P) values, i.e., C-P models. Recently, the structure (S)-property (P) statistical modeling has emerged as a complementary approach. The S-P modeling approach has also been shown to be a preferred method for modeling glass properties, particularly when a small data set is available, such as in single-component studies, or when strong nonlinearities exist between composition and properties. The combined model package, C-S-P, implements the concept of generic glass design, i.e., designing glass for performance by first selecting a specific or optimized set of glass network structural groups using S-P models and then transferring the designed structures (genes) to a particular composition using C-S models. This article reviews a set of supporting cases from the previous C-S-P modeling studies of phosphate, silicate, and borosilicate glasses, which are relevant for many critical commercial applications. The methodology for developing the statistical C-S-P database is presented, enabling the application of P?S?C to achieve a generic glass design and optimization, targeting multiple design criteria for both performance and processing properties simultaneously.

Network structure↗
DOE OSTI2024

Materials Characterization, Prediction and Control Project: Summary Report on Data Analytics Framework

This report summarizes the activities performed under the data analytics Vertex in the Materials Characterization, Prediction and Control Project funded under laboratory directed research and development at Pacific Northwest National Laboratory. The data analytics Vertex developed models for associating global or local process parameters, microstructural features, and performance properties of friction-stir-processed 316L stainless steel plates. Statistical, machine learning, and deep learning models, as well as generative artificial intelligence approaches, were used to develop the associations between the process-structure-property data streams. These associations formed the basis for predicting global properties of parts manufactured under different process envelopes, providing a basis for predicting performance using data driven as well as physics-informed and physics-constrained approaches. Additionally, the associations were used to predict local process parameters and microstructural features of the product, predictive relationships that have the potential to form the basis of a control framework that could eventually modulate a friction-stir process to maintain product quality.

316L stainless steel↗
DOE OSTI2026

Compressive Response and Energy Absorption of Additively Manufactured Elastomers with Varied Simple Cubic Architectures

Additive manufacturing, and particularly the vat photopolymerization process, enables the fabrication of complex geometries at high resolution and small length scales, making it well-suited for fabricating cellular structures (e.g., foams and lattices). Among these, elastomeric cellular structures are of growing interest due to their tunable compliance and energy dissipation. However, comprehensive data on the compressive behavior of these structures remains limited, especially for investigating the structure-property effects from changing the density and distribution of material within the cellular structure. This study explores how the mechanical response of polyurethane-based simple cubic structures changes when varying volume fraction, unit cell length, and unit cell patterning, which have not been systematically investigated previously in additively manufactured elastomers. Increasing volume fraction from 10% to 50% yielded significant changes in compressive stress–strain performance (decreasing strain at 0.5 MPa by 41.6% and increasing energy absorption density by 3962.5%). Although changing the unit cell length between 2.5 and 7 mm in ~30 mm parts did not result in statistically different stress–strain responses, modifying the configuration of struts of different thicknesses across designs with 30% volume fraction altered the stress–strain behavior (differences of 12.5% in strain at 0.5 MPa and 109.4% for energy absorption density). Power law relationships were developed to understand the interactions between volume fraction, unit cell length, and elastic modulus, and experimental data showed strong fits (R 2 > 0.91). These findings enhance the understanding of how multiple structural design aspects influence the performance of elastomeric cellular materials, providing a foundation for informing strategic design of tailorable materials for diverse mechanical applications.

36 MATERIALS SCIENCE↗
NASA NTRS1982

Effect of processing on Polymer/Composite structure and properties

Advances in the vitality and economic health of the field of polymer forecasting are discussed. A consistent and rational point of view which considers processing as a participant in the underlying triad of relationships which comprise materials science and engineering is outlined. This triad includes processing as it influences material structure, and ultimately properties. Methods in processing structure properties, polymer science and engineering, polymer chemistry and synthesis, structure and modification and optimization through processing, and methods of melt flow modeling in processing structure property relations of polymer were developed. Mechanical properties of composites are considered, and biomedical materials research to include polymer processing effects are studied. An analysis of the design technology of advances graphite/epoxy composites is also reported.

Source record↗