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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 1,657 records · Page 92
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Bio-treatment of poplar via amino acid for interface control in biocomposites

Advanced biocomposites reinforced by abundant biomass-derived fillers can add a revenue stream to enhance the economic viability of biofuel production chains and the energy efficiency of the composite industry. However, the low stiffness of biopolymers limits their use in structural applications. Poplar fibers (mesh size: <180 μm, Populus spp.), an abundant waste from the wood industry, were used as bio-filler to fabricate high-performance biocomposites based on polylactic acid (PLA), in which the poplar fibers were modified by an amino acid (l-lysine). As a benefit of the amino acid treatment, the tensile Young's moduli of the lysine/poplar/PLA composites increased by up to 68% with the addition of a small amount of lysine, compared with neat PLA. At the same time, the tensile strength, failure strain, and Young's modulus of the poplar/PLA composites all increased after adding only 0.1 wt % of lysine. It has been observed that the lysine content has a significant effect on the decomposition temperature, complex viscosity, storage modulus, crystallization temperature, and crystallinity of composites. The fracture surfaces of the composites with an optimum lysine content had fewer voids and were more compact compared with composites without any lysine. The pores on the surfaces of poplar fibers became more available for the penetration of PLA molecules as a result of lysine addition. Finally, this study presents a facile method for reinforcing biocomposites with extremely low-cost and environmentally friendly biofillers.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Role of electronic energy loss on defect production and interface stability: Comparison between ceramic materials and high-entropy alloys

High-entropy alloys (HEAs) and some complex alloys exhibit desirable properties and significant structural stability in harsh environments, including possible applications in advanced reactors. Energetic ion irradiation is often used as a surrogate for neutron irradiation; however, the impact of ion electronic energy deposition and dissipation is often neglected. Moreover, differences in recoil energy spectrum and density of cascade events on damage evolution must also be considered. In many chemically complex alloys, the mean free path of electrons is reduced significantly, thus their decreased thermal conductivity and slow dissipation of localized radiation energy can have noticeable effects on displacement cascade evolution that is greatly different from metals with high thermal conductivity. In this work, nanocrystalline HEAs of Ni 20 Fe 20 Co 20 Cr 20 Cu 20 and nonequiatomic (NiFeCoCr) 97 Cu 3 , both having much lower room-temperature thermal conductivity than pure Ni or Fe, are chosen as model HEAs to reveal the role that electronic energy loss during ion irradiation has in complex alloys. The response of nanocrystalline HEAs is investigated under irradiation at room temperature using MeV Ni and Au ions that have different ratios of electronic energy to damage energy, which is the energy dissipated in displacing atoms. Different from previously reported amorphization of nanocrystalline SiC, experimental results on these HEAs show that, similar to the process in nanocrystalline oxide materials, both inelastic thermal spikes via electron–phonon coupling and elastic thermal spikes via collisions among atomic nuclei contribute to the overall grain growth. The growth follows a power law dependence with the total deposited ion energy, and the derived value of the power-exponent suggests that the irradiation-induced instability at and near grain boundaries leads to local rapid atomic rearrangements and consequently grain growth. The high power-exponent value can be attributed to the sluggish diffusion and delayed defect evolution arising from the chemical complexity intrinsic to HEAs. Here, this work calls attention to quantified fundamental understanding of radiation damage processes beyond that of simplified displacement events, especially in simulating neutron environments.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Predicting receptor-ligand pairing preferences in plant-microbe interfaces via molecular dynamics and machine learning

Microbiome assembly, structure, and dynamics significantly influence plant health. Secreted microbial signaling molecules initiate and mediate symbiosis by binding to structurally compatible plant receptors. For example, lipo-chitooligosaccharides (LCOs), produced by nitrogen-fixing rhizobial bacteria and various fungi, are recognized by plant lysin motif receptor-like kinases (LysM-RLKs), which activate the common symbiotic pathway. Accurately predicting these molecular interactions could reveal complementary signatures underlying the initial stages of endosymbiosis. Despite the breakthrough in protein-ligand structure prediction with deep learning-based tools, such as AlphaFold3, the large size and highly flexible nature of signaling compounds like LCOs present major challenges for detailed structural characterization and binding-affinity prediction. Typical structure-/physics-based methods of ligand virtual screening are designed for small, drug-like molecules, often rely on high-resolution, experimentally determined structures of the protein receptors, and rarely achieve sufficient sampling to obtain converged thermodynamic quantities with large ligands. In this study, we developed a hybrid molecular dynamics/machine learning (MD/ML) approach capable of predicting binding affinity rankings with high accuracy in systems involving large, flexible ligands, despite limited experimental structural information. Using coarse initial structural models, the predictions using the MD/ML workflow achieved strong alignment with experimental trends, particularly in the top-affinity tier for four legume LysM-RLKs (LYR3) binding to LCOs and a chitooligosaccharide. Furthermore, the MD-based conformation selection protocol provided critical structural insights into substrate specificity and binding mechanisms. This study demonstrates a powerful method to screen for challenging cognate ligand-receptors and advance our understanding of the molecular basis of microbial colonization in plants.

Lipo-chitooligosaccharides↗
DOE OSTI2023

Snowmass white paper: Light dark matter direct detection at the interface with condensed matter physics

Direct detection experiments for light (sub-GeV) dark matter are making enormous leaps in reaching previously unexplored theory space. The need for accurate characterizations of target responses has led to a growing interplay between particle and condensed matter physics. This white paper summarizes recent progress on direct detection calculations that utilize state-of-the-art numerical tools in condensed matter physics and effective field theory techniques. These new results provide the theoretical framework for interpreting ongoing and planned experiments using electronic and collective excitations, and for optimizing future searches.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗