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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Genomic factors shaping codon usage across the Saccharomycotina subphylum

Codon usage bias, or the unequal use of synonymous codons, is observed across genes, genomes, and between species. It has been implicated in many cellular functions, such as translation dynamics and transcript stability, but can also be shaped by neutral forces. We characterized codon usage across 1,154 strains from 1,051 species from the fungal subphylum Saccharomycotina to gain insight into the biases, molecular mechanisms, evolution, and genomic features contributing to codon usage patterns. We found a general preference for A/T-ending codons and correlations between codon usage bias, GC content, and tRNA-ome size. Codon usage bias is distinct between the 12 orders to such a degree that yeasts can be classified with an accuracy >90% using a machine learning algorithm. We also characterized the degree to which codon usage bias is impacted by translational selection. We found it was influenced by a combination of features, including the number of coding sequences, BUSCO count, and genome length. Our analysis also revealed an extreme bias in codon usage in the Saccharomycodales associated with a lack of predicted arginine tRNAs that decode CGN codons, leaving only the AGN codons to encode arginine. Analysis of Saccharomycodales gene expression, tRNA sequences, and codon evolution suggests that avoidance of the CGN codons is associated with a decline in arginine tRNA function. Consistent with previous findings, codon usage bias within the Saccharomycotina is shaped by genomic features and GC bias. However, we find cases of extreme codon usage preference and avoidance along yeast lineages, suggesting additional forces may be shaping the evolution of specific codons.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Advancing Multiscale Simulation of Plasma-Surface Interfaces

We report the development of an atomistic-informed, surface-state-dependent predictive model for particle exchange in a carbon-tungsten plasma-surface interface. The predictive model uses machine learning (ML) techniques to learn the energy and angular distributions for particle exchange and rate functions for surface state evolution from molecular dynamics simulations of cumulative bombardment of tungsten by energetic carbon ions. Each predictive component is sensitive to the energy and trajectory of incident plasma species and the surface state. The surface state is represented by a set of surface state descriptors, which were derived from the atomistic surface state for each independent carbon bombardment event. These descriptors are representative of the composition and degree of amorphization of the outermost angstrom of surface material and were chosen to optimize predictive performance for particle exchange at the interface. The distributions for particle exchange (reflection/sputtering) are demonstrated to vary with each surface state descriptor, motivating the development of surface-state-dependent particle exchange models for plasma simulations. The performance of various ML methods was compared, including polynomial quantile regression, artificial neural networks, k-nearest neighbors, and random forest algorithms, with polynomial regression performing the best for interpolation and extrapolation of learned relationships. In addition to the particle exchange model, a neutral network was developed and used to identify data sufficiency throughout surface descriptor space, which will enable real-time feedback during future data production to ensure data is produced where it is most needed, and we provide commentary on improvements to the data production workflow for future endeavors.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

YeastWGD2025

Supplementary data for Discovery of additional ancient genome duplications in yeasts wgd_syn / - directory containing wgd syn output for all contiguous genomes [dataset] Tree - phylogeny [dataset]Duplications - duplication table from OrthoFinder output KOannotations - KEGG annotations used for enrichment analysis IPRannotations - InterPro annotations used for enrichment analysis DipodascalesOrthogroups - formatted orthogroup assignments for Dipodascales genes.fa and .gff3 files for each new genome assembly are also provided, those these are not required to replicate the analysis

Genomics↗
DOE OSTI2026

Interfacial Charge Transfer Pathways in Photoelectrochemical H 2 Evolution by a Single-Component Molecular Catalyst on a Conductive Metal Oxide

Dye-sensitized photoelectrosynthesis cells traditionally combine a photosensitizing dye to harvest light and a catalyst to generate chemical fuels on a semiconductor. Here, in this work, a photoactive catalyst capable of both light absorption and fuel formation, [Cp*Ir(4,4′-Y 2 -bpy)Cl][Cl] (Cp* = pentamethylcyclopentadienyl, bpy = 2,2′-bipyridine, Y = CH 2 PO 3 H 2 ), is anchored to a mesoporous tin-doped indium oxide (ITO) electrode and facilitates photoelectrochemical H 2 evolution in water without the need for additional photosensitizers or sacrificial reductants. Spectroelectrochemistry indicates a single-site H 2 evolution mechanism involving charge injection to ITO, in contrast to the bimetallic mechanism observed in solution. Cyclic voltammetry and variable-potential chronoamperometry under illumination probe competing pathways via interfacial electron transfer between the Ir hydride excited state and the conductive ITO electrode. A Marcus theory framework provides reorganization energies for competing interfacial electron transfer pathways from potential-dependent quantum yield measurements. The light-driven H 2 evolution catalysis on conducting oxide proceeds with high Faradaic efficiency and current densities comparable to photoelectrodes utilizing p-type semiconductors. By uncovering the principal electron transfer pathways that govern photocatalytic efficiency, this study establishes design principles for hybrid molecular photoelectrocatalysts.

catalysts↗
DOE OSTI2026

Role of Amorphous Chains in Nanoplastic Formation from Semicrystalline Polymers

Semicrystalline polymers, e.g., polyethylene terephthalate (PET), release micro- (100 nm to 1 mm) and nanoplastics (up to 100 nm) [MNPL] when they are degraded under quiescent conditions. However, the exact molecular mechanisms leading to material fragmentation into MNPL are unknown. Here, we monitor the evolution of chain molecular weight and the MNPL production kinetics during hydrolysis of PET pellets. We find that only ~0.6% of the amorphous phase ester bonds are hydrolyzed at the onset of MNPL release. Then, by combining a random scission model with measured amorphous spacings, we estimate that only ~15% of the stress transmitters in the amorphous phase, namely, bridges and entangled loops, have failed by this point. Thus, spontaneous fragmentation of the semicrystalline nanostructure occurs despite significant intercrystalline connectivity. We resolve this apparent contradiction by proposing that fragmentation can only occur when progressive tie-chain scission causes the material to undergo the ductile/brittle transition. Mechanistically, we speculate that the internal stresses responsible for material fragmentation are caused by processing (i.e., residual stresses) and/or sample densification induced by chemi-crystallization. We discuss additional factors that may affect our analysis and thus require further investigation, such as skin-core effects, preferential degradation of stress transmitters and/or recrystallization processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Rotational excitation and de-excitation of magnesium mono-sulphide (MgS) by He collisions

ABSTRACT Magnesium mono-sulphide (MgS) plays a crucial role in astrochemical processes, particularly in the interstellar medium (ISM), where metal-sulphur chemistry influences molecular formation and evolution. This work presents a detailed study of the rotational excitation and de-excitation of MgS through collisions with helium (He) atoms, the second most abundant species in the ISM after hydrogen, which includes both atomic (H) and molecular forms (H2). The focus on MgS–He collisions arises from He's high abundance, chemical inertness, and simpler electronic structure, which make it well suited for quantum scattering calculations. These characteristics establish He as an ideal candidate for initial studies, providing fundamental data for future investigations involving H2. The study uses quantum scattering methods to calculate the collisional rate coefficients over a broad temperature range. These rates are critical for interpreting observational data on MgS and predicting its abundance in space. The interaction potential between MgS and He is calculated using the rigid rotor approximation and the Jacobi coordinate system, employing the CCSD(T)-F12a/aug-cc-pVTZ method for accurate two-dimensional potential energy surface. The study explores the anisotropic nature of the MgS–He interaction, which favours odd Δj rotational transitions at low collision energies. The inelastic cross-sections for rotational transitions involving up to 16 rotational levels of MgS were computed up to 1000 cm−1, enabling the calculation of rate coefficients up to 150 K for Δj = ±1, ±2, and ± 3 rotational transitions. The results show that Δj = 1 transitions dominate at low temperatures, while Δj = 2 transitions become more significant at higher temperatures. This study provides valuable data for interpreting future astrophysical observations of MgS. The findings also propose new rotational transitions for MgS detection in space, enhancing our ability to track and study this molecule in various cosmic environments.

Hendaoui, Hamza (ORCID:0000000218641872)↗
DOE OSTI2024

Measurement of coherent vibrational dynamics with X-ray Transient Absorption Spectroscopy simultaneously at the Carbon K- and Chlorine L 2,3 - edges

X-ray Transient Absorption Spectroscopy (XTAS) is a powerful probe for ultrafast molecular dynamics. The evolution of XTAS signal is controlled by the shapes of potential energy surfaces of the associated core-excited states, which are difficult to directly measure. Here, we study the vibrational dynamics of Raman activated CCl 4 with XTAS targeting the C 1s and Cl 2p electrons. The totally symmetric stretching mode leads to concerted elongation or contraction in bond lengths, which in turn induce an experimentally measurable red or blue shift in the X-ray absorption energies associated with inner-shell electron excitations to the valence antibonding levels. The ratios between slopes of different core-excited potential energy surfaces (CEPESs) thereby extracted agree very well with Restricted Open-Shell Kohn-Sham calculations. The other, asymmetric, modes do not measurably contribute to the XTAS signal. The results highlight the ability of XTAS to reveal coherent nuclear dynamics involving < 0.01 Å atomic displacements and also provide direct measurement of forces on CEPESs.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Unraveling the multi-step crystallization mechanism of polytetrafluoroethylene, modified polytetrafluoroethylene, and their nanocomposites with boron nitride nanobarbs: Experimental insights and theoretical analysis

The non-isothermal crystallization behavior and kinetics of polytetrafluoroethylene (PTFE) composites with boron nitride nanobarb (BNNB), a new generation nanostructure with unique surface morphology and mechanical “barbs” have been analyzed, understanding these properties is essential for their high-end applications as thermal interface materials (TIM) for microwave, 5G and microelectronic devices. The analysis of the crystallization parameters includes crystallization onset, peak and end temperatures, crystallization half-life and overall crystallinity of PTFE, modified PTFE and their BNNB composites. The results were further analyzed using theoretical models such as the combined Avrami-Ozawa model. It was found that BNNB supports crystallization in the modified PTFE but shows minimal effect on the crystallization of PTFE. Due to the limitation of the classical theoretical models used above in fully characterizing the multi-step crystallization process of PTFE, an in-depth analysis using the model-free advanced isoconversional computation was used to characterize the PTFE crystallization based on the evolution of activation energy with fractional crystallinity and for the first time with temperature. Three kinetic regions were identified in the crystallization mechanism. Here, this study investigated the molecular organization and microstructural evolution of PTFE, modified PTFE and their composites during non-isothermal crystallization using advanced X-ray scattering measurements. An insight into the changes undergone by the material's microstructural units including crystallite size and morphology, lamellar thickness and lamellar interfacial layer thickness, and crystallographic phase dynamics during non-isothermal cooling from the melt, was provided here in this work. The effect of copolymer modification of PTFE and the inclusion of pristine and functionalized BNNB (a thermally conductive and electrically insulating ceramic) are both new investigations that provide valuable knowledge for the development of materials with strong matrix-nanofiller interaction and guidance for optimizing sintering and cooling cycles, two key steps in PTFE processing that largely affect the material microstructural features. Overall, the result of the three-part investigation demonstrates that BNNB supports crystallization in the modified PTFE up to 20 wt% concentration and at low and high cooling rates typically used in the industrial processing of PTFE.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Crossing the Oxo‐Peroxo Wall for Selective Electrochemical Epoxidation

Electrochemical oxidation in water requires the formation of reactive oxygen species to be able to oxidize unsaturated hydrocarbons to epoxides, aldehydes, and ketones. These reactions, broadly classified as alternative oxidation reactions (AOR), directly compete with the prevalent oxygen evolution reaction (OER). In molecular catalysis, the Oxo-Wall dictates a transition from a stable oxo intermediate (OER active) to a meta-stable metal-oxo (OER inactive) generally occurs. In this work on heterogeneous catalysis, the same Oxo-Wall applies, however, a meta-stable oxo preferentially coordinates with lattice oxygen to form a more stable surface peroxo intermediate. A universal free energy onset of this process is identified at 3.39 eV under electrochemical activation in water and show that it is completely decoupled from the OER oxo species. Such decoupling gives rise to a new region of oxygen reactivity relevant for AOR where a selective oxidation of the unsaturated C-C bonds is predicted to occur instead of OER. A distinct AOR overpotential volcano is constructed and identify recently reported electrocatalysts, including palladium-platinum for propylene epoxidation and silver-nickel for ethylene epoxidation, along with others such as TiO 2 and CuO. Broader implications and limitations of electrochemical AOR are discussed, highlighting their potential to enable electrochemically enhanced thermal catalysis.

Electrocatalysis↗
DOE OSTI2026

First-Principles Insights into Proton-Coupled Electron Transfer versus Hydrogen Evolution Reaction Selectivity from a Base-Appended Cobaltocene Mediator

Performing selective proton-coupled electron transfer (PCET) to substrates such as N 2 , CO 2 , and unsaturated organic molecules under electrochemical conditions requires the suppression of the competing hydrogen evolution reaction (HER). To address this challenge, our laboratory previously demonstrated a PCET mediator strategy using a dimethylaniline-appended cobaltocene complex, [(CpCoCp NMe2 )H] + , which performs selective reductive chemistry while suppressing the HER. However, the origin of the suppressed, yet still observable, HER has not been thoroughly established. In this work, we perform density functional theory (DFT) calculations to elucidate the HER mechanism involving this redox mediator and to provide atomistic insights into the bifurcation between the PCET and HER pathways. We find that protonation of the aniline moiety to form [CpCoCp NMe2H ] + is more favorable, both kinetically and thermodynamically, than formation of the ring-protonated species [(CpCo(Cp-H) NMe2 )] + . Furthermore, PCET to acetophenone is energetically more favorable via [CpCoCp NMe2H ] + than via [(CpCo(Cp-H) NMe2 )] +1/0 . In contrast, the most favorable HER pathway involves the ring-protonated Co(I) species. These results offer mechanistic insights into HER versus PCET bifurcation and establish guiding principles for designing PCET mediators for selective electroreductive transformations.

evolution reactions↗
DOE OSTI2026

EEPD1 evolved a unique DNA clamping dimer protecting reversed replication forks

Exonuclease/endonuclease/phosphatase (EEP)-fold hydrolases are canonically monomeric phosphodiesterases exemplified by APE1, DNase I, and TDP2 nucleases. While EEP family domain containing protein 1 (EEPD1) acts in DNA stress responses, its proposed nuclease activities are enigmatic. Here, we integrate hybrid structural methods, evolution, biochemistry, cancer genomics, plus molecular and cell biology to define EEPD1 structure, assembly, and function at stalled DNA replication forks. Results imply EEPD1 surprisingly requires both unique EEP domain dimer and distinctive tandem Helix-hairpin-Helix [(HhH) 2 ] domains to clamp double-stranded (ds) DNA at reversed DNA replication forks for fork protection. Small-angle X-ray Scattering (SAXS), crystal, and cryo-EM structures unveil an unprecedented tryptophan handshake dimer, conserved interface di-Trp-Pro pocket, and adjustable “wrist” enabling an open-closed conformational switch. EEPD1 dimer cooperatively binds complex dsDNA replication fork intermediates but alone lacks nuclease activity due to loss of key EEP catalytic residues during Metazoan evolution and atmospheric oxygen buildup. Instead, EEPD1 prevents nucleolytic degradation of reversed replication forks by MRE11. Furthermore, cancer bioinformatics support oxidative damage-dependent EEPD1 association as a significant modulator of overall patient survival. Collective findings uncover unexpected EEP dimer and fork protection function in clamping, not cleaving, reversed replication forks for metazoan oxidative stress responses controlling genome stability and cancer outcomes.

Shen, Runze [Univ. of Texas, Houston, TX (United S↗
DOE OSTI2025

Overcoming time and complexity limitations in molecular dynamics investigations of equilibrium melting

Abstract A hybrid Monte-Carlo molecular-dynamics method for determining solidus and liquidus compositions in multicomponent systems is presented that overcomes both the time limitations in conventional molecular dynamics that prevent the evolution of distinct solid and liquid compositions via diffusion and the complexity challenge that prevents use of thermodynamic assessment in systems of many components. This hybrid method is validated in the Cu–Ni system against an independent assessment of solidus and liquidus compositions based on the regular solution model. Strategies for efficient mapping of different phase diagrams, based on the thermodynamic parameter T 0 , the temperature at which two phases of the composition X 0 have equal free energies, are presented and then demonstrated for the copper-nickel fully miscible system and the gold–silicon eutectic system. A calculation of the solidus and liquidus sampled during the equilibrium melting of equiatomic CrMnFeCoNi is performed, indicating that this method has potential to be extended to the study of many component alloys.

Au-Si↗
DOE OSTI2024

Understanding the effect of crystal anisotropy on grain growth, texturing and transport via the orthorhombic ?-U system [Slides]

The alpha phase of uranium exhibits the orthorhombic crystal structure, resulting in significant physical property anisotropy. These complex properties make the material challenging to work with in engineering settings but provide a rich arena to investigate the fundamental, multi-scale effects of anisotropy on physical behaviors such as grain growth and microstructure evolution under irradiation. We apply molecular dynamics and phase field modeling to study mass transport and grain growth in alpha-uranium. We characterize the mobilities of crystalline defects and the interfacial energy, and We find that the grain boundary energy is highly variable depending on the interface structure and that the relative rates of defect transport change with temperature. We also find that anisotropic thermal expansion has a significant impact on grain growth kinetics and texture development. Our results are used to explain experimental observations and to provide a basis for further hypotheses into the complex physical behavior of alpha-uranium.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Designing a quantum-accurate machine-learning potential to enable large-scale simulations of deuterium under shock

Large-scale molecular dynamics of deuterium under shock can elucidate kinetic processes vital to the target design in inertial confinement fusion and high-energy-density experiments. However, modeling the complex evolution of this material from an insulating molecular state at ambient pressure to an ionized, atomic fluid under strong shock is beyond the capability of simple pair and even bond order potentials. We thus train a quantum-accurate and broadly transferable machine-learning interatomic potential for deuterium using the Chebyshev Interaction Model for Efficient Simulations framework. We show that due to an improved description of the molecular-to-atomic transition, our model is able to better reproduce the ab initio equation of state, radial distribution functions, and principal Hugoniot than bond order potentials. This represents an important step toward large-scale quantum-accurate and nonequilibrium simulations of complicated systems under dynamic changes including phase transitions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

An Unconventional Dark Radical Chemistry in Dense Molecular Clouds: Directed Gas-Phase Formation of Naphthyl Radicals

The synthetic pathways to aromatic molecules inside photon-shielded dense molecular clouds remain a fundamental, unsolved enigma in astrochemistry and astrophysics, with low-temperature molecular growth routes involving aromatic radicals, such as prototype bicyclic naphthyl (C 10 H 7 • ), implicated as key sources. Here, exploiting crossed molecular beam experiments augmented by electronic structure calculations, unexpected pathways are exposed leading to the gas-phase formation of 1- and 2-naphthyl via barrierless bimolecular reactions of atomic carbon (C) with indene (C 9 H 8 ) and of dicarbon (C 2 ) with styrene (C 8 H 8 ) accompanied by ring expansion and cyclization together with aromatization. These facile routes challenge conventional wisdom that aromatic radicals are formed in deep space solely via “bright” gas-phase photochemistry of their closed-shell polycyclic aromatic hydrocarbon (PAH) precursors. A hitherto disregarded “dark” aromatic radical chemistry with aromatic radicals synthesized via gas-phase reactions offers new concepts on the chemical evolution of the chemistry of dark molecular clouds eventually culminating in the rapid formation of aromatics, fullerenes, and carbonaceous nanostructures.

Aromatic compounds↗
DOE OSTI2025

Best of both worlds: Enforcing detailed balance in machine learning models of transition rates

The slow microstructural evolution of materials often plays a key role in determining material properties. When the unit steps of the evolution process are slow, direct simulation approaches such as molecular dynamics become prohibitive and Kinetic Monte-Carlo (kMC) algorithms, where the state-to-state evolution of the system is represented in terms of a continuous-time Markov chain, are instead frequently relied upon to efficiently predict long-time evolution. The accuracy of kMC simulations however relies on the complete and accurate knowledge of reaction pathways and corresponding kinetics. This requirement becomes extremely stringent in complex systems such as concentrated alloys where the astronomical number of local atomic configurations makes the a priori tabulation of all possible transitions impractical. Machine learning models of transition kinetics have been used to mitigate this problem by enabling the efficient on-the-fly prediction of kinetic parameters. While conventional KMC methods based on transition state theory naturally yield reversible dynamics that exactly obey the detailed balance criterion, providing strong guarantees on the properties of the stationary distribution, many recently-proposed ML-based approaches to barrier predictions provide no such guarantees. In this study, we derive conditions under which physics-informed ML architectures exactly enforce the detailed balance condition by construction, even when relying on non-extensive descriptions of states in terms of local environments around mobile defects. In conclusion, using the diffusion of a vacancy in a concentrated alloy as an example, we show that such ML architectures also exhibit superior performance in terms of prediction accuracy, demonstrating that the imposition of physical constraints can facilitate the accurate learning of barriers at no increase in computational cost.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Molecular catalyst and co-catalyst systems based on transition metal complexes for the electrochemical oxidation of alcohols

Molecular catalysts allow deeper study of underlying mechanisms relative to heterogeneous systems by offering a discrete active site to monitor. Mechanistic study with knowledge of key intermediates subsequently enables the development of design principles through an understanding of how improved reactivity or selectivity can be achieved through modification of the catalyst structure. The co-catalytic inclusion of redox mediators (RM), which are small molecules that can aid in the transfer of protons and electrons, has been shown to improve product conversion and selectivity in many molecular systems, through intercepting key intermediates to direct reaction pathways. The primary focus for the majority of molecular electrocatalysts has been on optimizing design for reductive reactions, such as the hydrogen evolution reaction (HER), the oxygen reduction reaction (ORR), and the carbon dioxide reduction reaction (CO 2 RR). By comparison, there has been much less focus on key oxidative reactions by molecular species, apart from the oxygen evolution reaction (OER). The focus of this review is to highlight molecular catalyst systems optimized for the electrochemical oxidation of alcohols. The electrochemical alcohol oxidation reaction (AOR) can serve a role in synthesizing value-added chemicals and can serve as the counterpart to the CO 2 RR by releasing electricity from energy-rich molecules. State-of-the-art molecular systems for the AOR are divided between single-site catalysts and co-catalytic systems with redox mediators. The AOR is contextualized as an energy relevant reaction, an overview of the area is provided, foundational improvements in catalyst systems are highlighted, and future development principles for incorporating redox mediators are suggested.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗