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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 OSTI2022

Orthogonal glycolytic pathway enables directed evolution of noncanonical cofactor oxidase

Abstract Noncanonical cofactor biomimetics (NCBs) such as nicotinamide mononucleotide (NMN + ) provide enhanced scalability for biomanufacturing. However, engineering enzymes to accept NCBs is difficult. Here, we establish a growth selection platform to evolve enzymes to utilize NMN + -based reducing power. This is based on an orthogonal, NMN + -dependent glycolytic pathway in Escherichia coli which can be coupled to any reciprocal enzyme to recycle the ensuing reduced NMN + . With a throughput of >10 6 variants per iteration, the growth selection discovers a Lactobacillus pentosus NADH oxidase variant with ~10-fold increase in NMNH catalytic efficiency and enhanced activity for other NCBs. Molecular modeling and experimental validation suggest that instead of directly contacting NCBs, the mutations optimize the enzyme’s global conformational dynamics to resemble the WT with the native cofactor bound. Restoring the enzyme’s access to catalytically competent conformation states via deep navigation of protein sequence space with high-throughput evolution provides a universal route to engineer NCB-dependent enzymes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Oscillations and random walk of the soliton core in a fuzzy dark matter halo

We report that a fuzzy dark matter halo consists of a soliton core close to the center and a Navarro-Frenk-White–like density profile in the outer region. Previous investigations found that the soliton core exhibits temporal oscillations and random walk excursions around the halo center. Analyzing a set of numerical simulations, we show that both phenomena can be understood as the results of wave interference - a suitable superposition of the ground (solitonic) state and excited states in a fixed potential suffices to account for the main features of these phenomena. Such an eigenmode analysis can shed light on the evolution of a satellite halo undergoing tidal disruption. As the outer halo is stripped away, reducing the amplitudes of the excited states, the ground state evolves adiabatically. This suggests diminished soliton oscillations and random walk excursions, an effect to consider in deducing constraints from stellar heating.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

Pressure-Induced Chemical Bonding Effects on Lattice and Magnetic Instabilities in Antiferromagnetic Insulating CaMn 2 Sb 2

Exotic quantum phenomena often emerge near an electronic delocalization transition (EDT) from an antiferromagnetic insulating phase to a strongly correlated metallic state under pressure. We report the pressure-induced structural and magnetic evolution of the antiferromagnetic insulator CaMn 2 Sb 2 . Single-crystal X-ray diffraction reveals a first-order phase transition near 5.4 GPa from a trigonal P-3m1 structure to a monoclinic P2 1 /m phase accompanied by a ∼7% volume collapse. Residual electron density analysis at intermediate pressures reveals charge localization along Mn–Sb chains, signaling electronic instability preceding the structural transition. Bonding analysis indicates anisotropic Mn–Sb orbital reconfiguration under pressure, driving a distorted square-pyramidal geometry. Neutron scattering confirms the transition and identifies a pressure-induced incommensurate magnetic order, distinct from the ambient antiferromagnetic state. In the monoclinic phase, zigzag Mn chains exhibit antiferromagnetic coupling along the ac-plane, enabled by enhanced orbital overlap. These results establish CaMn 2 Sb 2 as a model system for studying the coupling of structural distortion, charge redistribution, and magnetic order in layered Mn pnictides under pressure.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Correlational selection and genetic architecture shape the evolution of the leaf economics spectrum in a perennial grass

The generality of the worldwide leaf economics spectrum (LES) has made it a pillar of trait-based ecological research. Yet, few studies have examined the processes shaping the evolution of the LES within species, in part, because most species occupy only a small portion of the LES. Here, to address this gap, we took advantage of the distinct leaf economics strategies present in different ecotypes of the phenotypically diverse perennial grass Panicum virgatum (switchgrass) to generate a genetic mapping population, which we planted in common gardens at three sites spanning 12 degrees of latitude in the central United States. With this genetic mapping population, we evaluated two potentially interacting causes of LES evolution: 1) genetic architecture, where multiple traits are influenced by either the same gene (pleiotropy) or by genes in close physical proximity (genetic linkage), and 2) correlational selection, where selection acts on traits in combination rather than in isolation. We found that shared genetic architecture influenced covariation between photosynthetic rate (A MASS ) and leaf nitrogen (N MASS ) and between A MASS and leaf mass per area (LMA). We also found that correlational selection favored the trait combinations predicted by the LES (e.g., high LMA with low N MASS or low LMA with high N MASS ) and disfavored other, mismatched trait combinations at two of the three sites. Together, these results demonstrate how the evolution of an integrated LES within species can arise from multiple evolutionary causes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

A novel open-source cultivation system helps establish the first full cycle chemosynthetic symbiosis model system involving the giant ciliate Zoothamnium niveum

Symbiotic interactions drive species evolution, with nutritional symbioses playing vital roles across ecosystems. Chemosynthetic symbioses are globally distributed and ecologically significant, yet the lack of model systems has hindered research progress. The giant ciliate Zoothamnium niveum and its sulfur-oxidizing symbionts represent the only known chemosynthetic symbiosis with a short life span that has been transiently cultivated in the laboratory. While it is experimentally tractable and presents a promising model system, it currently lacks an open-source, simple, and standardized cultivation setup. Following the FABricated Ecosystems (EcoFABs) model, we leveraged 3D printing and polydimethylsiloxane (PDMS) casting to develop simple flow-through cultivation chambers that can be produced and adopted by any laboratory. The streamlined manufacturing process reduces production time by 86% and cuts cost by tenfold compared to the previous system. Benchmarking using previously established optimal growth conditions, the new open-source cultivation system proves stable, efficient, more autonomous, and promotes a more prolific growth of the symbiosis. For the first time, starting from single cells, we successfully cultivated the symbiosis in flow-through chambers for 20 days, spanning multiple generations of colonies that remained symbiotic. They were transferred from chamber to chamber enabling long-term cultivation and eliminating the need for continuous field sampling. The chambers, optimized for live imaging, allowed detailed observation of the synchronized growth between the host and symbiont. Highlighting the benefit of this new system, we here describe a new step in the first hours of development where the host pauses growth, expels a coat, before resuming growth, hinting at a putative symbiont selection mechanism early in the colony life cycle. With this simple, open-source, cultivation setup, Z. niveum holds promises for comparative studies, standardization of research and wide adoption by the symbiosis research community.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Hot and dense homogeneous nucleonic matter constrained by observations, experiment, and theory

We propose a new class of phenomenological equations of state for homogeneous matter for use in simulations of hot and dense matter in local thermodynamic equilibrium. We construct a functional form which respects experimental, observational, and theoretical constraints on the nature of matter in various density and temperature regimes. Our equation of state (EOS) matches (i) the virial coefficients expected from nucleon-nucleon scattering phase shifts, (ii) experimental measurements of nuclear masses and charge radii, (iii) observations of neutron star radii, (iv) theory results on the equation of state of neutron matter near the saturation density, and (v) theory results on the evolution of the EOS at finite temperatures near the saturation density. Our analytical model allows one to compute the variation in the thermodynamic quantities based on the uncertainties in the nature of the nucleon-nucleon interaction. Lastly, we perform a correction to ensure the equation of state is causal at all densities, temperatures, and electron fractions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2016

Dodging the dark matter degeneracy while determining the dynamics of dark energy

One of the key issues in cosmology is to establish the nature of dark energy, and to determine whether the equation of state evolves with time. When estimating this from distance measurements there is a degeneracy with the matter density. We show that there exists a simple function of the dark energy equation of state and its first derivative which is independent of this degeneracy at all redshifts, and so is a much more robust determinant of the evolution of dark energy than just its derivative. We show that this function can be well determined at low redshift from supernovae using Gaussian Processes, and that this method is far superior to a variety of parameterisations which are also subject to priors on the matter density. This shows that parametrised models give very biased constraints on the evolution of dark energy.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

The Cost of Scaling Up in Large-Format Additive Manufacturing

Additive manufacturing (AM) of large objects has, over the last decade, required the scaling of existing material extrusion processes. The current generation of large-scale printers are primarily gantry robots with high-throughput extrusion systems. With workspaces approaching 50 m 3 , these printers have pushed the boundaries of achievable print volume while allowing the utilization of low-cost feedstocks, such as cementitious materials and polymer pellets, like those used in injection molding. Continued workspace expansion requires an examination of the inherent trade-offs, which impact capital and operational costs. Here, in this work, the authors examine these trade-offs to determine fundamental scaling laws for existing system architectures, survey the state of the art for alternative system configurations, and pose recommendations for future system designers to continue the evolution of large-scale AM systems.

3D printing↗
DOE OSTI2017

Solvent Entropy Contributions to Catalytic Activity in Designed and Optimized Kemp Eliminases

This work reports on the role of solvation for enzymatic catalysis in two distinct, artificially designed Kemp Eliminases, KE07 and KE70, and mutated variants that were optimized by laboratory directed evolution. Using a spatially resolved analysis of hydration patterns, intermolecular vibrations, and local solvent entropies, we identify distinct classes of hydration water and follow their changes upon substrate binding and transition state formation for the designed KE07 and KE70 enzymes and their evolved variants. We observe that differences in hydration of the enzymatic systems are concentrated in the active site and undergo significant changes during substrate recruitment. For KE07, directed evolution reduces variations in the hydration of the polar catalytic center upon substrate binding, preserving strong protein-water interactions, while the evolved enzyme variant of KE70 features a more hydrophobic reaction center for which the expulsion of low-entropy water molecules upon substrate binding is substantially enhanced. While our analysis suggests a system-dependent role of solvation for the substrate binding process, we identify more subtle changes in solvation for the transition state formation, which are less affected by directed evolution.

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

Multiscale modeling of metal-hydride interphases—quantification of decoupled chemo-mechanical energies

Abstract The quantification of interphase properties between metals and their corresponding hydrides is crucial for modeling the thermodynamics and kinetics of the hydrogenation processes in solid-state hydrogen storage materials. In particular, interphase boundary energies assume a pivotal role in determining the kinetics of nucleation, growth, and coarsening of hydrides, alongside accompanying morphological evolution during hydrogenation. The total interphase energy arises from both chemical bonding and mechanical strains in these solid-state systems. Since these contributions are usually coupled, it is challenging to distinguish via conventional computational approaches. Here, a comprehensive atomistic modeling methodology is developed to decouple chemical and mechanical energy contributions using first-principles calculations, of which feasibility is demonstrated by quantifying chemical and elastic strain energies of key interfaces within the FeTi metal-hydride system. Derived materials parameters are then employed for mesoscopic micromechanical analysis, predicting crystallographic orientations in line with experimental observations. The multiscale approach outlined verifies the importance of the chemo-mechanical interplay in the morphological evolution of growing hydride phases, and can be generalized to investigate other systems. In addition, it can streamline the design of atomistic models for the quantitative evaluation of interphase properties between dissimilar phases and allow for efficient predictions of their preferred phase boundary orientations.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Light-induced insulator–metal transition in Sr 2 IrO 4 reveals the nature of the insulating ground state

Sr 2 IrO 4 has attracted considerable attention due to its structural and electronic similarities to La 2 CuO 4 , the parent compound of high-T c superconducting cuprates. It was proposed as a strong spin–orbit-coupled J eff = 1/2 Mott insulator, but the Mott nature of its insulating ground state has not been conclusively established. Here, in this study, we use ultrafast laser pulses to realize an insulator–metal transition in Sr 2 IrO 4 and probe the resulting dynamics using time- and angle-resolved photoemission spectroscopy. We observe a gap closure and the formation of weakly renormalized electronic bands in the gap region. Comparing these observations to the expected temperature and doping evolution of Mott gaps and Hubbard bands provides clear evidence that the insulating state does not originate from Mott correlations. We instead propose a correlated band insulator picture, where antiferromagnetic correlations play a key role in the gap opening. More broadly, our results demonstrate that energy–momentum-resolved nonequilibrium dynamics can be used to clarify the nature of equilibrium states in correlated materials.

36 MATERIALS SCIENCE↗
NASA NTRS2000

Calculating Free Energies Using Scaled-Force Molecular Dynamics Algorithm

One common objective of molecular simulations in chemistry and biology is to calculate the free energy difference between different states of the system of interest. Examples of problems that have such an objective are calculations of receptor-ligand or protein-drug interactions, associations of molecules in response to hydrophobic, and electrostatic interactions or partition of molecules between immiscible liquids. Another common objective is to describe evolution of the system towards a low energy (possibly the global minimum energy), 'native' state. Perhaps the best example of such a problem is folding of proteins or short RNA molecules. Both types of problems share the same difficulty. Often, different states of the system are separated by high energy barriers, which implies that transitions between these states are rare events. This, in turn, can greatly impede exploration of phase space. In some instances this can lead to 'quasi non-ergodicity', whereby a part of phase space is inaccessible on timescales of the simulation. A host of strategies has been developed to improve efficiency of sampling the phase space. For example, some Monte Carlo techniques involve large steps which move the system between low-energy regions in phase space without the need for sampling the configurations corresponding to energy barriers (J-walking). Most strategies, however, rely on modifying probabilities of sampling low and high-energy regions in phase space such that transitions between states of interest are encouraged. Perhaps the simplest implementation of this strategy is to increase the temperature of the system. This approach was successfully used to identify denaturation pathways in several proteins, but it is clearly not applicable to protein folding. It is also not a successful method for determining free energy differences. Finally, the approach is likely to fail for systems with co-existing phases, such as water-membrane systems, because it may lead to spontaneous mixing. A similar difficulty may be encountered in any method relying on global modifications of phase space.

Darve, Eric↗
DOE OSTI2026

PRIME: An evaluation framework for protein representation inference and generalization in viral mutation space

Background Protein language models (PLMs) have revolutionized protein fitness prediction, yet their application to rapidly evolving viral pathogens is often confounded by extreme sequence homology. This homology leads to “data leakage” in standard random validation splits, yielding inflated performance metrics that fail to translate into real-world biosurveillance utility. Results We present Protein Representation Inference for Mutation Evaluation (PRIME), a framework that integrates domain-specific fine-tuning with a rigorous position-stratified validation protocol to evaluate viral threats. Using a dataset of 347,432 SARS-CoV-2 receptor binding domain (RBD) sequences, we demonstrate that while random training data split yields deceptive R 2 values (> 0.90), they fail to generalize to novel mutational sites. By benchmarking models up to 650 M parameters, we show that domain-specific fine-tuning of the ESM-C 600 M model with correctly stratified data provides an initial demonstration of predictive signal for binding affinity and expression at unseen mutational sites of binding affinity and expression on unseen sites (R 2 ~0.23), a significant advancement over base foundation models which exhibit no predictive power (R 2 <0). PRIME’s embedding-based clustering identified 3.03% of bat coronavirus sequences as candidates for further experimental prioritization based on their functional similarity to human-infective strains in embedding space, offering a perspective complementary to traditional phylogenetic methods. Conclusion PRIME establishes a new benchmark for the application of PLMs in pathogen surveillance. Our findings demonstrate that state-of-the-art models and fine-tuning, when paired with stratified validation, provide biologically meaningful insights into pathogen evolution and zoonotic risk.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Ground Vibrational State SiO Emission in the VLA BAaDE Survey

Using a subsample of the Bulge Asymmetries and Dynamical Evolution (BAaDE) survey of stellar SiO masers, we explore the prevalence and characteristics of {sup 28}SiO J = 1 − 0, v = 0 emission. We identify 90 detections of maser, thermal, or composite {sup 28}SiO J = 1 − 0, v = 0 emission out of approximately 13,000 candidate spectra from the National Science Foundation’s Karl G. Jansky Very Large Array (VLA). We find that the detected sources are likely asymptotic giant branch stars belonging to a bright, foreground Milky Way stellar disk population. For the 32 sources showing thermal components, we extract values for outflow velocity by fitting thermal line profiles. We find a range of circumstellar envelope expansion velocities, and compare to previously recorded OH and CO expansion velocities. This preliminary survey is already the largest study of stellar ground vibrational state SiO masers to date, and will be expanded to include the entire VLA BAaDE data set when data reduction for the 18,988 target sources is completed.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1995

Double core evolution. 7: The infall of a neutron star through the envelope of its massive star companion

Binary systems with properties similar to those of high-mass X-ray binaries are evolved through the common envelope phase. Three-dimensional simulations show that the timescale of the infall phase of the neutron star depends upon the evolutionary state of its massive companion. We find that tidal torques more effectively accelerate common envelope evolution for companions in their late core helium-burning stage and that the infall phase is rapid (approximately several initial orbital periods). For less evolved companions the decay of the orbit is longer; however, once the neutron star is deeply embedded within the companion's envelope the timescale for orbital decay decreases rapidly. As the neutron star encounters the high-density region surrounding the helium core of its massive companion, the rate of energy loss from the orbit increases dramatically leading to either partial or nearly total envelope ejection. The outcome of the common envelope phase depends upon the structure of the evolved companion. In particular, it is found that the entire common envelope can be ejected by the interaction of the neutron star with a red supergiant companion in binaries with orbital periods similar to those of long-period Be X-ray binaries. For orbital periods greater than or approximately equal to 0.8-2 yr (for companions of mass 12-24 solar mass) it is likely that a binary will survive the common envelope phase. For these systems, the structure of the progenitor star is characterized by a steep density gradient above the helium core, and the common envelope phase ends with a spin up of the envelope to within 50%-60% of corotation and with a slow mass outflow. The efficiency of mass ejection is found to be approximately 30%-40%. For less evolved companions, there is insufficient energy in the orbit to unbind the common envelope and only a fraction of it is ejected. Since the timescale for orbital decay is always shorter than the mass-loss timescale from the common envelope, the two cores will likely merge to form a Thorne-Zytkow object. Implications for the origin of Cyg X-3, an X-ray source consisting of a Wolf-Rayet star and a compact companion, and for the fate of the remnant binary consisting of a helium star and a neutron star are briefly discussed.

Terman, James L.↗
DOE OSTI2025

Towards a Quantum Algorithm for the Incompressible Nonlinear Navier-Stokes Equations

In this work, we present novel concepts for quantum algorithms to solve transient, nonlinear partial differential equations (PDEs). The challenge lies in how to effectively represent, encode, process, and evolve the nonlinear system of PDEs on quantum computers. We will discuss the new techniques using the incompressible Navier-Stokes equations as an example, because it represents the fundamental nonlinear feature and yet removes certain complexity in physics, allowing us to focus on the design of quantum algorithms. Previous attempts solving nonlinear PDEs in quantum computation have often involved storing multiple copies of solutions or employing linearizations. Neither is practical due to exponential scaling with evolution time or insufficient solution accuracy. We propose a new framework based on matrix product states (MPSs) and matrix product operators (MPOs), in addition to the Krylov subspace methods. For example, the solution variables of the Navier-Stokes equations are represented by MPSs, and the linear and nonlinear terms are processed by MPOs. The time evolution of the operators is attained by a fast-forwarding algorithm using Krylov subspace methods. Furthermore, we discuss various techniques for efficient encoding of MPSs, measurement reduction for MPOs, and use of tensor operations to treat multi-variate, multi-physics characteristics of Navier-Stokes.

Gopalakrishnan Meena, Murali [ORNL] (ORCID:0000000↗
DOE OSTI2017

Atomically Thin Mesoporous Co 3 O 4 Layers Strongly Coupled with N-rGO Nanosheets as High-Performance Bifunctional Catalysts for 1D Knittable Zinc-Air Batteries [Atomically Thin Mesoporous Co 3 O 4 /N-rGO Nanosheets as the Bifunctional Catalysts for One-Dimensional Knittable Zinc-Air Batteries]

Here, under development for next–generation wearable electronics are flexible, knittable, and wearable energy–storage devices with high energy density that can be integrated into textiles. Herein, knittable fiber–shaped zinc–air batteries with high volumetric energy density (36.1 mWh cm –3 ) are fabricated via a facile and continuous method with low–cost materials. Furthermore, a high–yield method is developed to prepare the key component of the fiber–shaped zinc–air battery, i.e., a bifunctional catalyst composed of atomically thin layer–by–layer mesoporous Co 3 O 4 /nitrogen–doped reduced graphene oxide (N–rGO) nanosheets. Benefiting from the high surface area, mesoporous structure, and strong synergetic effect between the Co 3 O 4 and N–rGO nanosheets, the bifunctional catalyst exhibits high activity and superior durability for oxygen reduction and evolution reactions. Compared to a fiber–shaped zinc–air battery using state–of–the–art Pt/C + RuO 2 catalysts, the battery based on these Co 3 O 4 /N–rGO nanosheets demonstrates enhanced and stable electrochemical performance, even under severe deformation. Such batteries, for the first time, can be successfully knitted into clothes without short circuits under external forces and can power various electronic devices and even charge a cellphone.

36 MATERIALS SCIENCE↗