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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Modulating Cu electrode microenvironments with MOF coatings: insights from molecular dynamics and electrochemical experiments of CO reduction

Metal-organic frameworks (MOFs) present a compelling strategy for tuning electrochemical interfaces by reshaping interfacial solvent structure. In this study, we examine how MOF coatings influence the microenvironment at copper electrodes during the CO electroreduction reaction (CORR) using a combined approach of molecular dynamics (MD) simulations and electrochemical experiments. Two MOFs, NU-901 and ZIF-8, are selected to explore the impact of pore size and channel hydrophobicity on electrochemical activity and interfacial concentration in acetonitrile (ACN) and dimethyl sulfoxide (DMSO) electrolytes. Electrochemical measurements reveal that MOF@Cu electrodes exhibit lower Faradaic efficiencies for CO hydrogenation products (ethylene and methane) compared to bare copper but have dramatic impacts on the interfacial microenvironment. NU-901, with its larger pores and strong interactions with DMSO, traps DMSO molecules and enhances CO coordination in DMSO but suppresses CORR selectivity in favor of the hydrogen evolution reaction (HER). ZIF-8, with smaller pores and hydrophobic channels, limits the interfacial water concentration, and, in ACN, promotes CO coordination. The simulations provide insights into how MOFs can act as physical modulators of reactant delivery and interfacial structure to control electrochemical microenvironments. This work highlights the value of molecular dynamics in uncovering how structural features of MOFs influence interfacial phenomena, even when catalytic performance is not directly improved.

Copper electrode microenvironments↗
DOE OSTI2024

A combinatorially complete epistatic fitness landscape in an enzyme active site

Protein engineering often targets binding pockets or active sites which are enriched in epistasis—nonadditive interactions between amino acid substitutions—and where the combined effects of multiple single substitutions are difficult to predict. Few existing sequence-fitness datasets capture epistasis at large scale, especially for enzyme catalysis, limiting the development and assessment of model-guided enzyme engineering approaches. We present here a combinatorially complete, 160,000-variant fitness landscape across four residues in the active site of an enzyme. Assaying the native reaction of a thermostable β-subunit of tryptophan synthase (TrpB) in a nonnative environment yielded a landscape characterized by significant epistasis and many local optima. These effects prevent simulated directed evolution approaches from efficiently reaching the global optimum. There is nonetheless wide variability in the effectiveness of different directed evolution approaches, which together provide experimental benchmarks for computational and machine learning workflows. The most-fit TrpB variants contain a substitution that is nearly absent in natural TrpB sequences—a result that conservation-based predictions would not capture. Thus, although fitness prediction using evolutionary data can enrich in more-active variants, these approaches struggle to identify and differentiate among the most-active variants, even for this near-native function. Overall, this work presents a large-scale testing ground for model-guided enzyme engineering and suggests that efficient navigation of epistatic fitness landscapes can be improved by advances in both machine learning and physical modeling.

biocatalysis↗
DOE OSTI2026

Effects of slope steepness and cross-slope wind speed on fire spreading behavior for various vegetation

Wildland fire behavior is significantly influenced by environmental factors such as slope steepness, wind speed, and fuel type. Understanding these interactions is critical for improving predictive models and fire management. This study explores how slope steepness and cross-slope wind speed influence fire spread dynamics in various fuel bed types. Simulations are conducted using a physics-based wildland fire model, HIGRAD/FIRETEC, across six slope angles (0–50 %), four cross-slope wind speeds (4–10 m s –1 ), and three fuel bed types (grass, shrubland, and forest). Representative cases are additionally compared with FARSITE fireline evolution. Fire behavior is categorized into distinct propagation types based on spread characteristics and analyzed. The fire propagation angle, which indicates deviation from the wind direction, generally increases with steeper slopes and decreases with stronger cross-slope winds. Secondary upslope propagation is observed in shrubland under moderate slopes, while secondary downwind propagation occurs in all fuel beds at higher wind speeds. These findings highlight fire spread characteristics that differ from predictions by traditional models like Rothermel’s. By capturing complex propagation patterns and dynamics, this study demonstrates the value of a physics-based, atmosphere-fire coupled model for accurate wildland fire prediction. Incorporating secondary propagations and the influence of fuel bed complexities into predictive models can improve the accuracy of fire spread forecasts, enabling more effective fire management and risk mitigation efforts.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

From Micro-environments to Macroscopic Effects: How the Alkaline Hydrogen Evolution Reaction Drives Cu Cathodic Corrosion

Cathodic corrosion of copper (Cu) has posed a significant challenge for over a century, impeding various technological progresses such as electrochemical conversion of CO 2 (eCO 2 RR) into fuels and other value-added carbon products. Here, in this study, employing a combined Density Functional Theory (DFT) and kinetic Monte Carlo (kMC) simulation approach, we delve into the atomistic level mechanism driving this phenomenon in Cu. Our hypothesis posits the pivotal role of alkaline hydrogen evolution reaction (HER) in facilitating cathodic corrosion in Cu. We rigorously develop a pH-dependent hydroxide (OH) adsorption mechanism and calculate the equilibrium OH coverage (𝜃 OH ) at varying pH levels, the thermodynamic stability of subsurface oxygen (O sub ), as well as the Cu-vacancy mediated diffusion of subsurface oxygens (O sub ). Through comprehensive analysis, we establish correlation among various microenvironments, including oxygen diffusion in subsurface layers, pH-dependent OH adsorption, and Cu dissolution into the electrolyte as (Cu-OH) complexes. Furthermore, our investigation explores the correlation between surface coordination environment of active sites and cathodic corrosion of Cu. Finally, by integrating DFT-derived thermodynamic data into a kMC model, we successfully predict the formation of experimentally observed corrosion pits on Cu-surfaces. This combined approach not only advances our fundamental understanding of Cu cathodic corrosion but also offers insights crucial for developing effective corrosion mitigation strategies.

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

Hydrotrope-enabled high concentration aqueous electrolytes for reversible and sustainable iron metal anodes

Iron metal-based energy storage devices hold great potential in stationary grid-scale sustainable energy due to the high theoretical specific capacity, ultralow cost, and abundance of iron. However, their practical deployment is limited by the poor reversibility of iron plating and stripping, as well as competitive hydrogen evolution. Here we introduce the concept of hydrotropy into iron electrolytes by developing an environmentally friendly and cost-effective high-concentration ferrous sulfate electrolyte using urea as a hydrotropic agent. The designed electrolyte increases the Coulombic efficiency of iron metal electrodes to approximately 96.5%, compared with ~84.6% for the dilute electrolyte. Molecular dynamics simulations and Raman spectroscopy illustrate that urea regulates the competitive coordination of anions and urea in the iron solvation sheath, while reconstructing the hydrogen-bond network in free water molecules. This reduces the activity of both solvated and free water, thereby alleviating hydrogen evolution. Moreover, the coordinated anions and urea molecules facilitate the in-situ formation of an organic-inorganic hybrid protective layer on the metallic iron, establishing a physical barrier against water and promoting homogeneous interfacial reactions. This work demonstrates an appealing opportunity to design cost-effective and high-performance electrolytes and propels the practical application of iron metal-based energy storage devices.

Feng, Guangxia [Stanford Univ., CA (United States)↗
DOE OSTI2024

Towards High-Performance AI4NP Applications on Modern GPU Platforms

The evolution of modern heterogeneous accelerators, such as GPUs, has significantly advanced the landscape of artificial intelligence (AI). There is a notable surge to adopt AI within the nuclear physics domain (AI4NP). While most AI4NP studies focus on feasibility analysis, our attention is directed towards evaluating their performance on contemporary GPUs that integrate tensor cores. We first benchmark the throughput of hyperparameterized multi-layer perceptron (MLP) models. We then examine the performance of an AI4NP application: Hydra. We assess the performance gain and accuracy loss caused by the tensor cores for low-precision floating-point operations. Our experiments encompass the PyTorch and TensorFlow Keras frameworks on NVIDIA’s T4 and A100 GPUs. We explore the behavior of different GPU hardware platforms and AI software tools. This study can be a valuable resource for guiding the performance optimization of larger-scale deployments of AI4NP applications.

Mei, Xinxin↗
DOE OSTI2025

Invariant discovery of features across multiple length scales: Applications in microscopy and autonomous materials characterization

Physical imaging is a foundational characterization method in areas from condensed matter physics and chemistry to astronomy and spans length scales from atomic to universe. Images encapsulate crucial data regarding atomic bonding, materials microstructures, and dynamic phenomena such as microstructural evolution and turbulence, among other phenomena. The challenge lies in effectively extracting and interpreting this information. Variational Autoencoders (VAEs) have emerged as powerful tools for identifying the underlying factors of variation in image data, providing a systematic approach to distilling meaningful patterns from complex data sets. However, a significant hurdle in their application is the definition and selection of appropriate descriptors reflecting local structures. Here, we introduce the scale-invariant VAE approach (SI-VAE) based on the progressive training of the VAE with the descriptors sampled at different length scales. The SI-VAE allows the discovery of the length scale-dependent factors of variation in the system. Here, we illustrate this approach using the ferroelectric domain images and generalize it to the movies of the electron-beam induced phenomena in graphene and topography evolution across combinatorial libraries. This approach can further be used to initialize the decision making in automated experiments including structure–property discovery and can be applied across a broad range of imaging methods. This approach is universal and can be applied to any spatially resolved data including both experimental imaging studies and simulations, and can be particularly useful for exploration of phenomena such as turbulence and scale-invariant transformation fronts.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Total absorption spectroscopy for the 𝛽 + decay strength distribution of 60 Ga

𝛽-decay properties play an important role in most astrophysical processes. In the absence of experimental data, astrophysical models rely on global theoretical calculations to provide the relevant properties. It is therefore important to provide strong experimental constraints when possible. In the case of 𝛽-decay, the most sensitive probe is the 𝛽-decay strength distribution. We report here on the first measurement of the latter quantity for the 𝛽 + decay of 60 Ga using the total absorption spectroscopy technique. The experimental results are compared to theoretical calculations often used in astrophysical models, namely the shell model and the quasiparticle random phase approximation (QRPA), as well as an extension of QRPA that includes higher-order nucleonic calculations. Both models are in reasonable agreement with the experimental results.

59 ≤ A ≤ 89↗
DOE OSTI2024

Autonomous hybrid optimization of a SiO 2 plasma etching mechanism

Computational modeling of plasma etching processes at the feature scale relevant to the fabrication of nanometer semiconductor devices is critically dependent on the reaction mechanism representing the physical processes occurring between plasma produced reactant fluxes and the surface, reaction probabilities, yields, rate coefficients, and threshold energies that characterize these processes. The increasing complexity of the structures being fabricated, new materials, and novel gas mixtures increase the complexity of the reaction mechanism used in feature scale models and increase the difficulty in developing the fundamental data required for the mechanism. This challenge is further exacerbated by the fact that acquiring these fundamental data through more complex computational models or experiments is often limited by cost, technical complexity, or inadequate models. In this paper, we discuss a method to automate the selection of fundamental data in a reduced reaction mechanism for feature scale plasma etching of SiO 2 using a fluorocarbon gas mixture by matching predictions of etch profiles to experimental data using a gradient descent (GD)/Nelder–Mead (NM) method hybrid optimization scheme. These methods produce a reaction mechanism that replicates the experimental training data as well as experimental data using related but different etch processes.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Influence of Annealing Temperature on the OER Activity of NiO(111) Nanosheets Prepared via Microwave and Solvothermal Synthesis Approaches

Earth-abundant transition metal oxides are promising alternatives to precious metal oxides as electrocatalysts for the oxygen evolution reaction (OER) and are intensively investigated for alkaline water electrolysis. OER electrocatalysis, like most other catalytic reactions, is surface-initiated, and the catalyst performance is fundamentally determined by the surface properties. Most transition metal oxide catalysts show OER activities that depend on the predominantly exposed crystal facets/surface structure. Therefore, the design of synthetic strategies to obtain the most active crystal facets is of significant research interest. In this work, rock salt NiO OER catalysts with (111) predominantly exposed facets were synthesized by a solvothermal (ST) method either heated under supercritical or microwave-assisted (MW) conditions. Particular emphasis was placed on the influence of the post annealing temperature on the structural configuration and OER activity to compare their catalytic performances. The as-prepared electrocatalysts are pure α-Ni hydroxides which were converted to rock salt NiO (111) nanosheets with hexagonal pores after heat treatment at different temperatures. The OER activity of the electrodes has been evaluated in 0.1 M KOH using geometric and intrinsic current densities via normalization by the disk area and BET area, respectively. The lowest overpotential at a geometric current density of 10 mA/cm 2 is found for samples pretreated by heating between 400 and 500 °C with a catalyst loading of 115 μg/cm 2 . Despite the very similar nature of the catalysts obtained from the two methods, the ST electrodes show a higher geometric and intrinsic current density for 500 °C pretreatment. The MW electrodes, however, achieve an optimal geometric current density for 400 °C pretreatment, while their intrinsic current density requires pretreatment over 600 °C. Interestingly, pretreated electrodes show consistently higher OER activity as compared to the poorly crystalline/less ordered hydroxide as-prepared electrocatalysts. Thus, our study highlights the importance of the synthesis method and pretreatment at an optimal temperature.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Null states and time evolution in a toy model of black hole dynamics

Abstract Spacetime wormholes can provide non-perturbative contributions to the gravitational path integral that make the actual number of statese S in a gravitational system much smaller than the number of states$$ {e}^{S_{\textrm{p}}} $$ e S p predicted by perturbative semiclassical effective field theory. The effects on the physics of the system are naturally profound in contexts in which the perturbative description actively involvesN=O(e S ) of the possible$$ {e}^{S_{\textrm{p}}} $$ e S p perturbative states; e.g., in late stages of black hole evaporation. Such contexts are typically associated with the existence of non-trivial quantum extremal surfaces. However, by forcing a simple topological gravity model to evolve in time, we find that such effects can also have large impact forN≪e S (in which case no quantum extremal surfaces can arise). In particular, even for smallN, the insertion of generic operators into the path integral can cause the non-perturbative time evolution to differ dramatically from perturbative expectations. On the other hand, this discrepancy is small for the special case where the inserted operators are non-trivial only in a subspace of dimensionD≪e S . We thus study this latter case in detail. We also discuss potential implications for more realistic gravitational systems.

Physics↗
DOE OSTI2024

Semicoherent symmetric quantum processes: Theory and applications

Discovering pragmatic and efficient approaches to construct ε-approximations of quantum operators such as real (imaginary) time-evolution propagators in terms of the basic quantum operations (gates) is challenging. Prior ε-approximations are invaluable, in that they enable the compilation of classical and quantum algorithm modeling of, e.g., dynamical and thermodynamic quantum properties. In parallel, symmetries are powerful tools concisely describing the fundamental laws of nature; the symmetric underpinnings of physical laws have consistently provided profound insights and substantially increased predictive power. In this work, we consider the interplay between the ε-approximate processes and the exact symmetries in a semicoherent context—where measurements occur at each logical clock cycle. Here we draw inspiration from Pascual Jordan's groundbreaking formulation of nonassociative, but commutative, symmetric algebraic form. Our symmetrized formalism is then applied in various domains such as quantum random walks, real-time evolutions, variational algorithm ansatzes, and efficient entanglement verification. Our work paves the way for a deeper understanding and greater appreciation of how symmetries can be used to control quantum dynamics in settings where coherence is a limited resource.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Demonstration of the rodeo algorithm on a quantum computer

The rodeo algorithm is an efficient algorithm for eigenstate preparation and eigenvalue estimation for any observable on a quantum computer. This makes it a promising tool for studying the spectrum and structure of atomic nuclei as well as other fields of quantum many-body physics. The only requirement is that the initial state has sufficient overlap probability with the desired eigenstate. While it is exponentially faster than well-known algorithms such as phase estimation and adiabatic evolution for eigenstate preparation, it has yet to be implemented on an actual quantum device. In this work, we apply the rodeo algorithm to determine the energy levels of a random one-qubit Hamiltonian, resulting in a relative error of 0.08% using mid-circuit measurements on the IBM Q device Casablanca. This surpasses the accuracy of directly-prepared eigenvector expectation values using the same quantum device. We take advantage of the high-accuracy energy determination and use the Hellmann-Feynman theorem to compute eigenvector expectation values for a different random one-qubit observable. For the Hellmann-Feynman calculations, we find a relative error of 0.7%. Here, we conclude by discussing possible future applications of the rodeo algorithm for multi-qubit Hamiltonians.

algorithm↗
DOE OSTI2025

Electrochemical Activation of Ni–Fe Oxides for the Oxygen Evolution Reaction in Alkaline Media

The oxygen evolution reaction (OER) is essential to many key electrochemical devices, including H 2 O electrolyzers, CO 2 electrolyzers, and metal−air batteries. NiFe oxides have been historically identified as active for the OER, though they have been less studied in their more commercially relevant bulk oxide forms, such as NiFe 2 O 4 . Past works have demonstrated that the initial starting phase of Ni(Fe) precatalysts can influence their activation to the Ni(Fe)OOH active phase, including the rate and degree of conversion, pointing to the necessity of understanding activation protocols and in situ characteristics of catalyst materials at the device level. In this work, we investigate the characteristics of commercially relevant NiFe bulk oxides (NiFe 2 O 4 and a physical mixture of NiO and γ-Fe 2 O 3 ) during multiple activation procedures. Our results demonstrate that significant performance enhancement is observed for these bulk oxides regardless of the Fe incorporation in the initial form (i.e., atomically or macroscopically integrated), leading to significant performance enhancement (up to 30×) over time on stream. We hypothesize that this activation is due to the formation of NiFeOOH active sites on the surface, supported by in situ cyclic voltammetry and Raman spectroscopy results. We further show that not only the starting material but also the method of activation influences the number of Ni(Fe)OOH active sites formed and suggest that these sites can be quantified from the Ni 2+ to Ni 3+ redox transition using cyclic voltammetry. Broadly, this work demonstrates the necessity of in situ characterization of catalyst materials for cell-level design and testing.

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

An introduction to Spent Nuclear Fuel decay heat for Light Water Reactors: a review from the NEA WPNCS

This paper summarized the efforts performed to understand decay heat estimation from existing spent nuclear fuel (SNF), under the auspices of the Working Party on Nuclear Criticality Safety (WPNCS) of the OECD Nuclear Energy Agency. Needs for precise estimations are related to safety, cost, and optimization of SNF handling, storage, and repository. The physical origins of decay heat (a more correct denomination would be decay power) are then introduced, to identify its main contributors (fission products and actinides) and time-dependent evolution. Due to limited absolute prediction capabilities, experimental information is crucial; measurement facilities and methods are then presented, highlighting both their relevance and our need for maintaining the unique current full-scale facility and developing new ones. The third part of this report is dedicated to the computational aspect of the decay heat estimation: calculation methods, codes, and validation. Different approaches and implementations currently exist for these three aspects, directly impacting our capabilities to predict decay heat and to inform decision-makers. Finally, recommendations from the expert community are proposed, potentially guiding future experimental and computational developments. One of the most important outcomes of this work is the consensus among participants on the need to reduce biases and uncertainties for the estimated SNF decay heat. If it is agreed that uncertainties (being one standard deviation) are on average small (less than a few percent), they still substantially impact various applications when one needs to consider up to three standard deviations, thus covering more than 95% of cases. The second main finding is the need of new decay heat measurements and validation for cases corresponding to more modern fuel characteristics: higher initial enrichment, higher average burnup, as well as shorter and longer cooling time. Similar needs exist for fuel types without public experimental data, such as MOX, VVER, or CANDU fuels. A third outcome is related to SNF assemblies for which no direct validation can be performed, representing the vast majority of cases (due to the large number of SNF assemblies currently stored, or too short or too long cooling periods of interest). A few solutions are possible, depending on the application. For the final repository, systematic measurements of quantities related to decay heat can be performed, such as neutron or gamma emission. This would provide indications of the SNF decay heat at the time of encapsulation. For other applications (short- or long-term cooling), the community would benefit from applying consistent and accepted recommendations on calculation methods, for both decay heat and uncertainties. This would improve the understanding of the results and make comparisons easier.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Far-from-equilibrium slow modes and momentum anisotropy in an expanding plasma

The momentum distribution of particle production in heavy-ion collisions encodes information about thermalization processes in the early-stage quark-gluon plasma. We use kinetic theory to study the far-from-equilibrium evolution of an expanding plasma with an anisotropic momentum-space distribution. We identify slow and fast degrees of freedom in the far-from-equilibrium plasma from the evolution of moments of this distribution. At late times, the slow modes correspond to hydrodynamic degrees of freedom and are naturally gapped from the fast modes by the inverse of the relaxation time, τ R − 1 . At early times, however, there are an infinite number of slow modes with a gap inversely proportional to time, τ − 1 . From the evolution of the slow modes we generalize the paradigm of the far-from-equilibrium attractor to vector and tensor components of the energy-momentum tensor, and even to higher moments of the distribution function that are not part of the hydrodynamic evolution. We predict that initial-state momentum anisotropy decays slowly in the far-from-equilibrium phase and may persist until the relaxation time. Published by the American Physical Society 2024

Brewer, Jasmine (ORCID:0000000230840663)↗
DOE OSTI2024

Guest Editorial for Nondestructive Testing and Evaluation (NDT&E) Special Section

Nondestructive testing and evaluation (NDT&E) are interdisciplinary fields that require a significant amount of interconnection between fundamental physics, measurement techniques, data processing, decision making, and reporting to have a significant impact on industry. NDT&E practitioners are challenged to keep up with the fast-paced evolution of materials, structures, processing, and manufacturing technologies. The development of engineered materials, complex structures and composites, and novel forming techniques require NDT&E to rapidly evolve to meet the needs of industry.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗