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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Harvest and nitrogen effects on bioenergy feedstock quality of grass-legume mixtures on Conservation Reserve Program grasslands

Perennial grass mixtures established on Conservation Reserve Program (CRP) lands can be an important source of feedstock for bioenergy production. This study aimed to evaluate management practices for optimizing the quality of bioenergy feedstock and stand persistence of grass-legume mixtures under diverse environments. A 5-year field study (2008–2012) was conducted to assess the effects of two harvest timings (at anthesis vs after complete senescence) and three nitrogen (N) rates (0, 56, 112 kg N ha -1 ) on biomass chemical compositions (i.e., cell wall components, ash, volatiles, total carbon, and N contents) and the feedstock energy potential, examined by the theoretical ethanol yield (TEY) and the total TEY (i.e., the product of biomass yield and TEY, L ha -1 ), of cool-season mixtures in Georgia and Missouri and a warm-season mixture in Kansas. The canonical correlation analysis (CCA) was used to investigate the effect of vegetative species transitions on feedstock quality. Although environmental variations (mainly precipitation) greatly influenced the management effect on chemical compositions, the delayed harvest after senescence generally improved feedstock quality. In particular, the overall cell wall concentrations and TEY of the warm-season mixtures increased by approximately 7%. Additional N supplies improved the total TEY of both mixtures by ~1.6–4.2 L ha -1 per 1.0 kg N ha -1 input but likely lowered the feedstock quality, particularly for the cool-season mixture. The cell wall concentrations of cool-season mixture reduced by approximately 3%–6%. The CCA results indicated that the increased legume compositions (under low N input) likely enhanced lignin but reduced ash concentrations. This field research demonstrated that with proper management, grass-legume mixtures on CRP lands can provide high-quality feedstock for bioenergy productions.

09 BIOMASS FUELS↗
DOE OSTI2021

Laser-Irradiated Holey Graphene-Supported Single-Atom Catalyst towards Hydrogen Evolution and Oxygen Reduction

Single-atom catalysts (SAC) can boost the intrinsic catalytic activity of hydrogen evolution reaction (HER) and oxygen reduction reaction (ORR). However, the challenge remains due to the complex synthesis process and insufficient stability. A sustainable approach is applied to synthesizing SACs through laser irradiation and gaining mesoporous graphene oxide (MGO). The surface dangling bonds of nitrogen-doped MGO (NMGO) extract metal atoms species from Co or Fe metal foams and convert them to SAC via an appropriate synthesis approach. Notably, the Co-NMGO electrocatalyst requires low potentials of 146 mV to convey a current density of 10 mA cm -2 towards HER. Similarly, the Fe-NMGO electrocatalyst offers an onset of 0.79 V towards ORR in acidic solution. The individual metal atoms are confirmed via aberration-corrected scanning transmission electron microscopy, and X-ray absorption near-edge structure and extended X-ray absorption fine structure. Density functional theory calculations by applying the grand canonical potential kinetics model revealed that Co-NMGO shows the optimum free reaction energy of -0.17 eV at -0.1 V for HER, and Fe-NMGO has less limiting potential than that of Co-NMGO for ORR case. Furthermore, this work opens a new approach towards the synthesis of SAC and its mechanistic understandings.

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

Mapping the Binary Covalent Alloy Space to Pursue Superior Nitrogen Reduction Reaction Catalysts

The electrochemical nitrogen reduction reaction (NRR) has the potential to decarbonize industrial ammonia production. However, NRR has poor activity and selectivity versus the competing hydrogen evolution reaction for catalysts that adhere to scaling relations. Overcoming the limitations imposed by scaling relations requires more complex catalyst materials, however, evaluating materials beyond simple metal systems is a large combinatorial problem that requires an improved understanding of the electrocatalyst surface to rationally guide the discovery of superior catalysts. The study uses grand canonical density functional theory to uncover NRR trends on a large and disparate set of binary covalent alloys (BCA) with variable compositions and active-site geometries. The studied BCAs generally follow scaling relations, albeit with larger variance and several systems that significantly break scaling. BCAs with early- to mid-transition metals tend to lie near the volcano peak and activate the N 2 triple bond via a side-on binding configuration. Trends in the BCA space cannot be readily predicted using simple electronic descriptors, which is ascribed to the large geometric variability of the BCA surfaces. Furthermore, it is anticipated that these findings will provide a foundation for the rational design of superior NRR electrocatalysts with increasing material complexity.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Predicting High‐Resolution Spatial and Spectral Features in Mass Spectrometry Imaging with Machine Learning and Multimodal Data Fusion

Recent advancements in molecular Mass Spectrometry Imaging have sparked interest in integrating high spatial resolution methods with molecular mass-spectrometry-based chemical imaging. Fusion-based algorithms have proven effective in generating high spatial-resolution molecular mass spectra. However, a significant challenge stems from the differing physical mechanisms underlying image generation and data upsampling techniques, potentially leading to discrepancies in integrated information channels. Integrating physical constraints into data processing workflows is essential to tackle this issue. In this study, we propose an innovative approach that merges data from Fourier transform ion cyclotron resonance (FTICR), time-of-flight matrix-assisted laser desorption/ionization, and time-of-flight secondary ion mass spectrometry imaging techniques. By leveraging FT-ICR's unparalleled spectral resolution and ToF-SIMS's exceptional spatial resolution, we achieve submicron spatial resolution, enabling the observation of intact molecular species with remarkable spectral precision. Canonical correlation analysis is employed to incorporate physical constraints. Through sophisticated image processing and machine learning techniques, the results of this fusion hold significant promise for advancing our comprehension of complex systems and unveiling concealed molecular intricacies.

canonical correlation analysis↗
DOE OSTI2020

Structural Rearrangements of Subnanometer Cu Oxide Clusters Govern Catalytic Oxidation

Sub-nanometer metal oxide clusters are very important materials that are widely used, for example, in catalysis or electronic devices such as sensors. Hence, it is critical to understand the atomic structures and properties of sub-nanometer metal oxide clusters under a reactive gas environment, such as O 2 . We consider here experimentally accessible precise-size Cu clusters (Cu 4 ) supported on partially hydroxylated amorphous alumina and show that such clusters can access, in catalytic conditions at high temperature under a pressure of O 2 , a large ensemble of oxidized structures, representing a large variety of oxygen content, of geometries in link with the support, and of catalytic activities for oxidation reactions, as seen from their reducibilities. A grand canonical basin hopping method based on first-principles energy reveals an ensemble of 24 configurations for the Cu 4 O x cluster of low free energy, less than 0.8 eV above the global minimum. The low free energy ensemble consists of clusters of different stoichiometries, which are mainly Cu 4 O 3 and Cu 4 O 4 in the temperature range of 200–400 °C and under a pressure of 0.5 bar of O 2 . The presence of several competitive isomers at each composition implies that cluster fluxionality impacts the phase diagram, which should be ensemble-averaged. In terms of catalytic oxidation activity, Cu 4 O 3 isomers present highly variable O abstraction energy: the most stable isomers are inactive for alkane oxidative dehydrogenation, but isomerization to metastable isomers, that proceed with low barrier, enable to create active configurations with low O abstraction energy. O atoms with the lowest anionic character, and thus of more electrophilic nature, present the best oxidation capability. In contrast, all Cu 4 O 4 isomers show a low O abstraction energy and a high potential catalytic activity. Here, this manuscript demonstrates the unique structural and electronic properties of sub-nano Cu oxide clusters and illustrates the critical roles of configuration ensembles and rearrangement to highly reactive metastable cluster isomers in nanocatalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

How the Bioinspired Fe 2 Mo 6 S 8 Chevrel Breaks Electrocatalytic Nitrogen Reduction Scaling Relations

The nitrogen reduction reaction (NRR) is a renewable alternative to the energy- and CO 2 -intensive Haber–Bosch NH 3 synthesis process but is severely limited by the low activity and selectivity of studied electrocatalysts. The Chevrel phase Fe 2 Mo 6 S 8 has a surface Fe–S–Mo coordination environment that mimics the nitrogenase FeMo-cofactor and was recently shown to provide state-of-the-art activity and selectivity for NRR. Here, we elucidate the previously unknown NRR mechanism on Fe 2 Mo 6 S 8 via grand-canonical density functional theory (GC-DFT) that realistically models solvated and biased surfaces. Fe sites of Fe 2 Mo 6 S 8 selectively stabilize the key *NNH intermediate via a narrow band of free-atom-like surface d-states that selectively hybridize with p-states of *NNH, which results in Fe sites breaking NRR scaling relationships. These sharp d-states arise from an Fe–S bond dissociation during N 2 adsorption that mimics the mechanism of the nitrogenase FeMo-cofactor. Furthermore, we developed a new GC-DFT-based approach for calculating transition states as a function of bias (GC-NEB) and applied it to produce a microkinetic model for NRR at Fe 2 Mo 6 S 8 that predicts high activity and selectivity, in close agreement with experiments. Furthermore, our results suggest new design principles that may identify effective NRR electrocatalysts that minimize the barriers for *N 2 protonation and *NH 3 desorption and that may be broadly applied to the rational discovery of stable, multinary electrocatalysts for other reactions where narrow bands of surface d-states can be tuned to selectively stabilize key reaction intermediates and guide selectivity toward a target product. Furthermore, our results highlight the importance of using GC-DFT and GC-NEB to accurately model electrocatalytic reactions.

10 SYNTHETIC FUELS↗
DOE OSTI2023

Zero-truncated Poisson regression for sparse multiway count data corrupted by false zeros

Abstract We propose a novel statistical inference methodology for multiway count data that is corrupted by false zeros that are indistinguishable from true zero counts. Our approach consists of zero-truncating the Poisson distribution to neglect all zero values. This simple truncated approach dispenses with the need to distinguish between true and false zero counts and reduces the amount of data to be processed. Inference is accomplished via tensor completion that imposes low-rank tensor structure on the Poisson parameter space. Our main result shows that an $N$-way rank-$R$ parametric tensor $\boldsymbol{\mathscr{M}}\in (0,\infty )^{I\times \cdots \times I}$ generating Poisson observations can be accurately estimated by zero-truncated Poisson regression from approximately $IR^2\log _2^2(I)$ non-zero counts under the nonnegative canonical polyadic decomposition. Our result also quantifies the error made by zero-truncating the Poisson distribution when the parameter is uniformly bounded from below. Therefore, under a low-rank multiparameter model, we propose an implementable approach guaranteed to achieve accurate regression in under-determined scenarios with substantial corruption by false zeros. Several numerical experiments are presented to explore the theoretical results.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Perturbative quantum evolution of the gravitational state and dressing in general backgrounds

This paper sets up a perturbative treatment of the evolving quantum state of a gravitational system, in a Schrödinger-like picture, working about a general background. This connects gauge symmetry, the constraints, gravitational dressing, and evolution. Starting with a general time slicing, we give a simple derivation of the relation between the constraints, the Hamiltonian, and its well-known boundary term. Among different approaches to quantization with constraints, we focus on a “gauge-invariant canonical quantization,” which is developed perturbatively in the gravitational coupling. The leading-order solution of the constraints (including the Wheeler-DeWitt equation) for perturbations about the background is given in terms of an explicit construction of gravitational dressings built using certain generalized Green’s functions; different such dressings corresponding to adding propagating gravitational waves to a particular solution of the constraints. Dressed operators commute with the constraints, expressing their gauge invariance, and have an algebraic structure differing significantly from the undressed operators of the underlying field theory. These operators can act on the vacuum to create dressed states, and evolution of general such states is then generated by the boundary Hamiltonian, and alternately may be characterized using other relational observables. This provides a concrete approach to studying perturbative time evolution, including the leading gravitational backreaction, of quantum states of black holes with flat or anti–de-Sitter asymptotics, for example on horizon-crossing slices. This description of evolution in turn provides a starting point for investigating possibly important corrections to quantum evolution, that go beyond quantized general relativity. Published by the American Physical Society 2024

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Quantum Mechanics of a Spherically Symmetric Causal Diamond in Minkowski Spacetime

We construct the phase space of a spherically symmetric causal diamond in ( d + 2 )-dimensional Minkowski spacetime. Utilizing the covariant phase space formalism, we identify the relevant degrees of freedom that localize to the d -dimensional bifurcate horizon and, upon canonical quantization, determine their commutators. On this phase space, we find two Iyer-Wald charges. The first of these charges, proportional to the area of the causal diamond, is responsible for shifting the null time along the horizon and has been well documented in the literature. The second charge is much less understood, being integrable for d ≥ 2 only if we allow for field-dependent diffeomorphisms and is responsible for changing the size of the causal diamond. Published by the American Physical Society 2025

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Multi-Area Model-Free State Estimation via Distributed Tensor Decomposition

This paper proposes a model-free method for distribution system state estimation based on tensor completion using canonical polyadic decomposition. In particular, we consider a setting where the network is divided into multiple areas. The measured physical quantities at buses located in the same area are processed by an area controller. A third-order tensor is constructed to collect these measured quantities. The measurements are analyzed locally to recover the full state information of the network. A closed-form iterative algorithm based on the alternating direction method of multipliers is developed to obtain the low-rank factors of the whole network state tensor where information exchange happens only between neighboring areas. To demonstrate the efficacy of the developed algorithm, numerical simulations are carried out using an IEEE test system.

alternating direction method of multipliers↗
DOE OSTI2022

Zero-Truncated Poisson Tensor Decomposition for Sparse Count Data

We propose a novel statistical inference paradigm for zero-inflated multiway count data that dispenses with the need to distinguish between true and false zero counts. Our approach ignores all zero entries and applies zero-truncated Poisson regression on the positive counts. Inference is accomplished via tensor completion that imposes low-rank structure on the Poisson parameter space. Our main result shows that an $\textit{N}$-way rank-R parametric tensor 𝓜 ϵ (0, ∞) $I$Χ∙∙∙Χ$I$ generating Poisson observations can be accurately estimated from approximately $IR^2 \text{log}^2_2(I)$ non-zero counts for a nonnegative canonical polyadic decomposition. Several numerical experiments are presented demonstrating that our zero-truncated paradigm is comparable to the ideal scenario where the locations of false zero counts are known $\textit{a priori}$.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Data readiness pipeline patterns for scientific AI at scale: Insights from climate, fusion, life sciences, and materials

This article examines how data readiness for AI principles apply to large scientific datasets used to train foundation models. We analyze archetypal workflows across four representative domains—climate, nuclear fusion, life sciences, and materials—to identify common preprocessing patterns and domain‐specific constraints. We introduce a two‐dimensional readiness model that combines canonical preprocessing patterns with a five‐level operational readiness scale, both tailored to high‐performance computing (HPC) environments. This construct helps outline key challenges in transforming large‐scale scientific data into formats suitable for scalable AI training. Together, these dimensions form a conceptual maturity matrix that characterizes scientific data readiness and guides infrastructure development toward standardized, cross‐domain support for scalable and reproducible AI for science. Finally, we evaluate this maturity matrix in the context of case studies including ClimaX (climate), AFLOW (materials), OpenFold (proteomics), and DIII‐D fusion disruption‐prediction workflows, from which we distill lessons learned and provide recommendations to guide practitioners in developing robust AI‐readiness pipelines. Finally, we discuss remaining cross‐cutting challenges that persist across scientific domains.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Strongly Correlated Exciton-Magnetization System for Optical Spin Pumping in CrBr 3 and CrI 3 .

Ferromagnetism in van der Waals systems, preserved down to a monolayer limit, attracted attention to a class of materials with general composition CrX 3 (X=I, Br, Cl), which are treated now as canonical two-dimensional ferromagnets. Their diverse magnetic properties, such as different easy axes or varying and controllable character of in-plane or interlayer ferromagnetic coupling, make them promising candidates for spintronic, photonic, optoelectronic, and other applications. Still, significantly different magneto-optical properties between the three materials, have been presenting a challenging puzzle for researchers over the last few years. Herewith, we demonstrate that despite similar structural and magnetic configurations, the coupling between excitons and magnetization is qualitatively different in CrBr 3 and CrI 3 films. Through a combination of the optical spin pumping experiments with the state-of-the-art theory describing bound excitonic states in the presence of magnetization, we concluded that the hole-magnetization coupling has the opposite sign in CrBr 3 and CrI 3 and also between the ground and excited exciton state. Consequently, we demonstrate efficient spin pumping capabilities in CrBr 3 driven by magnetization via spin-dependent absorption and unraveled the different origins of the magnetic hysteresis in CrBr 3 and CrI 3 are unraveled

36 MATERIALS SCIENCE↗
DOE OSTI2023

Defect‐Induced, Ferroelectric‐Like Switching and Adjustable Dielectric Tunability in Antiferroelectrics

Abstract Antiferroelectrics, which undergo a field‐induced phase transition to ferroelectric order that manifests as double‐hysteresis polarization switching, exhibit great potential for dielectric, electromechanical, and electrothermal applications. Compared to their ferroelectric cousins, however, considerably fewer efforts have been made to understand and control antiferroelectrics. Here, it is demonstrated that the polarization switching behavior of an antiferroelectric can be strongly influenced and effectively regulated by point defects. In films of the canonical antiferroelectric PbZrO 3 , decreasing oxygen pressure during deposition (and thus increasing adatom kinetic energy) causes unexpected “ferroelectric‐like” polarization switching although the films remain in the expected antiferroelectric orthorhombic phase. This “ferroelectric‐like” switching is correlated with the creation of bombardment‐induced point‐defect complexes which pin the antiferroelectric–ferroelectric phase boundaries, and thus effectively delay the phase transition under changing field. The effective pinning energy is extracted via temperature‐dependent switching‐kinetics studies. In turn, by controlling the concentration of defect complexes, the dielectric tunability of the PbZrO 3 can be adjusted, including being able to convert between “positive” and “negative” tunability near zero field. This work reveals the important role and strong capability of defects to engineer antiferroelectrics for new performance and functionalities.

Pan, Hao↗
DOE OSTI2022

Passive Oxide Film Growth Observed On the Atomic Scale

Despite of the ubiquitous presence of passivation on most metal surfaces, the microscopic-level picture of how surface passivation occurs has been hitherto unclear. Using the canonical example of the surface passivation of aluminum, here we employ in situ atomistic transmission electron microscopy observations and computational modeling to disentangle entangled microscopic processes and identify the atomic processes leading to the surface passivation. Based on atomic-scale observations of the layer-by-layer expansion of the metal lattice and its subsequent transformation into the amorphous oxide, it is shown that the surface passivation occurs via a two-stage oxidation process, in which the first stage is dominated by intralayer atomic shuffling whereas the second stage is governed by interlayer atomic disordering upon the progressive oxygen uptake. The first stage can be bypassed by increasing surface defects to promote the interlayer atomic migration that results in direct amorphization of multiple atomic layers of the metal lattice. The identified two-stage reaction mechanism and the effect of surface defects in promoting interlayer atomic shuffling can find broader applicability in utilizing surface defects to tune the mass transport and passivation kinetics, as well as the composition, structure and transport properties of the passivation films.

25 ENERGY STORAGE↗
DOE OSTI2020

Sulfonyl PIM–1: A diverse separation membrane with dilation resistance

A sulfone modified variant (soPIM–1) of the first polymer of intrinsic microporosity has been studied through molecular simulations to analyze its applicability for adsorption–based separations of diverse nonpolar, quadrupolar, and dipolar adsorbate species. Single component gas phase adsorption isotherms of each adsorbate are provided. Here, the adsorptive properties of soPIM–1 are reported from the application of two methods: (a) traditional grand canonical Monte Carlo (GCMC) simulations and (b) a combination of Monte Carlo and molecular dynamics (GCMC/MD) techniques, which accounts for sorption–induced polymer dynamics. The calculated isosteric heats of adsorption are compared to those from the parent PIM–1 structure and reveals increased CO2 affinity with relatively no change in hydrocarbon affinity. Moreover, to quantify soPIM–1's resistance to dilation the evolution of the microporous structure across the adsorption isotherm loading pressures has been evaluated. Relatedly, nonequilibrium MD simulations have been utilized to determine that soPIM–1 is approximately twice as stiff as PIM–1.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Water Catalysis of the Reaction of Methanol with OH Radical in the Atmosphere is Negligible

Abstract Faced with the contradictory results of two recent experimental studies [Jara‐Toro et al., Angew. Chem. Int. Ed . 2017 , 56 , 2166 and Chao et al., Angew. Chem. Int. Ed . 2019 , 58 , 5013] of the possible catalytic effect of water vapor on CH 3 OH + OH reaction, we report calculations that corroborate the conclusion made by Chao et al. and extend the rate constant evaluation down to 200 K. The rate constants of the CH 3 OH + OH reaction catalyzed by a water molecule are computed as functions of temperature and relative humidity using high‐level electronic structure and kinetics calculations. The Wuhan–Minnesota Scaling (WMS) method is used to provide accurate energetics to benchmark a density functional for direct dynamics. Both high‐frequency and low‐frequency anharmonicities are included. Variational and tunneling effects are treated by canonical variational transition state theory with multidimensional small‐curvature tunneling. And, most significantly, we include multistructural effects in the rate constant calculations. Our calculations show that the catalytic effect of water vapor is not observable at 200–400 K.

Wu, Junjun↗
DOE OSTI2024

Biosynthesis of Strained Amino Acids by a PLP‐Dependent Enzyme through Cryptic Halogenation

Abstract Amino acids (AAs) are modular building blocks which nature uses to synthesize both macromolecules, such as proteins, and small molecule natural products, such as alkaloids and non‐ribosomal peptides. While the 20 main proteinogenic AAs display relatively limited side chain diversity, a wide range of non‐canonical amino acids (ncAAs) exist that are not used by the ribosome for protein synthesis, but contain a broad array of structural features and functional groups. In this communication, we report the discovery of the biosynthetic pathway for a new ncAA, pazamine, which contains a cyclopropane ring formed in two steps. In the first step, a chlorine is added onto the C 4 position of lysine by a radical halogenase, PazA. The cyclopropane ring is then formed in the next step by a pyridoxal‐5′‐phosphate‐dependent enzyme, PazB, via an S N 2‐like attack at C 4 to eliminate chloride. Genetic studies of this pathway in the native host, Pseudomonas azotoformans , show that pazamine potentially inhibits ethylene biosynthesis in growing plants based on alterations in the root phenotype of Arabidopsis thaliana seedlings. We further show that PazB can be utilized to make an alternative cyclobutane‐containing AA. These discoveries may lead to advances in biocatalytic production of specialty chemicals and agricultural biotechnology.

Sosa, Max B.↗