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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 1,045 records · Page 58
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Understanding the structural and morphological effects of synthesis route on NpO 2

The availability of actinide standard materials for use in nuclear safeguard applications is critical, as is thorough characterization thereof. Although accurate trace element compositions and isotopic considerations are paramount for deployment of reference standards, structural characterization is also essential towards accurately describing the chemical form and potential matrix effects in candidate materials. Here, to this end, samples of NpO 2 were synthesized via a direct denitration (DD) method and probed with powder X-ray diffraction (PXRD), Raman spectroscopy, and scanning electron microscopy (SEM) for structural and morphological characterization and comparison with NpO 2 materials produced via modified direct denitration (MDD). PXRD confirmed the bulk identity of NpO 2 , and no additional phases were identified using this method. Analysis of Raman data collected using a 532 nm excitation wavelength indicates that samples are mostly phase pure; however, some variability in spectral features is observed. Analysis of additional spectroscopic data collected with a 785 nm excitation wavelength revealed variability in the relative intensity of spectral features. Raman spectroscopy indicates that the sample is primarily NpO 2 ; however, additional signals indicate possible structural disorder, oxidized species, or potential contributions from other Np phases. To further investigate the possibility of additional phase contributions within the sample of NpO 2 , Raman spectroscopic mapping was employed to examine the homogeneity of the sample produced via DD. From this analysis, we determined that despite variability in the intensity of Raman-active vibrational modes, consistent spectra are obtained throughout the area of the sample investigated. SEM images show aggregates with variable sizes and shapes, with rounded, primary particles possessing an average diameter of approximately 100 nm. Comparison of the results of these multimodal analyses to the literature indicates that the crystal chemical, spectroscopic, and microstructural properties of NpO 2 vary based on synthesis method, even if X-ray diffraction data indicate that the bulk phase is NpO 2 .

Direct denitration↗
DOE OSTI2024

Navigating the Use of Direct Current in Residential Settings: Merits and Obstacles

This review paper provides an in-depth analysis of the role of Direct Current (DC) power systems in residential settings, focusing on their safety, efficiency, and environmental advantages. It recognizes the significant contribution of the residential sector to global carbon dioxide emissions and explores how DC power systems can help mitigate these effects. The paper traces the historical evolution of DC power, its resurgence with renewable energy technologies, and the advancements in power electronics that facilitate its integration. Emphasizing the efficiency and safety benefits, especially in low-voltage applications, the paper highlights the seamless integration of DC systems with inherently DC-generating renewable sources like solar PV and wind. The review discusses the critical role of converter technologies in the transition to DC power and examines the compatibility of DC systems with energy storage solutions, underscoring their potential for enhanced energy management. It also addresses the environmental impacts of adopting DC power, aligning with global carbon reduction efforts. The paper analyzes regional case studies, exploring practical applications and outcomes, and addresses challenges such as the need for standardization. It concludes with recommendations for stakeholders and future research directions, emphasizing the economic, technological, and environmental aspects of DC power systems. Overall, the paper presents DC power as a viable and sustainable option for residential energy conservation, contingent upon ongoing technological progress, supportive policies, and standardization.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

The dual role of iron in alkaline water electrolysis: A friend or a foe?

Trace iron (Fe) impurities pose a challenge in alkaline water electrolysis (AWE) and can significantly impact long-term performance, yet their comprehensive system-level effects remain poorly understood. Here, we present the mechanistic roles of Fe in AWE, using combined rotation disk electrode studies, zero-gap cell measurements, and durability tests up to 1,000 h. Fundamental electrochemistry shows that Fe deposition proceeds through a solution-mediated pathway, with dendritic growth triggered under specific mass-transport and potential conditions. In single-cell operation, Fe incorporation substantially enhances nickel (Ni)-based anode activity by forming highly active Ni-Fe oxyhydroxides, while cathodic Fe forms either thin films or dendrites, depending on potential, surface morphology, and electrolyte distribution. Although dendrites do not degrade hydrogen evolution performance up to 1,000 h, they reveal partial intrusion into the separator, indicating a potential durability risk. We identify five governing factors controlling Fe dendrite formation and provide design principles for impurity-resilient AWE systems.

Lyu, Xiang [ORNL] (ORCID:0000000208673248)↗
DOE OSTI2020

An empirical study of I/O separation for burst buffers in HPC systems

To meet the exascale I/O requirements for the High-Performance Computing (HPC), a new I/O subsystem, Burst Buffer, based on solid state drives (SSD), has been developed. However, the diverse HPC workloads and the bursty I/O pattern cause severe data fragmentation that requires costly garbage collection (GC) and increases the number of bytes written to the SSD. To address this data fragmentation challenge, a new multi-stream feature has been developed for SSDs. In this work, we develop an I/O Separation scheme called BIOS to leverage this multi-stream feature to group the I/O streams based on the user IDs. We propose a stream-aware scheduling policy based on burst buffer pools in the workload manager, and integrate the BIOS with the workload manager to optimize the I/O separation scheme in burst buffer. We evaluate the proposed framework with a burst buffer I/O traces from Cori Supercomputer including a diverse set of applications. Experimental results show that the BIOS could improve the performance by 1.44x on average and reduce the Write Amplification Factor (WAF) by up to 1.20x. Finally, these demonstrate the potential benefits of the I/O separation scheme for solid state storage systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Beyond green with synthetic chlorophylls – Connecting structural features with spectral properties

The distinct features of chlorophylls in photosynthesis have led to the formation of numerous derivatives for applications encompassing solar energy conversion, molecular photonics, photodynamic therapy, and molecular imaging. Synthetic chlorins created de novo and bearing a geminal dimethyl group in the reduced ring have proved invaluable for fundamental studies. Four decades of research have led to accumulation of tabulated spectra for > 400 such synthetic chlorins with distinct structural frameworks (17-oxochlorins, 13 1 -oxophorbines, chlorinimides) and substituents (alkyl, aryl, ethynyl, phenylethynyl, acetyl, formyl) located at specific (meso, β) positions. In this review, spectral traces (324 absorption, 247 fluorescence) are assembled along with photophysical data including the molar absorption coefficient (ε), fluorescence quantum yield (Φ f ) and singlet excited-state lifetime (τ s ). The review uses the accumulated spectral data derived from chlorins all containing a uniform molecular scaffold to (1) highlight the effects of molecular structure on spectral features, and (2) identify trends including how ε, Φ f and τ s vary with wavelength and other features. Use of a common geminal-dimethyl-substituted chlorin scaffold – beginning with no substituents, to one substituent at designated sites, and to 2 or more substituents – provides a systematic Aufbau approach for understanding the absorption spectra of chlorins on a path to and beyond the native chlorophylls. Finally, the review provides insights concerning the rational design of potent analogues of Nature’s preeminent red-region absorbers for potential utilization in diverse applications and is aimed at multiple audiences: those interested in spectral properties, tetrapyrrole photophysics, and the molecular design of new chromophores.

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

pCAM precursor produced from electroextraction technology and its application in synthesis of NMC 811 cathode material

The synthesis and characterization of LiNi 0.8 Co 0.1 Mn 0.1 O 2 (LNMC811) cathodes produced from recycled hydroxide precursors obtained from spent lithium-ion batteries is evaluated. Two precursor batches (Sample 1 and Sample 2) are prepared using modified recycling processes to examine how residual impurities and processing conditions influence the properties of the regenerated materials. Structural and compositional characterization by X-ray diffraction, ICP and SEM shows that the recycled precursors exhibit layered hydroxide structures containing both α Ni(OH) 2 and β Ni(OH) 2 phases. Trace impurities including sodium, boron, and aluminum are detected and partially mitigated during processing, with boron found to play a beneficial role in electrochemical behavior. Following lithiation with lithium carbonate and lithium hydroxide at 800 °C under an oxygen rich atmosphere, the resulting LNMC811 materials show electrochemical performance comparable to conventionally synthesized cathodes. Sample 2, which contains higher boron levels and improved cation ordering, delivers an initial discharge capacity of 174 mAh g -1 and retains more than 93 percent of its capacity after 50 cycles. The stable cycling behavior and structural integrity of these materials demonstrate that recycled precursors can be converted into high performance layered cathodes and support recycling as a practical and sustainable route for lithium-ion battery manufacturing.

25 ENERGY STORAGE↗
DOE OSTI2023

Microstructure development and properties of micro-alloyed copper, Cu-0.3Zr-0.15Ag, produced by electron beam additive manufacturing

A micro-alloyed copper powder, Cu-0.3Zr-0.15Ag wt.%, was produced using gas atomization reaction synthesis. Zirconium was added to copper to sequester the oxygen present as copper oxide surface films on the powder particles. The as-received powders, as well as the intentionally oxidized powders were used to fabricate solid test articles by electron beam powder bed fusion additive manufacturing. Dense samples fabricated from as-received powder demonstrated nominal UTS, yield, and elongation values at 260 MPa, 150 MPa, and 34%, respectively. The average electrical conductivity of these samples was measured at 95% of the international annealed copper standard (IACS). Samples fabricated from the oxidized powder exhibited nominal UTS, yield, and elongation of 241 MPa, 146 MPa, and 43%, respectively, with an electrical conductivity of 95 % IACS. During characterization, it was observed that, rather than forming nano-scale dispersoids, the Zirconia (ZrO 2 ) appeared as discontinuous stringers in the metallographic cross-sections that crossed grain and melt pool boundaries. This was rationalized by tracing the presence of the micro-alloying addition of elemental zirconium, which was found to react with surface oxides dissociated in the melt pool to form ZrO 2 , which then solidified on the surface of the melt pool through an allotropic transformation to monoclinic ZrO 2 in discontinuous films and spheroids ranging in size from nanometers to microns. This was confirmed by microscopic analysis of the tops of the melt pools. On subsequent melt passes, these ZrO 2 structures were displaced and redistributed within the melt pool.

36 MATERIALS SCIENCE↗
DOE OSTI2025

El Agente: An autonomous agent for quantum chemistry

Computational chemistry tools are widely used to study the behavior of chemical phenomena. Yet, the complexity of these tools can make them inaccessible to non-specialists and challenging even for experts. In this work, we introduce El Agente Q, an LLM-based multi-agent system that dynamically generates and executes quantum chemistry workflows from natural language user prompts. The system is built on a novel cognitive architecture featuring a hierarchical memory framework that enables flexible task decomposition, adaptive tool selection, post-analysis, and autonomous file handling and submission. El Agente Q is benchmarked on six university-level course exercises and two case studies, demonstrating robust problem-solving performance (averaging >87% task success) and adaptive error handling through in situ debugging. It also supports longer-term, multi-step task execution for more complex workflows, while maintaining transparency through detailed action trace logs. Together, these capabilities lay the foundation for increasingly autonomous and accessible quantum chemistry.

agentic systems↗
DOE OSTI2023

Spatially Resolved Top-Down Proteomics of Tissue Sections Based on a Microfluidic Nanodroplet Sample Preparation Platform

Conventional proteomics measures the averaged signal from mixed cell populations or bulk tissues, leading to the dilution of significant changes in subpopulations of cells that might serve as important biomarkers. Recent developments in bottom-up proteomics have enabled spatial mapping of cellular heterogeneity in tissue microenvironments. However, bottom-up proteomics cannot precisely infer the abundance changes of intact proteins, which are presented as proteoforms. Herein, we described a spatially resolved top-down proteomics (TDP) platform for proteoform identification and quantification directly on thin tissue sections. The spatial TDP platform consisted of a nanoPOTS (nanodroplet Processing in One pot for Trace Samples)-based sample preparation system and an LCM (laser capture microdissection)-based cell isolation system. We improved the nanoPOTS sample preparation by adding benzonase in the extraction buffer to enhance the coverage of nucleus proteins. Using ~200 cultured cells as model samples, the improved approach increased proteoform identifications from 493 to 700; newly identified proteoforms primarily corresponded to nuclear proteins. To demonstrate the spatial TDP platform in tissue samples, we analyzed LCM-isolated tissue voxels from rat brain cortex and hypothalamus regions. We quantified 426 proteoforms by combining identifications from TopPIC and TDPortal with the quantitation from ProMex. Several proteoforms corresponding to the same gene exhibited mixed abundance profiles between two tissue regions, suggesting potential PTM-specific spatial distributions. The spatial TDP workflow has prospects for biomarker discovery at proteoform level from small tissue sections.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Liquid chromatography at critical conditions (LCCC): Capabilities and limitations for polymer analysis

This paper investigates liquid chromatography at critical condition (LCCC) for polymer analysis. Based on controversial claims on the separation of cyclic polymers from linear analogues in the literature, the efficiency of LCCC for separation and purity analysis is questioned. Polyisobutylene (PIB) and poly(3,6-dioxa-1,8-octanedithiols) (polyDODT) were used for the study. Here, the structure of low molecular weight cyclic and linear polyDODT was demonstrated by MALDI-ToF. NMR did not show the presence of thiol end groups in higher molecular weight PIB-disulfide and polyDODT samples, so they were considered cyclic polymers. When a low molecular weight polyDODT oligomer with only traces of cycles, as demonstrated by MALDI-ToF, was mixed with an M n = 27K g/mol cyclic sample, LCCC did not detect the presence of linear oligomers at 6 wt%. Based on the data presented here, it can be concluded that the LCCC method is not capable of measuring < 6 wt% linear contamination so earlier claims for cyclic polystyrene (PS) samples purified by LCCC having < 3 % linear contaminants are questioned.

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

Understanding the deformation behavior of the γ rich transformative Fe 38.5 Mn 20 Co 20 Cr 15 Si 5 Cu 1.5 complex concentrated alloy using in situ synchrotron diffraction

In situ tensile testing coupled with synchrotron x-ray diffraction was used to study the deformation behavior of metastability-engineered Fe 38.5 Mn 20 Co 20 Cr 15 Si 5 Cu 1.5 complex concentrated alloy. Monitoring the evolution of phase fraction and strain hardening response allowed the determination of true critical stress for the onset of the transformation-induced plasticity (TRIP) to be ∼375 MPa, preceded by slip starting at ∼255 MPa. In situ EBSD was used to validate the critical stress for transformation at the microstructure level and observe slip traces to confirm prior slip activity before the transformation. Further, a modeling framework based on stacking fault energy (SFE) was developed to predict the critical stress for transformation. Modeling suggested the SFE of the alloy to fall nearly 15 mJ/m 2 , which agrees well with SFE values calculated using synchrotron peak shifting (12 mJ/m 2 ) and thermodynamic calculation (11 mJ/m 2 ). As a result of γ-fcc to ε-hcp phase transformation, new {0002} ε planes emerged parallel to unaligned {111} γ planes with the tensile loading following S-N orientation relationship. Such selective emergence of new diffraction rings corresponding to ε phase is understood based on the reorientation of γ crystals with reference to tensile axis. In conclusion, this approach can be extended to effectively design alloys based on critical stress required for activating different deformation mechanisms to further push the limits of the strength-ductility envelope.

Complex concentrated alloy↗
DOE OSTI2022

Layered topological semimetal GaGeTe: New polytype with non-centrosymmetric structure

GaGeTe is a layered van der Waals material composed of germanene and GaTe sublayers that has been recently predicted to be a basic Z 2 topological semimetal. To date, only one polytype of GaGeTe is known with trigonal centrosymmetric structure (α phase, space group R-3m, No. 166). Here we show that as-grown samples of GaGeTe show traces of at least another polytype with hexagonal non-centrosymmetric structure (β phase, space group P6 3 mc, No. 186). Moreover, we suggest that another bulk hexagonal polytype (γ phase, space group P-3m1, No. 164) could also be found near room conditions. Both α and β polytypes have been identified and characterized by means of X-ray diffraction and Raman scattering measurements with the support of ab initio calculations. We provide the vibrational properties of both polytypes and show that the Raman spectrum reported for GaGeTe almost forty years ago and attributed to the α phase, was, in fact, that of the secondary β phase. Additionally, we show that a Fermi resonance occurs in α-GaGeTe under non-resonant excitation conditions, but not under resonant excitation conditions. Theoretical calculations show that bulk β-GaGeTe is a non-centrosymmetric weak topological semimetal with even smaller lattice thermal conductivity than centrosymmetric bulk α-GaGeTe. In perspective, our work paves the way for the control and engineering of GaGeTe polytypes to design and implement complex van der Waals heterostructures formed by a combination of centrosymmetric and non-centrosymmetric layers of up to three different polytypes in a single material, suitable for a number of fundamental studies and technological applications.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Development and assessment of hierarchical multi-reward reinforcement learning based potential for silicene with state-of-the-art models

We develop a new interatomic force field for Silicene, a 2D material with a buckled hexagonal lattice structure with high polymorphism. We introduce new parameterizations of a Tersoff model using a hierarchical multi-reward reinforcement learning (RL) methodology coupled with a continuous Monte Carlo Tree Search optimization. Our model significantly outperforms existing methods by enhancing the accuracy of predictions for the structural and thermodynamic properties of seven silicene polymorphs-including structure, energy, equation of state, elasticity, and phonon dispersion-when compared to established models. We further make a comprehensive comparison of the various models in predicting the mechanical and thermal properties of silicene. We trace the origin of the improved performance to the description of the angular dependence in the bond-order term, suggesting that modifying the angular terms in short-range models is essential to capture the structural diversity in low dimensional systems.

2D materials↗
DOE OSTI2021

Bridging the gap between simulated and experimental ionic conductivities in lithium superionic conductors

Lithium superionic conductors (LSCs) are of major importance as solid electrolytes for next-generation all-solid-state lithium-ion batteries. While ab initio molecular dynamics have been extensively applied to study these materials, there are often large discrepancies between predicted and experimentally measured ionic conductivities and activation energies due to the high temperatures and short time scales of such simulations. Here, we present a strategy to bridge this gap using moment tensor potentials (MTPs). We show that MTPs trained on energies and forces computed using the van der Waals optB88 functional yield much more accurate lattice parameters, which in turn leads to accurate prediction of ionic conductivities and activation energies for the Li 0·33 La 0·56 TiO 3 , Li 3 YCl 6 and Li 7 P 3 S 11 LSCs. NPT MD simulations using the optB88 MTPs also reveal that all three LSCs undergo a transition between two quasi-linear Arrhenius regimes at relatively low temperatures. This transition can be traced to an increase in the number and diversity of diffusion pathways, in some cases with a change in the dimensionality of diffusion. Furthermore, this work presents not only an approach to develop high accuracy MTPs, but also outlines the diffusion characteristics for LSCs which is otherwise inaccessible through ab initio computation.

25 ENERGY STORAGE↗
DOE OSTI2023

Effect of Sn oxides on the thermal conductivity of polycrystalline SnSe

SnSe is a promising thermoelectric material, with intrinsically low lattice thermal conductivity, κL. Surprisingly, in several reports, polycrystalline samples are found to have a higher thermal conductivity than single crystals. This disparity has been attributed to trace amounts of thermally conductive Sn oxides at the grain boundaries of polycrystalline samples. The same culprit was recently proposed to explain the reduction of κL in purified, oxide-free, SnSe polycrystals. Here, we test this hypothesis by: (i) tuning the type of oxide in SnSe by exploiting thermodynamic stability regions, since Sn-rich or Sn-poor compositions favour the formation of SnO or SnO 2 , respectively; and (ii) varying the quantity of SnO 2 by intentionally oxidizing SnSe powder before consolidation, to obtain samples with quantifiable amounts - up to 15% - of SnO 2 . We find that the κL of SnSe is impervious to changes in the type or the amount of Sn oxide present in the samples. Our results show that a simple “rule of mixtures” cannot be used to estimate the effect of grain boundary oxides on the thermal conductivity of SnSe. These results call for an improved understanding of the intriguing thermal transport mechanisms in SnSe and numerous other systems where a two-phase transport is presumed.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Selective dopant segregation modulates mesoscale reaction kinetics in layered transition metal oxide

Incorporation of foreign elements into the cathode material is broadly adopted by both academia and industry to improve the battery performance. The lack of an in-depth understanding for the underlying mechanism, however, makes it a largely try-and-error process with unsatisfactory efficiency and effectiveness. This is particularly true for the electrochemical reaction kinetics that is heterogeneous over a broad range of length scales and is determined collectively by the cathode’s electronic structure, lattice configuration, and micro-morphology. In this work, we unveiled a facet-dependent dopant segregation effect in Zr-modified single-crystal LiNi 0.6 Co 0.2 Mn 0.2 O 2 cathode. By forming kinetically favored corners on the cathode particles, the presence of a trace amount of Zr critically modulates the mesoscale reaction kinetics. Our findings suggest that a delicately controlled dopant distribution is a viable strategy for designing the next-generation battery cathode with superior structural and chemical robustness.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Rational synthesis of high-performance Ni-rich layered oxide cathode enabled via probing solid-state lithiation evolution

Lithium (Li)-ion batteries using nickel (Ni)-rich layered oxide cathode have been pursued with interest due to high practical energy density. A fundamental understanding of the reaction pathways and structural evolution of the solid-phase synthesis of these materials is crucial for their rational design and process development for mass production. In this work, structural evolution during solid-state synthesis was traced via in situ technique, with a particular emphasis on the lithiation reaction and migration of transition metal (TM) ions. The sintering process is governed by the competitive relationship of decomposition and lithiation reactions, which can be regulated through temperature windows. Controlling the melting point of the Li sources, as well as their affinity to cathode precursors, is highly desired to maintain the layered ordering of TM ions throughout the whole synthesis process, which simplifies the manufacturing process and improves the quality of the manufactured cathode material.

25 ENERGY STORAGE↗
DOE OSTI2020

Enhancing nuclear data validation analysis by using machine learning

In this work, we demonstrate how machine learning (ML) techniques can be used as an auxiliary tool for nuclear data validation analysis. The output of the ML analysis can inform evaluators and validators on the quality, or lack thereof, of specific nuclear data and benchmark experiments with respect to simulating these experimental benchmark values. To this end, measured and simulated effective neutron multiplication factors, k eff , of 875 selected ICSBEP critical assemblies and the latter's sensitivities with respect to nuclear data as well as benchmarks' features (e.g., material nuclide, core geometry) are used as input for a random forest (RF) regression model. The RF is used to encode the complex inter-dependencies between thousands of nuclear data features (i.e., sensitivity profiles and aspects describing the measurements) and 875 simulated and experimental k eff values in order to understand what nuclear data features are most informative for predicting bias. The complexity of relationships and high-dimensional space is difficult-to-impossible to search fully using simply expert judgment. As a first proof-of-concept—step, it is demonstrated that this technique is able to correctly trace large discrepancies between simulated and experimental k eff back to fabricated shortcomings in nuclear data that were perturbed to simulated k eff values. In a second, real-case scenario, step, the RF algorithm is used to validate the ENDF/B-VIII.0 library in comparison to ENDF/B-VII.1 nuclear data. One case is showcased where the chosen ML algorithms highlighted nuclear data (the 19 F(n,inl) cross section from 0.4–0.9 MeV) that are shown to be problematic by comparing them to associated differential experimental data and nuclear data from other libraries. In addition to that, it is shown that the RF results point towards poor benchmark experiments and associated underestimated uncertainties (e.g., the PU-SOL-THERM-028 series). However, using the RF algorithm for validating nuclear data with respect to k eff is currently limited to pinpointing groups of questionable nuclear data due to the inherent correlations between features introduced by the nuclear data themselves and how k eff is simulated. Due to this, we recommend that the ML methods presented be used to augment—rather than replace—the expert knowledge of evaluators and validators.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗