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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Bulk‐Boundary Correspondence of Semimetal Ru 3 Sn 7 and Topological Surface States on Chemically Realistic Terminations

Ru 3 Sn 7 is experimentally demonstrated as an efficient catalyst, with potential utilization of topological surface states for hydrogen evolution reaction. Despite its promising catalytic performance, the topological nature of Ru 3 Sn 7 remains uncertain. Particularly, the bulk-boundary correspondence has not yet been established, hence hindering a rigorous justification of its topologically-protected surface states. In this work, the bulk topology of Ru 3 Sn 7 is detailed using first-principles calculations and the topological quantum chemistry formalism. Ru3Sn7 turns out to be an enforced semimetal possessing symmetry-protected crossings within a set of bands near the Fermi level, which are enforced and prescribed by the violations of symmetry-prescribed compatibility relations. Moreover, the surface states and the associated origin from the same set of entangled bands are identified, thereby establishing the bulk-boundary correspondence. To evaluate the effects of chemical modifications, the response of topological surface states to various surface terminations, stoichiometry, and oxidation is examined. The surface structures are globally optimized, and the phase diagrams for various experimental conditions are built. It is shown that, due to changes in the local chemical environment, the original surface states are significantly altered. Modified surface bands can be observed near the Fermi level on surface terminations that preserve the C 4v symmetry.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Tailoring Binder Molecular Weight to Enhance Slurry-Cast NMC Cathodes for Sulfide Solid-State Batteries

We demonstrate for the first time the critical influence of binder molecular weight on the performance of slurry-cast lithium nickel manganese cobalt oxide (NMC) cathodes in sulfide-based all-solid-state batteries (SSBs). SSBs are increasingly recognized as a safer and potentially more efficient alternative to traditional Li-ion batteries, owing to the superior ionic conductivities and inherent safety features of sulfide solid electrolytes. However, the integration of high-voltage NMC cathodes with sheet-type sulfide solid electrolytes presents significant fabrication challenges. Our findings reveal that higher molecular weight binders not only enhance the discharge capacity and cycle life of these cathodes but also ensure robust adhesion and structural integrity. By optimizing binder molecular weights, we effectively shield the active materials from degradation and mechanical stress, significantly boosting the functionality and longevity of SSBs. These results underscore the paramount importance of binder properties in advancing the practical application of high-performance all-solid-state batteries.

25 ENERGY STORAGE↗
DOE OSTI2025

Tunable Crosslinked Ether Polymer Network Electrolytes for High‐Performance All‐Solid‐State Sodium Batteries

All-solid-state batteries (ASSBs) are critical for achieving high energy density and enhanced safety. Solid polymer electrolytes (SPEs) offer key advantages over other electrolytes, including improved safety, flexibility, and interfacial contact. Among the SPEs, ether-based polymers are widely studied due to their ease of processing and high ionic conductivity (σi) in the amorphous state. In this work, the introduction of poly(ethylene glycol) methyl ether methacrylate (PEGMEMA) into an SPE matrix composed of poly(ethylene glycol) diacrylate (PEGDA), poly(ethylene glycol) (PEG2k), and sodium bis(fluorosulfonyl)imide (NaFSI) salt is investigated to facilitate the formation of amorphous, high σ i SPEs through end-group engineering and polymer ratio optimization. PEGMEMA enhances structural integrity via crosslinking with PEGDA through its methacrylate group, while its methyl end group aids ion conduction. A 2:1:7 ratio of PEGDA:PEGMEMA:PEG2k exhibits a σi of 1.16 x 10 -4 S cm -1 and oxidative stability up to 4.4 V at 60 °C. A solid-state cell incorporating this SPE, a Na 2/3 Ni 1/3 Mn 2/3 O 2 (NM12) cathode, and a sodium-metal anode demonstrates excellent cycling stability, retaining over 80 % of its initial capacity for 150 cycles at 60 °C. The findings highlight the potential of end-group engineering in improving the electrochemical performance of SPEs.

25 ENERGY STORAGE↗
DOE OSTI2026

Suppressing CO formation in low-temperature methanol steam reforming via Ce-modified CuZnGa layered oxide catalysts

Cu-based layered double hydroxides (LDHs) are widely recognized as effective catalysts for low-temperature methanol steam reforming, yet achieving high hydrogen productivity together with near-complete suppression of CO formation remains challenging. Here, we report the synthesis and evaluation of a series of CuZnGa LDH-derived catalysts and Ce-modified analogues prepared via an aqueous miscible organic method, which enables high metal dispersion and precise structural control. The optimized CuZnGa catalyst exhibits a hydrogen production rate of 16.9 µmol H 2 ·g cat −1 ·s −1 at 180 °C with an H 2 /CO ratio exceeding 3500, outperforming many state-of-the-art low-temperature systems. Importantly, the incorporation of small amounts of Ce further suppresses CO formation while maintaining high hydrogen productivity. Combined spectroscopic characterization and density functional theory calculations reveal that Ce is incorporated into the LDH lattice by substituting Ga 3+ sites up to a critical threshold, beyond which highly dispersed CeO x species are formed. These species provide mobile lattice oxygen that participates in a Mars-van Krevelen-type pathway, selectively oxidizing CO and suppressing the reverse water-gas shift reaction. This study establishes a clear relationship between Ce speciation, oxygen mobility, and catalytic selectivity in LDH-derived systems. The resulting catalysts demonstrate the potential of interface-engineered Cu-based materials for efficient low-temperature hydrogen production with minimal CO contamination.

09 BIOMASS FUELS↗
DOE OSTI2026

A Full-Induction Magnetohydrodynamics Solver for Liquid Metal Fusion Blankets in Vertex-CFD

Multiphysics modeling of liquid metal fusion blankets, which produce tritium and convert energy of neutrons created via fusion reactions into heat, is crucial for predicting performance, ensuring structural integrity, and optimizing energy production. While traditional blanket modeling of liquid metal flows during normal steady operating conditions commonly employs the inductionless approximation of the magnetohydrodynamics (MHD) equations, transient scenarios, when the plasma-confining magnetic field varies on millisecond time scales, require a full-induction MHD approach that dynamically evolves the magnetic field via the time-dependent induction equation. This paper presents the formulation, implementation, and initial verification of a full-induction MHD solver integrated within the open-source Vertex-CFD framework, which aims to achieve tight multiphysics coupling, a flexible software design enabling easy extension and addition of physics models, and performance portability across computing platforms. The solver utilizes finite element spatial discretization, implicit Runge–Kutta time integration, and an inexact Newton method to solve the resulting discrete nonlinear system, leveraging Trilinos packages for efficient computation. Verification against selected benchmark problems demonstrates accuracy and robustness of the solver. Furthermore, when the solver is applied to an idealized blanket model in 2.5D and full 3D, results obtained with Vertex-CFD are in good agreement with recently published quasi-2D simulations. These findings establish a computational foundation for future simulations of transient MHD phenomena in liquid metal blankets with Vertex-CFD, and open avenues for future extensions and performance optimizations.

Endeve, Eirik [ORNL] (ORCID:0000000312519507)↗
DOE OSTI2026

Identification of KLHL12 Ligands Using Fragment-Based Methods

Targeted protein degradation can be induced by recruiting a protein of interest to an E3 ligase, resulting in its ubiquitination and subsequent proteasome-mediated degradation. However, only a small number of E3 ligases have been utilized for degradation. Expansion of the repertoire of useful E3 ligases via the identification of ligands to those ligases could broaden the scope and applicability of the degradation paradigm. We have identified KLHL12 as an E3 ligase with higher expression in cancer over normal tissues. We report here the use of NMR-based screening to identify fragments that bind to KLHL12, and X-ray structures of a fragment hit bound to KLHL12. Using this structural information, we optimized the hits, leading to the first reported small molecules that bind to KLHL12 with submicromolar affinity. Derivatives of these compounds may be useful for the construction of PROTACs to selectively degrade protein targets in tumors while sparing normal cells.

Amines↗
DOE OSTI2026

Elucidating Compositional Differences in Halide Perovskites for Normal and Inverted Perovskite Solar Cells

Over the recent few years, extensive research efforts have shifted from normal (n-i-p) to inverted (p-i-n) perovskite solar cells (PSCs), owing to their promising efficiency and operational stability, enabled by low-temperature processing. Despite a fundamentally identical operation principle (only structurally inverted), the optimized perovskite compositions for normal and inverted PSCs differ significantly across the literature, suggesting an underlying design principle for perovskite composition. Here, we unveil the role of cesium cation in enhancing interfacial contact between the perovskite layer and the underlying hole-transporting layer (HTL) in inverted PSCs. Comprehensive in situ and device characterization reveal that cesium incorporation promotes the formation of initial nucleation seeds for heterogeneous nucleation at the perovskite/hydrophobic HTL interface, thereby improving their contact. The resulting compositional heterogeneity explains the focus of recent studies on resolving this issue. This study provides mechanistic insight into designing perovskite compositions to further enhance the performance and longevity of PSCs.

Park, Keonwoo↗
DOE OSTI2024

Systematic determination of a material’s magnetic ground state from first principles

Abstract We present a self-consistent method based on first-principles calculations to determine the magnetic ground state of materials, regardless of their dimensionality. Our methodology is founded on satisfying the stability conditions derived from the linear spin wave theory (LSWT) by optimizing the magnetic structure iteratively. We demonstrate the effectiveness of our method by successfully predicting the experimental magnetic structures of NiO, FePS 3 , FeP, MnF 2 , FeCl 2 , and CuO. In each case, we compared our results with available experimental data and existing theoretical calculations reported in the literature. Finally, we discuss the validity of the method and the possible extensions.

Chemistry↗
DOE OSTI2025

3D-printed micro ion trap technology for quantum information applications

Trapped-ion applications, such as in quantum information processing1, precision measurements, optical clocks and mass spectrometry, rely on specialized high-performance ion traps. The last three of these applications typically use traditional machining to customize macroscopic 3D Paul traps, whereas quantum information processing experiments usually rely on photolithographic techniques to miniaturize the traps and meet scalability requirements. Using photolithography, however, it is challenging to fabricate the complex 3D electrode structures required for optimal confinement. Here, in this work, we demonstrate a high-resolution 3D printing technology based on two-photon polymerization (2PP) that is capable of fabricating large arrays of high-performance miniaturized 3D traps. We show that 3D-printed ion traps combine the advantages, such as strong radial confinement, of traditionally machined 3D traps with on-chip miniaturization. We trap calcium ions in 3D-printed ion traps with radial trap frequencies ranging from 2 MHz to 24 MHz. The tight confinement eases ion cooling requirements and allows us to implement high-quality Rabi oscillations with Doppler cooling only. Also, we demonstrate a two-qubit gate with a Bell-state fidelity of 0.978 ± 0.012. With 3D printing technology, the design freedom is greatly expanded without sacrificing scalability and precision, so that ion trap geometries can be optimized for higher performance and better functionality.

quantum information↗
DOE OSTI2026

American cities in a time of global environmental change: the case of the Baltimore Social-Environmental Collaborative

The Baltimore Social-Environmental Collaborative (BSEC) Urban Integrated Field Laboratory seeks a new paradigm for urban climate research. Motivated by deep uncertainties in urban climate and the future of urban systems, BSEC works collaboratively across institutions and stakeholder groups to co-generate the science needed to advance energy security and resilience to extreme events across the city of Baltimore, Maryland, USA, and to do so in a manner that can inform similar efforts in other cities. BSEC begins with stakeholder priorities (health, affordable energy, etc) and designs observation networks and models to deliver climate science to address them. This takes the form of an iterative collaborative cycle, in which an initial research strategy is repeatedly updated in conversation with community partners, and researchers and stakeholders learn from each other. To date, this cycle has included multiple rounds of collaborative deliberation on urban heat mitigation, in which a multicriteria decision tool has been updated with more community-relevant spatial structure and modified optimization metrics. The guiding objective of this cycle is to inform potential ‘secure and resilient pathways’ for energy and infrastructure. In doing so, BSEC addresses fundamental urban science questions in natural and social sciences. It also tests our ability to integrate this science in a manner that advances participatory decision-making for urban resilience.

climate↗
DOE OSTI2024

The Role of Azimuthal Prestress in the Longitudinal Degradation of Nb 3 Sn Superconducting Magnets

Superconducting magnet coils are subject to enormous electro-magnetic forces which push the cables away from the winding pole, and against the surrounding structure. This structure is usually optimized trying to limit the overall motion and the strains experienced by the superconducting elements. To achieve this, preload forces are applied both in the coil cross-section and along its length. If the e.m. forces overcome these preloads, separation between the coil and the pole occurs, resulting in an overall loss of rigidity. During the magnet design process, it is often tempting to treat the optimization of the azimuthal and longitudinal preload systems separately. However, the two are inextricably related: as the cross-section preload increases, friction can prevent any motion in the longitudinal plane, and decreasing it can instead allow dangerous motions in the conductor ends. The latter can result in very high strains and, in Nb 3 Sn conductors, damage that can prevent the magnet to reach the desired performances. In an attempt to define design guidelines, in this paper we use simplified numerical models to compute, as a function of the in-plane prestress, the variation of the peak strains in the end region of the coils. Finally, we investigate the impact of the azimuthal prestress on a real magnet case, the High-Luminosity Nb 3 Sn Quadrupole MQXF.

Nb3Sn↗
DOE OSTI2025

SpectraCodec: A Hilbert curve-based method for encoding metadata in mass spectra for machine learning applications (SpectraCodec) v1

Machine learning approaches to mass spectrometry (MS) data analysis require structured metadata for optimal performance. However, current MS file formats necessitate external metadata sources, creating integration challenges that impede analytical workflows. Here, we present a novel approach for encoding metadata directly within mzML files using one-hot encoding of ASCII characters mapped via Hilbert space-filling curves. This strategy embeds metadata in the first spectrum's m/z-intensity space, ensuring persistence with the primary data, eliminating the need for external metadata files, and maintaining compatibility with existing MS software. We demonstrate that the Hilbert curve mapping efficiently utilizes the two-dimensional spectral space while maintaining robust data recovery. This method offers a practical solution for machine learning applications in mass spectrometry by ensuring metadata and spectral data remain unified through all stages of analysis.

Bowen, Benjamin [Lawrence Berkeley National Labora↗
DOE OSTI2024

CIGS Technology Advancement via Fundamental Modeling of Defect/Impurity Interactions (Final Technical Report)

The primary goals of the proposed work were to provide modeling tools (and the associated insight which comes along with model development) for design and optimization of CuIn x Ga 1-x Se 2 (CIGS) and CdSeTe (CST) solar cell manufacturing processes and to establish the foundation for comprehensive end-to-end predictive modeling tools to enable optimization of thin film photovoltaic technology for performance, cost, yield, and reliability. The initial focus of efforts within this project was to develop coupled process/optical/device models for CIGS PV technology and to work with Siva Power to apply that TCAD (technology computer-aided design) system to improve the efficiency and reduce manufacturing costs for CIGS solar cells. Our approach to that end was to generate an extensive database of DFT calculations and to use those calculations via statistical thermodynamics methods and Monte Carlo simulation to develop and characterize models for the behavior of native defects as well as intentional and unintentional impurities, including the redistribution of the primary components of CIGS films. Increased effort went toward coupling those models for defect behavior and composition evolution to the performance of multicrystalline CIGS solar cells via prediction of doping level and recombination lifetime as function of manufacturing process. In the second budget period, the project pivoted to developing a similar system for the CdSeTe system, focused especially on understanding the role of Se/Te alloy concentration. Execution of the project resulted in the successful development of TCAD systems for both CIGS and CdSeTe thin film PV within the Synopsys Sentaurus framework by utilizing the Alagator interface. In the first budget period of the project, we developed quantitative models for the major components of CIGS PV and implemented them within a framework that couples process, optical, and device simulation. From the insights we have gained, we identified novel opportunities for enhancing CIGS solar cell performance and have laid the groundwork to further optimize the layer structure, composition profile, and thermal cycles for substantially improved efficiency and lower manufacturing costs. For the CIGS system, process changes to achieve greater than 1% absolute enhancement in efficiency were identified, but testing of those approaches was stymied by lack of a domestic CIGS manufacturing partner after the closure of Siva Power as well as Miasole. For CdSeTe, a fully capable TCAD system only became ready to apply near the end of the project period, so substantial opportunities remain to apply those models to enhance the leading thin film PV technology.

14 SOLAR ENERGY↗
DOE OSTI2026

A Perspective on Traditional and Data Driven Electrochemical Modeling and Analysis

To understand the behavior of electrochemical systems, we need to reduce the dimensionality of the measured current-voltage-time (I-V-t) data by fitting models, thus enabling us to analyze and compare the governing physics. Traditionally, the process for this is an 'expert first' approach: defining the model and its explicit assumptions based on inductive reasoning or empirical observation, fitting small portions of the I-V-t data where assumptions are most valid or carefully designing experiments to enforce key assumptions, and then interpreting the model parameters. However, modern data-driven methods enable a new paradigm: a 'data first' approach, where the latent behaviors governing the system's measured response are identified directly using machine-learning models that optimize both model structure and parameters from the I-V-t data, guaranteeing that the learned model explains as much of the observed system response as possible. After model identification, the model can then be interrogated by an expert to connect observed behaviors with underlying physics. This talk will review several different types of electrochemical analysis (electrochemical impedance, differential voltage-capacity, electrochemical kinetics) and compare the traditional and data-driven methods for analyzing the data.

42 ENGINEERING↗
DOE OSTI2025

Advanced Modeling and Process-Materials Co-Optimization Strategies for Swing Adsorption Based Gas Separations

This project devised a computational framework for simultaneously co-optimizing pressure swing adsorption process designs along with the sorbent materials (specifically, metal-organic frameworks) to be employed in the associated packed bed columns. The materials optimization aspect involved search over a design space that can describe the material’s molecular structure, while the process optimization aspect considered various process degrees of freedom for steps arising in various cycle configurations. This framework was demonstrated on the separation of nitrogen and carbon dioxide, which arises ubiquitously in a multitude of post-combustion carbon capture and “blue” hydrogen production applications. Our results led to metal-organic framework molecular descriptor choices that are predicted to outperform standard structures used in practice, providing guidance for future metal-organic framework synthesis efforts.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2025

Ultra‐Flexible Pixelated Perovskite Photodetectors Enabled by Honeycomb Polymer Grids for High‐Resolution Imaging

Abstract A nature‐inspired fabrication method based on a photolithography‐free flexible polymer grid is reported for high‐resolution pixelation of perovskite photodiode arrays with exceptional mechanical ductility and a morphology resembling that of natural compound eyes. The resulting pixelated perovskite photosensitive layer has a ≈1 µm pixel size with 2000 Pixels per inch (PPI) resolution when fully assembled as a photodetector array, delivering a detectivity of >10 13 Jones while providing cross‐talk free imaging. Using a polymer grid effectively releases stress on the perovskite platform, greatly increasing the mechanical agility of the otherwise brittle perovskite film. This novel fabrication methodology and device design offer new possibilities for applications in robotics, biomedical imaging, and virtual and augmented reality.

Zheng, Ding [Department of Chemistry and the Mater↗