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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 OSTI2026

Coupling Noah-Multiparameterization land-surface Model with Energy Research and Forecasting Model

The Energy Research and Forecasting (ERF) model is a high-performance atmospheric model built on the AMReX adaptive mesh refinement (AMR) framework, enabling efficient simulations on heterogeneous computing platforms that combine multicore processors with hardware accelerators. To support land–atmosphere interactions within ERF’s AMR-based environment, a land-surface model must be capable of operating directly on hierarchically refined meshes. In this work, we present a methodology for coupling the Fortran-based Noah-Multiparameterization (Noah-MP) land-surface model with ERF’s C++ codebase. Rather than rewriting Noah-MP, we construct a Fortran–C interoperability layer using CodeScribe, a tool that leverages large language models (LLMs) to automate the generation of interface code. CodeScribe applies structured prompting techniques to generate bindings that support efficient data exchange and function calls between ERF and Noah-MP. The coupling framework also incorporates AMR-aware data handling strategies, allowing NoahMP to operate seamlessly within ERF’s hierarchical mesh structure. This work provides a structured approach for integrating legacy Fortran models into modern C++-based modeling systems using LLM-assisted code generation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Advanced Electrode Structures for Proton Exchange Membrane Fuel Cells: Current Status and Path Forward

Abstract Proton exchange membrane fuel cells (PEMFCs) have demonstrated their viability as a promising candidate for clean energy applications. However, performance of conventional PEMFC electrodes, especially the cathode electrode, suffers from low catalyst utilization and sluggish mass transport due to the randomly distributed components and tortuous transport pathways. Development of alternative architectures in which the electrode structure is controlled across a range of length scales provides a promising path toward overcoming these limitations. Here, we provide a comprehensive review of recent research and development of advanced electrode structures, organized by decreasing length-scale from the millimeter-scale to the nanometer-scale. Specifically, advanced electrode structures are categorized into five unique architectures for specific functions: (1) macro-patterned electrodes for enhanced macro-scale mass transport, (2) micro-patterned electrodes for enhanced micro-scale mass transport, (3) electrospun electrodes with fiber-based morphology for enhanced in-plane proton transport and through-plane O 2 transport, (4) enhanced-porosity electrodes for improved oxygen transport through selective inclusion of void space, and (5) catalyst film electrodes for elimination of carbon corrosion and ionomer poisoning. The PEMFC performance results achieved from each alternative electrode structure are presented and tabulated for comparison with conventional electrode architectures. Moreover, analysis of mechanisms by which new electrode structures can improve performance is presented and discussed. Finally, an overview of current limitations and future research needs is presented to guide the development of electrode structures for next generation PEMFCs. Graphical Abstract Development of improved electrode architectures with the control of structure on length scales ranging from millimeters to nanometers could enable a new generation of fuel cells with increased performance and reduced cost. This paper presents an in-depth review and critical analysis of recent developments and future outlook on the design of advanced electrode structures.

25 ENERGY STORAGE↗
DOE OSTI2024

Transmission-mounted combined energy recovery drive

An energy recovery drive system includes a motor-generator that is structured to selectively operate in a motor mode and a generator mode. A first shaft is operatively coupled to a transmission power take-off shaft. A second shaft is operatively coupled to the motor-generator and to an alternative power source. The energy recovery drive system is controllably operated in a plurality of operating modes. In a first operating mode, the motor-generator is in torque providing engagement with each of the first and second shafts. In a second operating mode, the motor-generator is in torque communicating engagement with each of the first and second shafts. In a third operating mode, which the motor-generator is in torque communicating engagement with the second shaft and is disengaged from transferring torque to the first shaft and from receiving torque from the first shaft.

Correa, Dixon Malcolm↗
DOE OSTI2025

Cavity-Assisted Coherent Phonon Generation and Control in a WSe 2 /Au Structure

Coherent phonons in the Terahertz (THz) regime have gained attention as potential candidates for next-generation high-speed, low-energy information carriers in atomically thin phononic or phonon-integrated on-chip devices. Nevertheless, achieving efficient control over THz coherent phonons continues to pose a considerable challenge. In this work, we explore THz coherent phonon generation in exfoliated van der Waals (vdW) flakes of WSe 2 on Au (WSe 2 /Au) and Si (WSe 2 /Si) using time-resolved pump-probe spectroscopy. The generation of THz coherent phonons was studied as a function of WSe 2 layer thickness and laser wavelength. Notably, a significant enhancement in THz coherent phonon generation was observed in the WSe 2 /Au structure, but only within specific ranges of WSe 2 thickness and laser wavelength. Further, the results from numerical simulations, which consider a self-hybridized optical cavity depending on WSe 2 thickness, along with optical reflectance and Raman spectroscopy measurements, aligned well with the time-domain observations of THz coherent phonon generation. We propose that the observed enhancement in THz coherent phonon generation is strongly influenced by light-matter interaction in the WSe 2 cavity, a mechanism that may be applicable to a broader range of vdW materials. These findings offer promising insights for the development of THz phononic or phonon-integrated devices.

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

Design of facilitated dissociation enables timing of cytokine signalling

Protein design has focused on the design of ground states, ensuring that they are sufficiently low energy to be highly populated. Designing the kinetics and dynamics of a system requires, in addition, the design of excited states that are traversed in transitions from one low-lying state to another. This is a challenging task because such states must be sufficiently strained to be poorly populated, but not so strained that they are not populated at all, and because protein design methods have focused on generating near-ideal structures. Here we describe a general approach for designing systems that use an induced-fit power stroke to generate a structurally frustrated and strained excited state, allosterically driving protein complex dissociation. X-ray crystallography, double electron–electron resonance spectroscopy and kinetic binding measurements show that incorporating excited states enables the design of effector-induced increases in dissociation rates as high as 5,700-fold. We highlight the power of this approach by designing rapid biosensors, kinetically controlled circuits and cytokine mimics that can be dissociated from their receptors within seconds, enabling dissection of the temporal dynamics of interleukin-2 signalling.

deformation dynamics↗
DOE OSTI2024

Deactivation of Cu/ZSM-5 Catalysts during the Conversion of 2,3-Butanediol to Butenes

This work determines the deactivation mechanisms of Cu/ZSM-5 catalysts used for the conversion of 2,3-butanediol to butene as part of an alcohol-to-jet route. The deactivation of the catalyst, reflected by a drop in the rate of the limiting hydrogenation step by over 90% in 24 h at a weight hourly space velocity of 5.92 h−1, proceeds via both the agglomeration of copper particles and the obstruction of copper surfaces due to carbonaceous deposits, although the former has less impact on the decrease in the hydrogenation rate. To reduce the detrimental effect of carbonaceous deposits on catalytic activity, ZMS-5 is modified through desilication of the HZSM-5 support with NaOH and CsOH solutions to generate a hierarchical structure with mesopores. The catalyst with the CsOH-treated support generates the highest overall yield of desired olefin products and experiences the slowest deactivation. This is a result of the lower Brønsted acidity and larger mesopores found in the CsOH-treated catalyst, leading to the slower formation of carbonaceous deposits and the faster diffusion of their precursors out of the pores.

Chemistry↗
DOE OSTI2020

Deep learning to generate in silico chemical property libraries and candidate molecules for small molecule identification in complex samples

Comprehensive and unambiguous identification of small molecules in complex samples will revolutionize our understanding of the role of metabolites in biological systems. Existing and emerging technologies have enabled measurement of chemical properties of molecules in complex mixtures and, in concert, are sensitive enough to resolve even stereoisomers. Despite these experimental advances, small molecule identification is inhibited by (i) chemical reference libraries (e.g. mass spectra, collision cross section, and other measurable property libraries) representing <1% of known molecules, limiting the number of possible identifications, and (ii) the lack of a method to generate candidate matches directly from experimental features (i.e. without a library). To this end, we developed a variational autoencoder (VAE) to learn a continuous numerical, or latent, representation of molecular structure to expand reference libraries for small molecule identification. We extended the VAE to include a chemical property decoder, trained as a multitask network, in order to shape the latent representation such that it assembles according to desired chemical properties. The approach is unique in its application to metabolomics and small molecule identification, with its focus on properties that can be obtained from experimental measurements (m/z, CCS) paired with its training paradigm, which involved a cascade of transfer learning iterations. First, molecular representation is learned from a large dataset of structures with m/z labels. Next, in silico property values are used to continue training, as experimental property data is limited. Finally, the network is further refined by being trained with the experimental data. This allows the network to learn as much as possible at each stage, enabling success with progressively smaller datasets without overfitting. Once trained, the network can be used to predict chemical properties directly from structure, as well as generate candidate structures with desired chemical properties. Our approach is orders of magnitude faster than first-principles simulation for CCS property prediction. Additionally, the ability to generate novel molecules along manifolds, defined by chemical property analogues, positions DarkChem as highly useful in a number of application areas, including metabolomics and small molecule identification, drug discovery and design, chemical forensics, and beyond.

Colby, Sean M.↗
DOE OSTI2025

Towards next-generation optical potentials for nuclear reactions and structure calculations

Optical-model potentials (OMPs) are critical ingredients for basic and applied nuclear physics. Present-day computational capabilities allow us to generate data-driven nucleon-nucleus OMPs that are non-local and exactly dispersive (as theoretically required to be), include statistically-sound uncertainty quantification, and are trained on both scattering and bound-state data from a wide area of the nuclear chart. Combined together, these features allow for significant improvement in fidelity and extrapolative power of the model. Here, we present preliminary work toward the development and training of such an OMP. The capability of the model to describe data at this first stage is encouraging.

Perrotta, Salvatore Simone [Lawrence Livermore Nat↗
DOE OSTI2021

Interorbital nematicity and the origin of a single electron Fermi pocket in FeSe

The electronic structure of the enigmatic iron-based superconductor FeSe has puzzled researchers since spectroscopic probes failed to observe the expected electron pocket at the Y point in the 1-Fe Brillouin zone. It has been speculated that this pocket, essential for an understanding of the superconducting state, is either absent or incoherent. In this study, we perform a theoretical study of the preferred nematic order originating from nearest-neighbor Coulomb interactions in an electronic model relevant for FeSe. We find that at low temperatures the dominating nematic components are of interorbital d x z – d x y and d y z – d x y character, with spontaneously broken amplitudes for these two components. This interorbital nematic order naturally leads to distinct hybridization gaps at the X and Y points of the 1-Fe Brillouin zone, and may thereby produce highly anisotropic Fermi surfaces with only a single electron pocket at one of these momentum-space locations. The associated superconducting gap structure obtained with the generated low-energy electronic band structure from spin-fluctuation mediated pairing agrees well with that measured experimentally. Finally, from a comparison of the computed spin susceptibility to available neutron scattering data, we discuss the necessity of additional self-energy effects, and explore the role of orbital-dependent quasiparticle weights as a minimal means to include them.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Durable and Low-Cost Fractal Structured Multifunctional Coatings for Next-Generation CSP

Fractal coatings on various low-cost and high-temperature metallic substrates such as SS316, SS347, In800H, In740H, In625, Haynes 230, etc. were fabricated employing our patented novel electrodeposition process at various deposition potentials and deposition times, as well as chemical etching. The best combination of the materials and processing conditions were co-optimized for the reliable and repeatable fabrication of the multifunctional coatings. Surface morphologies were examined using SEM and AFM, and fractal characterization was done using a 3D optical surface profiler. Fractal dimension was used to identify successful fabrication and material parameters. The mechanical durability of the coatings was evaluated using several standardized tests, such as sand abrasion (ASTM D968) and adhesion (ASTM D3359), to fully characterize and demonstrate the mechanical durability of the fabricated surfaces. HTF immersion tests on the fractal multifunctional coatings were conducted based on a modification of the ASTM D870, which is established for static water immersion testing. To calculate the corrosion rates and descaled weight loss of the samples subjected to thermal exposure for different time durations (100 h, 300 h, 500 h, and optionally 750 h) to estimate the corrosion rate. While protecting the substrates from corrosion is an important goal, an allied goals is also to examine the post-corrosion temperature stability and properties of the molten salts themselves due to the dissolution of the constituents of the alloys and the corrosion products from the coatings that cause “fouling” of the molten salts. Fouling characteristics of the different molten salt HTFs exposed to coated and uncoated substrates were investigated. Finally, considering a prototype molten salt/sCO2 heat exchanger, cost/performance model is developed to demonstrate that the coatings on low-cost alloys such as stainless steel provide lower levelized cost of heat exchanger compared to high nickel content Ha230.

14 SOLAR ENERGY↗
DOE OSTI2024

Towards next-generation optical potentials for nuclear reactions and structure calculations

Optical-model potentials (OMPs) are critical ingredients for basic and applied nuclear physics. Present-day computational capabilities allow us to generate data-driven nucleon-nucleus OMPs that are non-local and exactly dispersive (as theoretically required to be), include statisticallysound uncertainty quantification, and are trained on both scattering and bound-state data from a wide area of the nuclear chart. Combined together, these features allow for significant improvement in fidelity and extrapolative power of the model. Here, we present preliminary work toward the development and training of such an OMP. The capability of the model to describe data at this first stage is encouraging.

Perrotta, S.↗
DOE OSTI2025

AI-Assisted Conceptual Development of a Pre-Geometric Cosmological Model - An Exercise in AI-Assisted Conceptual Framework Generation, Paper II: Local Geometry and Metric Structure

This paper develops the geometric sector of the replication-driven cosmogenesis framework introduced in Paper I. Starting from a pre-geometric spectral substrate and a minimal set of replication axioms, we show how coherent self-replicating units generate a spatial adjacency graph whose continuum limit acquires an effective Riemannian structure. The replication dynamics determines a characteristic correlation length that seeds the local metric, while overlap relations among coherent units produce an isotropic neighborhood geometry with an emergent dimensionality $d_{\rm eff}\simeq 3$ across a broad range of replication factors. As replication slows and causal order stabilizes, a limiting signal speed $c_\ast$ appears, providing the basis for the Lorentzian structure of spacetime without assuming a pre-existing light cone. We derive conditions under which the adjacency graph converges to a smooth three-dimensional manifold, describe the transition from Euclidean to Lorentzian propagation, and identify geometric invariants controlled by the replication parameters. This work establishes the geometric and causal layer of the replication cosmogenesis program, bridging the spectral axioms of Paper I to the cosmological dynamics explored in Paper III.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Surfactant-Specific AI-Driven Molecular Design: Integrating Generative Models, Predictive Modeling, and Reinforcement Learning for Tailored Surfactant Synthesis

Molecular design is a critical aspect of various scientific and industrial fields, where the properties of molecules hold significant importance. In this study, a 3-fold methodology design is presented that leverages the power of generative artificial intelligence (AI), predictive modeling, and reinforcement learning to create tailored molecules with desired properties. This model synergistically combines deep learning techniques with Self-Referencing Embedded Strings (SELFIES) molecular representation to build a generative model that generates valid molecules and a graphical neural network model that accurately forecasts molecular properties. The Variational Autoencoder (VAE) coupled with reinforcement learning helps refine molecule generation based on targeted attributes. Data from an experimental study involving surfactants were used to test the framework. A validation of the structural integrity of the molecules generated was conducted, and Tanimoto similarities were used to quantify the similarity and diversity between the original and generated molecular structures. Also, saliency maps for the generated surfactants were produced to identify the features explaining the property values. Lastly, molecular dynamics simulations were used to validate the stability of the generated molecules. The results showed that the proposed framework can effectively produce valid molecules within the set property threshold value.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Temperature-dependent Battery Performance of a Na 3 V 2 (PO 4 ) 2 F 3 @MWCNT Cathode and In-situ Heat Generation on Cycling

Excellent structural stability, high operating voltage, and high capacity have made Na 3 V 2 (PO 4 ) 2 F 3 a promising cathode material for sodium-ion batteries. However, high-temperature battery performances and heat generation measurements have not been systematically reported yet. Carbon-coated Na 3 V 2 (PO 4 ) 2 F 3 @MWCNT (multi-walled carbon nanotube) samples are fabricated by a hydrothermal-assisted sol-gel method and the electrochemical performances are evaluated at three different temperatures (25, 45, and 55 °C). Furthermore, the well-crystallized Na 3 V 2 (PO 4 ) 2 F 3 @MWCNT samples exhibit good cycling stability at both low and high temperatures; they deliver an initial discharge capacity of 120–125 mAhg -1 at a 1 C rate with a retention of 53 % capacity after 1,400 cycles with 99 % columbic efficiency. The half-cell delivers a capacity of 100 mAhg -1 even at a high rate of 10 C at room temperature. Furthermore, the Na 3 V 2 (PO 4 ) 2 F 3 @MWCNT samples show good long-term durability; the capacity loss is an average of 0.05 % per cycle at a 1 C rate at 55 °C. Additionally, ionic diffusivity and charge transfer resistance are evaluated as functions of state of charge, and they explain the high electrochemical performance of the Na 3 V 2 (PO 4 ) 2 F 3 @MWCNT samples. In-situ heat generation measurements reveal reversible results upon cycling owing to the high structural stability of the material. Excellent electrochemical performances are also demonstrated in the full-cell configuration with hard carbon as well as antimony Sb/C anodes.

25 ENERGY STORAGE↗
DOE OSTI2024

Micro-patterning of spintronic emitters enables ultrabroadband structured terahertz radiation

Abstract Structured light beams offer promising properties for a variety of applications, but the generation of broadband structured light remains a challenge. New opportunities are emerging in the terahertz frequency range owing to recent progress in light-driven ultrafast vectorial currents through spatially patterning spintronic and optoelectronic systems.

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

Biopolymer Concrete

Cement production for concrete has been responsible for ~7–8% of global greenhouse gas (GHG) emissions, and nearly equally contribution for steel production processes (EPA, 2020). In order to achieve carbon neutrality by 2050, a novel solution has to be investigated. This project aims to develop fundamental mechanistic understanding and experimental characterization to create a 3D printable biopolymer concrete using plant-based polyurethane as an innovative and sustainable alternative for Portland cement concrete, with significantly low carbon footprint. Future construction will utilize the advances in digital additive manufacturing (3D printing) to produce optimal geometries with a minimum waste of materials. Understanding the polymerization process, factors impacting the composite rheology, and the structural behavior of this biopolymer concrete will enable us to engineer the next generation of concrete structures with low carbon footprint. This project aims to improve the nation’s ability to control Greenhouse Gas emission neutrality for the set goal of 2050 via introducing a structurally viable bio-based polymer concrete.

42 ENGINEERING↗