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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 181 records · Page 10

Magnetic Flux Plays an Important Role during a Black Hole X-Ray Binary Outburst in Radiative Two-temperature General Relativistic Magnetohydrodynamic Simulations

Abstract Black hole (Bh) X-ray binaries cycle through different spectral states of accretion over the course of months to years. Although persistent changes in the Bh mass accretion rate are generally recognized as the most important component of state transitions, it is becoming increasingly evident that magnetic fields play a similarly important role. In this article, we present the first radiative two-temperature general relativistic magnetohydrodynamics simulations in which an accretion disk transitions from a quiescent state at an accretion rate of M ̇ ∼ 10 − 10 M ̇ Edd to a hard-intermediate state at an accretion rate of M ̇ ∼ 10 − 2 M ̇ Edd . This huge parameter space in mass accretion rate is bridged by artificially rescaling the gas density scale of the simulations. We present two jetted BH models with varying degrees of magnetic flux saturation. We demonstrate that in “standard and normal evolution” models, which are unsaturated with magnetic flux, the hot torus collapses into a thin and cold accretion disk when M ̇ ≳ 5 × 10 − 3 M ̇ Edd . On the other hand, in “magnetically arrested disk” models, which are fully saturated with vertical magnetic flux, the plasma remains mostly hot with substructures that condense into cold clumps of gas when M ̇ ≳ 1 × 10 − 2 M ̇ Edd . This suggests that the spectral signatures observed during state transitions are closely tied to the level of magnetic flux saturation.

Astronomy & Astrophysics↗

Atomistic Modeling of Irradiation-Induced Defects and Clusters in Additively-Manufactured Austenitic Stainless Steel

Understanding the progression of irradiation-induced defects in real materials and alloys requires insight into the interaction between point defects, defect clusters, and the existing microstructure. This is particularly true when it comes to additively manufactured (AM) materials with complicated microstructures and residual stresses. In this work, we employ molecular dynamics (MD) to simulate the creation of point defects via primary radiation damage modeling and point defect interactions with extended defects such as voids and dislocations using simplified but representative alloy compositions. We analyze the effect of alloying elements on the formation energies of the defect clusters and measure interactions such as sink strengths and binding energies. This study provides insight into the unique behaviors of irradiation damage in AM materials and information necessary to bridge the gap in length and time scales to connect the atomistic behavior of defects to longer length scale simulations such as cluster dynamics.

36 MATERIALS SCIENCE↗

Superclustering with the Atacama Cosmology Telescope and Dark Energy Survey. I. Evidence for Thermal Energy Anisotropy Using Oriented Stacking

The cosmic web contains filamentary structure on a wide range of scales. On the largest scales, superclustering aligns multiple galaxy clusters along intercluster bridges, visible through their thermal Sunyaev–Zel'dovich signal in the cosmic microwave background. We demonstrate a new, flexible method to analyze the hot gas signal from multiscale extended structures. We use a Compton y-map from the Atacama Cosmology Telescope (ACT) stacked on redMaPPer cluster positions from the optical Dark Energy Survey (DES). Cutout images from the y-map are oriented with large-scale structure information from DES galaxy data such that the superclustering signal is aligned before being overlaid. We find evidence of an extended quadrupole moment of the stacked y signal at the 3.5σ level, demonstrating that the large-scale thermal energy surrounding galaxy clusters is anisotropically distributed. We compare our ACT × DES results with the Buzzard simulations, finding broad agreement. Using simulations, we highlight the promise of this novel technique for constraining the evolution of anisotropic, non-Gaussian structure using future combinations of microwave and optical surveys.

79 ASTRONOMY AND ASTROPHYSICS↗

State of Innovation 2025: Progress in Accelerating Next-Generation Cement and Concrete Technologies

The cement and concrete sectors are entering a decisive period as next-generation technologies advance from laboratory research to demonstration, early deployment, and first-of-a-kind commercial plants. Building on the 2024 State of Innovation report, the 2025 outlook highlights both the rapid acceleration of innovation and the urgent need for coordinated action across the value chain. Venture capital activity into the cement and concrete space stabilized following the record surge of 2022-2023, yet landmark financings, such as Sublime Systems' $200 million round and Terra CO2's $124 million Series B, signal continued investor confidence in companies approaching commercialization. Corporate procurement has become a powerful new catalyst, with Microsoft, Amazon, and CRH (Cement Roadstone Holdings) Ventures providing long-term commitments that underpin the first wave of next-generation cementitious products. The sector is shifting from early-stage experimentation toward the scaling of well-capitalized leaders capable of bridging the critical "capitalization gap." Early innovators continue to expand the toolkit through novel binders, electrochemical cements, biogenic limestone, and carbonate mineralization pathways. Going into 2026, cost competitiveness, durability validation, and scalability enabled by resilient supply chains remain the decisive factors for market adoption. At the 2025 Next Generation Cement and Concrete Critical Technologies Meeting, attendees emphasized dual-track funding strategies that integrate federal grants with private capital as key to enabling market breakthrough. State programs and corporate demand are sustaining momentum, while successful companies increasingly demonstrate both economic value and reduced dependence on imported materials. The National Concrete Pavement Technology Center and others underscored that broad integration of next-generation materials will hinge on standards compatibility, verified field performance, and workforce readiness. Colorado continues to serve as a proving ground through pilot programs that combine supplier training, phased implementation, and real-world data to de-risk innovation and provide replicable models for other regions. The 2025 Cement and Concrete Critical Technologies Workshop reinforced that scaling next-generation materials will require alignment among technology innovation, performance validation, and market demand. Stakeholders must move beyond siloed efforts toward collaborative frameworks that coordinate standards, funding, and infrastructure deployment. As a neutral convener and technical validator, the National Laboratory of the Rockies (NLR) plays a pivotal role in bridging innovation and market adoption through collaborative research, technology validation, and entrepreneurship programs. By uniting innovators, incumbents, policymakers, contractors, and investors, NLR and its partners are helping chart a credible pathway toward widespread commercialization in the decade ahead.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Recent progress on coarse graining simulations

We focus on coarse graining simulations based on the primary conservation equations, effectively codesigned physics and algorithms, and low-Mach-number corrected (LMC) hydrodynamics. Simulation methods involve LANL’s x-Radiation-Adaptive-Grid-Eulerian Large-Eddy Simulation, Besnard-Harlow-Rauenzahn (BHR) Reynolds-Averaged Navier-Stokes (RANS) approach, and Dynamic BHR – a paradigm bridging RANS and LES. A relevant question addressed relates to whether 3D RANS and RANS/LES hybrids – the industry standards for aerospace and automotive research, are presently relevant for practical variable-density applications involving shocked and accelerated interface instabilities. Furthermore, recent simulations of the GaTECH inclined mixing-layer shock-tube and NIF ICF-capsule experiments are used to demonstrate issues, challenges, and potential for 3D coarse grained LMC simulation strategies for robustly simulating complex transitional and coupled hydrodynamics-multiphysics with coarser resolution. Present LES readiness to provide accurate predictions at scale is demonstrated – whereas 3D RANS and RANS/LES bridging do not appear impactful in this context.

42 ENGINEERING↗

Simulation of Particulate Transport for Delivery of Solid Amendments into the Subsurface: FY24 Status Report

For particulate-based amendments to be viable for field-scale remediation at the Hanford Site (e.g., 200 DV-1 Operable Unit), particles need to be delivered a sufficient radial distance from an injection well and retained at concentrations high enough for effective treatment. An accurate description of the particle radius of influence (ROI) is critical for developing an overall remediation strategy. However, field-scale particle simulations are currently limited due to insufficient simulation capabilities and a lack of experimental data to validate and parameterize particle transport models. To help build toward field-scale deployment, this fiscal year (FY) we have (1) developed a pre screening tool to estimate particle transport, (2) implemented particle transport models within PFLOTRAN, and (3) conducted preliminary estimations of particle ROI. While field-scale numerical simulations will ultimately be necessary before remedy design and field implementation, we have developed a pre-screening tool that offers valuable estimations of expected particle injectability and ROI in a 1-D system. The advantage of the tool is that it does not require extensive laboratory experiments and instead makes predictions based solely on routine laboratory measurements. This tool can assist in down-selection and decision-making by identifying which particle amendment systems are worth pursuing in future laboratory experiments, such as 1-D column tests and beyond. With any system, scaling up from the lab to the field presents challenges. Currently, there is no field data available for model calibration or validation. However, the theoretical particle models being developed herein are the best tools available to guide progress toward field deployment. To help bridge this gap and verify model predictions, larger-scale lab experiments are being proposed. To advance simulation capabilities, six particle transport models are being integrated into the reactive transport simulator PFLOTRAN. These include colloid filtration theory (CFT) and five additional particle transport models (M1-M5). Each model, from M1 to M5, progressively incorporates additional particle transport and retention processes. Ultimately, the simplest model capable of accurately describing 1-D column data will be selected and parameterized. During FY24, the CFT and M1 model have been fully implemented within PFLOTRAN. Using an existing 1 D column experiment, the two currently implemented particle transport models (CFT and M1), and associated parameters, were fit to this experiment. While simpler model formulations are helpful for estimations, these formulations could not fully describe particle transport and retention behavior in the previous 1-D column experiment. Thus, additional complexities will need to be considered, which will be accounted for in the M2-M5 model formulations. Additionally, because a viscous, shear thinning fluid was required to keep particles in suspension, considerations for flow will also need to also be accounted for. Therefore, a new immiscible two-phase flow mode is currently being implemented in PFLOTRAN. With some modifications, this new flow module could also support simulation of non-Newtonian liquid amendments, foams, and emulsions. We also estimated the expected ROI of solid amendments using 1-D simulations. The average predicted ROI was approximately 15 ft for micron-sized zero valent iron (mZVI) suspended in xanthan gum (XG). Using the pre screening tool and ROI estimates, additional amendment-delivery laboratory characterization and experiments are proposed. The results from additional experiments can be used to validate and parametrize particulate transport model formulations, which will ultimately provide predictive capabilities for field amendment-delivery systems.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Nanoscale chromatin imaging and analysis platform bridges 4D chromatin organization with molecular function

Extending across multiple length scales, dynamic chromatin structure is linked to transcription through the regulation of genome organization. However, no individual technique can fully elucidate this structure and its relation to molecular function at all length and time scales at both a single-cell level and a population level. Here, we present a multitechnique nanoscale chromatin imaging and analysis (nano-ChIA) platform that consolidates electron tomography of the primary chromatin fiber, optical super-resolution imaging of transcription processes, and label-free nano-sensing of chromatin packing and its dynamics in live cells. Using nano-ChIA, we observed that chromatin is localized into spatially separable packing domains, with an average diameter of around 200 nanometers, sub-megabase genomic size, and an internal fractal structure. The chromatin packing behavior of these domains exhibits a complex bidirectional relationship with active gene transcription. Furthermore, we found that properties of PDs are correlated among progenitor and progeny cells across cell division.

59 BASIC BIOLOGICAL SCIENCES↗

Comprehensive evaluation of commercially scalable atomic-layer-deposited alumina coating impact on full cell battery performance across varied test conditions

Atomic Layer Deposition (ALD) has emerged as a strategic enhancement method for lithium-ion battery (LIB) materials offering potential benefits and durability benefits for industrial battery production. However, the translation from laboratory achievements to commercial-scale applications has been limited. Here, this study aims to bridge this gap by comprehensively evaluating the effects of commercially scalable Al 2 O 3 ALD coatings using full pouch cell performance as a means to assess the ALD impact. We utilized large-scale slot-die coating techniques to ensure consistent electrode quality and tested four configurations of pouch cells to analyze the individual effects of ALD coating on anode and cathode electroactive materials. Our extensive testing matrix included long-term cycling, fast discharge, fast charge, leakage current, and high voltage tests. While at lower C-rates (<~1C), the influence of Al 2 O 3 coatings on cell performance is not significant. Fast charging conditions reveal that the anode ALD coating significantly enhances performance via a passivating effect, while on the cathode, it is detrimental, potentially due to increased resistance of the thin interfacial layer formed during the ALD processing. Leakage current and high-voltage tests show that the application of ALD coatings on either anode or cathode effectively minimizes side reactions at the electrode-electrolyte interface. Additionally, ALD coatings significantly mitigate concentrated and localized lithium plating on the anodes. These insights provide a valuable understanding of the potential of ALD technologies in LIB manufacturing to tailor cell performance, paving the way for safer, more efficient, and cost-effective battery solutions.

25 ENERGY STORAGE↗

Annual IC Progress Report

The goal of this project is to computationally investigate the progenitors of astrophysical gamma-ray bursts (GRB), the most extreme explosions in the universe across length and time scales. We have developed a cutting-edge, code-bridging approach to exploring the physics behind these luminous events to test the hypothesis that GRBs with electromagnetic radio emission originate from massive star (MS) and black hole (BH) binary systems. Our multi-scale, multi-physics theoretical framework for GRBs is based on solving well-defined and testable hydrodynamics problems associated with the dynamical evolution of the system. We solve stages of the evolution in a tractable way with a suite of well-developed state-of-the-art computational tools that include the stellar evolution code MESA, the general relativistic magnetohydrodynamics (GRMHD) code Athena++, and the binary black hole (BBH) population synthesis code COSMIC, as well as a number of self-written python post-processing tools.

79 ASTRONOMY AND ASTROPHYSICS↗

Scalable simulation of coupled adsorption and transport of methane in confined complex porous media with density preconditioning

The growing significance of shales and tight formations in the transition to less carbon-intensive and clean energy drives the research endeavor to understand the physics of gas flow within these systems. However, shales are composed of massively heterogeneous physical and chemical features. Most nano-sized pores connect to millimeter-scale fractures, leading to multiscale transport. These nano-scale pore throats demonstrate non-classical flow behavior, such as non-negligible slip velocities and adsorbed gas layers at the boundary. As a result, classical computational fluid dynamics models do not capture the physics. In this work, we develop a coupling scheme for the multiple-relaxation-time (MRT) lattice Boltzmann (LB) method that integrates the Peng-Robinson equation of state into a pseudo-potential interaction model to capture the physics of methane flow in irregular networks of channels that represent nano-scale porous media. We use atomistic simulations to calibrate and validate our model in slit nano-channels. We propose a preconditioning scheme to initialize the coupled transport and adsorption simulation of methane in complex porous media. The results of this implementation of LB agree with Direct Simulation Monte Carlo (DSMC) and Molecular Dynamics (MD) simulations. We then scale up the LB implementation through vectorization and indirect addressing. We parallelize it using Message Passing Interface (MPI) and OpenMP frameworks to simulate transport and adsorption in complex media with a million lattices. Additionally, we analyze the differences between coupled and transport-only simulations in two case studies and show that considering phase behavior, i.e., adsorption, can significantly change the flow behavior. This work constitutes an important step towards bridging the gap between molecular flow and system-scale behavior of complex disordered porous media.

42 ENGINEERING↗

Molecular diversity of dissolved organic matter reflects macroecological patterns in river networks

Deciphering dissolved organic matter (DOM) molecular complexity is crucial for understanding ecosystem function. Using the continental-scale Worldwide Hydrobiogeochemistry Observation Network for Dynamic Rivers Systems (WHONDRS) Fourier-transform ion cyclotron resonance mass spectrometry (FTICR-MS) dataset, we reveal fundamental scaling patterns of DOM chemodiversity with watershed characteristics. Analysis of 54 river sites shows local and regional watershed features significantly influence DOM chemodiversity (2500–8718 unique formulae), exhibiting consistent scaling patterns across compound classes and a novel latitudinal gradient (decreasing diversity with increasing latitude). Scaling relationships for DOM composition vary by compound class. Crucially, the scaling parameters (B, baseline chemodiversity; Z, sensitivity) are linearly interrelated. This B–Z relationship is most robust for potentially bio-labile carbohydrates (coefficient of determination R 2 ≈ 0.85), diminishing for recalcitrant, plant-derived molecules (such as lignin), and indicates (potential) biolability-dependent coupling between baseline diversity and environmental responsiveness. These quantitative scaling relationships, with scaling exponents ranging from − 2.1 to 2.2 across compound classes, enable prediction of DOM composition across watersheds, offering a framework to understand ecosystem responses to environmental change. This research bridges biogeochemistry and ecology, providing tools to anticipate molecular transformations across scales.

59 BASIC BIOLOGICAL SCIENCES↗

Multiscale Aerosol Modeling Across Space and Composition (Final Report)

The objective of this project was to harness the capabilities of our unique particle-resolved aerosol model PartMC as an integrating tool between models and measurements across scales. This particle-resolved model explicitly resolves aerosol aging processes that must be approximated in large-scale models, making it ideal for quantifying structural uncertainty and rigorously deriving simplified parameterizations (“coarse graining”) to be used in large-scale models. It also directly connects with laboratory and field measurements at both particle and bulk scales. The significant accomplishments of this project are as follows: 1. Advancing the state of the art in particle-resolved modeling; 2. Connecting modeling with ASR/ARM measurements; 3. Bridging from the process level to aerosol impacts on the global scale; 4. Community engagement through leading and participating in ASR program activities and publishing a review paper on aerosol mixing state that synthesizes experimental and modeling perspectives.

58 GEOSCIENCES↗

Lyman-$α$ forest holography: 3D predictions from 1D measurements

Cosmological analyses of Lyman-$α$ forest clustering rely on either one-dimensional correlations along individual sightlines or three-dimensional correlations between different sightlines. Because these observables probe the matter distribution on very different scales, they have traditionally been analyzed independently. In this work, we bridge this gap using ForestFlow, an emulator trained on a suite of cosmological hydrodynamical simulations that provides a unified description of Lyman-$α$ forest clustering from linear to nonlinear scales. This framework enables us to determine the range of three-dimensional clustering models compatible with the DESI one-dimensional flux power spectrum ($P_{\rm 1D}$). The resulting predictions successfully reproduce the large-scale clustering measured by the DESI BAO analysis and provide physically motivated priors on nonlinear clustering that are used in a companion paper presenting the full-shape analysis of the DESI DR2 Lyman-$α$ forest. We validate our methodology using the large-volume, high-resolution hydrodynamical simulation ACCEL-2, demonstrating excellent agreement across the full range of scales considered. Finally, we combine constraints from the $P_{\rm 1D}$ and BAO analyses on the parameter combinations $b_δσ_8$ and $b_ηf σ_8$, finding that the two probes provide comparable constraining power while exhibiting complementary parameter degeneracies. Our results establish a direct connection between one- and three-dimensional Lyman-$α$ forest measurements through ForestFlow, an approach we term Lyman-$α$ holography by analogy with the reconstruction of higher-dimensional structure from lower-dimensional information.

Chaves-Montero, J. [Barcelona, IFAE] (ORCID:000000↗

Self-supervised and multi-fidelity learning for extended predictive soil spectroscopy

Infrared spectroscopy is a cost-effective, non-destructive, and environmentally benign technology that is increasingly recognized as an important solution for meeting the global demand for soil data. While both near-infrared (NIR) and mid-infrared (MIR) diffuse reflectance spectroscopy enable rapid estimation of soil properties, they present a significant trade-off: NIR offers superior scalability and lower operational costs, whereas MIR provides higher analytical fidelity by capturing fundamental molecular vibrations. In this study, we propose a self-supervised, multi-fidelity learning framework designed to bridge this gap. Our approach leverages large-scale MIR spectral libraries to learn a compact, transferable latent representation, into which NIR spectra are subsequently aligned for downstream prediction. The workflow consists of pretraining a latent model on a large MIR library, adapting the representation using a smaller paired NIR–MIR dataset, and evaluating generalization on an independent external test set. Across a range of chemical and physical soil properties, we found that MIR-derived embeddings improved prediction accuracy relative to baseline models that used raw MIR inputs. Predictions derived from the spectrum conversion (NIR to MIR) task did not match the performance of the original MIR spectra but were similar or superior to predictive performance of NIR-only models, suggesting the unified spectral latent space can effectively leverage the larger and more diverse MIR dataset for prediction of soil properties not well represented in current NIR libraries.

54 ENVIRONMENTAL SCIENCES↗

Kinetic Model of Acid Gas Induced Defect Propagation in Zeolitic Imidazolate Frameworks

Understanding the degradation of nanoporous materials under exposure to common acid gas contaminants (e.g., SO 2 , CO 2 , NO 2 , and H 2 S) is essential to elongate their lifetime and thus enable their practical applications in separations and catalysis. Previous theoretical investigations have focused on the formation of isolated point defects, which are insufficient to provide direct insights into the long-term evolution of the bulk properties of materials such as zeolitic imidazolate frameworks (ZIFs) under sustained acid gas exposure. Here, to bridge this divide in both length and time scales, we developed a first-principles lattice-based kinetic model to simulate the defect propagation and bulk material breakdown in ZIFs. This model closely reproduces the experimentally measured macroscopic evolution of the time-dependent bulk materials proprieties and also yields important new insights regarding the autocatalytic nature of ZIF degradation and the spatial distribution of defects. Our results suggest new experimental directions to identify nascent defect clusters in degraded ZIFs and avenues to mitigate degradation under challenging conditions of acid gas exposure.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Carbon Mineralization in Fractured Mafic and Ultramafic Rocks: A Review

Mineral carbon storage in mafic and ultramafic rock masses has the potential to be an effective and permanent mechanism to reduce anthropogenic CO 2 . Several successful pilot-scale projects have been carried out in basaltic rock (e.g., CarbFix, Wallula), demonstrating the potential for rapid CO 2 sequestration. However, these tests have been limited to the injection of small quantities of CO 2 . Thus, the longevity and feasibility of long-term, large-scale mineralization operations to store the levels of CO 2 needed to address the present climate crisis is unknown. Moreover, CO 2 mineralization in ultramafic rocks, which tend to be more reactive but less permeable, has not yet been quantified. In these systems, fractures are expected to play a crucial role in the flow and reaction of CO 2 within the rock mass and will influence the CO 2 storage potential of the system. Therefore, consideration of fractures is imperative to the prediction of CO 2 mineralization at a specific storage site. In this review, we highlight key takeaways, successes, and shortcomings of CO 2 mineralization pilot tests that have been completed and are currently underway. Laboratory experiments, directed toward understanding the complex geochemical and geomechanical reactions that occur during CO 2 mineralization in fractures, are also discussed. Experimental studies and their applicability to field sites are limited in time and scale. Many modeling techniques can be applied to bridge these limitations. We highlight current modeling advances and their potential applications for predicting CO 2 mineralization in mafic and ultramafic rocks.

25 ENERGY STORAGE↗

SU(3) Gauge Symmetry: An Experimental Review of Diffractive Physics in e+p, p+p, p+ A, and A+A Collision Systems

This review focuses on diffractive physics, which involves the long-range interactions of strong nuclear force at high energies described by SU(3) gauge symmetry. It is expected that diffractive processes account for nearly 40% of the total cross-section at LHC energies. These processes consist of soft-scale physics where perturbation theory cannot be applied. Although highly successful and often described as a perfect theory, quantum chromodynamics relies heavily on perturbation theory, a model best suited for hard-scale physics. The study of pomerons could help bridge the soft and hard processes and provide a complete description of the theory of the strong interaction across the full momentum spectrum. Here, we will discuss some of the features of diffractive physics, experimental results from SPS, HERA, and the LHC, and where the field could potentially lead. With the recent publication of the odderon discovery in 2021 by the D0 and TOTEM collaborations and the new horizon of physics that lies ahead with the upcoming Electron-Ion Collider at Brookhaven National Laboratory, interest is seemingly piquing in high energy diffractive physics.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Systems-To-Atoms (S2A): enabling hydrogen for climate security

The project addresses a critical gap in hydrogen infrastructure by integrating system-level energy models with atomic-scale material simulations in a unified Systems-to-Atoms (S2A) framework. The motivation stems from the need to develop efficient, cost-effective, and durable hydrogen transport and utilization technologies to support decarbonization of hard-to-electrify sectors such as heavy-duty transportation. Current system models lack awareness of material performance mechanisms, while material-scale models do not account for system-level usage and variability. To bridge this divide, the team developed a co-simulation capability linking techno-economic analyses, reactor/process-flow modeling, and molecular-scale catalysis simulations. Applied to hydrogen delivery in California, the framework enabled comparative evaluations of compressed, cryogenic, and liquid organic hydrogen carrier (LOHC) pathways, highlighting how catalyst operation and unit process efficiency influence overall performance. The results demonstrate that no single material or transport mode is universally optimal; instead, heterogeneous solutions tuned to specific operational contexts deliver better performance. The project delivers a new capability for cross-scale material co-design, advancing hydrogen infrastructure readiness and informing DOE and LLNL missions in climate and energy resilience.

organic↗