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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Defying Thermodynamics: Stabilization of Alane Within Covalent Triazine Frameworks for Reversible Hydrogen Storage

The highly unfavorable thermodynamics of direct aluminum hydrogenation can be overcome by stabilizing alane within a nanoporous bipyridine-functionalized covalent triazine framework (AlH 3 @CTF-bipyridine). This material and the counterpart AlH 3 @CTF-biphenyl rapidly desorb H 2 between 95 and 154°C, with desorption complete at 250°C. Sieverts measurements, 27 Al MAS NMR and 27 Al{ 1 H} REDOR experiments, and computational spectroscopy reveal that AlH 3 @CTF-bipyridine dehydrogenation is reversible at 60°C under 700 bar hydrogen, >10 times lower pressure than that required to hydrogenate bulk aluminum. DFT calculations and EPR measurements support an unconventional mechanism whereby strong AlH 3 binding to bipyridine results in single-electron transfer to form AlH 2 (AlH 3 ) n clusters. Here the resulting size-dependent charge redistribution alters the dehydrogenation/rehydrogenation thermochemistry, suggesting a novel strategy to enable reversibility in high-capacity metal hydrides.

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

SHASTA: Task 2.2: Sensor Development for Subsurface Hydrogen Storage Monitoring Technology Maturation and Commercialization Plan (TMCP)

In Task 2.2 under the SHASTA program, NETL is developing in-situ optical fiber sensors for real-time monitoring of hydrogen, methane, and chemical parameters such as pH at subsurface hydrogen storage conditions. This Technology Maturation and Commercialization Plan report will provide the summary of NETL sensor development and test results under the SHASTA program to meet the subsurface application requirements and proposed technology maturation and deployment plan, and commercialization potential.

08 HYDROGEN↗
NASA NTRS1978

Atomic hydrogen storage method and apparatus

Atomic hydrogen, for use as a fuel or as an explosive, is stored in the presence of a strong magnetic field in exfoliated layered compounds such as molybdenum disulfide or an elemental layer material such as graphite. The compound is maintained at liquid helium temperatures and the atomic hydrogen is collected on the surfaces of the layered compound which are exposed during delamination (exfoliation). The strong magnetic field and the low temperature combine to prevent the atoms of hydrogen from recombining to form molecules.

Woollam, J. A.↗
NASA NTRS1980

Atomic hydrogen storage method and apparatus

Atomic hydrogen, for use as a fuel or as an explosive, is stored in the presence of a strong magnetic field in exfoliated layered compounds such as molybdenum disulfide or an elemental layer material such as graphite. The compounds maintained at liquid helium temperatures and the atomic hydrogen is collected on the surfaces of the layered compound which are exposed during delamination (exfoliation). The strong magnetic field and the low temperature combine to prevent the atoms of hydrogen from recombining to form molecules.

Woollam, J. A.↗
DOE OSTI2026

Discovery of hydrogen storage molecules using large language models and machine learning

Accelerating the discovery of new molecules with targeted properties is a central challenge in molecular design. In this contribution, we present an AI-driven molecular discovery framework that integrates Large Language Models (LLMs) for generative molecular design with Machine Learning (ML)-based screening to identify novel Liquid Organic Hydrogen Carrier (LOHC) candidates. Using the developed framework, LOHC molecules were systematically generated, evaluated, and refined iteratively, combining LLM-guided molecular generation and ML-predicted hydrogenation enthalpies (Δ H ), under physicochemical property constraints such as optimal melting points (MP), desired hydrogen storage capacity (wt% H 2 ), and synthetic accessibility (SA) scores. This approach enabled the discovery of 42 new LOHC candidates in two distinct campaigns, one seeded with experimentally known and another with previously computationally identified LOHCs, respectively. Although we began with different numbers of starting molecules (31 vs . 7 seed molecules), both runs yielded a comparable number of viable candidates, suggesting an influence of chemically intuitive seed molecule selection for success. Selected LOHC molecules, such as 3-methyl pyridine, 1-ethylnapthalene, 1,1-diphenylethane, and benzofuran, were experimentally tested and compared with benchmark LOHCs (toluene and 9-ethylcarbazole) for hydrogenation using a series of commercial supported metal catalysts. The order of conversion into fully hydrogenated products at 200 °C was 3-methyl pyridine (100%) > 9-ethyl carbazole (86.4%) > 2,3-benzofuran (74%) > 1,1-diphenylethane (66.9%) > 1-ethylnapthalene (66.7%) > toluene (57%), further validating the AI-guided molecular design. This study demonstrates promise of LLM-driven molecular design in conjunction with ML-based screening for accelerated discovery and design of molecules.

Harb, Hassan [Argonne National Laboratory (ANL), A↗
DOE OSTI2024

Leveraging Curvature on N–Doped Carbon Materials for Hydrogen Storage

Carbon sorbent materials have shown great promise for solid-state hydrogen (H 2 ) storage. Modification of these materials with nitrogen (N) dopants has been undertaken to develop materials that can store H 2 at ambient temperatures. In this work density functional theory (DFT) calculations are used to systematically probe the influence of curvature on the stability and activity of undoped and N-doped carbon materials toward H binding. Specifically, four models of carbon materials are used: graphene, [5,5] carbon nanotube, [5,5] D 5d -C 120 , and C 60 , to extract and correlate the thermodynamic properties of active sites with varying degrees of sp 2 hybridization (curvature). From the calculations and analysis, it is found that graphitic N-doping is thermodynamically favored on more pyramidal sites with increased curvature. In contrast, it is found that the hydrogen binding energy is weakly affected by curvature and is dominated by electronic effects induced by N-doping. These findings highlight the importance of modulating the heteroatom doping configuration and the lattice topology when developing materials for H 2 storage.

08 HYDROGEN↗
NASA NTRS1984

Hydrogen storage in the form of metal hydrides

Reversible reactions between hydrogen and such materials as iron/titanium and magnesium/ nickel alloy may provide a means for storing hydrogen fuel. A demonstration model of an iron/titanium hydride storage bed is described. Hydrogen from the hydride storage bed powers a converted gasoline electric generator.

Zwanziger, M. G.↗
DOE OSTI2025

Deep Learning for Subsurface Flow: A Comparative Study of U‐Net, Fourier Neural Operators, and Transformers in Underground Hydrogen Storage

Subsurface flow research is essential for the sustainable management of natural resources and the environment. Deep learning (DL) has significantly advanced this field by developing efficient and accurate surrogate models to replace computationally expensive physics‐based simulations. These surrogate models are commonly used to predict the spatiotemporal evolution of state variables, such as gas saturation and reservoir pressure, in heterogeneous geological formations. Despite the various DL models applied to this task, there is a lack of studies systematically comparing their performance. This absence of comparative analysis leads to somewhat arbitrary DL model selection in subsurface flow research, resulting in suboptimal performance and potentially inaccurate predictions. To bridge this gap, we conduct a systematic comparison study of three popular DL architectures—U‐Net, Fourier Neural Operators (FNO), and Segmentation Transformer (SETR)—in surrogate modeling of underground hydrogen storage (UHS). We focus on UHS due to its promise of enhancing clean energy resilience and its cyclic operational conditions that represent common scenarios in various subsurface applications. We evaluate the models based on accuracy, training cost, and inference speed. The comparison shows that U‐Net achieves the highest accuracy, followed by SETR and FNO. Despite its lower accuracy, FNO has the highest inference speed. SETR offers competitive accuracy with the least training memory usage, demonstrating the potential of transformers in learning subsurface flow. Our results provide guidance for selecting DL models for surrogate modeling in a wide range of subsurface flow problems.

42 ENGINEERING↗
DOE OSTI2024

Wellbore cement alteration and roles of CO 2 and shale during underground hydrogen storage

To mitigate climate change and adopt renewable energy, energy storage is crucial and can be done in the form of hydrogen gas (H 2 ). Subsurface geologic reservoirs are positioned to store H 2 on the largest scales for the longest terms of all potential options. However, H 2 injection may boost reactions that consume hydrogen, generate undesired gases, and alter pore structures of geomedia. To explore the extent of H 2 -associated biotic reactions at a near wellbore location, four experiments were conducted under underground storage conditions with wellbore cement cores and, in most instances, shale samples submerged in synthetic formation brine. Post-reaction gas, aqueous, and solid phase samples were analyzed using olfactory screening and, later, gas chromatography (GC-MS), inductively coupled plasma optical emission spectroscopy (ICP-OES), scanning electron microscopy (SEM), and synchrotron micro-scale x-ray fluorescence (μ-XRF). Within a period of 16 weeks, hydrogen sulfide (H 2 S) was generated in systems containing both H 2 and shale. XRF mapping identified a zone enriched in iron(II) and reduced sulfur along the rim of cement cross sections that was largely associated with CO 2 -induced cement carbonation. Shale did not show noticeable alteration, but there is evidence it contributed to the initial inoculation of the system and provided nutrients for microbes via water-rock interactions. Here, this study considers both rock formations and wellbore cement not previously evaluated concurrently. Findings support understanding and modeling of H 2 -associated biogeochemical reactions during underground hydrogen storage.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Influence of Non-Equilibrium Conditions on Liquid Hydrogen Storage Tank Behavior [Slides]

Understanding liquid hydrogen tank fluid dynamics is key for modeling liquid hydrogen systems. The tank is the source for nearly all liquid hydrogen systems. Accurate flow modeling out of the tank is needed to predict flows through downstream components. Tank contains liquid and gas that may not be at equilibrium. Questions to be addressed are: Does heat and mass transfer between liquid and vapor affect the flow rate? Is boiling an important consideration? For what conditions is a pressure relief valve (PRV) sufficient to relieve pressure and when is the burst disc needed?

08 HYDROGEN↗
DOE OSTI2021

A predictive modeling tool for damage analysis and design of hydrogen storage composite pressure vessels

In this study, a predictive modeling tool is developed for damage analysis and design of hydrogen (H 2 ) storage composite pressure vessels. It integrates micromechanics of matrix cracking into a continuum damage mechanics (CDM) description for damage evolution, and three-dimensional (3D) finite element (FE) modeling of the vessel structural response. At the scale of the composite layer (mesoscale), the temperature-dependent stiffness reduction law in terms of the damage variable for transverse matrix cracking is computed using an Eshelby-Mori-Tanaka approach for the initial composite thermoelastic properties and a self-consistent model for the stiffness reduction as a function of the damage variable. While transverse matrix cracking obeying a damage evolution relation can progressively evolve from an initiation to a saturation state, fiber failure is predicted by a micromechanical fiber rupture criterion that accounts for the fiber strength and matrix stress. The implementation of this integrated multiscale modeling model into a 3D FE formulation enables damage analysis and design of H 2 storage composite pressure vessels. The developed tool is illustrated through 3D damage analyses of a cryogenically compressed H 2 storage vessel model subjected to thermomechanical loadings to investigate effects of the helical layer fiber orientation and loading scenario on damage development, vessel integrity and burst pressure.

08 HYDROGEN↗
DOE OSTI2021

A Multiscale Modeling Approach to Cryocompressed Hydrogen Storage Pressure Vessels – Part II: Constitutive Modeling and Finite Element Analysis

Subjected to thermomechanical cycling, composite cryogenic hydrogen (H2) storage pressure vessels experience high stresses in the carbon fiber (CF)/epoxy overwrap which can lead to vessel failure due to a combination of degradation mechanisms such as matrix cracking, fiber/matrix debonding, delamination, and fiber rupture. The present paper is the second part of a set of two articles on this subject that addresses analysis and design of these pressure vessels. Predictive finite element (FE) modeling capabilities have been used to support a material acceptance process that aims at providing guidance to evaluate specialty resins, vessel liner options, and CF composites through thermomechanical testing. We have applied a multiscale modeling approach recently developed (B.N. Nguyen et al., International Journal of Hydrogen Energy, 2019, https://doi.org/10.1016/j.ijhydene.2019.09.200) to perform three-dimensional (3D) FE analysis and design of a cryo-compressed H2 storage pressure vessel for its operation in a large temperature range from room to cryogenic temperatures. The developed approach termed the micro-meso-macro approach determines the laminar stresses in different layers of the vessel in addition to constituent (i.e., fiber and matrix) stresses that are important to the design of the composite overwrap for its layup and material combination to reduce the risk of vessel failure.

Nguyen, Ba Nghiep↗