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At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Identifying Potential Geochemical and Microbial Impacts of Hydrogen Storage in a Deep Saline Aquifer

Hydrogen is valuable commodity and a promising energy carrier for variable energy production. Storage of hydrogen may occur through injection of hydrogen or a hydrogen/methane gas blend in subsurface reservoirs. However, the geochemical and biological reactions that may impact the stored hydrogen are not yet understood. Therefore, we collected samples from a deep storage aquifer located in the St. Peter Formation in southern Illinois. The reservoir material was primarily quartz with sulphur and iron deposits, while the major constituents of the fluid were chloride and sulphate. 16S rRNA gene amplicon sequencing revealed a low biomass microbial community that contained no obvious hydrogen-consuming bacteria. Next, we enriched a field sample to increase the biomass and completed a metagenomic analysis, finding a low number of genes present that are associated with hydrogen consumption. Then, we completed a series of reactor experiments under reservoir conditions with 15% H2/85% CH4 gas simulating a short-term hydrogen storage, high withdrawal scenario. We found minimal changes in the geochemistry or microbiology for the reactor experiments. This work suggests that short-term storage may be highly successful, although significant additional work needs to be completed in order to accurately evaluate the risks associated with long-term hydrogen storage scenarios. It is essential we continue to expand our understanding of the dynamics present in saline aquifers and provide new insights into how hydrogen storage may impact underground geological storage environments.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Design of lightweight BCC multi-principal element alloys with enhanced hydrogen storage using a machine learning-driven genetic algorithm

Body-centered cubic (BCC) based multi-principal element alloy (MPEA) hydrides have demonstrated significant potential for compact and efficient hydrogen storage. In this work, we first leverage machine learning (ML) models to predict the hydrogen affinity, storage capacity and phase stability of BCC MPEAs, creating a unique hydrogen-to-metal (H/M) predictor for materials with unprecedented performance. We developed a metaheuristic optimizer high-throughput framework by interfacing ML models with a genetic algorithm for the accelerated search of {Mg, Al, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Nb, Mo} based lightweight BCC MPEAs with improved hydrogen storage characteristics. We report five new MPEAs with a predicted gravimetric hydrogen storage capacity of around 3.5 wt% or more, including Cr 0.09 Mg 0.73 Ti 0.18 (4.25 wt% H) and Cr 0.21 Nb 0.11 Ti 0.35 V 0.33 (3.5 wt% H). The electronic structure of the top-performing composition, Cr 0.09 Mg 0.73 Ti 0.18 , was analyzed using density functional theory (DFT) to understand the reasons for its improved hydrogen storage properties compared to TiFe (1.90 wt% H), LaNi 5 (1.37 wt% H) or BCC MPEAs like TiVNbCr (3.70 wt% H). Temperature-dependent molecular dynamics (MD) studies were further performed on optimized BCC MPEAs to qualitatively study hydrogen mobility and analyze the effect of different elemental composition on bulk hydrogen diffusion. Our findings demonstrate how a ML assisted genetic algorithm framework can be used for efficient search of stable, lightweight and cost-effective MPEAs while minimizing the need for expensive ab initio calculations.

DFT↗
DOE OSTI2026

A generative machine learning model for designing metal hydrides applied to hydrogen storage

Developing new metal hydrides is a critical step toward efficient hydrogen storage in carbon-neutral energy systems. However, existing materials databases, such as the Materials Project, contain a limited number of well-characterized hydrides, which constrains the discovery of optimal candidates. This work presents a framework that integrates causal discovery with a lightweight generative machine learning model to generate novel metal hydride candidates that may not exist in current databases. Using a dataset of 450 samples (270 training, 90 validation, and 90 testing), the model generates 1000 candidates. After ranking and filtering, six previously unreported chemical formulas and crystal structures are identified, four of which are validated by density functional theory simulations and show strong potential for future experimental investigation. Overall, the proposed framework provides a scalable and time-efficient approach for expanding hydrogen storage datasets and accelerating materials discovery.

generative model↗
DOE OSTI2025

Application of Machine Learning and Data Augmentation Algorithms in the Discovery of Metal Hydrides for Hydrogen Storage

The development of efficient and sustainable hydrogen storage materials is a key challenge for realizing hydrogen as a clean and flexible energy carrier. Among various options, metal hydrides offer high volumetric storage density and operational safety, yet their application is limited by thermodynamic, kinetic, and compositional constraints. In this work, we investigate the potential of machine learning (ML) to predict key thermodynamic properties—equilibrium plateau pressure, enthalpy, and entropy of hydride formation—based solely on alloy composition using Magpie-generated descriptors. We significantly expand an existing experimental dataset from ~400 to 806 entries and assess the impact of dataset size and data augmentation, using the PADRE algorithm, on model performance. Models including Support Vector Machines and Gradient Boosted Random Forests were trained and optimized via grid search and cross-validation. Results show a marked improvement in predictive accuracy with increased dataset size, while data augmentation benefits are limited to smaller datasets and do not improve accuracy in underrepresented pressure regimes. Furthermore, clustering and cross-validation analyses highlight the limited generalizability of models across different material classes, though high accuracy is achieved when training and testing within a single hydride family (e.g., AB2). The study demonstrates the viability and limitations of ML for accelerating hydride discovery, emphasizing the importance of dataset diversity and representation for robust property prediction.

augmentation↗
DOE OSTI2025

Computational Optimization of Room Temperature Usable Capacity for Hydrogen Storage in MFU-4-Type Metal–Organic Frameworks via Pairwise Metal Substitutions

The efficient storage of hydrogen is a critical challenge in the quest for sustainable energy solutions. Current adsorbent-based methods achieve satisfactory storage densities predominantly under cryogenic temperatures and/or high pressures, which imposes problems with cost-efficient and safe implementation of this technology. Materials that can bind hydrogen gas reversibly at ambient temperatures and more moderate pressures could play a pivotal role in enabling hydrogen-powered technologies. In this study, we use reliable computational modeling to investigate two synthetically feasible paths for tuning the enthalpy of H2 binding in MFU-4-type metal–organic frameworks (MOFs), aiming to maximize usable capacity. This study examines MIM4 IICl3(bta)6 (bta– = benzotriazolate) Kuratowski-type clusters as a model for strong binding sites in MFU-4l frameworks. We systematically evaluate the impact of separately tuning the central MII metal ion (which plays a structural role) and the peripheral MI metal ion (which binds the substrate) on the energetics of H2 binding. Our computational study reveals that H2 binding at an MI site mostly follows the trend AgI < CuI < NiI < CoI < AuI while a larger central MII site generally weakens the H2 binding at a MI site. Importantly, we have identified three new combinations of MI and MII to achieve high fractional usable capacities of the total H2 adsorbed under a pressure swing from 5 to 100 bar at room temperature. Additionally, we examine the nature of the binding interaction between the peripheral metal atom and the hydrogen molecule. While charge transfer predominantly induces this interaction, for several atom combinations, a change in the polarization (associated with variations in the ionic radius of the MI binding atom) is another important factor for adjusting the strength of the interaction. We suggest that the proposed compositions of Kuratowski-type clusters are highly desirable synthetic targets for future laboratory study.

Tkachenko, Nikolay V↗
DOE OSTI2024

Evaluation of hydrogen storage in sandstone reservoirs using 1 H nuclear magnetic resonance spectroscopy

Evaluation of the hydrogen storage capacity of porous rocks is crucial for underground hydrogen storage. Using 1 H nuclear magnetic resonance (NMR) spectroscopy, we successfully characterized the hydrogen responses and identified storage mechanisms in Berea sandstone under varying water saturation. Here, the results indicate that the injected hydrogen behaves as a free gas phase and is capable of occupying the empty pore volume regardless of the saturation state. No hysteresis was observed during injection and production cycles.

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

Strain-Based Assessment of Shale Caprock during Cyclic Underground Hydrogen Storage

Successful large-scale underground hydrogen storage (UHS) in depleted gas reservoirs depends on the integrity of the overlying caprock to prevent hydrogen loss during cyclic injection and depletion. Prior studies on crushed Marcellus shale, a potential caprock, indicate that cyclic hydrogen injection and depletion induces microstructural changes, increasing porosity and permeability. However, the extent of these changes in intact shale remains unclear. This study presents a strain-based experimental approach to quantify volumetric strain evolution in intact Marcellus shale matrix under unconstrained stress conditions. A quadrant-shaped shale sample without visible fractures underwent eight hydrostatic pore-pressure cycles (injection to 1500 psi and depletion to 500 psi in 250 psi steps). Linear strain gauges measured strain in three orthogonal directions. Results indicate progressive plastic strain accumulation, leading to an ∼12% increase in matrix porosity after eight cycles, with an estimated 19% increase after 30 cycles. This porosity increase follows a logarithmic trend, suggesting a diminishing effect in later cycles. Additionally, permeability and diffusive mass flux are projected to rise by ∼70% over 30 cycles, enhancing hydrogen migration risk. The shale matrix also exhibited mechanical stiffening over successive cycles, limiting large-scale deformation but not preventing porosity enhancement. A new parameter, α, was introduced to characterize shale sensitivity to cyclic loading, aiding UHS caprock assessments. These findings underscore the necessity of incorporating cyclic loading effects in UHS site selection and operational strategies to ensure long-term storage integrity.

08 HYDROGEN↗
DOE OSTI2025

Williston Basin Resource Study for Commercial-Scale Subsurface Hydrogen Storage

This closeout presentation summarizes a Department of Energy–funded study that evaluated whether large amounts of hydrogen can be safely stored underground in the North Dakota portion of the Williston Basin. The project combined lab testing, computer simulations, and basin‑wide analysis to assess saline formations, depleted oil and gas reservoirs, and salt formations for hydrogen storage capacity, recovery, and risks. Results show that underground hydrogen storage is technically feasible across multiple formation types, with depleted oil and gas reservoirs offering higher recovery and saline formations providing large long‑term storage potential. The study also identifies key challenges—such as wellbore material durability and gas purity management—and recommends pilot projects and further site‑specific studies to support future commercialization.

08 HYDROGEN↗
DOE OSTI2025

Computational investigation of the impact of metal–organic framework topology on hydrogen storage capacity

Metal–organic frameworks (MOFs) are promising, tunable materials for hydrogen storage. For application under cryogenic operating conditions, past work has run into a ceiling on performance due to a trade-off in the volumetric deliverable capacity (VDC) versus the gravimetric deliverable capacity (GDC). In this study, we computationally constructed and screened 105 230 MOF structures based on 529 nets to explore the effect of underlying topology on the hydrogen storage performance of the resulting materials. A machine learning model was developed based on simulated hydrogen uptake to facilitate screening of the entire dataset, and it successfully identified the top 10% of materials with a root-mean-square error of approximately 1 g L −1 as validated by subsequent grand canonical Monte Carlo simulations. We identified a promising structure based on the tsx topology that exhibits both VDC and GDC higher than the current benchmark material, MOF-5. Our data-driven analysis indicates that nets with higher net density yield MOFs with enhanced volumetric and gravimetric surface areas, thereby improving maximum VDC while shifting the capacity trade-off toward higher GDC.

36 MATERIALS SCIENCE↗
DOE OSTI2026

In Situ Formed Pt–Ga Hetero Duo-Atomic Catalyst for Efficient Hydrogen Storage in N-Heterocycles

Efficient catalysts for the dehydrogenation and hydrogenation of liquid organic hydrogen carriers (LOHCs) are essential for advancing hydrogen storage and transportation. Conventional nanoparticle catalysts suffer from low metal utilization, while single-atom catalysts (SAC) are limited by isolated active sites. Here, in this work, we present a hetero duo-atomic catalyst, Pt 1 –Ga 1 /CeO 2 DAC, which exhibits exceptional activity, selectivity, stability, and recyclability for N-heterocycle hydrogen storage. Ga plays a critical role in C–H bond activation, acting as a mediator in catalytic bond-breaking and formation. Compared with Pt 1 /CeO 2 SAC, Pt 1 –Ga 1 /CeO 2 DAC enhances metal utilization while overcoming SAC limitations for large substrates. This work establishes a promising strategy for designing highly efficient catalysts for LOHC applications.

Chen, Luning [Univ. of California, Los Angeles, CA↗
DOE OSTI2025

A quantitative risk assessment framework for fault reactivation in underground hydrogen storage: Coupled simulation and deep learning approach

Underground hydrogen storage (UHS) is emerging as a critical solution for large-scale energy storage. However, like all subsurface fluid injection activities, UHS poses the risk of injection-induced fault reactivation. Accurate risk assessment is essential to ensuring the safety and efficiency of UHS operations. This study presents the development of deep-learning surrogate models for fault reactivation prediction in UHS, trained on a comprehensive database of fully coupled fluid flow-geomechanics simulations. Our findings reveal that analytical models often yield unreliable estimates, with errors up to 54% in the allowable injection pressure, potentially leading to a 40% reduction in UHS operational capacity. The developed surrogate models were incorporated into a quantitative risk assessment (QRA) framework, enabling probabilistic evaluation of fault reactivation risk while accounting for uncertainties in the input variables. Site-specific features, such as horizontal stress gradients, fault’s dip and strike angles, and operational parameters like bottom-hole injection pressure and well-fault distance, were identified as the primary drivers of fault reactivation across various stress regimes. Whereas other hydraulic, geological, and poroelastic reservoir properties were found to have a secondary impact. Notably, we observed that the risk of fault reactivation for a critically oriented fault with a static friction coefficient greater than 0.55 remains below 10% in a normal faulting stress regime. However, the risk significantly increases as the stress regime transitions from normal to strike-slip and ultimately to reverse faulting conditions. These findings underscore the importance of rigorous site characterization and comprehensive QRA evaluations to optimize UHS performance and minimize geomechanical risks.

25 ENERGY STORAGE↗
DOE OSTI2024

Modeling based assessment of salt cavern performance for underground hydrogen storage

This poster is about the recent progress in my LDRD project of underground hydrogen storage in multiple salt caverns. The main progress of my work is to develop modeling-based workflow to evaluate the salt cavern performance and assess the potential of geomechanical risk for hydrogen storage.

Chang, Kyung Won [Sandia National Laboratories (SN↗
DOE OSTI2025

Williston Basin Resource Study for Commercial-Scale Subsurface Hydrogen Storage

The Energy & Environmental Research Center (EERC), in partnership with the U.S. Department of Energy (DOE) National Energy Technology Laboratory (NETL), the EERC’s State Energy Research Center (SERC), MPLX Operations LLC, and TC Energy Development Holdings Inc. (a subsidiary of TC Energy Corporation), studied the potential for subsurface hydrogen storage and recovery in the Williston Basin of western North Dakota. The project’s goal was to evaluate the feasibility of large-scale, secure geologic H 2 storage to support future hydrogen generation, storage, and use. This work included laboratory testing, H 2 –rock–fluid exposure experiments, literature reviews on H 2 embrittlement, and reservoir modeling and simulations. The study included an assessment of storage potential across three types of storage reservoirs using both reservoir simulation and DOE’s web-based tool SHASTA-HELP (Subsurface Hydrogen Assessment, Storage, and Technology Acceleration – Hydrogen Estimator for Logistical Planning), as well as investigation of potential H 2 production and markets for commercial-scale deployment. Building on prior EERC gas storage research, three storage options were selected for detailed evaluation: the Broom Creek Formation (a clastic saline reservoir), the Dickinson Lodgepole Mounds (DLM) complex (carbonate mud mound structures) of the Lodgepole Formation (an active oil and gas producing reservoir), and the Dunham Salt Interval of the Piper Formation (to be used for engineered salt cavern development). These targets were prioritized based on prior EERC research using datasets related to seal capacity, reservoir quality, mechanical integrity, and injectivity. Exposure tests on Broom Creek and DLM samples showed mineral dissolution and precipitation that increased brine salinity and altered reservoir rock surfaces. Although these results provide useful insight, they are limited by small sample sizes and short-term (30-day) exposure, requiring further study to assess long-term storage integrity. Salt formations were not tested because of their known nonreactivity and established mechanical stability. Results of reservoir simulations performed for a single site demonstrated that the Broom Creek Formation may be capable of receiving up to 42,000 tonnes of injected H 2 over 7 months via one well. H 2 recovery took place over 5 months, resulting in approximately 26,000 tonnes (~62% without cushion gas [CG]). This work suggests water production may be important and subsequent cycles of injection and production may perform more efficiently; however, significant site-specific work in the future is needed to assess actual reservoir performance of injection and withdrawal of H 2 storage. For oil reservoir potential, a multiple-well model was used to simulate injection of approximately 32,000 tonnes of H 2 into a single wellbore while simultaneously producing in place reservoir fluids from four offset wells to maintain reservoir pressure. The simulation results suggested a high recovery (~98%); in addition, cost advantages through existing infrastructure could be realized. Challenges in this reservoir include vi managing gas purity and leakage risks. In both scenarios, production of H 2 takes place in a single-well scenario with 10 cycles (7 months of injection and 5 months of production) over 10 years. Finally, the use of engineered caverns in the Dunhan Salt was evaluated, and the results suggest that while they have a smaller capacity (<1000 tonnes per cavern), they exhibit nearly complete gas recovery (>99%), fast response times, and low purity risk. While caverns in North Dakota may be smaller in capacity, fields can be developed in galleries to accommodate the volumetric needs and rapid turnaround times necessary to meet market demands. Geographic limitations and thin salt intervals in North Dakota may represent less total storage potential than salt domes elsewhere, but significant opportunities exist to expand this market for gas storage in North Dakota. A basinwide assessment was performed to estimate a first-of-its-kind value for H 2 storage on a large scale. DOE’s SHASTA-HELP, combined with EERC simulation work, was used to perform the assessment. Estimated H 2 storage potential varied widely for each formation type. The Broom Creek saline formation was estimated to have a storage potential of approximately 1.7–90.5 million tonnes (MMt). The DLM oil reservoirs were estimated to have 0.07–0.19 MMt of capacity. Notably, each of these estimates relies on significant assumptions regarding reservoir thickness, porosity, permeability, and CG needed for operation. Much research is needed to understand the true site-specific storage resource potential of each formation. Using the Dunham Salt Interval for cavern development may result in as much as 4.79 MMt (up to 2.87 MMt working gas) of H 2 storage potential. An important note for consideration is that the values presented here need significantly more geological characterization and engineering assessments prior to gaining confidence in performance. This will be a focal point for future research and development needs. The basinwide evaluation also indicated that North Dakota has significant H 2 generation potential, with estimates up to a possible 13 MMt annually, suggesting a substantial opportunity for H 2 market development and thus the need for commercial-scale H 2 storage to facilitate growth and resilience. Key Recommendations 1. Conduct detailed site characterization (3D seismic, well logs, core sampling) to reduce geologic uncertainty. 2. Perform techno-economic analyses incorporating market, regulatory, and incentive frameworks. 3. Investigate long-term interactions among H 2 , CGs, well materials, and formations to assess risks. 4. Develop pilot- and field-scale demonstrations to validate models and establish best practices.

03 NATURAL GAS↗
DOE OSTI2025

Safety Hazards of Batteries and Hydrogen Storage Systems in Proximity

This report addresses the safety concerns and mitigations for battery failures and their impact on hydrogen storage systems. Through an analysis of failure modes, this report highlights the risks posed by thermal runaway and chemical emissions caused by batteries. Although rare, battery thermal failure events may prompt the opening of the relief valve on the hydrogen tank. Strategies such as battery management systems, thermal management systems, and multiple thermally activated pressure relief devices can mitigate these risks. Potential simulations and experiments to better quantify the unique risks posed by lithium-ion batteries near tanks are suggested. Improving safety standards will enable integration of batteries and hydrogen storage systems in various energy storage technologies.

08 HYDROGEN↗
DOE OSTI2025

Technoeconomic Insights into Metal Hydrides for Stationary Hydrogen Storage

Abstract Metal hydrides (MHs) are promising candidates for storing hydrogen at ambient conditions at high volumetric energy densities. Recent developments suggest hydride‐based systems can cycle and operate at favorable pressures and temperatures that work well with fuel cells used in stationary power applications. In this study, we present a comprehensive design and cost analysis of MH‐based long duration hydrogen storage facilities for a variety of power end users (0 to 20 megawatts (MW) supplied over 0 to 100 hours), to offer insights on technical targets for material development and operation strategies. Our findings indicate that hydride‐based storage systems hold significant size advantage in physical footprint, requiring up to 65% less land than 170‐bar compressed gas storage. Metal hydride systems can be cost competitive with 350‐bar compressed gas systems, with TiFe 0.85 Mn 0.05 achieving $0.45/kWh and complex MH Mg(NH 2 ) 2 ‐2.1LiH‐0.1KH achieving $0.38/kWh. Extending charging times and increasing operating cycles significantly reduce levelized cost of storage, especially for complex MHs. Key strategies to further enhance the competitiveness of MHs include leveraging waste heat from fuel cells, reducing use of critical minerals, and achieving MH production costs of US$10/kg.

08 HYDROGEN↗
NASA NTRS1981

Technical and economic aspects of hydrogen storage in metal hydrides

The recovery of hydrogen from such metal hydrides as LiH, MgH2, TiH2, CaH2 and FeTiH compounds is studied, with the aim of evaluating the viability of the technique for the storage of hydrogen fuel. The pressure-temperature dependence of the reactions, enthalpies of formation, the kinetics of the hydrogen absorption and desorption, and the mechanical and chemical stability of the metal hydrides are taken into account in the evaluation. Economic aspects are considered. Development of portable metal hydride hydrogen storage reservoirs is also mentioned.

Schmitt, R.↗
DOE OSTI2025

Risk assessment of wellbore leakage during underground hydrogen storage

The expansion of renewable energy sources would require large-scale energy storage options to overcome the intermittent nature of these sources. Underground hydrogen storage (UHS) in depleted hydrocarbon reservoirs offers a scalable and practical energy storage solution. These reservoirs are chosen for their availability and large capacity, but the unique properties of hydrogen raise concerns about potential leakage pathways, particularly through wellbores. In this study, we develop and apply, for the first time, reduced-order models (ROMs) specifically designed for efficient leakage risk prediction in UHS systems operating in depleted hydrocarbon reservoirs. Using 3,000 high-fidelity simulation scenarios, we examine the influence of 11 key parameters, including reservoir and aquifer depths, wellbore permeability and porosity, initial saturations of water, oil and gas fractions (hydrogen, light, intermediate, and heavy hydrocarbons), reservoir pressure multiplier, and the aquifer-to-reservoir volume ratio, to simulate leakage behavior over a 1,000-year timescale. We train ROMs using a two-step classification-regression approach, achieving R 2 values exceeding 99 % across all targets. These ROMs effectively capture the leakage evolution and identify critical controls of leakage, guiding the design of mitigation strategies. Results indicate that gas leakage occurs in about 27 % of scenarios as early as five years post-operation, reaching volumes of up to 106 ft3. Oil leakage is less frequent (~17 %) and typically begins decades later. Our findings also show that hydrogen often migrates first, owing to its smaller molecular size and higher buoyancy, followed by heavier hydrocarbons. Over time, these heavier components contribute significantly to the total leaked volume, reinforcing the need for targeted monitoring and remediation strategies. Our analysis highlights that deeper storage reservoirs, shallower aquifers, and low-permeability wellbores significantly reduce leakage risks. In conclusion, this work offers a robust framework for risk-informed UHS deployment, supporting energy security through reliable large-scale hydrogen storage while safeguarding environmental integrity.

08 HYDROGEN↗