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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 973 records · Page 54
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

A hybrid analytical and numerical model for cross-over and performance decay in a unit cell vanadium redox flow battery

Developing an accurate and efficient model for cross-over is critical for improving the long-term performance of redox flow batteries (RFBs). Here, this work presents a hybrid analytical and numerical model that combines a two-dimensional analytical solution to the active species, a one-dimensional analytical model for cross-over mechanisms, and a zero-dimensional numerical model for outlet concentrations of reactants. By comparing with experiment over 41 cycles (ca. 144 h), the model reported a mean voltage difference of 0.0089 V, mean time difference of 14 s per cycle (of 3.5 h), maximum relative difference for capacity and energy of 1.34% and 1.63%, respectively. The predicted mean concentrations for V 2+ , V 3+ , and VO$_{2}^{+}$ in membrane are 65%~77% of measured values from the literature. Upon validation, the model reproduced behaviors in electrolyte imbalance similar to those observed in experiments and numerical models, and revealed the control of cross-over, self-discharge, stoichiometry of side reactions, and Coulombic efficiency on electrolyte imbalance. The model also demonstrates excellent computational efficiency for simulating 41 cycles (around 37,000 points) within 3~4 s. The demonstrated efficiency and accuracy for predicting cross-over and its impacts on voltage, capacity&energy decay, membrane concentrations, and electrolyte imbalance makes it a reliable tool for optimizing RFBs’ long-term performance.

25 ENERGY STORAGE↗
DOE OSTI2023

Structure and lithium insertion in oxides of molybdenum

Oxides of molybdenum, MoO x , have a rich structural chemistry arising from the accommodation of oxygen deficiency as MoO 3 is reduced and varied redox behavior arising from the ability of Mo to take on several different oxidation states. We review MoO 3 , MoO 2 , and all the reduced Mo oxides with intermediate compositions for their performance as Li-ion battery electrode materials. These reduced oxides are perhaps the most structurally diverse in the field of energy storage materials, taking on structures ranging from ones with crystallographic shear to bronze-like structures and distorted rutile. The crystal structure can have a significant impact on the performance of battery materials, which makes the reduced Mo oxides a promising domain of study. Electrochemical studies of these oxides from as early as 1971 to as recently as 2022 are compiled, and characteristics of capacity, capacity retention, and rate performance are compared. We find that certain oxides indeed display promising and highly reversible capacities for Li + storage. Typical redox voltages for Mo oxides lie in a regime that hinders maximizing energy density when they are paired with higher-voltage cathodes or lower-voltage anodes. The possibility of decreasing the redox voltage in the future will expand the promise of these materials while offering an alternative to more critical elements such as Nb.

25 ENERGY STORAGE↗
DOE OSTI2024

Hybrid Storage Solution

With the rise of artificial intelligence and machine learning, data sets used to train models have become increasingly large. The availability, accessibility and integrity of large data sets has become important to the research conducted at Los Alamos National Laboratory. Ceph is a storage solution suitable for use with critical data because of its distributed nature and ability to keep multiple copies of a file in different locations. The amount of data means that bandwidth, latency, and cost are important factors and the reason most storage solutions are on-premises. However, there are distinct advantages to hosting services in the cloud, namely scalability and ease-of-use. In this paper, we explore the possibility of provisioning a hybrid Ceph cluster that leverages the benefits of both cloud architectures and on-premise performance.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Final Report For Project TCF-18-15778

This report documents work performed under the Technology Commercialization Fund (TCF-18-15778, Used (spent) nuclear fuel management and analysis tool) award provided by the US Department of Energy (DOE) Office of Technology Transitions (OTT). This report describes various Used Nuclear Fuel-Storage, Transportation & Disposal Analysis Resource and Data System (UNF-ST&DARDS) enhancements to advance the technology readiness level (TRL). The principal work performed under TCF is the integration of the initial dry storage loading optimization algorithm into UNF-ST&DARDS.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

CAFE AU LAIT: Compute-Aware Federated Augmented Low-Rank AI Training

Federated finetuning is crucial for unlocking the knowledge embedded in pretrained Large Language Models (LLMs) when data are geographically distributed across clients. Unlike finetuning with data from a single institution, federated finetuning allows collaboration across multiple institutions, enabling the utilization of diverse and decentralized datasets while preserving data privacy. Given the high computing costs of LLM training and the emphasis on energy efficiency in Federated Learning (FL), Low-Rank Adaptation (LoRA) has emerged as a widely adopted algorithm due to its significantly reduced number of trainable parameters. However, this assumes that all data silos have the necessary computing resources to compute local updates of LLMs. Nevertheless, in practice, the computing resources across clients are highly heterogeneous: while some may have access to hundreds of GPUs, others might have limited or no GPU access. Recently, federated finetuning using synthetic data has been proposed, allowing clients to participate in a collaborative training run without training LLMs locally. However, our experimental results reveal a performance gap between models trained using synthetic data and those trained using local updates. Motivated by the observed heterogeneity in computing resources and the performance gap, we propose a novel two-stage algorithm that leverages the storage and computing capabilities of a strong server. In the first stage, under the coordination of the strong server, clients with limited computing resources collaborate to generate synthetic data, which is transferred to and stored on the strong server. In the second stage, the strong server uses this synthetic data on behalf of the resource-constrained clients to perform federated LoRA finetuning alongside clients with sufficient computing resources. This approach ensures that all clients can participate in the finetuning process. Experimental results demonstrate that incorporating local updates from even a small fraction of clients improves performance compared to using synthetic data for all clients. Furthermore, we incorporate the Gaussian mechanism in both stages to guarantee client-level differential privacy.

Wang, Jiayi [ORNL]↗
DOE OSTI2026

Ultra-thick three-dimensional interpenetrating graphene electrode architectures for high volumetric density energy storage

For electrochemical energy storage, increasing the electrode thickness is an effective approach to achieving higher energy density from a given material. However, this often compromises ion transport, leading to diminished performance. Here, in this study, we present a novel platform for fabricating complex 3D interpenetrating electrode structures via photo-polymerization 3D printing, integrated with computational structural optimization for energy storage. The platform employs an acrylate resin system infused with graphene oxide (GO), enabling high-fidelity printing of optimized porous structures and facilitating efficient electron and ion transport in ultra-thick electrodes. The optimized 3D layouts substantially enhance energy and power densities compared to conventional configurations, ensuring superior material utilization and minimal ohmic losses. Supercapacitors fabricated using this approach achieved an exceptional energy density of 4.7 Wh L−1 at a power density of 1689.0 W L−1, surpassing traditional designs. This work underscores the transformative role of structural optimization in advancing electrochemical performance and establishes a versatile pathway for developing next-generation energy storage systems with exceptional efficiency and functionality.

Wang, Zhen [University of California, Berkeley, CA↗
DOE OSTI2025

MC Formula Protocol for H35HF Fueling (CRADA Final Report)

The National Renewable Energy Lab (NREL), Frontier Energy, and the industry partners worked together to help SAE J2601-5 develop an H35 high-flow (HF) medium-duty (MD) and heavy-duty (HD) fueling protocol. The team upgraded NREL's hydrogen filling simulations (H2FillS) model to accommodate an MC Formula fueling (t-final) table generation capability by leveraging NREL's high-performance computing system. Based on protocol boundary conditions (e.g., allowable maximum flow rate, range of storage system size) set by SAE J2601-5, the team generated the fueling tables and then validated the reliability of those tables by installing them on NREL's HD dispenser and ZBT's H35HF dispenser and then performing H35HF fueling experiments. Through the validation process, this team certified that the fueling tables generated were reliable to install in commercial H35HF dispensers and then performed H35HF fueling of commercial MD/HD vehicles.

08 HYDROGEN↗
DOE OSTI2020

Assessing geothermal/solar hybridization – Integrating a solar thermal topping cycle into a geothermal bottoming cycle with energy storage

Geothermal and concentrating solar power (CSP) technologies typically use heat at different temperatures in their commercial deployments. This enables a technically viable hybridization of a solar topping cycle and a geothermal bottoming cycle at locations where both resources are available. In this article, an underperforming geothermal power system based at Burley, Idaho is used as a baseline to investigate the technical and economic potential of such a hybrid cycle. A direct thermal energy storage (TES) system is also integrated to overcome the intermittency of the solar resource. Design and off-design behavior of key components are modelled to simulate the annual performance of the hybrid system on an hourly basis. The sizing of the solar field and thermal storage is investigated and is seen to significantly impact the annual electricity generation and efficiency. Various cost scenarios for the solar field and thermal energy storage are investigated. An economic metric - levelized cost of electricity (LCOE) - is used to optimize the solar field sizing and TES capacity. The hybrid plant converts the additional solar heat input into additional work with an efficiency of 32.9%. Retrofitting a geothermal plant with solar and eight hours of energy storage can achieve an LCOE of 0.136 $/kWhe in current cost scenarios and 0.081 $/kWhe in a future cost reduction scenario. Although the hybrid system cannot directly compete with current PV systems without batteries, it has an LCOE 32% lower than that of a PV-battery system. This paper provides insights into the research and development of the future grid with a high renewable energy penetration and encourages further study of energy hybridization for improved efficiencies and economics.

15 GEOTHERMAL ENERGY↗
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 OSTI2025

Interactive multiscale modeling to bridge atomic properties and electrochemical performance in Li-CO 2 battery design

Li-CO 2 batteries are promising energy storage systems due to their high theoretical energy density and CO 2 fixation capability, relying on reversible Li 2 CO 3 /C formation during discharge/charge cycles. Here, we present a multiscale modeling framework integrating Density Functional Theory (DFT), Ab-Initio Molecular Dynamics (AIMD), classical Molecular Dynamics (MD), and Finite Element Analysis (FEA) to investigate atomic and cell-level properties. The considered Li-CO 2 battery consists of a lithium metal anode, an ionic liquid electrolyte, and a carbon cloth cathode with Sb 0.67 Bi 1.33 Te 3 catalyst. DFT and AIMD determined the electrical conductivities of Sb 0.67 Bi 1.33 Te 3 and Li 2 CO 3 using the Kubo–Greenwood formalism and studied the CO 2 reduction mechanism on the cathode catalyst. MD simulations calculated the CO 2 diffusion coefficient, Li + transference number, ionic conductivity, and Li + solvation structure. The FEA model, parameterized with atomistic simulation data, reproduced the available experimental voltage–capacity profile at 1 mA/cm 2 and revealed spatio-temporal variations in Li 2 CO 3 /C deposition, porosity, and CO 2 concentration dependence on discharge rates in the cathode. Accordingly, Li 2 CO 3 can form large and thin film deposits, leading to dispersed and local porosity changes at 0.1 mA/cm 2 and 1 mA/cm 2 , respectively. The capacity decreases exponentially from 81,570 mAh/g at 0.1 mA/cm 2 to 6200 mAh/g at 1 mA/cm 2 , due to pore clogging from excessive discharge product deposition that limits CO 2 transport to the cathode interior. Therefore, the performance of Li-CO 2 batteries can be improved by enhancing CO 2 transport, regulating Li 2 CO 3 deposition, and optimizing cathode architecture.

Battery performance↗
DOE OSTI2024

Hydrogen Storage for Load-Following and Clean Power: Duct-firing of Hydrogen to Improve the Capacity Factor of NGCC Plants (Final Report, Phase II Pre-Front End Engineering Design Study)

GTI Energy (GTI) and team members Southern Company Services (SCS), Pacific Gas & Electric (PG&E) and the Electric Power Research Institute (EPRI) performed a Phase II Pre-Feed Study under contract DE-FE0032008 for Hydrogen Storage for Load-Following and Clean Power. The configuration of the proposed system consists of subsystems for on-site H 2 production, on-site H 2 storage (up to 54 MWth in commercial vessels) and H 2 combustion in a duct burner in a Heat Recovery Steam Generator (HRSG) integrated with an existing fossil asset. Here, the firing rate of the duct burner is varied to let the plant respond to fluctuations of electrical load and H 2 production is relatively constant by storing H 2 . The proposed system is an improvement over alternate low carbon dispatchable power options. Technoeconomic analyses show H 2 produced with GTI’s patented Compact Hydrogen Generator (CHG) with inherent carbon capture will be lower cost (Levelized Cost of Hydrogen, LCOH) relative to hydrogen produced with a Steam Methane Reformer (SMR) with an amine system for carbon capture. This lower cost hydrogen enables our integrated system to deliver electricity (Levelized Cost of Electricity, LCOE) at 17.4% lower cost relative to a SMR sourced H 2 -fired HRSG (with an amine system for carbon capture) – Steam Turbine Generator (STG). Our analysis using EPRI’s US REGEN macroeconomic model shows our system will have significant demand in the power market and therefore require significant capacity expansion (CHG plants built to deliver hydrogen) to deliver low cost, low carbon power. In Phase II, our Team has completed a detailed system definition including the development of process models, definition of battery limits, Process Flow Diagrams (PFDs), Piping and Instrumentation Drawings (P&IDs), and a plant layout. A preliminary design for the key components of the CHG was developed including component lists & specifications. An evaluation of environmental and permitting considerations was completed and included the development of an Environmental Information Volume (EIV). The duct burners, which are flexible and can burn hydrogen and/or natural gas, were defined and initial CFD analyses were completed.

03 NATURAL GAS↗
DOE OSTI2022

The effect of micro-encapsulation on thermal characteristics of metallic phase change materials

Micro-encapsulated phase change material with metallic core can work under high temperature for energy storage purpose, making it an appealing candidate for renewable energy technologies, such as thermal energy storage for concentrating solar power plants. Here, the objective of this work is to study the impact of encapsulation on the thermal performance of the micro-encapsulated phase change materials under various operating conditions. To evaluate the thermal performance of the micro-encapsulated phase change material particles, the governing equation of transient heat conduction with phase change in spheres with composite walls is solved numerically. The impact of encapsulation shell on the convective heat transfer rate, total energy absorption, latent heat ratio, energy density, and duration of phase change is presented and analyzed under different operating conditions. Three different core materials including tin, aluminum and copper with distinct Stephan numbers are investigated. In addition to the encapsulation shell effect, this model can be used to study micro-encapsulated phase change materials with different material compositions, core to shell ratios, and it can be used to analyze the impact of air gaps in between materials. Understanding the thermal performance at particle level is essential, and the results of this study could potentially be used as input for thermal energy storage system level analysis, such as the charging and discharging processes.

42 ENGINEERING↗
DOE OSTI2024

DEVAP-EDDR-TES (Simulation framework for a desiccant assisted air conditioning system with heat pump regeneration and energy storage) [SWR-24-66]

This software is a simulation framework that models a load flexible air conditioner system. The system consists of an evaporatively cooled liquid desiccant air conditioner (eLD-AC) subsystem, an electrically driven desiccant regenerator (EDDR) subsystem, and a stratified liquid desiccant storage (SLDS) subsystem. The software can be used to 1) predict the steady-state performance of the system given user-specified convergence criteria; 2) predict the dynamic performance of the entire system over a typical drive cycle operation subjected to user-specified building thermal loads and desired electrical load profile; 3) evaluate the synergy of all three subsystems operating altogether and improve the energy storage control strategy.

Huang, Ransisi↗
DOE OSTI2023

Novel Structural Motif To Promote Mg-Ion Mobility: Investigating ABO 4 Zircons as Magnesium Intercalation Cathodes

There is an increasing need for sustainable energy storage solutions as fossil fuels are replaced by renewable energy sources. Multivalent batteries, specifically Mg batteries, are one energy storage technology that researchers continue to develop with hopes to surpass the performance of Li-ion batteries. However, the limited energy density and transport properties of Mg cathodes remain critical challenges preventing the realization of high-performance multivalent batteries. In this work, ABO 4 zircon materials (A = Y, Eu and B = V, Cr) are computationally and experimentally evaluated as Mg intercalation cathodes. Remarkably good Mg-ion transport properties were predicted and Mg-ion intercalation was experimentally verified in sol-gel synthesized zircon YVO 4 , EuVO 4 , and EuCrO 4 . Among them, EuVO 4 exhibited the best electrochemical performance and demonstrated repeated reversible cycling. While we believe that the one-dimensional diffusion channels and redox-active species tetragonal coordination limit the value of many zircons as high-performance cathodes, their unique structural motif of overlapping polyhedra along the diffusion pathway appears instrumental for promoting good Mg-ion mobility. The motif results in a favorable "6-5-4" change in coordination that avoids unfavorable sites with lower coordination along the diffusion pathway and a structural design metric for future Mg cathode development.

25 ENERGY STORAGE↗
DOE OSTI2024

Combining 3D printing of copper current collectors and electrophoretic deposition of electrode materials for structural lithium-ion batteries

Serving as a proof of concept, additive manufacturing and electrophoretic deposition are leveraged in this work to enable structural lithium-ion batteries with load-bearing and energy storage dual functionality. The preparation steps of a complex 3D printed copper current collector, involving the formulation of a photocurable resin formulation, as well as the vat photopolymerization process followed by a precursors-based solution soaking step and thermal post-processing are presented. Compression and microhardness testing onto the resulting 3D printed copper current collector are shown to demonstrate adequate mechanical performance. Electrophoretic deposition of graphite as a negative electrode active material and other additives was then performed onto the 3D printed copper collector, with the intention to demonstrate energy storage functionality. Half-cell electrochemical cycling of the 3D multi-material current collector/negative electrode versus lithium metal finally demonstrates that structural battery components can be successfully obtained through this approach.

25 ENERGY STORAGE↗
DOE OSTI2021

Emission Inventories from Natural Gas Storage Facilities using Regional Frequency Comb Laser Monitoring and Aircraft Flyovers. Final Report

The project centers around a ground-based regional methane sensor developed by the CU/NIST team members under the DOE ARPA-E MONITOR program, and sophisticated aircraft measurement techniques developed by the UCD/Scientific Aviation team (responsible for a recent Science publication quantifying the Aliso Canyon storage field release). The dual frequency-comb spectrometer is an invisible, eye-safe laser capable of measuring atmospheric methane concentrations along beam paths 1+ miles in length with high precision and stability (<1 ppb methane over 1 mile). The CU/NIST team has developed a unique approach to using a single, central spectrometer to locate and size methane emissions as small as 6 scfh from specific gas field structures within the 1+ mile range of the laser. Deployment involves the stationing of small cubic mirrors at strategic locations across the gas storage site. The mirrors direct light from the spectrometer back to a detector, where methane concentrations are recorded based on light absorption at specific wavelengths. The measurements are coupled with high resolution gas transport models based on meteorological measurements (wind, etc.) to determine the precise location and emission rate of methane sources. The calibration-free and continuous nature of dual frequency-comb spectrometer measurements means that a large area can be monitored continuously for temporal variability of emissions over long periods of time. The aircraft measurements involve spiral flights around storage facilities with a sensitive ethane/methane measurement package. Upwind/downwind concentration comparisons and wind data provide total facility emissions data. During this project, a new micrometeorological package was integrated onto the Scientific Aviation aircraft to provide even greater emissions quantification capability. In this project, the ground-based measurement system was deployed for 11 months (to capture seasonal variability) at a West Coast storage facility, together with a campaign of twice monthly aircraft total facility emissions flights. The data from these two modalities was combined to quantify the methane emissions from the facility with first-of-its-kind temporal and spatial detail. Concurrent with this deployment, the aircraft team performed flights to quantify emissions at a wider array of previously un-surveyed storage sites. The ground-based measurement system was then moved to an additional site of differing total storage and delivery capacity. Aircraft mass balance flights continued, repeatedly surveying (twice monthly) this site, as well as surveying a large number of previously un-assessed sites spanning a variety of size, reservoir type and age. Assessment of ground-based, temporally and spatially detailed methane emissions information alongside aircraft-derived methane total facility emissions information led to an improved understanding of emissions, relevant for inventories of the natural gas storage sector. In particular, this work provided temporal detail (seasonal of emissions and frequency of leaks) to stakeholders and personnel responsible for updates to the EPA’s GHGI. The impact of the proposed work has been a dramatic improvement in the temporal, spatial, and site- and type- specific detail and quantification of emissions inventories for the natural gas storage sector. This work directly benefits the EPA’s GHGI, directly ameliorates the environmental impacts and public health and safety of the natural gas storage sector, and aids policymakers and industry to make sound choices with respect to management and regulation.

03 NATURAL GAS↗
DOE OSTI2020

Beyond Idealized Models of Nanoscale Metal Hydrides for Hydrogen Storage

Metal hydrides are attractive for compact, low-pressure hydrogen storage, yet a foundational understanding of factors governing their thermodynamics and kinetics is still lacking. Predictive modeling from the atomic to the microstructural scale plays a critical role in addressing these gaps, particularly for nanoscale materials, which promise improved performance but are difficult to probe. In this paper, we summarize strategies being developed within the Hydrogen Materials—Advanced Research Consortium (HyMARC) for going beyond conventional models to incorporate more complex physics, more realistic structures, and better approximation of operation conditions in simulations of nanoscale metal hydrides. We highlight four beyond-ideal factors that influence predicted performance: (1) surface anharmonic dynamics, (2) interface and surface energy penalties, (3) mechanical stress under confinement, and (4) the presence of native surface oxide. Approaches for addressing these factors are demonstrated on model materials representative of high-capacity hydrogen storage systems, and implications for understanding performance under operating conditions are discussed.

08 HYDROGEN↗