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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 379 records · Page 21

Potential of porous nodal-line semi-metallic carbon for sodium-ion battery anode

As an alternative to lithium-ion batteries (LIBs), sodium-ion batteries (SIBs) have attracted much attention because sodium is abundant, cost-effective, and environmentally benign. However, due to the larger size of Na-ion compared to the Li-ion, graphite does not work well as an anode for SIBs, as it does for LIBs. In this work, based on first-principles calculations, we show that the recently proposed topological semi-metallic carbon, HZGM-42, has great potential as an anode material for SIBs. With a large capacity of 318.5 mAhg -1 , low diffusion barrier of 0.08–0.21 eV, low average open-circuit voltage of 0.43 V, and a small volume expansion of 1.85%, the all-carbon topological quantum HZGM-42 has high energy density, good rate capability, and excellent cycling stability and can serve as a universal anode material for both LIBs and SIBs.

25 ENERGY STORAGE↗

Accurate prediction of core-level spectra of radicals at density functional theory cost via square gradient minimization and recoupling of mixed configurations

State-specific orbital optimized approaches are more accurate at predicting core-level spectra than traditional linear-response protocols, but their utility had been restricted due to the risk of "variational collapse" down to the ground state. We employ the recently developed square gradient minimization algorithm to reliably avoid variational collapse and study the effectiveness of orbital optimized density functional theory (DFT) at predicting second period element 1s core-level spectra of open-shell systems. Several density functionals (including SCAN, B3LYP, and ωB97X-D3) are found to predict excitation energies from the core to singly occupied levels with high accuracy (≤0.3 eV RMS error) against available experimental data. Higher excited states are, however, more challenging by virtue of being intrinsically multiconfigurational. We thus present a configuration interaction inspired route to self-consistently recouple single determinant mixed configurations obtained from DFT, in order to obtain approximate doublet states. This recoupling scheme is used to predict the C K-edge spectra of the allyl radical, the O K-edge spectra of CO + , and the N K-edge of NO 2 with high accuracy relative to experiment, indicating substantial promise in using this approach for the computation of core-level spectra for doublet species [vs more traditional time dependent DFT, equation of motion coupled cluster singles and doubles (EOM-CCSD), or using unrecoupled mixed configurations]. Finally, we also present general guidelines for computing core-excited states from orbital optimized DFT.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Valuing EV Managed Charging for Bulk Power Systems

When and where electric vehicle (EV) charging occurs has significant implications for power systems supporting widespread EV adoption, especially with high shares of wind and solar generation. This study extends previous works by leveraging detailed simulation models for EV adoption, EV use, EV charging, and bulk power system operations, and by linking them with methods for describing charging flexibility at both the individual vehicle and aggregate levels. This technical potential study focuses on how the value of EV managed charging (EVMC) changes depending on charging flexibility type (within-charging session or within-week scheduling), dispatch mechanism (direct load control or one of several price-based mechanisms), and managed charging participation rate. We show that naively aggregating EV charging flexibility from individual vehicles into megawatt-scale resources grossly overestimates the flexibility of the fleet, because such aggregate models can unrealistically pair, e.g., one already-fully-charged vehicle's ability to increase load with another already-charging vehicle's ability to accept more charge, effectively requesting a charging rate that is infeasible for the latter vehicle. We find per-vehicle bulk system value is highest at low participation rates for all dispatch mechanisms. Factoring in production cost savings, avoided firm capacity savings, and combustion-related power sector emissions savings, we estimate the value of EVMC at low participation rates (5%) to be $33/vehicle-year to $69/vehicle-yr for within-session charging flexibility and $40/vehicle-yr to $120/vehicle-yr for within-week charging flexibility in an envisioned 2038 New England power system and monetary value reported in 2016 U.S. dollars. At 100% participation, per-vehicle value declines to $25/vehicle-yr to $31/vehicle-yr for within-session charging flexibility and to $29/vehicle-yr to $36/vehicle-yr for within-week charging flexibility; however, 100% participation yields the highest total system savings.

ADVANCED PROPULSION SYSTEMS↗

Static Subspace Approximation for Random Phase Approximation Correlation Energies: Applications to Materials for Catalysis and Electrochemistry

Modeling complex materials using high-fidelity, ab initio methods at low cost is a fundamental goal for quantum chemical software packages. The GW approximation and random phase approximation (RPA) provide a unified description of both electronic structure and total energies using the same physics in a many-body perturbative approach that can be more accurate than generalized-gradient density functional theory (DFT) methods. However, GW/RPA implementations have historically been limited to either specific materials classes or application toward small chemical systems. Here, the static subspace approximation allows for reduced cost full-frequency GW/RPA calculations and has previously been benchmarked thoroughly for GW calculations. Here, we describe our approach to including partial occupations of electronic orbitals in full-frequency GW and RPA calculations for the study of electrocatalysts. We benchmarked RPA total energy calculations using the subspace approximation across a diverse test suite of materials for a variety of computational parameters. The benchmarking quantifies the impact of different extrapolation procedures for representing the static polarizability at infinite screened cutoff, and shows that using screened cutoffs above 20-25 Ryd result in diminishing accuracy returns for predicting RPA total energies. Additionally, for moderately sized electrocatalytic models, 2-3 times fewer computational resources are used to compute RPA total energies by representing the static polarizability with 20-30% of the static subspace basis, with an error of approximately 0.01 eV or better in RPA adsorption energy calculations. Finally, we show that for these electrochemical models RPA can shift DFT adsorption energy shifts by up to 0.5 eV and that GW can frequently shift DFT eigenvalues of surface and adsorbate states by approximately 0.5-1 eV.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Machine learned features from density of states for accurate adsorption energy prediction

Materials databases generated by high-throughput computational screening, typically using density functional theory (DFT), have become valuable resources for discovering new heterogeneous catalysts, though the computational cost associated with generating them presents a crucial roadblock. Hence there is a significant demand for developing descriptors or features, in lieu of DFT, to accurately predict catalytic properties, such as adsorption energies. Here, we demonstrate an approach to predict energies using a convolutional neural network-based machine learning model to automatically obtain key features from the electronic density of states (DOS). The model, DOSnet, is evaluated for a diverse set of adsorbates and surfaces, yielding a mean absolute error on the order of 0.1 eV. In addition, DOSnet can provide physically meaningful predictions and insights by predicting responses to external perturbations to the electronic structure without additional DFT calculations, paving the way for the accelerated discovery of materials and catalysts by exploration of the electronic space.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Electric Vehicle Managed Charging: Estimating the Potential Bulk Power System Value

With more and more electric vehicles (EVs) on the road, the grid of the future can greatly benefit from EV managed charging, which coordinates charging based on people's travel needs, electricity supply, and grid conditions. The added flexibility could be especially valuable for the bulk power system as it transitions to high shares of variable renewable generation, like wind and solar. Numerous studies have estimated the potential value of EV managed charging. In this study, NREL leveraged more detailed modeling of EV adoption, use, charging, and bulk power system operations to understand the potential value. Unique to this study, NREL modeled different charging flexibility types and dispatch mechanisms - as well as participation rates among drivers in having their EV charging managed - starting from vehicle-specific descriptions of charging flexibility. The study is based on a passenger light-duty vehicle adoption scenario with 100% EV sales by 2035 and a New England power system in 2038 with 84% clean generation and 26% of the electric load met by net imports. The 2038 New England light-duty vehicle feet is modeled as 45% electric.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗

Carrier control in Sn–Pb perovskites via 2D cation engineering for all-perovskite tandem solar cells with improved efficiency and stability

All-perovskite tandem solar cells are promising for achieving photovoltaics with power conversion efficiencies above the detailed balance limit of single-junction cells, while retaining the low cost, light weight and other advantages associated with metal halide perovskite photovoltaics. However, the efficiency and stability of all-perovskite tandem cells are limited by the Sn-Pb-based narrow-bandgap perovskite cells. Here we show that the formation of quasi-two-dimensional (quasi-2D) structure (PEA) 2 GAPb 2 I 7 from additives based on mixed bulky organic cations phenethylammonium (PEA+) and guanidinium (GA+) provides critical defect control to substantially improve the structural and optoelectronic properties of the narrow-bandgap (1.25 eV) Sn-Pb perovskite thin films. Additionally, this 2D additive engineering results in Sn-Pb-based absorbers with low dark carrier density (~1.3 x 10 14 cm -3 ), long bulk carrier lifetime (~9.2 us) and low surface recombination velocity (~1.4 cm s -1 ), leading to 22.1%-efficient single-junction Sn-Pb perovskite cells and 25.5%-efficient all-perovskite two-terminal tandems with high photovoltage and long operational stability.

14 SOLAR ENERGY↗

Identification and Testing of Electric Vehicle Fast Charger Cybersecurity Mitigations

Fast-charging infrastructure for electric vehicles (EVs) is needed to enable and achieve the national goals of transitioning the vehicle fleet toward more electrification. Idaho National Laboratory, Oak Ridge National Laboratory, and the National Renewable Energy Laboratory (NREL) have jointly worked to identify, evaluate, and mitigate potential cyber-related consequences associated with fast charger systems. NREL contributed by considering cyberattack scenarios and consequences associated with integrating distributed energy resources (DERs) at fast-charging stations. The dynamic nature of fast-charger load profiles would encourage site operators to incorporate solar for energy cost reduction and energy storage for peak demand cost management at future charging facilities with multiple fast chargers at a site. These energy resources would be monitored and coordinated via a site energy management controller with data exchange between devices and local power metering infrastructure; thus, networking between devices and the design of the system becomes important in the overall cybersecurity posture. In addition, component vendors and system operators might have remote interfaces to any of these systems. It is therefore important to understand the breadth of the cyberattack surface and potential strategies to mitigate impacts. This project has focused on components and protocols expected to be found within a local charging site that includes multiple chargers and DER resources. Our methods and results are summarized in this final report.

42 ENGINEERING↗

Direct recycling of spent nickel-rich cathodes in reciprocal ternary molten salts

Lithium-ion batteries (LIBs) have revolutionized portable electronics and electric vehicles (EVs), but the growing accumulation of end-of-life (EOL) batteries poses environmental challenges. Recycling high-value cathodes from EOL LIBs can minimize waste and reduce the need for mining critical minerals. Here, this study focuses on the direct recycling of Ni-rich cathodes, particularly lithium-manganese-cobalt-oxide (NMC) 622 in a “reciprocal ternary molten salts (RTMS)" system. The ionothermal relithiation in the RTMS system successfully restores the layered structure, lithium content, and electrochemical performance of the NMC 622 cathode, comparable to the pristine material. The cost analysis reveals that cathode regeneration through ionothermal relithiation is more economical than virgin production or conventional recycling methods.

25 ENERGY STORAGE↗

Stochastic GW -GPU: Rapid Quasi-Particle Energies for Molecules beyond 10,000 Atoms

StochasticGW is a code for computing accurate quasi-particle (QP) energies of molecules and material systems in the GW approximation. StochasticGW utilizes the stochastic Resolution of the Identity (sROI) technique to enable a massively parallel implementation with computational costs that scale semilinearly with system size, allowing the method to access systems with tens of thousands of electrons. Here, we introduce a new implementation, StochasticGW-GPU, for which the main bottleneck steps have been ported to GPUs and give substantial performance improvements over previous versions of the code. We showcase the new code by computing band gaps of hydrogenated silicon clusters (Si x H y ) containing up to 10,001 atoms and 35,144 electrons, and we obtain individual QP energies with a statistical precision of better than ±0.03 eV with times-to-solution of less than 1 h.

Thomas, Phillip S. [Lawrence Berkeley National Lab↗

Development and transferability of neural-network models for plasma-surface interactions

Plasma-surface interactions are increasingly critical to modern technologies; yet, accurate molecular dynamics simulations remain limited by the capabilities of interatomic potentials. Deep Potentials (DPs) promise to revolutionize the field by providing a systematic method for producing accurate interatomic potentials. The primary challenge of DP development is selecting a dataset, which efficiently spans the set of atomic environments one expects to encounter in the subsequent molecular dynamics simulations. The computational cost of density functional theory calculations, which are the typical basis for DP development, makes it impossible to directly verify the quality of a given DP. To address this challenge, we explore the development of a deep-learned interatomic potential, “DeepREBO,” trained to reproduce the behavior of the REBO2 empirical potential, enabling direct validation of training methodology and transferability. Using an active learning framework, we begin with a minimal dataset and iteratively expand it to train a Deep Potential-Smooth Edition model that faithfully reproduces REBO2 results for 25 eV hydrogen bombardment of diamond (001), a particularly challenging case. We show that small, carefully curated datasets can outperform large, unguided ones, with effective models requiring fewer than 15 000 snapshots. Subsequent transferability tests demonstrate that while DeepREBO generalizes well to diamond (111) surfaces, performance degrades for amorphous carbon or higher-energy impacts, highlighting the need for use-case-specific training data. We also evaluate methods to improve short-range repulsion. This study outlines best practices for training robust deep potentials and underscores the importance of dataset design for predictive plasma simulations.

Ab-initio molecular dynamics↗

Excited States of Crystalline Point Defects with Multireference Density Matrix Embedding Theory

Accurate and affordable methods to characterize the electronic structure of solids are important for targeted materials design. Embedding-based methods provide an appealing balance in the trade-off between cost and accuracy-particularly when studying localized phenomena. Here, we use the density matrix embedding theory (DMET) algorithm to study the electronic excitations in solid-state defects with a restricted open-shell Hartree-Fock (ROHF) bath and multireference impurity solvers, specifically, complete active space self-consistent field (CASSCF) and n-electron valence state second-order perturbation theory (NEVPT2). In this work, we apply the method to investigate the electronic excitations in an oxygen vacancy (OV) on a MgO(100) surface and find absolute deviations within 0.05 eV between DMET using the CASSCF/NEVPT2 solver, denoted as CAS-DMET/NEVPT2-DMET, and the nonembedded CASSCF/NEVPT2 approach. Next, we establish the practicality of DMET by extending it to larger supercells for the OV defect and a neutral silicon vacancy in diamond where the use of nonembedded CASSCF/NEVPT2 is extremely expensive.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Long-life lithium-ion batteries realized by low-Ni, Co-free cathode chemistry

The increasing demand for lithium-ion battery-powered electric vehicles (EVs) has led to a surge in recent prices of strategic battery materials such as cobalt (Co) and nickel (Ni). While all EV makers are eager to eliminate Co usage, Ni has rapidly become another ‘pain point’ for the industry, as its price is nearing half that of Co. The sustainability issue facing both Ni and Co puts forward a grand materials challenge, that is, to reduce Ni content and eliminate Co while maintaining high specific energy and stability. Here in this work, a complex concentrated doping strategy is used to eliminate Co in a commercial NMC-532 cathode. The LiNi 0.5 Mn 0.43 Ti 0.02 Mg 0.02 Nb 0.01 Mo 0.02 O 2 cathode shows potential cost advantage with relatively high specific energy and significantly improved overall performance (~95% capacity retained after 1,000 cycles in pouch-type cells, 2.8–4.3 V vs graphite, at 1 C, 1.5 mA cm -2 ). Combining X-ray techniques and electron microscopy, we uncover the origins of the superior stability.

36 MATERIALS SCIENCE↗

Design and Comparison of Surface Inset Permanent Magnet Machine and Surface Permanent Magnet Machine without Heavy Rare Earth Magnets for Traction Applications

This paper presents two machine designs: a surface inset permanent magnet (SIPM) machine and a surface permanent magnet (SPM) machine, both without heavy rare-earth magnets, that achieve 50 kW/L active power density and a constant-power speed ratio of 3 for EV traction applications. Compared to surface PM machines, SIPM machines do not require a special containment sleeve to hold the magnets in place at high speeds, provided that the rotor laminations are carefully designed together with the magnet mounting configuration to ensure the rotor’s structural integrity. Comparisons between the SPM and SIPM machines sharing the same stator, same current level, and same power speed envelope are presented. Both deliver very similar performance characteristics, but the SIPM machine’s simpler magnet containment configuration may give it an advantage in terms of reduced material and manufacturing costs.

42 ENGINEERING↗

Suppression of phase separation in AlGaInAs compositionally graded buffers for 1550 nm photovoltaic converters on GaAs

We investigate strategies to suppress phase separation and reduce threading dislocation density (TDD) in AlGaInAs compositionally graded buffers (CGBs) that span the lattice constant range from GaAs to InP. Combining the results from high resolution x-ray diffraction, cathodoluminescence, transmission electron microscopy, and photovoltaic device measurements, we correlate the choices of epitaxial growth conditions with the defect structure of the CGBs and subsequent device performance. Both the use of substrates with high misorientation off (100) toward the (111)A plane and Zn doping instead of Si doping are shown to suppress phase separation and reduce TDD. We demonstrate a 0.74 eV GaInAs device grown on a GaAs substrate offcut 19.5° toward (111)A using a Zn-doped AlGaInAs CGB with TDD = 3.5 ± 0.2 × 10 6 cm -2 that has a bandgap-open circuit voltage offset of only 0.434 V measured under the AM1.5G solar spectrum. We characterized this device under high-intensity irradiance from a 1570 nm laser and measured a 31.9% peak laser power conversion efficiency at 3.6 W/cm 2 irradiance. These results provide a roadmap to the manufacture of laser- and thermal-power conversion devices with the performance and cost-effectiveness needed to drive adoption of these technologies at scale.

14 SOLAR ENERGY↗

A Reverse Logistics Tool For Ev Battery Recycling And Repurposing,

The demand for electric vehicles (EVs) in the United States is projected to rise significantly, with sales expected to reach approximately 4.1 million units by 2030. However, the U.S. remains heavily reliant on imports for the batteries and critical raw materials—such as lithium, cobalt, and nickel—that power these vehicles. As of 2024, around 70% of these imports originate from China. This dependency has become even more precarious following China’s imposition of export restrictions in April 2025, a retaliatory move against U.S. tariffs. These developments highlight the strategic vulnerabilities posed by China’s dominant position in the critical materials market. Compounding the issue, decades of intensive extraction have severely depleted global reserves of critical materials, widening the gap between supply and growing demand. This situation underscores the urgent need for the U.S. and other nations to diversify their sources of critical materials and enhance domestic capabilities to secure these resources—an essential step toward ensuring long-term energy security. At the end of their lifecycle—whether due to the battery’s degradation or the retirement of the vehicle—EV batteries are often improperly disposed of or sent to landfills. However, many of these batteries still retain usable capacity and can follow one of three alternative pathways: (a) Re-used: deployed in another vehicle with a shorter driving range, (b) Re-purposed: utilized act as a backup storage/power for data centers, solar panels, and e-scotters or (c) Recycled: broken down to recover the critical materials. To that end, the proposed tool (REBORN) is designed to optimize the reverse logistics network for battery repurposing and recycling. Its goal is to minimize associated costs while identifying optimal locations for battery collection and processing. Ultimately, REBORN ensures that each battery is used to its fullest potential.

Srinivas, SrikarV. [Idaho National Laboratory (INL↗

Assessing Customer Experience and Business Models around Price-to-Device Communication and Smart Control Pathways in CalFlexHub

California is facing three major challenges in electrical grid operation: renewable overgeneration, steep evening ramping, and growing peak demand. The state has identified dynamic retail price response as a key strategy evidenced by CPUC’s Dynamic Rates proceeding and CEC’s Load Management Standards. Furthermore, the CEC launched a $16M “California Load Flexibility Research and Deployment Hub (CalFlexHub)” administered by Berkeley Lab to accelerate price-response flexible load technologies in buildings and EV charging. There are more than 16 laboratory and field demonstration projects in CalFlexHub, each demonstrating innovative automated price-response technologies. CalFlexHub tests various pathways through which hourly price signals and triggered control commands are communicated to load-flexible devices such as smart thermostats, heat pumps, water heaters, and EVs. We identified seven unique communication and control pathways, which involve combinations of third-party cloud, device OEM’s cloud, building central gateway, and local controller in between the price server and the load-flexible devices. It is important for utilities and policy makers to understand the long-term implications of each pathway in designing future programs and creating related policies and mandates for market transformation. We propose an evaluation framework including the following aspects: ● Functionality: connectivity and uptime, resilience, and optimization; ● Customer experience: simplicity in setup, troubleshooting support, continuity, customer choice, first cost, and ongoing cost; ● Business model and scalability: advance interoperability, holistic solution, bridge unique gap, customer base, and value streams and pricing structures. In this paper, we identify emerging business models associated with each communication pathway and discuss their positive features and challenges from the above aspects.

Liu, Jingjing↗

Transportation and electricity systems integration via electric vehicle charging-as-a-service: A review of techno-economic and societal benefits

Here, in support of global decarbonization efforts, the adoption of electric vehicles is proceeding rapidly across transportation sectors, population groups, and regions. However, access to electric vehicle charging infrastructure remains sparse and inequitable, and technical, economic, and procedural challenges have encumbered its expansion. Charging-as-a-service, which can mitigate cost and effort risks of charging equipment ownership, adds a means of meeting many of these challenges. As charging-as-a-service has not been analyzed or addressed in the scholarly literature, we synthesize media, marketing, and analogous scholarly publications to categorize and describe the functions asserted by existing charging-as-a-service vendors. We demonstrate and quantify the benefits of many of these functions via four example business cases, sited at a detached residence, a multi-unit dwelling, a consumer-facing business, and a commercial fleet depot. Outcomes show that savings and revenues realized via charging-as-a-service can reduce charging costs, beneficially shape grid loads, and make charging installation economical where it otherwise would not be. Discussion highlights the need to deploy charging-as-a-service in cooperation with initiatives promoting societal benefits, including charging access equity.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗