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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 217 records · Page 12

Characterizing Electrode Materials and Interfaces in Solid-State Batteries

Solid-state batteries (SSBs) could offer improved energy density and safety, but the evolution and degradation of electrode materials and interfaces within SSBs are distinct from conventional batteries with liquid electrolytes and represent a barrier to performance improvement. Over the past decade, a variety of imaging, scattering, and spectroscopic characterization methods has been developed or used for characterizing the unique aspects of materials in SSBs. These characterization efforts have yielded new understanding of the behavior of lithium metal anodes, alloy anodes, composite cathodes, and the interfaces of these various electrode materials with solid-state electrolytes (SSEs). This review provides a comprehensive overview of the characterization methods and strategies applied to SSBs, and it presents the mechanistic understanding of SSB materials and interfaces that has been derived from these methods. This knowledge has been critical for advancing SSB technology and will continue to guide the engineering of materials and interfaces toward practical performance.

25 ENERGY STORAGE↗

From Powder to Power: Tailored Pre-Milling Strategy that Optimizes Microstructure for Efficient Hydrogen Evolution

The hydrogen evolution reaction (HER) plays a critical role in enabling large-scale electrolytic hydrogen production and advancing future technologies and fuel production. Among non-precious metals, NiMo-based catalysts are particularly attractive due to their capability to promote both water dissociation and hydrogen adsorption in alkaline media. However, conventional NiMo catalysts often suffer from incomplete alloying, particle aggregation, weak metal–support interactions, and surface oxidation, which significantly limit active site utilization, electronic conductivity, and long-term stability. Herein, we report a scalable, solid-state, two-step ball milling strategy for constructing an efficient NiMo/C catalyst for the HER. Pre-milling the metal precursors prior to carbon incorporation promotes efficient solid-state activation, leading to the formation of uniformly alloyed, ultrafine, and defect-rich Ni–Mo nanoparticles with robust metal–carbon interfacial anchoring. Benefiting from this integrated structural design, the optimized NiMo/C catalyst exhibits low overpotentials and Tafel slopes, reduced charge-transfer resistance, and excellent durability under alkaline conditions. Comprehensive structural and surface analysis reveal that the enhanced HER performance can be attributed to the synergistic interplay of homogeneous Ni–Mo alloying, uniform nanoparticle dispersion on a defect-rich carbon scaffold, enhanced accessibility of catalytically active sites, and optimized electronic coupling that stabilizes the catalyst surface. This work highlights the two-step solid-state ball milling strategy as a simple, robust, and scalable route for the preparation of effective and durable non-precious metal HER electrocatalysts, offering practical insights toward large-scale and inexpensive hydrogen production.

Yang, Xiaoxuan [Oak Ridge National Laboratory (ORN↗

ZENN: A thermodynamics-inspired computational framework for heterogeneous data–driven modeling

Traditional entropy-based methods—such as cross-entropy loss in classification problems—have long been essential tools for representing the information uncertainty and physical disorder in data and for developing artificial intelligence algorithms. However, the rapid growth of data across various domains has introduced new challenges, particularly the integration of heterogeneous datasets with intrinsic disparities. To address this, we introduce a zentropy-enhanced neural network (ZENN), extending zentropy theory into the data science domain via intrinsic entropy, enabling more effective learning from heterogeneous data sources. ZENN simultaneously learns both energy and intrinsic entropy components, capturing the underlying structure of multisource data. To support this, we redesign the neural network architecture to better reflect the intrinsic properties and variability inherent in diverse datasets. We demonstrate the effectiveness of ZENN on classification tasks and energy landscape reconstructions, showing its superior generalization capabilities and robustness-particularly in predicting high-order derivatives. In image and text classification tasks, ZENN demonstrates superior generalization by introducing a learnable temperature variable that models latent multisource heterogeneity, allowing it to surpass state-of-the-art models on CIFAR-10/100, BBC News, and AG News. As a practical application in materials science, we employ ZENN to reconstruct the Helmholtz energy landscape of Fe3Pt using data generated from density functional theory and capture key material behaviors, including negative thermal expansion and the critical point in the temperature–pressure space. Overall, this work presents a zentropy-grounded framework for data-driven machine learning, positioning ZENN as a versatile and robust approach for scientific problems involving complex, heterogeneous datasets.

36 MATERIALS SCIENCE↗

Generalized Cycle Benchmarking Algorithm for Characterizing Midcircuit Measurements

Midcircuit measurements (MCMs) are crucial ingredients in the development of fault-tolerant quantum computation. While there have been rapid experimental progresses in realizing MCMs, a systematic method for characterizing noisy MCMs is still under exploration. In this work, we develop a cycle benchmarking (CB)-type algorithm to characterize noisy MCMs. The key idea is to use a joint Fourier transform on the classical and quantum registers and then estimate parameters in the Fourier space, analogous to Pauli fidelities used in CB-type algorithms for characterizing the Pauli-noise channel of Clifford gates. Furthermore, we develop a theory of the noise learnability of MCMs, which determines what information can be learned about the noise model (in the presence of state preparation and terminating measurement noise) and what cannot, which shows that all learnable information can be learned using our algorithm. As an application, we show how to use the learned information to test the independence between measurement noise and state-preparation noise in an MCM. Finally, we conduct numerical simulations to illustrate the practical applicability of the algorithm. Similar to other CB-type algorithms, we expect the algorithm to provide a useful toolkit that is of experimental interest. Published by the American Physical Society 2025

Zhang, Zhihan (ORCID:0009000862907691)↗

New Advances in Optical Stochastic Cooling

Recently, Optical Stochastic Cooling (OSC) became the first demonstrated method for ultra-high-bandwidth stochastic cooling. The initial experiments at Fermilab’s IOTA ring explored the essential physics of the method and demonstrated cooling, heating and manipulation of beams and single particles. Having been validated in practice, with continued development, OSC carries the potential for dramatic advances in the state-of-the-art performance and flexibility for beam cooling and control. The ongoing program at Fermilab is now focused on the development of an OSC system that includes high-gain optical amplification, which promises a two-order-of-magnitude increase in the strength of the OSC force. In this talk, we briefly review the results of the initial experimental campaign, describe the status of the conceptual and hardware designs for the amplified OSC system, report initial experimental results of our high-gain amplifier development, and explore near-term operational plans and use cases.

43 PARTICLE ACCELERATORS↗

The Optical Stochastic Cooling Program at Fermilab

Recently, Optical Stochastic Cooling (OSC) became the first demonstrated method for ultra-high-bandwidth stochastic cooling. The initial experiments at Fermilab’s IOTA ring explored the essential physics of the method and demonstrated cooling, heating and manipulation of beams and single particles. Having been validated in practice, with continued development, OSC carries the potential for dramatic advances in the state-of-the-art performance and flexibility for beam cooling and control. The ongoing program at Fermilab is now focused on the development of an OSC system that includes high-gain optical amplification, which promises a two-order-of-magnitude increase in the strength of the OSC force. Here we review the progress and plans for the amplified OSC program. This includes detailed lattice designs and tracking simulations for the various experimental configurations, designs and status for the various hardware systems, and near-term operational plans and use cases.

Jarvis, J. [Fermilab]↗

A Regional Approach to Offshore Wind Energy Manufacturing in the Central Atlantic: Workforce

Meeting the additional job requirements spurred by potential growth in the offshore wind industry is likely to involve intentional and effective recruitment practices and training program development across all occupations (e.g., skilled trades, engineers, professionals) at state, regional, and local levels. The workforce development ecosystem is complex, especially for an industry like offshore wind, so assessing the readiness of an area to support the workforce needs of new manufacturing facilities involves evaluating numerous economic and training factors at an occupational level. Funded by the National Offshore Wind Research and Development Consortium and led by the National Renewable Energy Laboratory, this report represents one part of a two-part study that explores the challenges and opportunities for Delaware, Maryland, Virginia, and North Carolina in fostering regional collaboration to build a domestic supply chain for the U.S. offshore wind energy sector.

17 WIND ENERGY↗

Best Practices for Grid Communications

As the grid evolves, the communications architecture will need to evolve with it. That architecture affords a structured means by which the evolving complexities of the modern electric grid can be managed. This document provides best practices that can be implemented in the grid of today and evolve towards the grid and grid architecture of the future. The evolving grid and its control communications increasingly rely on commercial communications providers and a variety of technologies, from wireless (e.g., 5G, microwave, Wi-Fi) to wireline (fiber, copper) to radio communications (P25, other repeater-based systems), and all these communications systems rely on electric power. A reliable and resilient grid must account for this complex set of interdependencies in its planning activities, especially those involving restoration and recovery. The participation of all relevant parties in both planning and exercising of plans can prevent unexpected conditions that impede the reliable operation and recovery of the grid. Best practices for grid communications include using a Network Management System to document the operational state, define and monitor baselines, detect changes, and accelerate response to abnormalities. If transitioning from SONET to IP/packet-based systems, translating grid requirements into communications requirements for latency, bandwidth and throughput, IP packet delay variation, packet loss, and availability should inform and drive technology planning and selection as well as that communication system’s Quality of Service (QoS) policies and Service Level Agreements (SLAs). Secure and reliable timing is another key component of a reliable and resilient grid that can operate through adverse events. A trusted internal NTP configuration, an integrated and diverse timing delivery system, optimizing the timing architecture based on the transport technologies of the communications system, and using established standards can deliver the level of timing accuracy required by a range of time-sensitive power system applications.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Direct reactions for astrophysical p-capture rates with ORRUBA and GODDESS

Understanding the nucleosynthesis and energy generation in quiescent and explosive stellar burning requires a detailed understanding of reaction rates on many unstable nuclides. Such reaction rates are often governed by the properties of low-lying, isolated proton resonances. Though direct measurements of resonance strengths are ultimately desired, and are a focus of rare isotope beam facilities worldwide, such tour-de-force experiments must be guided by indirect techniques, in order to know resonance energies, J π assignments, and estimated widths, to inform targeted measurements. Furthermore, some important low-lying resonances may be too weak for direct measurements with radioactive beams, and indirect techniques provide the only practical constraints. Additionally, there has been growing interest in the astrophysical role of isomeric states, which can influence the reaction flow in nucleosynthetic reaction networks, and hence impact the quantitative interpretation of astronomical observables, such as γ-ray signatures, and elemental and isotopic ratios. Properties of single-proton resonances can be obtained by exploiting the selectivity of direct reactions, such as single-nucleon transfer and charge-exchange reactions. Constraining proton-capture rates via direct reactions has been a focus of the astrophysics program at ORNL for over two decades, spurring the development of the ORRUBA and GODDESS detector systems. Herein, a review of recent developments in instrumentation and radioactive beam delivery (including isomeric beam experiments) is presented, along with some specific examples of astrophysically interesting sd-shell nuclides, which have been a target of recent ORRUBA and GODDESS experiments.

79 ASTRONOMY AND ASTROPHYSICS↗

Time-Evolved Hetero-Alkali Interphases Enable Long-Life Sulfide-Based Anode-Free Solid-State Batteries

Sulfide-based anode-free solid-state batteries (AFSSBs) offer compelling advantages in terms of energy density and safety, yet their practical implementation is severely hindered by undesirable interfacial reactions between sulfide solid electrolytes (SEs) and freshly plated lithium (Li), as well as non-uniform Li plating/stripping behavior. Herein, an effective interfacial stabilization strategy by incorporating sodium bis(fluorosulfonyl)imide (NaFSI) additive into the Li5.4PS4.4Cl1.6 (LPSC) is investigated. Unlike conventional Li-based additives that form static passivation layers, NaFSI introduces a transient hetero-alkali chemistry that kinetically governs interphase evolution during fresh Li plating. NaFSI induces a timesequenced interphase evolution: an initial NaF/LiF-rich layer that suppresses early sulfide reduction, followed by a LiF/Li3N-rich layer that optimizes Li⁺ transport during repeated anode-free cycling. This evolved robust and fast ion conducting layer mitigates interfacial impedance growth, enhances Li + transport kinetics, and suppresses localized Li growth and filamentary shorting. As a result, the anode-free full cell with NaFSI modified LPSC as the interlayer exhibits an excellent cycling stability over 500 cycles at 0.2 C with a capacity retention of 77.6%, whereas the cell with bare LPSC suffers from rapid capacity decay after 100 cycles, retaining only 32.1% of its initial capacity. This work establishes dynamic heteroalkali additive chemistry as a general strategy to kinetically program solid-solid interphases, guiding the interface design in anode-free solid-state batteries.

25 ENERGY STORAGE↗

Resilient Operation of Networked Community Microgrids with High Solar Penetration

This project, funded by the US Department of Energy’s Solar Energy Technologies Office (SETO), focused on the operation of microgrids as a coordinated network. The primary objective, which was successfully achieved, was to develop both control strategies and hardware solutions to support the resilient and efficient operation of networked microgrids with high solar penetration. The work was structured around the following four main tasks: • Development of distributed and scalable optimization algorithms for AC-coupled networked microgrids. • Design and implementation of a novel DC interconnection hardware to enable precise power exchange between microgrids. • Laboratory operational validation of the developed technologies using 480 V testbeds and commercially available hardware. • Field operational validation of the complete solution in Adjuntas, Puerto Rico, interconnecting two kW-scale, split-phase microgrids of Casa Pueblo’s microgrids. This project addressed multiple technical challenges across the domains of optimization, control, hardware interconnection, and protection. One of its key contributions was delivering tangible, real-world solutions for networking microgrids. In contrast to purely theoretical or simulation-based work, this project included full-scale hardware operational validation both in the lab and in the field. The work conducted as part of this project—in collaboration with the University of Puerto Rico; the University of Tennessee, Knoxville; the University of Central Florida; and Casa Pueblo—has advanced the state of the art in networked microgrids. Key contributions include the development of distributed control strategies, practical solutions for real-world implementation challenges, and the introduction of a novel DC interlink approach for microgrid interconnection. The project featured both laboratory and field validation using commercial off-the-shelf components. The field deployment successfully validated that a group of microgrids can operate in a coordinated manner, enabling precise power flow between systems and mutual support during extreme events. This project resulted in 15 journal publications and 15 conference papers; 5 graduate students and 15 undergraduate students were supported. The codes of distributed optimization and forecasting were made open-source through OSTI.gov for distributed optimization and forecasting. All the publications are available in the ORNL-hosted project landing page. The DC interlink with state-of-charge balancing control was operationally validated in Adjuntas by interconnecting two real-world, 240 V split-phase microgrids. To the best knowledge of the team, this represents the first operational validation of AC microgrids interconnected via DC-interlinks. As a culmination of this project, a follow-on grant was awarded to support the technology transfer of the distributed optimization framework to a commercial microgrid controller, Stellar Edge, developed by the California-based company New Sun Road.

14 SOLAR ENERGY↗

Innovative Symmetrical Electrolyte Architecture Enables Ultra-Flat and Thermal Resilient Protonic Ceramic Electrochemical Cells

Protonic ceramic electrochemical cells (PCECs) represent a promising class of solid‐state energy conversion devices capable of high‐efficiency hydrogen production and power generation. However, the practical deployment of planar PCECs is fundamentally constrained by severe structural deformation and mechanical failure during fabrication, stemming from asymmetric shrinkage between the thin electrolyte and the thick NiO‐based support layer. Here, in this work, a functionally integrated, symmetry‐engineered double‐sided electrolyte (DE) design is unveiled, which not only suppresses thermally induced curvature but also unlocks significant gains in electrochemical performance and stability. This architecture intrinsically balances shrinkage dynamics across the cell bilaterally, enabling the fabrication of ultra‐flat 5 × 5 cm 2 cells with sub‐100 µm thickness variation. A numerical solid mechanics simulation is introduced to investigate and interpret this achievement. Beyond structural advantages, the DE configuration enhances the cell operational stability, delivering a low open‐circuit voltage degradation of 9.5 mV/100 h across 80 thermal cycles. This work establishes a compelling paradigm wherein architectural symmetry directly translates to both mechanical fidelity and functional enhancement, offering a promising route toward PCECs scale‐up.

08 - HYDROGEN↗

Methods for Quantitative Thermal Analysis of Lithium Solid-State and Beyond Battery Safety

The use of differential scanning calorimetry (DSC) to measure the thermal behavior of individual components and electrolyte/electrode combinations is common. However, here we focus on DSC tests on an anode, cathode, and electrolyte (ACE) component combination over a temperature range that includes many of the phase transitions and key reactions (i.e., to 500 °C) that contribute to thermal runaway. This method can help quantify the complex reaction network in a full cell, thereby informing potential safety issues. Here, we used DSC heat flow data from a solid-state Li 0.43 CoO 2 +C+PVDF | LLZO | Li metal ACE sample and its components to quantify key factors affecting results. We focused on three areas: (1) ACE sample preparation and assembly in DSC pans, (2) DSC measurement parameters, and (3) heat flow analysis. Key points include the choice of component ratios (e.g., commercially relevant N:P capacity ratio), the importance of conductive carbon and binder, type of pan used, DSC ramp rate, and integration method used when dealing with broad and overlapping exothermic peaks. This work deepens the scientific basis and best practices for obtaining heat flow data from ACE samples for early-stage evaluation of solid-state and beyond battery safety.

25 ENERGY STORAGE↗

Unveiling phase evolution of complex oxides toward precise solid-state synthesis

The precise synthesis of high-purity materials is crucial in accelerating materials discovery. However, the lack of theoretical understanding and practical guidance poses challenges, particularly for materials with compositional and structural complexity. Here, we propose a feasible principle toward synthesizing complex inorganic solids. This principle involves the introduction of an inducer that induces crucial intermediates, which in turn guide the synthesis pathway toward the target materials through structural templating, named inducer-facilitated assembly through structural templating (i-FAST). We validate this principle with three distinct oxides: garnet Li6.5La3Zr1.5Ta0.5O12, perovskite BaCo0.8Sn0.2O3, and pyrochlore Gd1.5La0.5Zr2O7. This structural templating approach enables synthesis along predesigned pathways, forming intermediates that are thermodynamically favored for prior formation and kinetically preferred for the final product, resulting in precisely synthesizing high-purity target materials. This study not only represents a substantial advancement in comprehending the interplay between thermodynamics/kinetics and phase evolution in complex solid synthesis but also provides an effective strategy for guiding exploratory solid-state synthesis.

Yang, Lin↗

Symmetry-protected electronic metastability in an optically driven cuprate ladder

Optically excited quantum materials exhibit non-equilibrium states with remarkable emergent properties, but these phenomena are usually transient, decaying on picosecond timescales and limiting practical applications. Advancing the design and control of non-equilibrium phases requires the development of targeted strategies to achieve long-lived, metastable phases. Here, in this study, we report the discovery of symmetry-protected electronic metastability in the model cuprate ladder Sr 14 Cu 24 O 41 . Using femtosecond resonant X-ray scattering and spectroscopy, we show that this metastability is driven by a transfer of holes from chain-like charge reservoirs into the ladders. This ultrafast charge redistribution arises from the optical dressing and activation of a hopping pathway that is forbidden by symmetry at equilibrium. Relaxation back to the ground state is, hence, suppressed after the pump coherence dissipates. Our findings highlight how dressing materials with electromagnetic fields can dynamically activate terms in the electronic Hamiltonian, and provide a rational design strategy for non-equilibrium phases of matter.

36 MATERIALS SCIENCE↗

A Practical Probabilistic Benchmark for AI Weather Models

Since the weather is chaotic, it is necessary to forecast an ensemble of future states. Recently, multiple AI weather models have emerged claiming breakthroughs in deterministic skill. Unfortunately, it is hard to fairly compare ensembles of AI forecasts because variations in ensembling methodology become confounding and the baseline data volume is immense. We address this by scoring lagged initial condition ensembles—whereby an ensemble can be constructed from a library of deterministic hindcasts. This allows the first parameter‐free intercomparison of leading AI weather models' probabilistic skill against an operational baseline. Lagged ensembles of the two leading AI weather models, GraphCast and Pangu, perform similarly even though the former outperforms the latter in deterministic scoring. These results are elaborated upon by sensitivity tests showing that commonly used multiple time‐step loss functions damage ensemble calibration.

54 ENVIRONMENTAL SCIENCES↗

Modulating Oxide‐Based Quantum Materials by Ion Implantation

Ion implantation has emerged as a powerful tool for manipulating and investigating oxide quantum materials, where strong electron correlations give rise to exotic phases and functionalities. This Review examines how controlled ion bombardment enables targeted modulation of structural, electronic, and magnetic properties in complex oxides. Recent advances in ion beam techniques is analyzed that provide unprecedented control over defect profiles, from point defects to extended damage cascades. In application, ion irradiation has demonstrated the ability to tune quantum phenomena including metal‐insulator transitions, magnetism, and superconductivity through selective doping, defect creation, and lattice strain. The ability to write quantum states with nanoscale precision using focused ion beams is opening new paths for quantum device fabrication. Challenges in understanding radiation damage mechanisms in strongly correlated systems is discussed, and identify opportunities for designing quantum functionality through defect‐engineering approaches. The technique's demonstrated capability to write quantum states with nanoscale precision, combined with its compatibility with existing semiconductor processing infrastructure, suggests a clear pathway for translating fundamental discoveries in quantum materials into practical technological applications.

defect engineering↗

Enhancing the mass resolving power of FRIB’s proposed high-voltage MR-ToF mass separator and spectrometer: Addressing non-ideal conditions

Multi-reflection time-of-flight mass separators and spectrometers (MR-ToF MSs) are indispensable tools at radioactive ion beam (RIB) facilities. These electrostatic ion beam traps act as highly selective mass separators and high-precision mass spectrometers for rare and exotic nuclei. When well-tuned and designed to minimize higher-order flight-time aberrations, state-of-the-art MR-ToF MSs approach, and slightly exceed, mass resolving powers of m/Δm = 10 6 . Achieving m/Δm ≥ 3 ⋅ 10 6 would provide the ability to resolve > 90 % of all known isomeric states with half-lives above 10 ms. However, the ability to mass separate in all practical setups is limited by non-ideal conditions which place such resolving powers out of reach. Here, to this end, we present a simulated analysis of these conditions in the newly proposed high-voltage MR-ToF MS for the Facility for Rare Isotope Beams (FRIB). It is expected to store ions at 30 keV beam energy and increase ion throughput by two orders of magnitude compared to current devices. Existing efforts to mitigate the effects of non-ideal conditions employed for current MR-ToF devices storing ions at < 3 keV beam energy will already enable mass resolving powers approaching 10 6 for FRIB’s high-voltage MR-ToF device. Simulations of newly proposed mitigation strategies show that even mass resolving powers approaching 10 7 might become feasible.

Electrostatic ion beam traps↗