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772 records · Page 37

STANDARD REFERENCE MATERIAL CHARPY TESTING FROM HIGH FLUENCE SURVEILLANCE CAPSULE

The Palisades Nuclear Generating Station included in its original surveillance program a surveillance capsule, designated A-60. The capsule was removed from its surveillance position in early 1995 and has been resident in the spent fuel pool since that time. It was harvested to perform characterization of surveillance specimens in this capsule in 2023. This capsule was irradiated to a fluence of 1.96x1020 n/cm2 (E> 1MeV) that is equivalent for more than 150 effective full power years for the current US reactor pressure vessel (RPV) fleet. This capsule contained several materials, including Charpy specimens of standard reference material (SRM) from Heavy-Section Steel Technology (HSST) A533-B Plate 01. To perform Charpy testing of this highly irradiated material, the new Charpy specimen transfer system was designed and implemented on Charpy impact testing machine in the hot cell to accommodate remote testing of these specimens. This new transfer system includes integrated environmental chamber to cool or heat Charpy specimens to the desired temperature. Testing of this highly irradiated material revealed very large shift of Charpy transition temperature, 188oC.

Sokolov, Mikhail [ORNL] (ORCID:0000000256373346)

Activity-induced migration of viscous droplets on a solid substrate

Active matter exploits motion to induce changes in shape and conformation via external input. Here, in this paper, we establish theoretically that viscous liquid droplets containing magnetic nanoparticles with frozen-in magnetic moments, sitting on a solid substrate and surrounded by an ambient gas phase, can deform and migrate under the influence of a magnetic torque. The effect arises because the collective rotation of the magnetic nanoparticles at the liquid–gas interface tilts the droplet away from a symmetric configuration, breaks the reflection symmetry with respect to the centre axis, and leads to a left–right asymmetry of the contact angles. A sufficiently strong magnetic torque leads the contact angles to overcome hysteresis effects leading the droplet to migrate. We develop a general framework to explain how symmetry-breaking affects droplet migration. Thus previous results of droplet spreading and migration can be recovered as special cases. Such droplets can be employed as agents in active surfaces and can move against gravity, chemical and thermal gradients, providing a mechanism that could be utilized by both industry and medicine.

Aggarwal, A. [Northwestern Univ., Evanston, IL (Un

Low-Temperature Gold Deposition Improves CdTe Back Contacts

Improved back contacts can benefit CdTe photovoltaics (PV). In this work, Cd(Se,Te) PV absorbers are cooled during Au evaporation to thermally quench a chemical reaction occurring between gold and CdTe and the generation of a reaction product that lowers device efficiency. Reducing substrate temperature enhances PV power conversion efficiency via open-circuit voltage and fill factor increases. X-ray photoelectron spectroscopy (XPS) reveals that lower temperature also reduces chemical perturbations of the CdTe, potentially linking back contact formation to a CdTe degradation product that hinders PV performance. Comparing reaction enthalpy and substrate heating energy shows that back contact formation by sputtering elemental metals onto ZnTe may exhibit a degradation pathway analogous to that of CdTe/Au reported here. Degradation-diminishing contact formation processes are therefore of general interest for optoelectronic devices, and the reduced substrate temperature in this study is one example.

14 SOLAR ENERGY

Feedback, physics, and forecasts: The emerging paradigm of machine learning-driven battery research

Machine learning (ML) is reshaping how we understand, predict, and optimize electrochemical systems. In batteries, ML accelerates discovery across chemistry, design, and operation by transforming massive experimental and simulated datasets into predictive, interpretable models. This review consolidates a decade of progress in ML-driven battery innovation, from early-cycle feature extraction to operando image analysis and physics-informed modeling. We categorize approaches by data domain and physical fidelity, emphasizing interpretable ML for diagnostics, reinforcement learning for control, and multi-objective optimization for lifetime extension strategies. Additionally, we demonstrate how integrated models accelerate discovery, reduce testing time, and guide sustainable design. Economic analyses furthermore illustrate how these advances can lower cost per cycle and improve circularity. Together, these developments chart a path toward self-optimizing, sustainable battery technologies.

artificial intelligence

Trajectory-independent speed limits for controlled open quantum systems

Existing quantum speed limits for controlled open quantum systems depend on the specified trajectory. For example, lower bounds on quantum annealing times in the presence of dissipation depend explicitly on the chosen annealing schedule. Recently, schedule-independent speed limits have been derived for annealing in the closed quantum system setting [L. P. García-Pintos et al ., SciPost Phys. 18 , 159 (2025)]. In this work, we generalize these results to open quantum systems, deriving schedule-independent lower bounds for quantum annealing times in systems described by a Lindblad master equation. We analyze the interplay between coherent control and dissipation in single- and two-qubit examples, demonstrating that the derived lower bounds capture key scaling behavior with respect to the strength of the dissipator. Finally, we apply the bound to thermal state preparation and show that the bound matches the expected asymptotic behavior for an Ising model in the high-temperature limit.

open quantum systems & decoherence

Propane Activation on Pt Electrodes at Room Temperature: Quantification of Adsorbate Identity and Coverage

Abstract C−H bond activation is the first step in manufacturing chemical products from readily available light alkane feedstock and typically proceeds via carbon‐intensive thermal processes. The ongoing emphasis on decarbonization via electrification motivates low‐temperature electrochemical alternatives that could lead to sustainable chemicals production. Platinum (Pt) electrocatalysts have shown activity towards reacting alkanes; however, little is known about propane electrocatalytic activation and conditions suitable for enabling selective oxidation to valuable products. Herein, we utilize a combination of electrochemical mass spectrometry (ECMS) and density functional theory (DFT) calculations to elucidate the potential dependence of propane activation on Pt electrocatalysts. Results show a strong dependence of adsorption on the applied potential in room‐temperature aqueous acidic electrolyte, with a maximum coverage of propane‐derived adsorbates at 0.30 V vs RHE. Using charge deconvolution and deuterated experiments, the mechanism of adsorption was elucidated, and C 3 H 2 * was determined as the average dehydrogenated propane‐derived adsorbate species. DFT calculations further corroborate these results, showing that the formation of deeply dehydrogenated species is energetically accessible at room temperature. The combined theoretical and experimental findings yield insights for selective activation of paraffinic C−H bonds at room temperature, aqueous conditions—a critical step towards decarbonized chemical manufacturing.

Chemistry

Phase stability in the Hf-N and Zr-N systems

Hf and Zr nitrides are promising compounds for many technologically important areas, including high-temperature structural applications, quantum computing, and solar and optical applications. Here, this article reports on a comprehensive first-principles statistical mechanics study of phase stability in the Hf-N and Zr-N binary systems. A high solubility of nitrogen in the hcp forms of Hf and Zr is predicted. The rocksalt forms of HfN and ZrN can also tolerate a high degree of off-stoichiometry through the introduction of nitrogen and metal vacancies. The Hf-N binary favors a family of stacking faulted parent crystal structures at intermediate nitrogen concentrations that host a unique form of short-range order among nitrogen interstitials and vacancies. These phases can accommodate some degree of configurational entropy and remain ordered to temperatures as high as 1200 K.

Monte Carlo methods

System for controller area network payload decoding

A system for decoding an unknown automotive controller area network (“CAN”) message definitions. CAN data vehicle signal mappings are typically held in secret and varied by automotive model and year. Without knowledge of the mappings, the wealth of real-time vehicle data hidden in the automotive CAN packets is uninterpretable—impeding research, after-market tuning, efficiency and performance monitoring, fault diagnosis, and privacy-related technologies. This system can ascertain the CAN signals' boundaries (start bit and length), endianness (byte ordering), signedness (binary-to-integer encoding) from raw CAN data. This allows conversion of CAN data to time series. Interpreting the translated CAN data's physical meaning and finding a linear mapping to standard units (e.g., knowing the signal is speed and scaling values to represent units of miles per hour) can be achieved for many signals by leveraging diagnostic standards to obtain real-time measurements of in-vehicle systems. The system can be integrated into lightweight hardware enabling an OBD-II plugin for real-time in-vehicle CAN decoding or run on standard computers. The system can output a standard DBC file with the signal definition information.

Verma, Kiren E.

Atomic- and Molecular-Scale Interphase Engineering for High-Performance Solid-State Batteries

Solid-state batteries (SSBs) promise a decisive advance beyond conventional Li-ion systems, yet their development remains constrained by persistent solid–solid interfacial instabilities that degrade performance and durability. Interfaces between solid electrolytes and both cathodes and Li metal often exhibit poor wettability, limited physical contact, and high charge–transfer resistance, leading to chemical decomposition, mechanical failure, and impedance growth. Overcoming these limitations requires interphase engineering with atomic-scale precision—capabilities that conventional coating methods cannot reliably deliver. Atomic layer deposition (ALD) and molecular layer deposition (MLD) uniquely meet this need by enabling ultrathin, conformal, and composition-tunable films that stabilize reactive surfaces, suppress parasitic reactions, and regulate Li-metal morphology. Importantly, this Perspective highlights ALD/MLD systems that have already demonstrated effectiveness in liquid-electrolyte cells and discusses how these validated strategies can be deliberately translated to solid-state architectures. By grounding future directions in experimentally proven concepts rather than speculative hypotheses, we outline how atomic- and molecular-scale design principles can accelerate the development of robust, high-performance SSB technologies.

atomic and molecular layer deposition

POWER ELECTRONICS GRID TIED SYSTEM FINAL REPORT

Across the country, electric utilities are grappling with the persistent hurdles of integrating Distributed Energy Resources (DERs). Managing these assets safely and effectively is a complex endeavor, complicated by varying ownership structures, management philosophies, and the diversity of the technologies themselves. Consequently, the industry has seen a proliferation of bespoke system designs, control strategies, and communication frameworks—forcing utilities to spend significant time and resources developing one-off integration solutions. This project addressed these integration hurdles through a scalable demonstration of intelligent devices designed to coordinate and control diverse resources in low-voltage applications. This concept minimized the need for complex integration by transforming the separate DERs into a dispatchable virtual power plant (VPP) with integrated resiliency functions (called a Node). By collaborating with a utility partner, the project focused on developing rapidly implementable use cases that bridged the gap between theoretical control and real-world deployment

99 GENERAL AND MISCELLANEOUS

Experimental observation and integrated modelling of proton-beryllium fusion in He and D plasmas at JET

Validated integrated modelling of JET ITER-like wall experiments in which fusion performance is driven by reactions between fast ions and intrinsically present metal wall impurities is presented. A steady-state L-mode plasma with dominant proton-beryllium fusion and neutron yields of up to ≈ 6·10 13 s -1 is developed in He and D, via radiofrequency heating of a H minority. The fusion drive is unambiguously confirmed by the neutral particle analyser, fast ion loss detector, and γ-ray diagnostics. Experiments are analysed via an integrated modelling framework, developed to model the two-stage proton beryllium-fusion chain and produce high-fidelity fusion product source terms. The modelling chain comprises TRANSP and JETTO for plasma core modelling, LOCUST for full orbit product tracking and collisional slowing-down, DRESS to resolve two- and three-body fusion kinematics, and MCNP for neutron transport calculations. Modelling shows that the primary 9 Be(p,n) 9 B reaction is the dominant neutron emitter at naturally present concentrations of beryllium in these experiments. The yield contribution of secondary reactions between fusion products and beryllium, 9 Be(d,n) 10 B and 9 Be(α,n) 12 C, is found to be negligible. The proton-deuteron knock-on effect in D plasmas is modelled, which is calculated to contribute ≈ 25% to the total neutron yield. For both He and D discharges the total computed neutron rates match fission chamber (FC) measurements within the combined experimental and computational uncertainty, with an average discrepancy of ≈ ± 20%. Realistic proton-beryllium neutron sources are propagated through JET’s MCNP neutron transport model which shows that 235 U FCs’ response is sensitive to p–Be source changes, with up to ≈ 10% variation compared to a D–D neutron source. We show that the high-energy tail of the fast proton minority can be studied with multi-foil neutron activation. The framework is also applied to the study of interactions between fast protons and boron impurities, of relevance to ITER. We calculate that in JET conditions a significant alpha source with DT-like energies could be generated through 11 B(p, α)2α fusion, and detected via γ-emission in secondary interactions between fast alphas and boron. The work represents an important step towards validating predictive integrated modelling capabilities for non-standard fusion reactions.

JET

Are CO2 batteries ready for the grid? A cross-cutting deployment checklist

Metal-CO2 batteries have attracted considerable research interest in the past decade due to the utilization of the greenhouse CO2 gas. The low cost and abundance of CO2 feedstocks, together with high specific capacity metal anodes, make this technology a promising candidate for electricity-demanding data centers and grids. However, nonstandard data reporting, ambiguous hardware designs, and questionable cycling parameters have emerged as the field has grown. A clear checklist and standardized reporting format for research and development are urgently needed. Here, after carefully re-analyzing 15 Na-CO2 and 9 Li-CO2 studies, we propose a general checklist and a flowchart for CO2 batteries and related gas conversion systems. Specific performance values from a deployment-oriented perspective, based on commercial lithium iron phosphate batteries, are integrated into the list. We frame research and development efforts around grid-relevant outputs, including areal rate and capacity, cyclability, gas utilization, and safety. While illustrated for Na- and Li-CO2 cells, this framework is directly transferable to other CO2 batteries and air/oxygen batteries, helping align benchtop demonstrations with systematic metrics that ultimately govern future deployment.

Wu, Wenda [ORNL] (ORCID:000900033307687X)

Heavy Element Spectroscopy in the Gas Phase

Actinides are inherently unstable and undergo nuclear decay processes with a concurrent release of energy. Consequently, they are used for nuclear power generation, nuclear weapons, and nuclear medicine. However, the radioactive decay processes also pose significant technological problems for the safe treatment and storage of spent nuclear materials. Cost-effective extraction of the actinides is the key first step in the remediation of nuclear waste, but the appropriate chemical means have yet to be determined. Our present understanding of the chemistry of actinides is limited, with the role of the 5f electrons posing a set of particularly challenging questions. The work reported here is focused on the use of electronic spectroscopy to probe the bonding of small molecules in the gas phase that contains thorium or uranium. Analyses of these data, carried out within the framework of ligand field theory, reveal clear evidence that the 5f electrons are spectators that retain their atomic metal ion character.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Integrated Approach to Post-Irradiation Examination of Nuclear Materials at Idaho National Laboratory

Idaho national Laboratory (INL) is the U.S. lead national laboratory for the Department of Energy’s Office of Nuclear Energy (DOE-NE), providing much of the nuclear research, development and demonstration capability needed to move nuclear innovation forward to deployment. INL’s Materials and Fuels Complex hosts a unique combination of personnel, facilities and infrastructure and offers the ability to perform post-irradiation examinations (PIE) of nuclear materials spanning multiple length scales. The ability to combine engineering-scale analysis and sub-microscopic characterization provides valuable insights into fuel and structural material behavior and degradation mechanisms. The holistic approach is used to accelerate these materials demonstration and deployment. Selected studies will be presented, highlighting the impact of these techniques on improving fuel reliability, safety, and efficiency, thereby advancing the development of sustainable and advanced nuclear energy technologies.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS

Microstructural Engineering of Cu-Rich Nanoprecipitate formation in NiCoFeCrCu0.12 High-Entropy Alloy via Severe Plastic Deformation for Enhanced Irradiation Tolerance

This study demonstrates a defect-engineering approach for controlling Cu-rich precipitates in FeNiCrCoCu0.2 high-entropy alloys (Cu-HEAs), delivering a novel pathway for next-generation nuclear reactor materials with superior irradiation resistance. This work establishes that severe plastic deformation (SPD) processing via Shear Assisted Processing and Extrusion (ShAPE) and Friction Stir Layer Deposition (FSLD) creates dense dislocation networks and subgrain boundaries that fundamentally alter precipitation behavior under identical thermal treatments. Atom probe tomography (APT) indicates that SPD produces a metastable, atomically homogeneous solid solution that, upon moderate heat treatment (500°C/10 hour), develops remarkedly stronger Cu clustering than the as-cast counterpart. High-temperature exposure (800°C/100 h) produces near-pure Cu precipitates (~90 at% Cu) with significantly enhanced defect-sink efficacy in SPD-processed alloys: precipitate sizes of 50-60 nm and number densities of 2.7-3.8 × 10¹7 m?³, compared to 89 nm and 0.44 × 10¹7 m?³ in as-cast materials. Collectively, the findings establish defect-mediated precipitation control as a scalable, high-impact route to tailor sink density and distribution in HEAs, enabling microstructures optimized for irradiation tolerance and mechanical robustness in nuclear reactor environments.

Meher, Subhashish

Contrasting structural reversibility and magnetic correlations in isostructural honeycomb magnets CrCl3 and 𝛼−RuCl3

We report a comparative neutron single crystal diffraction study of the structural and magnetic properties of layered halides CrCl3 and 𝛼−RuCl3. They host a honeycomb arrangement of transition metal ions with distinct electronic configurations and undergo a first-order structural transition between high-temperature 𝐶⁢2/𝑚 and low-temperature 𝑅⁢‾‾‾3. Both compounds show a step-like change in the 𝑐-lattice parameter across the structure transition. In contrast, the in-plane lattice response is quite different: 𝛼−RuCl3 exhibits an abrupt hysteretic change across the transition accompanied by progressive crystalline degradation upon thermal cycling, whereas CrCl3 shows a smooth in-plane lattice evolution and remains structurally robust. Magnetically, CrCl3 orders into an A-type antiferromagnetic structure at 𝑇𝑁=14 K and exhibits pronounced diffuse magnetic scattering extending up to about 40 K. 𝛼−RuCl3 shows no observable magnetic diffuse scattering above its zigzag antiferromagnetic ordering temperature 𝑇𝑁=7.6 K. These results suggest that the contrasting structural responses arise from an interplay between interlayer sliding energetics, stacking-strain coupling, and elastic accommodation of the stacking transition. The distinct chemical bonding and electronic configurations of the two compounds provide a microscopic basis for their different lattice responses to the structure transition and magnetic correlations.

Morgan, Zachary [ORNL] (ORCID:0000000243625911)

Glauber’s Salt Composites for HVAC Applications: A Study on the Use of the T-History Method with a Modified Data Evaluation Methodology

Phase change materials (PCMs) can be utilized in buildings for peak load shifting in air conditioning systems, and the use of salt hydrate-based PCMs can reduce the cost of thermal energy storage devices. Glauber’s salt is an economical salt hydrate PCM with a melting point of around 32 °C. However, the desired melting range typically falls between 18 and 22 °C for building air conditioning applications. Although many researchers have characterized Glauber’s salt and its composites with modified melting points, enthalpy–temperature curves for composites of Glauber’s salt and NaCl are unavailable. In this study, we report the melting and solidification enthalpy–temperature curves for two different composites of Glauber’s salt and NaCl with a melting point of 21 °C obtained by the T-history method. Both composites contain NaCl to suppress the melting point, borax to reduce supercooling, and sodium polyacrylate as a thickener to enhance cyclic stability. The first composite with 12 wt.% NaCl demonstrated 139 kJ·kg−1 of latent heat of fusion, and the second composite with 9 wt.% NaCl demonstrated 171 kJ·kg−1. Both the composites have high volumetric energy densities compared to their organic counterparts with similar melting points.

Chemistry

TRACE Input Modernization

This work presents a Tom’s Obvious Minimal Language (TOML)-based representation of input for the US Nuclear Regulatory Commission’s TRAC/RELAP Advanced Computational Engine (TRACE) thermal hydraulics code. Implemented using the Workbench Analysis Sequence Processor (WASP), the approach maps traditional TRACE input structures to a hierarchical format composed of named parameters, typed values, and native data collections. The resulting representation preserves TRACE’s existing modeling capabilities while providing a modern, structured interface for model development and management. WASP further extends TOML through a file import directive that supports modular model composition and reusable input organization. In addition, WASP provides extended array data entry convenience with various data repeat and interpolation capabilities. Examples of the new TOML syntax are provided for major TRACE input categories, including hydraulic components, heat structures, control systems, and trip logic. The TOML representation establishes a foundation for improved validation, tooling, automation, and model maintainability while remaining compatible with existing TRACE workflows. To facilitate migration to the TOML-based input format, the TRACE executable now supports conversion of native TRACE input into an intermediate JSON representation. A Python utility subsequently transforms the JSON data into an equivalent TOML model. Lastly, the TRACE executable now supports execution using TOML-formatted input.

Lefebvre, Robert A. [Oak Ridge National Laboratory