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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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239 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Unlocking superplasticity in medium and high-entropy alloys

Superplasticity, the capacity of materials to sustain extraordinary tensile elongations at elevated temperatures, underpins a range of advanced metal-forming technologies. Conventionally, it is achieved in fine-grained alloys where deformation is dominated by grain-boundary sliding, accommodated by diffusion and dislocation activity. The advent of medium- and high-entropy alloys (M/HEAs), with their high chemical complexity and unconventional phase stability, offers new pathways to superplastic behavior beyond traditional alloy systems. Although investigated only recently, several M/HEAs already exhibit elongations that rival or exceed those of classical superplastic materials, particularly when ultrafine or metastable microstructures are engineered. Here, we review progress in understanding superplastic deformation in M/HEAs, emphasizing the interplay among composition, initial microstructure, thermomechanical processing, and microstructural evolution during high-temperature deformation. We discuss approaches to generating the fine-grained structures necessary for grain-boundary sliding, including severe plastic deformation and tailored heat treatments. We further highlight dynamic phenomena such as phase transformations, evolving grain-boundary chemistry, and deformation-induced grain refinement that can enhance plasticity in these systems. These mechanisms often shift the balance of deformation processes, enabling large elongations even outside classical criteria. Finally, we outline key challenges for application, including cost, scalability, recyclability, and microstructural stability.

klenam, Desmond [University of the Witwatersrand, ↗
DOE OSTI2025

Tree tensor network hierarchical equations of motion based on time-dependent variational principle for efficient open quantum dynamics in structured thermal environments

In this work, we introduce an efficient method, TTN-HEOM, for exactly calculating the open quantum dynamics for driven quantum systems interacting with highly structured bosonic baths by combining the tree tensor network (TTN) decomposition scheme with the bexcitonic generalization of the numerically exact hierarchical equations of motion (HEOM). The method yields a series of quantum master equations for all core tensors in the TTN that efficiently and accurately capture the open quantum dynamics for non-Markovian environments to all orders in the system–bath interaction. These master equations are constructed based on the time-dependent Dirac–Frenkel variational principle, which isolates the optimal dynamics for the core tensors given the TTN ansatz. The dynamics converges to the HEOM when increasing the rank of the core tensors, a limit in which the TTN ansatz becomes exact. We introduce TENSO, tensor equations for non-Markovian structured open systems, as a general-purpose Python code to propagate the TTN-HEOM dynamics. We implement three general propagators for the coupled master equations: two fixed-rank methods that require a constant memory footprint during the dynamics and one adaptive-rank method with a variable memory footprint controlled by the target level of computational error. We exemplify the utility of these methods by simulating a two-level system coupled to a structured bath containing one Drude–Lorentz component and eight Brownian oscillators, which is beyond what can presently be computed using the standard HEOM. Our results show that the TTN-HEOM is capable of simulating both dephasing and relaxation dynamics of driven quantum systems interacting with structured baths, even those of chemical complexity, with an affordable computational cost.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

An integrated in-situ coordination strategy enabling high-performance layered cathodes for sodium-ion batteries

O3-type layered transition metal oxide cathodes hold tremendous potential in sodium-ion batteries (SIBs) due to their low cost and high energy density. However, the structure instability associated with detrimental phase transitions and severe interface parasitic reactions exacerbate the material's electrochemical performance degradation. Herein, we develop an integrated in-situ coordination strategy via heteroatomic modulation inducing coherent epitaxial layer to collaboratively enhance the overall framework robustness from surface to bulk. The theoretical calculation and multiple in/ex-situ characterizations demonstrate the charge density around oxygen is redistributed, which promotes the electron localization, thus widening the NaO 2 lattice space and accelerating the Na + transport dynamics. Furthermore, the formed strengthened oxygen bond energy effectively distributes the long-range coordination of Mn 3+ O 6 octahedron, thereby alleviating Jahn-Teller distortion and local stress. Importantly, the in-situ formed conformal buffer layer dramatically relieves the adverse interface side reactions, facilitating the construction of robust cathode-electrolyte interface, which ameliorate the whole structure stability of designed materials. Consequently, the optimized NFMZ@NZO-1.0 exhibits the excellent cycling stability with 80.2% capacity retention after 300 cycles at 1C, and delivers a high discharge capacity of 107.1 mAh g −1 at 10C. In conclusion, this distinctive coupling strategy provides valuable insights for developing high-performance layered cathode materials in SIBs.

Coherent epitaxial layer↗
DOE OSTI2026

A multiscale packed-bed reactor model for sustainable ethylene production via chemical looping oxidative coupling of methane

The rising global warming concerns and shale gas discovery have prompted research in the direction of greenhouse gas (GHG), such as methane, reduction and conversion. Oxidative coupling of methane (OCM) offers a pathway to low carbon-intense valorization of methane while producing ethylene, a chemical regarded as central to the petrochemical industry. Even after decades of OCM discovery, researchers keep understanding the process and underlying chemical reactions in a pursuit to achieve industrial viability for OCM. Here, in general, OCM suffers from low C 2 selectivity, yield and reactor temperature runaways due to highly exothermic nature of its reactions. Computational Fluid Dynamics (CFD) tools help analyze spatial gradients within the reactor to deeply understand the diffusion of species, mass and heat transfer phenomena. Furthermore, challenges associated with scaling up such as hot spot formation and parametric sensitivity can be addressed without having to expend on costly experiments. The current paper presents a multiscale packed-bed reactor CFD model coupled with a chemical kinetic model for the chemical looping OCM. The CFD model includes two scales i.e., macroscale for catalyst bed and microscale for individual pellets. Moreover, a chemical kinetic model based on 10 gas-phase reactions is integrated with the CFD model. An additional surface reaction for the formation of gas-phase oxygen from catalyst surface is added to account for the absence of feed oxygen. The model is calibrated against experimental results. The calibrated model captures trends in CH 4 conversion, C 2 selectivity and C 2 yield within a ± 4.35 % range across a temperature range of 700-900 °C. Moreover, model fidelity is evaluated by varying key computational parameters such as mesh resolution and time step size. The model is also verified by varying the inlet methane concentration and the gas hourly space velocity (GHSV) and comparing the results with literature. A sensitivity analysis and scale-up of the current model is undergoing.

Chemical looping↗
DOE OSTI2024

Thermal stability of 3D interface Cu/Nb nanolaminates

Nanocrystalline alloys are promising structural materials yet lack thermal stability in many cases. Recent work shows that interface structure has an outsize effect on the thermal behavior of nanostructured alloys. Here, this work focuses on the role of controlled heterophase interface structure in the thermal evolution of model Cu/Nb nanolaminates. We introduce 3D interfaces containing nanoscale heterogeneities in all spatial dimensions between Cu and Nb, forming 3D Cu/Nb. TEM, nanoindentation, and DSC are used in tandem to establish thermal stability and to identify shifts in microstructure as a function of static annealing temperature. 3D interfaces are shown to survive annealing to 300 °C for 1 hr., while 3D Cu/Nb microstructure evolves to form low-density and voided regions correlating to the onset of layer pinch-off between 500 and 600 °C annealing temperatures. A diffusivity- and vacancy energetics-based mechanism is developed to explain void formation driven by 3D interface degradation at elevated temperature.

3D interfaces↗
DOE OSTI2026

Toward Trustworthy Autonomous Science: A Two-Year Community Roadmap

One year ago, the AISLE roadmap argued that autonomous laboratories operated as isolated islands and proposed a grassroots network organized around five critical dimensions. The field has since moved faster than that roadmap anticipated: multi-agent systems have produced experimentally validated hypotheses, self-driving laboratories have grown more interoperable and orchestrated, reasoning-trained and domain foundation models have raised the capability ceiling, and the Genesis Mission has placed autonomous experimentation at the center of U.S. federal science strategy, with industry emerging as a primary actor. Progress has met a sobering counter-current, including a corrected flagship discovery result, benchmarks showing that agents which rival experts on closed-ended questions still complete only a fraction of open-ended research, and fabricated citations surfacing at leading venues. We read this as the defining tension of the field: producing a candidate discovery is no longer the hard part, but verifying it is, and this asymmetry now limits autonomous science more than raw model capability. Accordingly, we update the roadmap around seven dimensions, revisiting the original five and elevating two former cross-cutting concerns, trust, verification, and reproducibility, and safety, security, and governance, to first-class status. We assess the original milestones (M1 through M14) as achieved, partially achieved, reframed, or open, add four new milestones (M15 through M18) for the elevated dimensions, and scope the path forward to a two-year horizon, with the first year concentrating on interfaces, protocol adoption, and the scaffolding of verification, and the second targeting federation, zero-trust coordination, and governance. Throughout, we position the grassroots network as the interoperability fabric that lets national programs, international initiatives, and commercial platforms connect rather than re-silo.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Chemical Bond Covalency in Superionic Halide Solid‐State Electrolytes

Abstract Halide solid‐state electrolytes (SSEs) are promising superionic conductors with high oxidative stability and ionic conductivity, making them attractive for all‐solid‐state lithium‐ion batteries. However, most studies have focused on ion‐stacking structures, overlooking the role of bond characteristics in ionic transport. Here, we investigate bond dynamics and the superionic transition (SIT) in bromide electrolyte, Li 3 InBr 6 , using synchrotron X‐ray techniques and ab initio molecular dynamics (AIMD) simulations. We demonstrate that the SIT in halide SSEs is driven by a thermally induced transition in bonding character (ionic to covalent) rather than a change in crystal phase. AIMD simulations further reveal enhanced Li⁺ diffusion and collective anion motion at elevated temperatures. Expanding our study to Li 3 LnBr 6 (Ln = Gd, Tb, Ho, Tm, and Lu), we confirm the widespread occurrence of SIT in this material class, with Li 3 GdBr 6 exhibiting the highest ionic conductivity (5.2 mS cm −1 at 298 K). More importantly, the ionic‐covalent transition is highly tunable through electrolyte modifications, such as cation/anion substitution and synthesis methods. Our findings provide a new perspective on ionic transport, highlighting the critical role of chemical bond characteristics in halide SSEs.

Chemistry↗
DOE OSTI2024

Multiple Peaks and a Long Precursor in the Type IIn Supernova 2021qqp: An Energetic Explosion in a Complex Circumstellar Environment

Abstract We present optical photometry and spectroscopy of the Type IIn supernova (SN) 2021qqp. Its unusual light curve is marked by a long precursor for ≈300 days, a rapid increase in brightness for ≈60 days, and then a sharp increase of ≈1.6 mag in only a few days to a first peak ofM r ≈ −19.5 mag. The light curve then declines rapidly until it rebrightens to a second distinct peak ofM r ≈ −17.3 mag centered at ≈335 days after the first peak. The spectra are dominated by Balmer lines with a complex morphology, including a narrow component with a width of ≈1300 km s −1 (first peak) and ≈2500 km s −1 (second peak) that we associate with the circumstellar medium (CSM) and a P Cygni component with an absorption velocity of ≈8500 km s −1 (first peak) and ≈5600 km s −1 (second peak) that we associate with the SN–CSM interaction shell. Using the luminosity and velocity evolution, we construct a flexible analytical model, finding two significant mass-loss episodes with peak mass loss rates of ≈10 and ≈5M ⊙ yr −1 about 0.8 and 2 yr before explosion, respectively, with a total CSM mass of ≈2–4M ⊙ . We show that the most recent mass-loss episode could explain the precursor for the year preceding the explosion. The SN ejecta mass is constrained to be ≈5–30M ⊙ for an explosion energy of ≈(3–10) × 10 51 erg. We discuss eruptive massive stars (luminous blue variable, pulsational pair instability) and an extreme stellar merger with a compact object as possible progenitor channels.

Astronomy & Astrophysics↗
DOE OSTI2026

Decadal-Scale Hydrothermal Alteration of Basalt: Implications for Long-Term Reactivity in Subsurface Technologies

Global demands to secure critical mineral supply chains and managing water resources require innovative resource management strategies. Subsurface basalt reservoirs offer a dual-purpose application, where CO2 enhanced critical metal recovery can be coupled with water remediation strategies for the extraction of economically important and environmentally relevant elements. This study utilizes static batch experiments conducted on Columbia River Basalt Group samples to evaluate long-term fluid–rock interactions relevant to coupled subsurface applications. Samples were reacted under elevated temperature and pressure conditions, for 296 and 4,061 days, providing a unique dataset to assess geochemical evolution, element partitioning, and aqueous chemistry over decadal timescales. The alteration was dominated by silicate, aluminosilicate, and oxide phases. Progressive hydrothermal alteration increased the cation exchange capacity through the formation of secondary minerals (e.g. clays and zeolites), influencing solute retention, ion exchange behavior, and aqueous chemistry. Grain-scale and bulk analyses revealed selective cation release and retention patterns, establishing a mechanistic baseline for predicting element mobility. These geochemical constraints inform the prospective use of CO2-enhanced metal recovery for critical resources (e.g. Co, Ni, Mn, Mg, Ti, Fe) and associated water-quality impacts, providing a foundation for the design and management of engineered fluid–rock systems in basalt reservoirs.

Gibson, Marie N.↗
DOE OSTI2026

Polarized target nuclear magnetic resonance measurements with deep neural networks

Continuous-wave Nuclear Magnetic Resonance (CW-NMR) operated in constant-current mode has served as a foundational technique for polarization measurement in solid-state dynamically polarized targets within nuclear and high-energy physics experiments for several decades, and it remains an essential tool. Conventional Q-meter-based phase-sensitive detection is critical for precise real-time determination of target polarization during scattering runs. However, the accuracy and reliability of these measurements are frequently compromised by elevated noise levels, baseline drift, and systematic uncertainties arising from signal isolation and fitting, ultimately degrading the overall experimental figure of merit. In this work, we report the first successful application of neural network architectures to continuous-wave NMR polarization metrology. By leveraging advanced machine learning techniques for signal extraction and denoising, we achieve a substantial reduction of fitting uncertainties under a variety of realistic simulated and experimental conditions. These improvements translate directly into more robust real-time (online) polarization monitoring and higher precision in subsequent offline analysis. By reducing analysis-induced uncertainty, the resulting methodology can improve the effective figure of merit for scattering experiments employing dynamically polarized targets and provides a new toolset for NMR-based polarimetry in high-energy and nuclear physics.

Metrology↗
DOE OSTI2026

Nanoscale Compositional and Strain Gradients Enable High‐Speed and Amplitude‐Resolved Pyroelectric Sensing

The frequency response of pyroelectric sensors is fundamentally governed by thermal time constant (τth, determined by thermal mass and thermal conductance) and electrical impedance arising from film capacitance and readout circuit. Conventional bulk LiTaO3 detectors are optimized for high responsivity at low modulation frequencies (0.1-10 Hz), possessing a large τth that thermally averages rapid temperature oscillations at elevated modulation frequencies, limiting fidelity in resolving dynamic varying thermal signals. Here, compositional and strain gradients are introduced into 100-nm-thick relaxor-ferroelectric films reducing τth to ≈2 µs and producing built-in potentials (≈1.45 V or 145 kV cm-1) that enhance the pyroelectric coefficient and suppress the dielectric constant. This enables complementary dual-mode operation by enhancing current-mode electrical responsivity and improving the voltage-mode figure of merit - advantageous for superior temperature resolution (ΔTmin ≈ 30 µK). The responsivity peak shifts to near 1 kHz (>2500-times higher than conventional bulk sensors), with measurable responsivity extending to a carrier frequency of 100 kHz and amplitude-resolved detection at modulation frequencies up to 15 kHz. These results establish nanoscale internal-field engineering can reshape electro-thermal trade-off in pyroelectric thin films toward zero-bias, high-thermal-sensitivity, and amplitude-resolved thermal sensing across a wide frequency bandwidth.

Lin, Ching‐Che↗
DOE OSTI2026

Upper ocean mixing, surface heat fluxes, and heat content variability in the upper 150 m during Hurricane Laura (2020)

Observations (from thermistor sensors and a hurricane glider) and model-based temperature were used to answer questions including the following: 1) What physical and environmental conditions explain the rapid intensification of Hurricane Laura? 2) How did the pre-existing warm mixed layer at Stone mooring (StM) influence the degree of cooling in the mixed layer? 3) How did vertical mixing, surface heat fluxes, and advective processes collectively shape the mixed layer heat evolution at StM? Observations measured by thermistor sensors showed that Hurricane Laura induced a cooling of -1.2oC in the mixed layer when Hurricane Laura’s wind speed increased to 47 m/s on 26 August. This contrasts with the -1.04oC mixed layer temperature change estimated from model-based temperature. At StM, the presence of a 31oC warm mixed layer and elevated heat content (60-80kJ/cm2) effectively preconditioned the upper ocean ahead of Hurricane Laura’s passage. After Hurricane Laura passed, turbulent mixing associated with the storm transported the heat anomalies downward into subsurface layers. In addition, this study shows that a surface heat flux of 5.04 kJ/cm2 supported the intensity of Hurricane Laura as it traversed over the StM. Using a mixed layer heat balance model, this study shows that entrainment flux and surface flux mostly contributed to the observed change in the mixed layer temperature.

Tsai, Senam↗
DOE OSTI2024

Mechanically and Thermally Robust Gel Electrolytes Built from A Charged Double Helical Polymer

Polymer electrolytes have received tremendous interest in the development of solid-state batteries, but often fall short in one or more key properties required for practical applications. Herein, a rigid gel polymer electrolyte prepared by immobilizing a liquid mixture of a lithium salt and poly(ethylene glycol) dimethyl ether with only 8 wt% poly(2,2′-disulfonyl-4,4′-benzidine terephthalamide) (PBDT) is reported. The high charge density and rigid double helical structure of PBDT lead to formation of a nanofibrillar structure that endows this electrolyte with stronger mechanical properties, wider temperature window, and higher battery rate capability compared to all other poly(ethylene oxide) (PEO)-based electrolytes. The ion transport mechanism in this rigid polymer electrolyte is systematically studied using multiple complementary techniques. Li/LiFePO 4 cells show excellent capacity retention over long-term cycling, with thermal cycling reversibility between ambient temperature and elevated temperatures, demonstrating compelling potential for solid-state batteries targeting fast charging at high temperatures and slower discharging at ambient temperature.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Environmental Performance Report 2025: Annual Site Environmental Report per the U.S. Department of Energy Order 231.1B Chg 1

The National Laboratory of the Rockies (NLR) Environmental Performance Report provides a description of the laboratory's environmental management activities in calendar year 2025, including information on environmental performance, environmental compliance activities and status, and environmental protection programs, highlights, and successes. The purpose of this report is to ensure that the U.S. Department of Energy (DOE) and the public receive timely, accurate information about events that have positively affected or could adversely affect the health and safety of the public or workers, the environment, or the operations of DOE facilities. This report meets the DOE requirements of the Annual Site Environmental Report (ASER) and has been prepared in accordance with DOE Order 231.1B Chg 1, Environment, Safety and Health Reporting.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

EXERGETIC: De-Risking Next-Generation Resilient Geothermal Hybrids via At-Scale Evaluation Using Virtual Emulation Digital Twin Environment for Efficient Operation

The DOE-GTO-funded project, award number 5.1.2.12, entitled "EXERGETIC - De-risking Next Generation Resilient Geothermal Hybrids via at-Scale Evaluation Using a Virtual Emulation Digital Twin Environment for Efficient Operation," advances the solution to these challenges by developing and validating a geothermal co-emulation environment implemented at the National Laboratory of the Rockies (NLR)'s Advanced Research on Integrated Energy Systems (ARIES) platform. This framework enables the de-risking of next-generation geothermal and geothermal hybrid systems through high-fidelity modeling, real-time digital emulation, advanced control strategies, and techno-economic assessment. The project focused on geothermal hybrid configurations that integrate geothermal power plants with concentrated solar power and underground thermal energy storage, enabling enhanced efficiency, flexibility, and grid support capabilities. The main goal of this project was the development of a geothermal digital co-emulation environment to demonstrate the technical and economic value of geothermal hybrid systems and their contribution to grid stability and flexibility. The EXERGETIC framework combined physics-based models, controls, and real assets at ARIES, including digital real-time simulators (DRTS), a 20-MW-scale controllable grid interface (CGI), and a 2-MW conventional generator. Detailed transient models were developed for the key subsystems of a hybrid geothermal plant, including parabolic trough solar collectors, reservoir thermal energy storage (RTES), and a binary Organic Rankine Cycle (ORC) power plant. The ORC model explicitly captured thermal inertia and off-design operation and integrated control strategies to dynamically respond to electric load profiles. The models were validated against published experimental and numerical studies, demonstrating strong agreement and confirming the accuracy and robustness of the modeling approach. The resulting digital twin represents geothermal-solar-storage systems at multiple scales (1 MW to 100 MW) and enables realistic emulation of grid-connected operation. The control architecture allows the geothermal resource to provide stable baseload generation, while solar and stored thermal energy supply flexible, dispatchable support during periods of high demand or variable grid conditions. A key contribution of the EXERGETIC project is the demonstration that geothermal hybrid systems can be designed to be active grid assets rather than passive baseload generators. Using the ARIES platform, the digital twin was evaluated under multiple grid scenarios, including load following, voltage support at the distribution level, and frequency response at the transmission level. Results show that hybrid geothermal systems can respond effectively to dynamic grid conditions, providing inertia-like behavior, primary frequency support, and voltage regulation through coordinated control. In addition to the performance and grid services capability analysis of geothermal and hybrid geothermal systems, the EXERGETIC project also focused on scalability and techno-economic analysis of geothermal hybrid plants. In particular, for the scalability analysis, machine-learning (ML)-based surrogate models were trained using data generated from the geothermal digital twin under different grid-connected scenarios and plant capacities. These ML models demonstrated strong interpolation and extrapolation capabilities across plant sizes, accurately reproducing both steady-state and transient responses with very low errors. Regarding the techno-economic analysis, plant performance results were integrated with cost models for hybrid geothermal systems, and the levelized cost of electricity (LCOE) was used as the main economic metric to evaluate system performance across a range of system capacities, solar shares, solar multiples, and storage durations. Results indicate that economies of scale significantly reduce geothermal LCOE as plant capacity increases, with large-scale systems (25-100 MW) achieving substantially lower costs than small plants. Hybridization with solar thermal energy and storage further improves economic performance by increasing capacity utilization and enabling flexible dispatch. In addition, thermal storage plays a critical role in reducing LCOE by maximizing geothermal, solar, and stored energy resources. In summary, the results from this project demonstrate that geothermal hybrid systems represent a promising alternative for increasing the energy conversion efficiency of geothermal technologies, contributing to the preservation of geothermal resources, and supporting the transition of geothermal plants from traditional baseload resources into flexible, resilient, and cost-competitive energy conversion technologies.

15 GEOTHERMAL ENERGY↗
DOE OSTI2025

Internally Catalyzed Hydrogen Atom Transfer (I-CHAT)—A New Class of Reactions in Combustion Chemistry

The current paradigm of low-T combustion and autoignition of hydrocarbons is based on the sequential two-step oxygenation of fuel radicals. The key chain-branching occurs when the second oxygenation adduct (OOQOOH) is isomerized releasing an OH radical and a key ketohydroperoxide (KHP) intermediate. The subsequent homolytic dissociation of relatively weak O–O bonds in KHP generates two more radicals in the oxidation chain leading to ignition. Based on the recently introduced intramolecular “catalytic hydrogen atom transfer” mechanism (J. Phys. Chem. 2024, 128, 2169), abbreviated here as I-CHAT, we have identified a novel unimolecular decomposition channel for KHPs to form their classical isomers—enol hydroperoxides (EHP). The uncertainty in the contribution of enols is typically due to the high computed barriers for conventional (“direct”) keto–enol tautomerization. Remarkably, the I-CHAT dramatically reduces such barriers. The novel mechanism can be regarded as an intramolecular version of the intermolecular relay transfer of H-atoms mediated by an external molecule following the general classification of such processes (Catal. Rev.-Sci. Eng. 2014, 56, 403). Here, we present a detailed mechanistic and kinetic analysis of the I-CHAT-facilitated pathways applied to n-hexane, n-heptane, and n-pentane models as prototype molecules for gasoline, diesel, and hybrid rocket fuels. We particularly examined the formation kinetics and subsequent dissociation of the γ-enol-hydroperoxide isomer of the most abundant pentane-derived isomer γ-C5-KHP observed experimentally. To gain molecular-level insight into the I-CHAT catalysis, we have also explored the role of the internal catalyst moieties using truncated models. All applied models demonstrated a significant reduction in the isomerization barriers, primarily due to the decreased ring strain in transition states. In addition, the longer-range and sequential H-migration processes were also identified and illustrated via a combined double keto–enol conversion of heptane-2,6-diketo-4-hydroperoxide as a potential chain-branching model. To assess the possible impact of the I-CHAT channels on global fuel combustion characteristics, we performed a detailed kinetic analysis of the isomerization and decomposition of γ-C5-KHP comparing I-CHAT with key alternative reactions—direct dissociation and Korcek channels. Calculated rate parameters were implemented into a modified version of the n-pentane kinetic model developed earlier using RMG automated model generation tools (ACS Omega, 2023, 8, 4908). Simulations of ignition delay times revealed the significant effect of the new pathways, suggesting an important role of the I-CHAT pathways in the low-T combustion of large alkanes.

Biochemistry & Molecular Biology↗
DOE OSTI2026

Virtual Growth of SRF Materials

Niobium's native surface oxide affects SRF cavity and superconducting qubit performance, motivating interest in controlling its crystalline structure. We combine a literature-derived machine-learning analysis with temperature-dependent XRD to study crystalline ordering in Nb2O5. Random Forest models, trained on 74 processing conditions from 17 papers and validated by leave-one-group-out cross-validation, predicted broad crystallinity outcomes well (balanced accuracy 0.809), but struggled with specific polymorph identity (0.577). Annealing temperature was the dominant predictor across all targets; oxygen partial pressure showed negligible importance, reflecting narrow literature coverage rather than physical irrelevance. Temperature-dependent XRD on anodized and H2O2-treated Niobium showed structural evolution consistent with the machine learning predictions. Our model and overall approach provide a data-driven framework for identifying and optimizing conditions that promote crystallization in initially amorphous oxides. This framework can guide the selection of growth and post-annealing conditions for Nb surfaces by narrowing the experimental parameter space, thereby reducing trial-and-error efforts in developing oxide structures relevant to SRF applications.

Tilkin, Anthony [Fermilab]↗
DOE OSTI2026

Maintenance strategy, structural design, and site layout of the ST-E1 fusion power plant

An effective fusion reactor maintenance scheme enables safe operations and short downtimes. This in turn leads to high availability, which is critical to the commercial viability of a power-producing plant. In tokamak-based fusion power plants, the chosen maintenance approach has a significant impact on the spatial design of the tokamak, as well as the surrounding infrastructure, and therefore needs to be considered from the outset. Tokamak Energy has developed a pre-concept design of a fusion power plant, ST-E1. This work describes the major drivers and constraints that have been considered, presents the tokamak architecture and chosen maintenance regime, and discusses how this enables the plant’s two-phased approach to demonstrating commercial operations. It also shows the implications for the design of other systems areas, in particular the machine structural arrangement and bioshield and hot cell layout. The reactor core segmentation and removal scheme replaces entire toroidal segments radially through a large vacuum port, along a single axis only. The result is a change-tolerant machine and plant layout that can accommodate the evolving designs of the tokamak.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗