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All sourcesNASA NTRSDOE OSTI
NASA NTRS2026

The Thermal and Kinematic Sunyaev–Zeldovich Effect in Galaxy Clusters and Filaments Using Multifrequency Temperature Maps of the Cosmic Microwave Background A399–A401 Cluster Pair Case Study

We present a multifrequency and multi-instrument methodology to study the physical properties of galaxy clusters and cosmic filaments using cosmic microwave background observations. Our approach enables simultaneous measurement of both the thermal (tSZ) and kinematic Sunyaev–Zeldovich (kSZ) effects, incorporates relativistic corrections, and models astrophysical foregrounds such as thermal dust emission. We do this by jointly fitting a single physical model across multiple maps from multiple instruments at different frequencies, rather than fitting a model to a single Compton-y map. We demonstrate the success of this method by fitting the A399–A401 galaxy cluster pair and filament system using archival data from the Planck satellite and new, targeted deep data from the Atacama Cosmology Telescope, covering 11 different frequencies over 14 maps from 30 GHz to 545 GHz. Our tSZ results are consistent with previous work using Compton-y maps. We measure the line-of-sight peculiar velocities of the cluster–filament system using the kSZ effect and find statistical uncertainties on individual cluster peculiar velocities of ≲600 km s −1 , which are competitive with current state-of-the-art measurements. Additionally, we measure the optical depth of the filament component with a signal-to-noise of 8.5σ and reveal hints of its morphology. This modular approach is well-suited for application to future instruments across a wide range of millimeter and submillimeter wavebands.

Ajay S Gill↗
DOE OSTI2026

Polymer coatings on zirconia microspheres via rotating flow fluid dynamics

Conventional tristructural isotropic (TRISO) coatings for nuclear fuels require multi-step and expensive formation processes; any breakage of the coatings may lead to fission species release. Polymer derived ceramic (PDC) coatings can be a suitable alternative to address these issues. In this study, allylhydridopolycarbosilane (SMP-10) coatings were created on yttria stabilized zirconia (YSZ) microspheres using a Rotating Flow Fluid Dynamics (RFFD) coating method. The effects of curing temperature, rotation speed, and coating cycle/time on the coating were analyzed. Surface functionalization of YSZ microspheres with NaOH resulted in good adhesion between the polymer precursor and the YSZ kernel particles. Spectroscopy analysis revealed complete curing of SMP-10 coated YSZ at 160 °C. Rotation speed and coating time significantly affect the coating characteristics. After 3 cycles at lower rotation speed (50 rpm) for 10 min each, the coating obtained was uniform and homogeneous. In comparison, the coating showed almost 10 times less eccentricity at a high rotation speed of 300 rpm. Compared with the coatings prepared at 300 rpm condition, the coatings have higher sphericity and lower eccentricity at 50 rpm. Overall, this study provides a novel and effective route for fabricating and curing SMP-10 precursor coatings on YSZ microspheres.

Ravi, Nivetha [University of Alabama, Birmingham]↗
NASA NTRS2004

Ejecta Generation and Redistribution on 433 Eros: Modeling Ejecta Launch Conditions

The NEAR-Shoemaker mission to asteroid 433 Eros presents an unprecedented opportunity to gain fundamental new knowledge about the processes governing regolith formation and redistribution on small bodies. NEAR-Shoemaker’s high-resolution imaging of the surface of Eros makes the asteroid a valuable and heretofore unparalleled laboratory for the detailed study of impact ejecta reaccretion and regolith redistribution on low-gravity (of order 10 -3 g) objects. Regolith is produced on asteroids by impact cratering, and the existence of regolith on the smallest solar system bodies supports the view that some of the ejecta from impact events on such objects may be retained. Impact craters and retained ejecta on low-gravity objects like Eros represent valuable natural laboratories for evaluating various models of impact cratering processes, since they may present crater structures or ejecta features that either do not form or are hidden on higher-gravity bodies like the Moon. Further, quantifying the extent to which impact processes generate and redistribute regoliths on small body surfaces (excavation depths, retained fraction, turnover timescales, etc.) is pivotal to the issue of how to relate meteoritical samples to their asteroidal parent bodies when surficial processes ( i.e., “space weathering”) may disguise or cover up underlying material and confound the ability of remote sensing techniques to provide reliable mineralogical assays of the parent objects. The rich variety of data on Eros’ regolith properties and distribution returned by NEAR-Shoemaker now require detailed analysis in order to take full advantage of the clues these observations offer for elucidating details of the impact cratering process on small bodies. Complicating simple interpretations of crater and ejecta morphology are dynamical effects on ejecta emplacement resulting from Eros’ irregular shape, rapid (5.27 hr) rotation, and low gravity. Figure 1 shows the very different ejecta deposit morphology that can result if the effects of rotation alone are neglected. Considering the additional complicating factors of Eros’ irregular shape and complex gravitational field, simple calculations of the extent and thickness of ejecta blankets and the spatial distribution of ejecta blocks from basic crater scaling laws or numerical hydrocodes alone do not suffice. In order to fully interpret the suite of NEAR-Shoemaker observations of regolith features across the surface of Eros and to evaluate various impact models for specific craters on the asteroid, detailed dynamical modeling of the deposition of crater ejecta from those craters is required . Here, I describe some modifications and improvements to the dynamical model being used for these studies.

D D Durda↗
DOE OSTI2024

Machine learning the electric field response of condensed phase systems using perturbed neural network potentials

Abstract The interaction of condensed phase systems with external electric fields is of major importance in a myriad of processes in nature and technology, ranging from the field-directed motion of cells (galvanotaxis), to geochemistry and the formation of ice phases on planets, to field-directed chemical catalysis and energy storage and conversion systems including supercapacitors, batteries and solar cells. Molecular simulation in the presence of electric fields would give important atomistic insight into these processes but applications of the most accurate methods such as ab-initio molecular dynamics (AIMD) are limited in scope by their computational expense. Here we introduce Perturbed Neural Network Potential Molecular Dynamics (PNNP MD) to push back the accessible time and length scales of such simulations. We demonstrate that important dielectric properties of liquid water including the field-induced relaxation dynamics, the dielectric constant and the field-dependent IR spectrum can be machine learned up to surprisingly high field strengths of about 0.2 V Å −1 without loss in accuracy when compared to ab-initio molecular dynamics. This is remarkable because, in contrast to most previous approaches, the two neural networks on which PNNP MD is based are exclusively trained on molecular configurations sampled from zero-field MD simulations, demonstrating that the networks not only interpolate but also reliably extrapolate the field response. PNNP MD is based on rigorous theory yet it is simple, general, modular, and systematically improvable allowing us to obtain atomistic insight into the interaction of a wide range of condensed phase systems with external electric fields.

Science & Technology - Other Topics↗
NASA NTRS1993

Development of global/chemistry model for jet-fuel thermal stability based on observations from static and flowing experiments

Two global-chemistry models for oxidative deposition of jet fuels are evaluated by integrating them into a Computational Fluid Dynamics with Chemistry (CFDC) code. A previously developed two-step global-chemistry model was found to be insufficient to describe the thermal-oxidation and -deposition rates associated with a Jet-A fuel. A new global-chemistry model has been developed systematically based on observations from flowing and static experiments. The global-autoxidation reaction is modified such that the reaction rate becomes zeroth-order with respect to the dissolved oxygen concentration. The generation of deposit-forming precursor is coupled with the autoxidation reaction by introducing a radical species ROO. A formulation for the sticking probability has also been developed. Deposition profiles are well represented by this new model under a variety of temperature and flow conditions. The model correctly predicts the changes in magnitude and spatial location of the deposition peak due to changes in flow. The CFDC model, which is designed for flowing systems, has been extended to static experiments. The model incorporates a non-depleting species F(sub s) representing all non-oxygen compounds responsible for deposition. Static experiments were found to provide a useful and inexpensive method for estimating the concentration of F(sub s) in the fuel.

V. R. Katta↗
DOE OSTI2026

Techno-Economic Evaluation of Electrified Vehicle Options in Drayage Fleets

The electrification of drayage fleets offers potential economic and operational benefits, but the financial viability of electrified vehicles remains sensitive to battery cost, energy price, and fleet usage patterns. While total cost of ownership (TCO) is a useful benchmark, fleet operators and investors are equally concerned with investment performance metrics such as payback period (PB) and Internal Rate of Return (IRR), which better reflect financial risks and investment return timelines. This study develops a unified techno-economic framework that jointly evaluates TCO, PB, and IRR to determine when electrified trucks become cost-effective alternatives to diesel trucks. Building on a previously developed cost modeling tool and using real-world telematics data from a Class 8 drayage fleet at the Port of Savannah, the analysis incorporates projected battery cost trajectories, electricity and diesel price trends, vehicle efficiency improvements, and multiple battery capacities. Parameter ranges reflect widely cited projections and observed drayage-duty-cycle variability. A surrogate-modeling method approximates economic performance across thousands of battery cost–electricity price combinations, enabling high-resolution identification of conditions that achieve TCO parity, acceptable PB thresholds, and target IRR levels. Additionally, the study estimates the evolving share of the fleet that can feasibly electrify over time under multiple economic metrics. This integrated framework offers a novel, data-driven approach to inform risk-aware decision-making for fleet electrification and supports investment planning under evolving cost and operational conditions.

Sun, Ruixiao [ORNL] (ORCID:0000000341768676)↗
DOE OSTI2026

Investigation Into LiCl-LiF+Li 2 O as a Low Temperature Electrolyte in Direct Electrolytic Reduction of UO 2

Direct electrolytic reduction (DER) of UO 2 in a binary LiCl-Li2O (1–3 wt%) at 650 °C has been widely reported. The process temperature can be reduced to 550 °C in theory by using a near eutectic ternary LiCl-LiF+Li 2O (∼2 wt%) electrolyte, which will result in substantial reduction in rate of salt vaporization. The feasibility of using the ternary electrolyte for the process was tested via material compatibility testing, electrochemical polarization testing, and controlled potential or current DER experiments. MgO, Pt, and 625 nickel samples were each contacted with the ternary salt for 168 h. Negligible changes to dimensions and mass of the samples were measured, and concentrations of corrosion products in the salt were 102 ppm or less. O2−oxidation was observed to occur at a lower potential than Cl-or F-on a Pt anode. DER of UO2was performed in six trials. Process variables included type of reference electrode, electrochemical control method, type of cathode basket, and electrolyte composition. UO 2conversion ranged from 28.2 to 99.9 % , and current efficiency ranged from 38 to 52%. Overall, results indicate that the use of the ternary salt is feasible for DER.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Large Language Model for Validation, Optical Calibration, and Learning (VOCAL) Distributed Temperature Sensing Interface

Distributed temperature sensing (DTS) using fiber optic sensors (FOS) offers a promising method for temperature measurements in advanced reactors, such as sodium fast reactors and molten salt cooled reactors. To support the calibration and validation of DTS measurements, Argonne National Laboratory developed the Validation, Optical Calibration, and Learning (VOCAL) software package. This report describes the integration of a local large language model (LLM) with a retrieval-augmented generation (RAG) system into the VOCAL interface to serve as an interactive user assistant. The LLM framework enhances the VOCAL platform’s accessibility to users by explaining interface components, clarifying inputs and outputs, and answering user queries dynamically in real-time. The accuracy of the LLM assistant performance was evaluated with 20 queries regarding the interface and its parameters using experimental data from the Thermal Hydraulic Experimental Test Article (THETA) facility. Results demonstrate that the LLM achieved a 95% accuracy rate, with a BERTScore of 0.8816 and SBERT value of 0.7417. Furthermore, validation of the RAG system within the LLM framework showed optimal accuracy with k-values between 1 and 2 using the k-refinement convergence test. The prompt perturbation analysis demonstrated good initial consistency for the RAG system, exhibiting the highest accuracy under punctuation variations and the greatest sensitivity under query reordering. Notably, the model’s errors were limited to data retrieval failures rather than factual hallucinations, reinforcing its baseline reliability. The integration of LLM provides a highly accurate, userfriendly enhancement to the VOCAL platform without disrupting its core computational capabilities for FOS calibration and validation.

Hong, Evan↗
DOE OSTI2024

A novel digital lifecycle for Material‐Process‐Microstructure‐Performance relationships of thermoplastic olefins foams manufactured via supercritical fluid assisted foam injection molding

Abstract This research significantly enhances the applicability of thermoplastic olefins (TPOs) in the automotive industry using supercritical N 2 as a physical foaming agent, effectively addressing the limitations of traditional chemical agents. It merges experimental results with simulations to establish detailed material‐process‐microstructure‐performance (MP2) relationships, targeting 5–20% weight reductions. This innovative approach labeled digital lifecycle (DLC) helps accurately predict tensile, flexural, and impact properties based on the foam microstructure, along with experimentally demonstrating improved paintability. The study combines process simulations with finite element models to develop a comprehensive digital model for accurately predicting mechanical properties. Our findings demonstrate a strong correlation between simulated and experimental data, with about a 5% error across various weight reduction targets, marking significant improvements over existing analytical models. This research highlights the efficacy of physical foaming agents in TPO enhancement and emphasizes the importance of integrating experimental and simulation methods to capture the underlying foaming mechanism to establish material‐process‐microstructure‐performance (MP2) relationships. Highlights Establishes a material‐process‐microstructure‐performance (MP2) for TPO foams Sustainably produces TPO foams using supercritical (ScF) N 2 with 20% lightweighting Shows enhanced paintability for TPO foam improved surface aesthetics Digital lifecycle (DLC) that predicts both foam microstructure and properties DLC maps process effects & microstructure onto FEA mesh for precise prediction

Engineering↗
DOE OSTI2024

High‐Loading Lithium‐Sulfur Batteries with Solvent‐Free Dry‐Electrode Processing

Abstract Lithium‐sulfur (Li‐S) batteries, with their high energy density, nontoxicity, and the natural abundance of sulfur, hold immense potential as the next‐generation energy storage technology. To maximize the actual energy density of the Li‐S batteries for practical applications, it is crucial to escalate the areal capacity of the sulfur cathode by fabricating an electrode with high sulfur loading. Herein, ultra‐high sulfur loading (up to 12 mg cm −2 ) cathodes are fabricated through an industrially viable and sustainable solvent‐free dry‐processing method that utilizes a polytetrafluoroethylene binder fibrillation. Due to its low porosity cathode architecture formed by the binder fibrillation process, the dry‐processed electrodes exhibit a relatively lower initial capacity compared to the slurry‐processed electrode. However, its mechanical stability is well maintained throughout the cycling without the formation of electrode cracking, demonstrating significantly superior cycling stability. Additionally, through the optimization of the dry‐processing, a single‐layer pouch cell with a loading of 9 mg cm −2 and a novel multi‐layer pouch cell that uses an aluminum mesh as its current collector with a total loading of 14 mg cm −2 are introduced. To address the reduced initial capacity of dry‐processed electrodes, strategies such as incorporating electrocatalysts or employing prelithiated active materials are suggested.

Chemistry↗
NASA NTRSDate not supplied

In-Situ Scanning Electron Microscope Experiments for Microscale Mechanical Testing and Validated Modeling of Fiber Reinforced Thermoplastics

A novel, in-situ, scanning electron microscope (SEM) mechanical testing capability for materials at the microscale which provides experimental validation to a machine learning (ML) toolset for full-field validation of physics-based micromechanics models is being developed by researchers at NASA Glenn Research Center. These are enabling technologies for the integration of multiscale digital twins for materials into system level models which will result in the improved performance, material discovery, reduced production cost and time, rapid characterization, and prognostic structural health monitoring (SHM) for materials and structures for extreme environments in support of NASA space exploration missions. In order to bridge the material structure-to-system gap for digital twins, physics-based models must be experimentally validated at multiple length scales. Seminal microscale experiments, conducted at the Air Force Research Laboratory (AFRL), were limited to transverse compression of single-layer, unidirectional thermoset polymer matrix composite (PMC) micropillar specimens [1]. The early phases of the current project followed those initial results and setup to reproduce the compression testing of PMC material on the custom-built piezoelectric actuated micromechanical testing rig built by MicroTesting Solutions LLC. In this work, samples of thermoplastic PMC material were first machined into 3 mm cubes, and then further machining and final milling was done using a Focused Ion Beam (FIB). The initial experiment was done on a pillar roughly 20 µm x 20 µm x 40 µm tall. Additional pillars were milled with final sizes ranging from 20 µm x 20 µm x 40 µm tall to 40 µm x 40 µm x 65 µm tall. A speckle pattern for in-situ full-field measurements using Digital Image Correlation (DIC) was applied with platinum, which was coated on the surface, and then the FIB was used to mill away some of the coating to produce an irregular pattern of Pt on the pillar surface. The samples were loaded into the custom testing rig and placed into the SEM and loaded under compression until failure. Images were collected in the SEM during testing. Post-processing of the images was conducted using DIC to obtain full-field displacement and strain measurements elucidating the role of the matrix as well as fiber-fiber interaction at the microscale within the composite subjected to compression loading well into the non-linear regime of the material. Moreover, the evolution of fiber-matrix debonding and matrix cracking is observed in-situ at the microscale. This data, along with images segmented with a newly developed ML toolset [2], was used to create and validate physics-based micromechanics models. An image of the failed micropillar is shown in Figure 1. The techniques developed in the initial compression experiment was tailored to the validation needs of the models and expanded to include different sized samples as well as possibly tension and fatigue.

Laura Wilson↗
NASA NTRS2026

Developing a Pyrolysis Gas Thermal Blocking Model for Reentry Demise

In NASA’s Object Reentry Survival Analysis Tool (ORSAT), aerodynamic drag and aerothermal heating coefficients are computed for each of the free-molecular, continuum, and transitional flow regimes using analytical and semi-analytical methods. These heating coefficients were derived for typical metallic materials that melt and do not have a strong gas-phase contribution to the flow in the boundary layer. Modern satellites typically feature fiber-reinforced polymer (FRP) components, such as solar array booms, facesheets of sandwich panels, or overwraps for composite-overwrapped pressure vessels (COPV). These FRP materials do not behave the same as metals in the reentry environment, but instead will pyrolyze and develop significant volumes of gas into the boundary layer. Accurately predicting the reentry demise of FRP components is critical to assessing the reentry casualty risk for modern spacecraft. Research in recent years has shown that this demisability can depend heavily on how the expulsion of gaseous pyrolysis products through the outer surface of the material affects the heat flux at the surface. The ODPO has been developing a reduced-order model of the effect of pyrolysis gas blowing on the heat flux based on correlations between a blowing factor and a non-dimensional heat flux to be incorporated in the upcoming version 7.3 of the Object Reentry Survivability Analysis Tool (ORSAT). This presentation discusses the progress of this development project and the challenges remaining for generalizing the model across families of FRP materials.

Benton Greene↗
DOE OSTI2026

Dissecting Disorder: Defect-Driven Structural Complexity in Layered Li3InCl6 Solid Electrolyte

Halide solid electrolytes have emerged as promising candidates for solid-state batteries owing to their high oxidative stability and ionic conductivity. Among them, Li3InCl6 (LIC) has attracted significant attention. However, diffraction patterns of LIC synthesized via different methods exhibit distinct differences particularly at low-angle reflectionsindicative of underlying structural disorder. These variations are attributed to deviations from ideal crystallographic order, especially stacking faults, whose impact on structure and ion transport remains poorly understood. Here, we identify and quantify stacking faults in LIC samples prepared under different synthetic conditions. Using X-ray diffraction and time-of-flight neutron diffraction, we construct and refine stacking fault models that accurately reproduce the experimental diffraction features. LIC samples with higher degrees of stacking faults exhibit only negligible differences in ionic conductivities and activation energies. This indicates that stacking faults have a limited impact on altering the Li+ diffusion pathway along the c-axis, likely due to the high concentration of vacancies in the In layers, while Li+ diffusion remains nearly unchanged in the ab-plane. Our results account for the observed differences in diffraction patterns across samples and provide a quantitative assessment of faulting probabilities and stacking sequences. The insights gained from this study are expected to be broadly applicable to other layered halide solid electrolytes and contribute to a deeper understanding of the role of structural disorder in ion transport.

Liu, Jue [ORNL] (ORCID:000000024453910X)↗
NASA NTRSDate not supplied

First-Principles Investigation of Phase Transitions in RuNb, RuTa, and Ru-Nb-Ta Ultrahigh Temperature Shape Memory Alloys

Ultrahigh temperature shape memory alloys (UHT-SMAs) have transition temperatures above 600 C, and they have found applications for sensing and actuating devices in aerospace industry. Among very few such UHT-SMAs currently known are Ru-based alloys such as RuNb and RuTa, whose martensite structures and phase transitions are totally different from those of NiTi-based SMAs and were poorly understood. In this work, we carried out a systematical study of RuNb using first-principles total energy calculations and molecular dynamics (MD) simulations. The transition paths and mechanisms in cubic → tetragonal →monoclinic transitions are revealed. and the transition sequence and martensitic transition temperatures are determined (MTTs) by evaluating the Gibbs free energies using thermodynamic integration. The calculated MTTs are in very good agreement with the experimental data. We found that the monoclinic phase at the second transition has the 𝑃21/m symmetry instead of experimentally identified 𝑃2/m. Our calculations demonstrate that RuTa has very similar phase transitions to those of RuTa. Furthermore, we studied the Ru0.5Nb0.25Ta0.25 ternary. Our results can explain the measured significant drop of MTT (~ 200 C) in the second transition for Ru0.5Nb0.25Ta0.25 compared with those of RuNb and RuTa, while in the first transition its MTT is between MTTs of RuNb and RuTa. The insights gained by this study and the verified ab initio methods for accurate MTT calculations can be applied to fast screen and quantitatively design novel UHT-SMAs having similar properties with desirable MTTs and much reduced cost.

Zhigang Wu↗
DOE OSTI2026

Quantum Filtering and Analysis of Multiplicities in Eigenvalue Spectra

Fine-grained spectral properties of quantum Hamiltonians, including both eigenvalues and their multiplicities, provide useful information for characterizing many-body quantum systems as well as for understanding phenomena such as topological order. Extracting such information with small additive error is #BQP-complete in the worst case. In this work, we introduce QFAMES (quantum filtering and analysis of multiplicities in eigenvalue spectra), a quantum algorithm that efficiently identifies clusters of closely spaced dominant eigenvalues and determines their multiplicities under physically motivated assumptions, which allows us to bypass worst-case complexity barriers. QFAMES also enables the estimation of observable expectation values within targeted energy clusters, providing a powerful tool for studying quantum phase transitions and other physical properties. We validate the effectiveness of QFAMES through numerical demonstrations, including its applications to characterizing quantum phases in the transverse-field Ising model and estimating the ground-state degeneracy of a topologically ordered phase in the two-dimensional toric code model. We also generalize QFAMES to the setting of mixed initial states. Our approach offers rigorous theoretical guarantees and significant advantages over existing subspace-based quantum spectral analysis methods, particularly in terms of the sample complexity and the ability to resolve degeneracies.

97 MATHEMATICS AND COMPUTING↗
NASA NTRSDate not supplied

The NASA Turbulent Heat Flux (THX) Experiments: Summary and Lessons Learned

The Turbulent Heat Flux (THX) experiments were conducted at NASA Glenn Research Center (GRC) in order to collect measurements of velocities and temperatures for computational fluid dynamics (CFD) validation of heated flows, with a focus on propulsion system components. The experiments spanned 5 phases; four of which were conducted in the GRC AeroAcoustic Propulsion Laboratory (AAPL) using the Small Hot Jet Flow Rig (SHJAR). In addition to making velocity measurements with Particle Image Velocimetry (PIV), the THX experiments introduced a new Raman-scattering based capability to measure temperatures. Computational studies were also conducted for each of the experimental configurations, in order to provide a baseline of expected CFD results and conduct an assessment of the capability of various CFD approaches for calculating flows where the turbulent transport of heat was important. Two of the collected sets of data were used for American Institute of Aeronautics and Astronautics (AIAA) Propulsion Aerodynamic Workshops (PAWs). The data set from the 5th phase, collected for heated supersonic jets, was also used to construct new validation cases for the NASA Turbulence Model Resource (TMR). This paper provides an overview of the experiments and associated computations for each of the 5 test phases. Key experimental findings are presented. Lessons learned are provided concerning the effect of computational modeling choice on accuracy of predicting turbulent flows where thermal transport is important. Emphasis is placed on comparing Reynolds-averaged Navier-Stokes approaches with large-eddy simulation approaches. The benefits of utilizing a conjugate heat transfer method in conjunction with CFD solver for film cooling is demonstrated.

RANS↗
DOE OSTI2026

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↗
DOE OSTI1995

Nuclear Safety [Vol. 36, No. 1, January-June 1995]

Nuclear Safety is a journal that covers significant issues in the field of nuclear safety. Its primary scope is safety in the design, construction, operation, and decommissioning of nuclear power reactors worldwide and the research and analysis activities that promote this goal, but it also encompasses the safety aspects of the entire nuclear fuel cycle, including fuel fabrication, spent-fuel processing and handling, and nuclear waste disposal, the handling of fissionable materials and radioisotopes, and the environmental effects of all these activities. Table of Contents for this issue follows. THE CHORNOBYL ACCIDENT: 1 The Chornobyl Accident Revisited, Part II: The State of the Nuclear Fuel Located Within the Chornobyl Sarcophagus, A A. Borovoi and A. R. Sich; GENERAL SAFETY CONSIDERATIONS: 33 Nuclear Power Safety in Central and Eastern Europe, R. Wilson; 46 Safety of Nuclear Power Reactors in the Former Eastern European Countries, S. Chakraborty; 53 Technical Note: On the Definition of Common-Cause Failures, H. Paula; ACCIDENT ANALYSIS: 58 Modeling and Analysis of Core-Debris Recriticality During Hypothetical Severe Accidents in the Advanced Neutron Source Reactor, S.-H. Kim, V. Georgevich, D. B. Simpson, C. O. Slater, and R. P. Taleyarkhan; 68 Ignitability of Hydrogen/Oxygen/Diluent Mixtures in the Presence of Hot Surfaces, R. K. Kumar and G. W. Koroll; 94 Coupled RELAP5 and CONTAIN Accident Analysis Using PVM, K. A. Smith, A. J. Baratta, and G. E. Robinson; CONTROL AND INSTRUMENTATION: 109 Application of Fuzzy Logic in Nuclear Reactor Control Part I: An Assessment of State-of-the-Art, A. S. Heger, N. K. Alang-Rashid, and M. Jamshidi; DESIGN FEATURES: 122 Twenty-Third DOE/NRC Nuclear Air-Cleaning and Treatment Conference, R. R. Bellamy, J. J. Hayes, and M. W. First; ENVIRONMENTAL EFFECTS: 135 Atmospheric Dispersion and the Radiological Consequences of Normal Airborne Effluents from a Nuclear Power Plant, D. Fang, C. Z. Sun, and L. Yang; 142 Calculation of Distribution Coefficients for Radionuclides in Soils and Sediments, I. Puigdomenech and U. Bergstrom: OPERATING EXPERIENCES: 155 Reactor Shutdown Experience, Compiled by J. W. Cletcher; U.S. NUCLEAR REGULATORY COMMISSION INFORMATION AND ANALYSES: 158 Operating Experience Feedback Report—Reliability of Safety-Related Steam Turbine-Driven Standby Pumps Used in U.S. Commercial Nuclear Power Plants, J. R. Boardman; 166 Turbine Building Hazards, H. L Ornstein; RECENT DEVELOPMENTS: 169 Reports, Standards, and Safety Guides, D. S. Queener; 175 Proposed Rule Changes as of Dec. 31,1994; ANNOUNCEMENTS: 32 Harvard School of Public Health In-Place Filter Testing Workshop; 134 International Conference on Advances in the Operational Safety of Nuclear Power Plants; 193 30th Tennessee Industries Week; 193 DOE Technical Standards Program 1995 Workshop; 194 Multiphase Flow Experiments and Instrumentation; 180 The Authors; 185 Indexes to Nuclear Safety, Volumes 34 and 35.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗