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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 145 records · Page 8

Assessing the Intrinsic Roles of Key Dopant Elements in High–Nickel Layered Oxide Cathodes in Lithium–Based Batteries

A rational compositional design is critical for utilizing LiNiO 2 -based cathodes with Ni contents > 90% as promising next-generation cathode materials. Unfortunately, the lack of a fundamental understanding of the intrinsic roles of key elements, such as cobalt, manganese, and aluminum, makes the rational compositional design of high-Ni cathodes with a limited range of dopants (<10%) particularly challenging. Here, with 5% single-element doped cathodes, viz., LiNi 0.95 Co 0.05 O 2 , LiNi 0.95 Mn 0.05 O 2 , and LiNi 0.95 Al 0.05 O 2 , along with undoped LiNiO 2 (LNO), the influences of the dopants are systematically examined through a control of cutoff charge energy density and a common practice of cutoff charge voltage. Comprehensive investigations into the electrochemical properties, combined with in-depth analyses of the structural and interfasial stabilities and electrolyte decomposition pathways through advanced characterizations, unveil the following: i) the intrinsic role of dopants regulates the cathode energy density or state-of-charge and, more critically, the occurrence of H2–H3 phase transition, which essentially dictates cyclability; ii) undoped LNO can be stabilized well with the avoidance of H2–H3 phase transition; and iii) Co provides more merits overall with an optimized electrochemical operating condition. Finally, this work provides guidance for the compositional design of high-energy-density high-Ni cathodes and sheds light on the challenges of removing Co.

25 ENERGY STORAGE↗

Integral Experiment Request 554: CED-2 Summary Report

This report summarizes the critical experiment design 2 (CED-2) or final design study for Integral Experiment Request 554 (IER-554). This experiment describes the effects and importance of adding a commercially available neutron absorber material to a known light-water low-enriched uranium assembly. The assembly in question is the Seven Percent Critical Experiments (7uPCX) at Sandia National Laboratories. The neutron absorber plates considered for the experiment are known as Boralcan and are made of boron carbide (B 4 C) particles embedded in 1100 aluminum alloy. The concentrations of B 4 C and 1100 aluminum were changed as well as the thickness and the positions of the plates, and the fuel rod configuration was adapted to ensure that the assembly would be critical in each case studied. A total of 6 critical configurations, each with a neutron absorber plate inserted, are described in this report. No results of high-quality integral experiments involving neutron absorbers made with B 4 C and 1100 aluminum plates are currently publicly available. Sensitivity to the neutron absorber plate material definition, isotopes, and cross sections of specific regions and configurations are also analyzed. As part of the final design of the experiment, a safe plate holder made of 3003 aluminum was designed. The study results indicate that these experiments are achievable with sufficiently low uncertainties and minimal modification to the assembly, and the CED-3 phase can start when funding allows.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Computationally Guided and Experimentally Validated Design of Custom Chelators for Critical Mineral Recovery

Selective, high throughput separation of target critical metals from complex environments such as fly ash leachates and mining process streams presents a significant challenge for economical production. Custom chelators and sorbents are an attractive technology for selective metal extraction, however it can be difficult to predict their performance, and significant experimental efforts are often required to develop chelating technologies. Here, we present a computational strategy focused on modelling chelator-metal binding interactions and benchmark these results versus experimental data. A computational pipeline combining forcefield, semiempirical, and meta-GGA methods with a thermodynamic framework optimized for error cancellation has been developed to predict binding energies of chelator complexes towards critical mineral recovery applications. This approach, originally validated on [2.2.2] cryptates binding mono- and divalent cations, demonstrated robust predictive capabilities with an R2 of 0.850 against experimental aqueous binding energies. The workflow includes metadynamics for exploring high-dimensional potential energy surfaces and a cluster-continuum model for accurate yet computationally efficient solvation modeling. Error cancellation between solvation energies of free and chelator-coordinated ions enables faster convergence, even with finite cluster sizes. Initial studies on the cryptates revealed consistent metal-ligand coordination patterns, with systematic variations influenced by ion size and charge, highlighting key structural features linked to binding selectivity. Further studies of a proprietary chelator have resulted in identification of previously unreported selectivity towards economically significant metals, which in-house experiments have confirmed, demonstrating the feasibility of this approach. By applying this methodology to new chelators targeting critical minerals such as lithium, cobalt, nickel and other strategic metals, we aim to accelerate the discovery of next-generation chelators for efficient recovery, recycling, and separation processes. This computational framework serves as the backbone of a high-throughput design pipeline tailored for sustainable resource utilization and may be applied to a wide range of systems to meet experimental needs.

computational materials↗

Material Design Strategies for Recovery of Critical Resources from Water

Population growth, urbanization, and decarbonization efforts are collectively straining the supply of limited resources that are necessary to produce batteries, electronics, chemicals, fertilizers, and other important products. Securing the supply chains of these critical resources via the development of separation technologies for their recovery represents a major global challenge to ensure stability and security. Surface water, groundwater, and wastewater are emerging as potential new sources to bolster these supply chains. Recently, a variety of material-based technologies have been developed and employed for separations and resource recovery in water. Judicious selection and design of these materials to tune their properties for targeting specific solutes is central to realizing the potential of water as a source for critical resources. Here, the materials that are developed for membranes, sorbents, catalysts, electrodes, and interfacial solar steam generators that demonstrate promise for applications in critical resource recovery are reviewed. In addition, a critical perspective is offered on the grand challenges and key research directions that need to be addressed to improve their practical viability.

36 MATERIALS SCIENCE↗

A Review of TSUNAMI Applications

The TSUNAMI-1D and TSUNAMI-3D sequences for generating k eff sensitivity coefficients were first released in SCALE 5 in 2004. Several other tools were introduced in the same release, including primarily the TSUNAMI-IP code for uncertainty analysis and similarity assessments. The TSUNAMI sequences added capabilities for identifying important reactions and data for systems using sensitivity coefficients and also introduced new quantitative tools for rigorously assessing the similarity of systems. Over time, the capabilities of these tools have grown, and their use has expanded into other areas such as nuclear data assessment and nuclear covariance data testing. This paper discusses applications of the TSUNAMI tools for sensitivity calculations, sensitivity/uncertainty (S/U)-based validation, and nuclear data testing. This paper is one of a series of papers at this conference on the development and use of TSUNAMI tools. The other papers address the development of the TSUNAMI methods and the use of TSUNAMI for critical experiment design and optimization.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Sensitivity-based Experiment Design Optimization for a Molybdenum Critical Experiment

A lack of intermediate molybdenum benchmarks in the ICSBEP has been identified by LANL, Y-12, and IRSN. This lacking adversely effects criticality safety operations and leaves new differential molybdenum data unvalidated. NCERC is proposing a series of intermediate integral experiments to better the understanding of molybdenum systems. Using MCNP6.2 with the ENDF/B-VIII.0 nuclear data library a single unmoderated and four moderated system designs were identified using a sensitivity optimization method. Each proposed system was found to be at least twice as sensitive to the 95 Mo capture cross section in the URR as the sole existing intermediate molybdenum benchmark in the ISCBEP handbook. The addition of a new molybdenum sensitive intermediate system would improve future nuclear data evaluations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

A Visual Analytic Platform for Interactive Validation of Human Mobility Simulations

Human mobility insights guide domain experts in an array of decisions, including critical infrastructure design, disaster response, epidemic modeling, national security, and policy making. Due to the inherent noise and privacy concerns in real-world individual-level mobility data, it is often preferred to leverage simulators that generate synthetic mobility data instead. However, it is critical to inspect and validate the output of such simulators to ensure the synthetic data is aligned with the characteristics of the population and the area of interest known to domain experts. While there exist many quantitative approaches for validating synthetic data, we argue it is also important to also validate such data qualitatively to capture aspects that are known to domain experts but difficult to quantify. In this work, we demonstrate a visual analytic platform that empowers domain experts to interact with their simulation outputs along spatial and temporal dimensions. By augmenting automated techniques and human skills, our visual analytic platform is a step towards interactive capabilities for model steering and quality control of mobility simulators.

Monadjemi, Shayan↗

Fast extraction of nickel from aqueous media by using ionic metal-organic frameworks

As global demand for stainless steel rapidly increases, supply for minerals such as nickel, manganese, and chromium become more critical. To shift mineral peak production and delay scarcity of alloying minerals, recycling rate of the mineral needs to increase. Development of simple and cost-effective techniques for critical mineral production and recovery from industrial wastewater will lead to enhance the current recycling rate of the mineral and reduce potential hazards of industrial wastewater bearing high concentrations of minerals. Here, in this study, ionic metal-organic framework (iMOF)-based sorbents are successfully designed for critical metal ion extraction from aqueous solution. The iMOFs are highly stable in aqueous solution over wide pH ranges, indicating that they are suitable for use in industrial wastewater with harsh chemical environments. The sorption capacity of iMOFs towards Ni reaches 34.1 mg/g with a removal efficiency of >99.9%. Notably, complete extraction of Ni takes place within 5 min, which is much faster compared to other sorbents. Moreover, the iMOFs can simultaneously coextract multiple minerals, proving their effectiveness as general sorbents for critical mineral recovery.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Development of a Modular, Crushed-Rock Thermal Energy Storage Pilot Design

The goal of this project, primarily funded by the U.S. Department of Energy, is to design a next-step pilot to advance near-term energy storage integrated with a fossil plant to provide a facility capable of being viable and effective in a market with growing penetration of variable renewable energy (VRE). Thermal energy storage (TES) represents an ideal technology for this purpose. The current effort will complete a feasibility study to prepare for the Phase II pre-front end engineering design (pre-FEED) for implementing a crushed-rock TES system integrated with a natural gas combined cycle (NGCC) plant. The crushed rock storage technology, which is being developed by Brenmiller Energy, is a modular TES system termed bGen™, which can accommodate both thermal and electrical inputs and output steam, hot water, or hot air. For this application, the estimated efficiency is 80% thermal to thermal. The TES technology is being designed to operate on a slipstream from NYPA’s Eugene W. Zeltmann Power Project (Zeltmann) natural gas combined cycle (NGCC) plant. The projected size of the system will be up to 4 MWe with at least 4 hours of storage duration, or 16 MWh-e total. Final sizing is being determined during the ongoing feasibility study. The next-step pilot being designed as part of the current project will represent a 5-fold increase in scale for this TES technology, and will be used to validate the technology’s ability to provide effective and economical energy storage. This pilot would represent the next-to-last demonstration scale before the technology could be commercial ready at GWh-e scales in the 2030 timeframe. This project is expected to design the critical next-step pilot, which will be undertaken in real-world operating conditions to better determine the crushed rock TES technology’s ability to be integrated with an NGCC plant and assess degradation over transient cycling at rates befitting various marketplaces. The crushed-rock TES pilot design is a technically feasible next step in the development of the technology and is built upon years of prior testing and demonstration. The proposed TES technology was developed by Brenmiller over the last 8 years and has been tested in 3 generations of demonstration units at various sites, globally. During this field testing, different characteristics and performance of the technology were validated, including the following key features: energy storage capacity, energy storage charge/discharge rate, energy storage loses, energy storage mechanical testing. This presentation will provide an update on the results of the conceptual design study for the modular crushed-rock TES system, integrated with a NGCC power plant.

03 NATURAL GAS↗

Artificial Intelligence for Autonomous Molecular Design: A Perspective

Domain-aware artificial intelligence has been increasingly adopted in recent years to expedite molecular design in various applications, including drug design and discovery. Recent advances in areas such as physics-informed machine learning and reasoning, software engineering, high-end hardware development, and computing infrastructures are providing opportunities to build scalable and explainable AI molecular discovery systems. This could improve a design hypothesis through feedback analysis, data integration that can provide a basis for the introduction of end-to-end automation for compound discovery and optimization, and enable more intelligent searches of chemical space. Several state-of-the-art ML architectures are predominantly and independently used for predicting the properties of small molecules, their high throughput synthesis, and screening, iteratively identifying and optimizing lead therapeutic candidates. However, such deep learning and ML approaches also raise considerable conceptual, technical, scalability, and end-to-end error quantification challenges, as well as skepticism about the current AI hype to build automated tools. To this end, synergistically and intelligently using these individual components along with robust quantum physics-based molecular representation and data generation tools in a closed-loop holds enormous promise for accelerated therapeutic design to critically analyze the opportunities and challenges for their more widespread application. This article aims to identify the most recent technology and breakthrough achieved by each of the components and discusses how such autonomous AI and ML workflows can be integrated to radically accelerate the protein target or disease model-based probe design that can be iteratively validated experimentally. Taken together, this could significantly reduce the timeline for end-to-end therapeutic discovery and optimization upon the arrival of any novel zoonotic transmission event. Our article serves as a guide for medicinal, computational chemistry and biology, analytical chemistry, and the ML community to practice autonomous molecular design in precision medicine and drug discovery.

59 BASIC BIOLOGICAL SCIENCES↗

Sensitivity Studies, Gap Analysis, and Benchmark Experiment Optimization for Reactor Applications

In regards to nuclear data, some reactor applications may lack validation experiments, which reduces confidence in predicted results. This is especially true for emerging advanced reactor, micro reactor, and Accelerator Driven System (ADS) designs. This work presents an approach to design new criticality experiments that have similar k eff cross section sensitivities to an application of interest. This process involves simulations to generate cross-section sensitivities to a parameter of interest (such as k eff ), a gap analysis to determine which existing benchmarks are most similar to the application, and an experiment optimization. This work focuses on cross-section sensitives and gap analysis for three examples relevant to the reactor physics community including a Travelling Wave Reactor (TWR) type-design, Kilopower (a space reactor design), and a lead-bismuth eutectic cooled accelerator-driven system (ADS) to transmute minor actinides.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Roadmap of Solid-State Lithium-Organic Batteries toward 500 Wh kg –1

Over the past few years, solid-state electrolytes (SSEs) have attracted tremendous attention due to their credible promise toward high-energy batteries. In parallel, organic battery electrode materials (OBEMs) are gaining momentum as strong candidates thanks to their lower environmental footprint, flexibility in molecular design and high energy metrics. Integration of the two constitutes a potential synergy to enable energy-dense solid-state batteries (SSBs) with high safety, low cost, and long-term sustainability. Here, we present the technological feasibility of combining OBEMs with SSEs along with the possible cell configurations that may result from this peculiar combination. We provide an overview of organic SSBs and discuss their main challenges. We analyze the performance-limiting factors and the critical cell design parameters governing cell-level specific energy and energy density. Lastly, we propose guidelines to achieve 500 Wh kg –1 cell-level specific energy with solid-state Li–organic batteries.

25 ENERGY STORAGE↗

Recent trends in all-organic polymer dielectrics for high-temperature electrostatic energy storage capacitors

Electrostatic energy storage (EES) capacitors are critical for renewable energy and high-power systems, driving the search for dielectric materials that combine superior electrical insulation, mechanical flexibility, low density, cost-effectiveness, and processability. Polymer-based dielectrics have emerged as leading candidates, particularly for high electric field applications. However, conventional polymers often fail to meet the demands of high-temperature environments due to increased electrical conductivity and reduced discharged energy density at elevated temperatures, resulting in energy loss and reduced performance. High glass transition temperature (T g) polymers show promise but require further optimization to enhance their energy storage capabilities under thermal and electrical stress. This review provides a comprehensive update on recent advancements in high-T g polymer-based dielectrics for EES capacitors, focusing on both intrinsic polymers and all-organic composites. It outlines key design principles, critical performance parameters, and innovative strategies—such as nanofiller doping, layered architectures, physical blending, and chemical crosslinking—to improve electrical, thermal, and mechanical properties. The review also highlights emerging trends, including the integration of machine learning algorithms to explore novel polymer structures and expand the chemical design space. By bridging the gap between academic research and industrial application, this review aims to accelerate the development of next-generation dielectric materials capable of balancing multiple performance metrics for high-temperature EES capacitors.

Xie, Zongliang↗

Sensitivity Coefficients Calculated for the Prompt Neutron Decay Constant At or Near Delayed Critical

The derivation of a non-invasive prompt neutron decay constant sensitivity coefficient is provided in this work. The computation of the sensitivity coefficient derived in this work does not require modification of Monte Carlo source code and is based on capabilities available in Monte Carlo N-Particle R© Code Version 6.2. The prompt neutron decay constant sensitivity coefficients are calculated for 44-group and 252-group energy structures for specific nuclide-reaction pairs in the Jezebel benchmark experiment. The nuclide-reaction pairs investigated in this work include Pu- 239(n,f), Pu-240(n,f), and Pu-241(n,f). Physical explanations of the sensitivity profiles exhibited by the 252-group energy structure are investigated for the prompt neutron multiplication factor, mean neutron lifetime, and prompt neutron decay constant. The prompt neutron decay constant sensitivity coefficients calculated for the 44-group and 252-group energy structure of Pu-239(n,f) are compared. Lastly, the 44-group energy structure sensitivity coefficients calculated are used for nuclear-data induced uncertainty quantification of the neutron multiplication factor. This work shows that a reduction in the nuclear data-induced uncertainty of the neutron multiplication factor is possible for all nuclide-reaction pairs investigated when prompt neutron decay constant sensitivity coefficients are utilized. This is important for new critical experiment design optimization studies of measurement configurations. This work provides a basis for more detailed sensitivity analysis and uncertainty quantification of nuclide, reaction, and energy-specific cross section data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Optimization of screw design for continuous wet granulation: A case study of metoprolol succinate ER tablets

This study aimed at understanding the effect of screw design on the critical characteristics of granules and tablets of an extended-release (ER) formulation for twin screw granulation process. The screw design parameters assessed included number of kneading elements (KEs) per kneading zone, distance separating kneading zones, staggering angle (SA) of kneading elements and number of sizing elements (SEs). These input variables were varied using a design of experiment (DoE) approach to manufacture granules. Particle size distribution (PSD), flow and bulk properties of the granules, breaking strength and dissolution of tablets manufactured using these granules were characterized. The results of least square fitting showed that KEs, SA, and SEs of the screws significantly (p -values < 0.05) affected the PSD, cohesion, compressibility (CPS), conditioned bulk density (CBD) and permeability of the granules. The KEs and SEs significantly (p -value < 0.05) affected the dissolution, which was attributed to their effects on CPS and CBD of the granules. The distance between kneading zones had no significant effect on granules and tablet characteristics. Finally, these results may be used to further study the interaction of the identified critical screw design parameters with other processing parameters for continuous manufacturing of this ER matrix-based tablet formulation.

60 APPLIED LIFE SCIENCES↗

Local Structural Coherence and Interfacial Charge Transfer in Cu 2 ⁢S/Mo⁢S 2 Heterostructure

Precise control over electronic coupling at nanoscale interfaces is critical for designing materials with tunable charge-transfer behavior and catalytic function. Heterostructures with locally coherent interfaces provide a platform for interrogating interfacial charge redistribution in coupled material systems. Here, we report Cu 2 ⁢S/Mo⁢S 2 heterostructures exhibiting nanoscale crystallographic alignment, which are synthesized through a rapid thermal transformation pathway. We employed electrochemical reduction reactions to probe interfacial charge transfer, revealing shifts in product distribution attributable to modified interfacial energetics, even in the absence of optimized catalytic performance. The observed formate Faradaic efficiency suggests that interfacial electronic modulation in the heterostructure shifts product selectivity towards formate, highlighting how interface-driven electronic modulation can direct reaction pathways and influence product selectivity. Optimizing catalyst loading, architecture, and reactor configuration will be critical for future improvement. Structural and compositional integrity were confirmed through powder x-ray diffraction, x-ray photoelectron spectroscopy, and high-resolution transmission electron microscopy. Electron transfer between Cu 2 ⁢S and Mo⁢S 2 domains was further evaluated by electrochemical impedance spectroscopy, while selected-area electron diffraction revealed local crystallographic alignment consistent with a local epitaxial relationship at the Cu 2 S/Mo⁢S 2 heterointerface. To illustrate the broader applicability of this approach, a Zn⁢S/Mo⁢S 2 heterostructure was also synthesized using the same microwave strategy, confirming the generalizability of interfacial engineering principles across metal sulfide-Mo⁢S 2 systems. Collectively, these findings demonstrate that controlled local epitaxial alignment serves as an effective design principle for tuning interfacial energetics and catalytic reactivity in complex heterostructure materials.

carbon capture & utilization↗