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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 505 records · Page 28

Supramolecular Self-Assembled Multi-Electron-Acceptor Organic Molecule as High-Performance Cathode Material for Li-Ion Batteries

Organic electrode materials possess many advantages such as low toxicity, sustainability, and chemical/structural tunability toward high energy density. However, to compete with inorganic-based compounds, crucial aspects such as redox potential, capacity, cycling stability, and electronic conductivity need to be improved. Herein, a comprehensive strategy on the molecular design of small organic electron-acceptor-molecule—hexaazatrianthranylene (HATA) embedded quinone (HATAQ) is reported. By introducing conjugated quinone moieties into the electron-deficient hexaazatriphenylene-derivative core, HATAQ with highly extended π-conjugation can yield extra-high capacity for lithium storage, delivering a capacity of 426 mAh g -1 at 200 mA g -1 (0.4C). At an extremely high rate of 10 A g -1 (19C), a reversible capacity of 209 mAh g -1 corresponding to nearly 85% retention is obtained after 1000 cycles. A unique network of unconventional lock-and-key hydrogen bonds in the solid-state facilitates favorable supramolecular 2D layered arrangement, enhancing cycling stability. To the best of the authors’ knowledge, the capacity and rate capability of HATAQ are found to be the best ever reported for organic small-molecule-based cathodes. Finally, these results together with density functional theory studies provide proof-of-concept that the design strategy is promising for the development of organic electrodes with exceptionally high energy density, rate capability, and cycling stability.

25 ENERGY STORAGE↗

Performance Limits of an Alternating Current Electroluminescent Device

Abstract The use of an alternating current (AC) voltage is a simple, versatile method of producing electroluminescence from generic emissive materials without the need for contact engineering. Recently, it was shown that AC‐driven, capacitive electroluminescent devices with carbon nanotube network contacts can be used to generate and study electroluminescence from a variety of molecular materials emitting in the infrared‐to‐ultraviolet range. Here, performance trade‐offs in these devices are studied through comprehensive device simulations and illustrative experiments, enhancing understanding of the mechanism and capability of electroluminescent devices based on alternating as opposed to direct current (DC) schemes. AC‐driven electroluminescent devices can overcome several limitations of conventional DC‐driven electroluminescent devices, including the requirement for proper alignment of material energy levels and the need to process emitting materials into uniform thin films. By simultaneously optimizing device geometry, driving parameters, and material characteristics, the performance of these devices can be tuned. Importantly, the turn‐on voltage of AC‐driven electroluminescent devices approaches the bandgap of the emitting material as the gate oxide thickness is scaled, and internally efficient electroluminescence can be achieved using low‐mobility single‐layer emitter films with varying thicknesses and energy barrier heights relative to the contact.

Wang, Vivian↗

Materials and techniques for spacecraft static charge control

An overview of the design, development, fabrication, and testing of transparent conductive coatings and conductive lattices deposited or formed on high resistivity spacecraft dielectric materials to obtain control static charge buildup on spacecraft external surfaces is presented. Fabrication techniques for the deposition of indium/tin oxide coatings and copper grid networks on Kapton and FEP Teflon films and special frit coatings for OSR and solar cell cover glasses are discussed. The techniques include sputtering, photoetching, silkscreening, and mechanical processes. A facility designed and built to simulate the electron plasma at geosynchronous altitudes is described along with test procedures. The results of material characterizations as well as electron irradiation aging effects in this facility for spacecraft polymers treated to control static charge are presented. The data presents results for electron beam energies up to 30 kV and electron current densities of 30 nA/cm squared. Parameters measured include secondary emission, surface leakage, and through the sample currents as a function of primary beam energy and voltage.

Amore, L. J.↗

Measuring thermal profiles in high explosives using neural networks

We present a new method for calculating the temperature profile of high explosive (HE) material using a Convolutional Neural Network (CNN). To train/test the CNN, we have developed a hybrid experiment/simulation method for collecting acoustic and temperature data. We experimentally heat cylindrical containers of HE material until detonation/deflagration, where we continuously measure the acoustic bursts through the HE using multiple acoustic transducers lined around the exterior container circumference. However, measuring the temperature profile in the HE in an experiment would require inserting a large number of thermal probes, which would disrupt the heating process. Thus, we use two thermal probes, one at the HE center and one at the wall. We then use numerical simulation of the heating process to calculate the temperature distribution and correct the simulated temperatures based on the experimental center and wall temperatures. We calculate temperature errors on the order of 15 °C, which is ∼12% of the range of temperatures in the experiment. We also investigate how the algorithm’s accuracy is affected by the number of acoustic receivers used to collect each measurement and the resolution of the temperature prediction. This work provides a means of assessing the safety status of HE material, which cannot be achieved using existing temperature measurement methods. In addition, it has implications for a range of other applications where internal temperature profile measurements would provide critical information. These applications include detecting chemical reactions, observing thermodynamic processes such as combustion, monitoring metal or plastic casting, determining the energy density in thermal storage capsules, and identifying abnormal battery operations.

97 MATHEMATICS AND COMPUTING↗

Investigation of glass-ceramic lithium thiophosphate solid electrolytes using NMR and neutron scattering

Solid-state Li batteries require solid electrolytes which have high Li+ conductivity and good chemical/mechanical compatibility with Li metal anodes and high energy cathodes. Structure/function correlations which relate local bonding to macroscopic properties are needed to guide development of new solid electrolyte materials. This study combines diffraction measurements with solid-state nuclear magnetic resonance spectroscopy (ssNMR) and neutron pair distribution function (nPDF) analysis to probe the short-range vs. long-range structure of glass-ceramic Li 3 PS 4 -based solid electrolytes. Here, we demonstrate how different synthesis conditions (e.g., solvent selection and thermal processing) affect the resulting polyanionic network. More specifically, structures with high P coordination numbers (e.g., PS 4 3– and P 2 S 7 4– ) correlate with higher Li + mobility compared to other polyanions (e.g., (PS 3 ) n n– chains and P 2 S 6 4– ). Overall, this work demonstrates how ssNMR and nPDF can be used to draw key structure/function correlations for solid-state superionic conductors.

36 MATERIALS SCIENCE↗

PemNet: A Transfer Learning-Based Modeling Approach of High-Temperature Polymer Electrolyte Membrane Electrochemical Systems

Widespread adoption of high-temperature electrochemical systems such as polymer electrolyte membrane fuel cells (HT-PEMFCs) requires models and computational tools for accurate optimization and guiding new materials for enhancing fuel cell performance and durability. Furthermore, while robust and better suited for extrapolation, knowledge-based modeling has limitations as it is time-consuming and requires information about the system that is not always available (e.g., material properties and interfacial behavior between different materials). Data-driven modeling, on the other hand, is easier to implement but often necessitates large datasets that could be difficult to obtain. In this contribution, knowledge-based modeling and data-driven modeling are combined by implementing a few-shot learning (FSL) approach. A knowledge-based model originally developed for a HT-PEMFCs was used to generate simulated data (887,735 points) and used to pretrain a neural network source model tuned via a genetic algorithm-based AutoML. Then, experimental datasets from HT-PEMFCs with different materials and operating conditions (~50 points each) were used to train six target models via FSL. Models for the unseen data reached high accuracies in all cases (rRMSE < 10%).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Ground-state-based model reduction with unitary circuits

Here, we present a method to numerically obtain low-energy effective models based on a unitary transformation of the ground state. The algorithm finds a unitary circuit that transforms the ground state of the original model to a projected wavefunction with only the low-energy degrees of freedom. The effective model can then be derived using the unitary transformation encoded in the circuit. We test our method on the one-dimensional and two-dimensional square-lattice Hubbard model at half-filling, and obtain more accurate effective spin models than the standard perturbative approach.

Hubbard model↗

Neuroevolutionary Learning of Particles and Protocols for Self-Assembly

Within simulations of molecules deposited on a surface we show that neuroevolutionary learning can design particles and time-dependent protocols to promote self-assembly, without input from physical concepts such as thermal equilibrium or mechanical stability and without prior knowledge of candidate or competing structures. Furthermore, the learning algorithm is capable of both directed and exploratory design: it can assemble a material with a user-defined property, or search for novelty in the space of specified order parameters. In the latter mode it explores the space of what can be made, rather than the space of structures that are low in energy but not necessarily kinetically accessible.

74 ATOMIC AND MOLECULAR PHYSICS↗

ACTS for distance education in developing countries

The need for electrical energy supply in the rural communities of developing countries has been well documented. Equally well known is the potential for photovoltaic in cost effectively meeting this need. A major impediment to fulfilling the need is the lack of indigenous personnel with a knowledgeof photovoltaic systems, and the associated infrastructure required to implement project. Various delivery schemes for providing the needed training to developing countries personnel have been investigated. Various train methods and programs that have been employed to remedy the problem have had significant drawbacks in terms of cost, consistency, impact, reach, and sustainability. The hypothesis to be tested in this project posits that satellite-based distance education using ACTS technologies can overcome these impediments. The purpose of the project is to investigate the applicability of the ACTS satellite in providing distance education in photovoltaic systems to developing countries and rural communities. An evaluation of the cost effectiveness of using ACTS unique technologies to overcome identified problems shall be done. The limitations of ACTS in surmounting distance education problems in developing countries shall be investigated. This project will, furthermore, provide training to Savannah State College faculty in photovoltaic (PV) systems and in distance education configurations and models. It will also produce training materials adequate for use in PV training programs via distance education. Savannah State College will, as a consequence become well equipped to play a leading role in the training of minority populations in photovoltaic systems and other renewables through its Center for Advanced Water Technology and Energy Systems. This communication provides the project outline including the specific issues that will be investigated during the project. Also presented i the project design which covers the participations of the various components of a network of institutions that is formed for optimal project execution. The expected results and project output, including plans for potential leverages and linkages to be derived, are also discussed. Finally, we point out possible extensions from this project and other related projects that could be initiated based on the experiences gained from the project.

Kalu, A↗

Multimode Metastructures: Novel Hybrid 3D Lattice Topologies

With the rapid proliferation of additive manufacturing and 3D printing technologies, architected cellular solids including truss-like 3D lattice topologies offer the opportunity to program the effective material response through topological design at the mesoscale. The present report summarizes several of the key findings from a 3-year Laboratory Directed Research and Development Program. The program set out to explore novel lattice topologies that can be designed to control, redirect, or dissipate energy from one or multiple insult environments relevant to Sandia missions, including crush, shock/impact, vibration, thermal, etc. In the first 4 sections, we document four novel lattice topologies stemming from this study: coulombic lattices, multi-morphology lattices, interpenetrating lattices, and pore-modified gyroid cellular solids, each with unique properties that had not been achieved by existing cellular/lattice metamaterials. The fifth section explores how unintentional lattice imperfections stemming from the manufacturing process, primarily sur face roughness in the case of laser powder bed fusion, serve to cause stochastic response but that in some cases such as elastic response the stochastic behavior is homogenized through the adoption of lattices. In the sixth section we explore a novel neural network screening process that allows such stocastic variability to be predicted. In the last three sections, we explore considerations of computational design of lattices. Specifically, in section 7 using a novel generative optimization scheme to design novel pareto-optimal lattices for multi-objective environments. In section 8, we use computational design to optimize a metallic lattice structure to absorb impact energy for a 1000 ft/s impact. And in section 9, we develop a modified micromorphic continuum model to solve wave propagation problems in lattices efficiently.

36 MATERIALS SCIENCE↗

Integration of LIBS with Machine Learning for Real-Time Monitoring of Feedstock in H 2 Gasification Applications

This project, funded by the U.S. Department of Energy (DOE) – Office of Fossil Energy under Award Number DE-FE0032177, aimed to assess the feasibility of an integrated Laser-Induced Breakdown Spectroscopy (LIBS) system with advanced machine learning (ML) models for real-time characterization and potential control of hydrogen gasifiers running on waste materials as feedstocks. This was a multidisciplinary effort that encompassed the acquisition and standardized analysis of individual and blended feedstocks—comprising biomass, coal waste, and plastic waste, followed by the development of a dynamic LIBS bench system for material sample analysis and development of predictive ML models. Comprehensive laboratory testing enabled the creation of a robust elemental dataset that served as the foundation for ML model training. Techniques such as Random Forest, Gradient Boosting, Support Vector Regression, and Neural Networks were employed to predict key feedstock properties, including higher heating value (HHV), moisture content, thermal conductivity, and ash composition with high accuracy. The results were validated against experimental data and demonstrated strong potential for real-time application in gasifier control systems. The project concluded with a study on the integration of the LIBS+ML approach for gasifier control and a techno-economic analysis of the implementation of the approach into hydrogen (H 2 ) gasification systems. Dissemination of results was carried out at a DOE meeting. This work establishes a scalable framework for automated, in-line feedstock quality assessment, offering significant implications for process optimization and emissions reduction in hydrogen production.

01 COAL, LIGNITE, AND PEAT↗

Li 21 Ge 8 P 3 S 34 : New Lithium Superionic Conductor with Unprecedented Structural Type

Abstract Lithium superionic conductors are pivotal for enabling all‐solid‐state batteries, which aim to replace liquid electrolytes and enhance safety. Herein, we report the discovery of an unprecedented lithium superionic conductor, Li 21 Ge 8 P 3 S 34 , featuring a novel structural type and a new composition in the Li–Ge–P–S system. This material exhibits high lithium ionic conductivity of approximately 1.0 mS cm −1 at 303 K with a low activation energy of 0.20(1) eV. It's unique crystal structure was elucidated using three‐dimensional electron diffraction (3D ED) and further refined through combined powder X‐ray and neutron diffraction analyses. The structure consists of alternating two‐dimensional slabs: one of corner‐sharing GeS 4 tetrahedra and the other of isolated PS 4 tetrahedra, enabling efficient lithium‐ion transport through a tetrahedrally interconnected network of 1D, 2D, and 3D diffusion pathways. This distinctive structural motif provides a novel design strategy for next‐generation solid electrolytes, broadening the structural landscape of lithium superionic conductors. With further advancements in compositional tuning and interfacial engineering, Li 21 Ge 8 P 3 S 34 could contribute to the development of high‐performance all‐solid‐state batteries.

Chemistry↗

High‐pressure Synthesis of Cobalt Polynitrides: Unveiling Intriguing Crystal Structures and Nitridation Behavior

Abstract In this study, we conduct extensive high‐pressure experiments to investigate phase stability in the cobalt‐nitrogen system. Through a combination of synthesis in a laser‐heated diamond anvil cell, first‐principles calculations, Raman spectroscopy, and single‐crystal X‐ray diffraction, we establish the stability fields of known high‐pressure phases, hexagonal NiAs‐type CoN, and marcasite‐type CoN 2 within the pressure range of 50–90 GPa. We synthesize and characterize previously unknown nitrides, Co 3 N 2 ,Pnma‐CoN and two polynitrides, CoN 3 and CoN 5 , within the pressure range of 90–120 GPa. Both polynitrides exhibit novel types of polymeric nitrogen chains and networks. CoN 3 feature branched‐type nitrogen trimers (N 3 ) and CoN 5 show π‐bonded nitrogen chain. As the nitrogen content in the cobalt nitride increases, the CoN 6 polyhedral frameworks transit from face‐sharing (in CoN) to edge‐sharing (in CoN 2 and CoN 3 ), and finally to isolated (in CoN 5 ). Our study provides insights into the intricate interplay between structure evolution, bonding arrangements, and high‐pressure synthesis in polynitrides, expanding the knowledge for the development of advanced energy materials

Chemistry↗

Structural Anomalies and Electronic Properties of an Ionic Liquid under Nanoscale Confinement

Ionic liquids (ILs) promise far greater electrochemical performance compared to aqueous systems, yet key physicochemical properties governing their assembly at interfaces within commonly used graphitic nanopores remain poorly understood. Here, we combine synchrotron X-ray scattering with first-principles molecular dynamics simulations to unravel key structural characteristics of 1-alkyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide ([TFSI] – ) ionic liquids confined in carbon slit pores. X-ray scattering reveals selective pore filling due to size exclusion, while filled pores exhibit disruption in the IL intermolecular structure, the extent of which increases for narrower slit pores. First-principles simulations corroborate this finding and quantitatively describe how perturbations in the local IL structure, particularly the hydrogen-bond network, depend strongly on the degree of confinement. Despite significant deviations in structure under confinement, electrochemical stability remains intact, which is important for energy storage based on nanoporous carbon electrodes (e.g., supercapacitors).

36 MATERIALS SCIENCE↗

Community Geothermal: Soil Conductivity, Borehole Design, Energy Models, and Load Data for a Residential System Development - Hinesburg, VT

This dataset contains materials from the Coalition for Community-Supported Affordable Geothermal Energy Systems (C2SAGES) project, which evaluated the techno-economic feasibility of a community geothermal system for a residential development in Hinesburg, VT. The dataset includes detailed soil conductivity test reports, energy models, borehole design reports, hourly energy loads for heating, cooling, and hot water, and design layouts. EnergyPlus was used to model building energy loads, and Modelica software was applied for geothermal loop sizing based on these loads and soil conductivity results. Python scripts for network design further refined the models. Key files include PDF reports on borehole design (with projections for 1-year, 15-year, and 30-year systems), soil conductivity test results, EnergyPlus modeling outputs, and 2D/3D design drawings in PDF, DWG, and DXF formats. Python notebooks for network design and OnePipe model files are also provided, with Modelica required for viewing certain files. Outputs and modeling data are in various formats including CSV, JPG, HTML, and IDF, with units and data clearly labeled to support understanding of system design and performance for the proposed geothermal solution.

15 GEOTHERMAL ENERGY↗

Traditional Forensic Examinations on Bulk Special Nuclear Material

The Federal Bureau of Investigation (FBI) Laboratory at Quantico, Virginia is responsible for the forensic examination of radiological evidence and evidence contaminated with radioactive materials. Due to these unique hazards and the necessary specialized safety protocols, the FBI has developed a network of Partner Laboratories (PLs) across the United States of America to support conventional forensic examinations of radiological evidence and evidence contaminated with radioactive materials. In support of this, the FBI Laboratory has established the Hazardous Evidence Analysis Team (HEAT), a group of qualified forensic examiners, scientists, technicians, and photographers who can deploy to laboratories outside of the FBI Laboratory at Quantico, VA to perform conventional forensics on evidence containing/contaminated with hazardous materials. One of the FBI’s PLs, the United States Department of Energy’s Los Alamos National Laboratory (LANL), in Los Alamos, New Mexico, has unique facilities, personnel, and procedures to secure, safely handle, and process significant quantities of special nuclear material (SNM). While LANL’s procedures for working with SNM are well established, working with SNM under evidentiary controls is not. Close cooperation between LANL and FBI HEAT is required due to FBI policies on evidence handling, as well as the challenges associated with the exploitation and preservation of conventional forensics (fingerprints, trace evidence, and photography) on SNM evidence.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

Evolution and use of combined mechanical and thermal codes for cryogenic turbopump bearings

Shaft bearing system analysis codes were developed, improved, and used to investigate Space Shuttle Main Engine (SSME) Liquid Oxygen (LOX) turbopump bearing problems, and to support the Marshall Space Flight Center Bearing and Seal Materials Test (BSMT) program. Thermal network modeling uses the SINDA thermal code, and the modeling of bearing quasi-dynamic characteristics uses the SHABERTH bearing/shaft code. These codes are solved concurrently for a bearing/shaft system using software developed for this purpose. Simulation of the SSME LOX turbopump turbine and pump end bearings and the MSFC BSMT operating in liquid nitrogen (LN sub 2) and LOX was done. The thermal network models include the bearing components, bearing carriers, shaft, housing, frictional heat, and viscous fluid energy. A cage model was included to account for heat generation between the cage and rolling elements. Since most bearing surfaces operate at temperatures well above the coolant saturation temperature, and move at high speed relative to the coolant, forced convection boiling is the dominant mechanism for heat removal. Improved modeling of forced convection film boiling was incorporated to take into account the local vapor generation at the high temperature surfaces. Rearing preloads in the pump and tester are provided by preload springs. As bearing operating clearances and contact angles change due to thermal effects and loading, the bearing preload changes with these varying conditions. These characteristics were modeled and are included in the overall system models. Results from these models indicate an operational limit which, if exceeded, predicts a thermal excursion.

Cody, Joe C.↗

Fabrication of Si-As-Te ternary amorphous semiconductor in the microgravity environment (M-13)

Ternary chalcogenide Si-As-Te system is an interesting semiconductor from the aspect of both basic physics and technological applications. Since a Si-As-Te system consists of a IV-III-II hedral bonding network, it has a very large glass forming region with a wide physical constant controllability. For example, its energy gap can be controlled in a range from 0.6 eV to 2.5 eV, which corresponds to the classical semiconductor Ge (0.66 eV), Si (1.10 eV), GaAs (1.43 eV), and GaP (2.25 eV). This fact indicates that it would be a suitable system to investigate the compositional dependence of the atomic and electronic properties in the random network of solids. In spite of these significant advantages in the Si-As-Te amorphous system, a big barrier impending the wide utilization of this material is the huge difficulty encountered in the material preparation which results from large differences in the weight density, melting point, and vapor pressure of individual elements used for the alloying composition. The objective of the FMPT/M13 experiment is to fabricate homogeneous multi-component amorphous semiconductors in the microgravity environment of space, and to make a series of comparative characterizations of the amorphous structures and their basic physical constants on the materials prepared both in space and in normal terrestrial gravity.

Hamakawa, Yoshihiro↗