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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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Group14 Technologies is leading a word-class team composed of Cabot Corporation, Silatronix, Arkema, Pacific Northwest National Laboratories, and Farasis Energy to research, fabricate, test and demonstrate lithium-ion batteries (LIB) implementing ≥30% silicon-carbon (Si-C) composite anode material achieving aggressive next generation automotive energy targets.
All magnetically confined plasma fusion power plant concepts (Tokamak, Spherical Tokamak, Stellarator, Mirror, ...) must exhaust the heat and plasma from the core confinement region to the material walls. The primary channel for this exhaust is through a plasma divertor which directs plasma along open magnetic field lines to a material target. The Material Plasma Exposure eXperiment (MPEX) illustrated in Figure 1, is a high-power, steady-state linear plasma device designed to produce the plasma material interaction (PMI) conditions of the divertor of future magnetic confinement fusion power plants: energy flux 20MW/m 2 , ion fluence 1031/m 2 , pulse duration 106 sec. These goals of plasma exposure in MPEX are well beyond those achieved in magnetic fusion experimental devices. Successfully achieving these high power steady state conditions for long pulses requires operational control of the heating and particle sources and the plasma flux to the walls and target. The MPEX AI Hot Spot Controller, proposed in this project, will help achieve the operational milestones of MPEX. The MPEX device will begin commissioning at the end of FY26. A smaller proto-MPEX was operated for 14,666 plasma discharges and will resume operation in September of 2025 as proto-MPEX-lite, with reduced capability, to test a new window for the Helicon plasma source. The proto-MPEX data has undergone surrogate modeling with machine learning methods (R. Archibald, 2022 IEEE International Conference on Big Data). This proto-MPEX data will be used to begin development of the AI digital twins described in this white paper. The scientific mission of MPEX is to qualify materials of different composition for use in the high energy and plasma flux conditions of a fusion power plant. The materials exposed in MPEX will in some cases be exposed to high neutron fluxes at other ORNL facilities to measure the changes to their PMI properties. The targets exposed in MPEX will be transported under vacuum to a Surface Analysis Station (SAS). The SAS will be equipped with the following diagnostics: Focused Ion Beam (FIB) for trench milling, 100-400 angstrom resolution scanning electron microscope (SEM), surface mapping x-ray spectrometer, high resolution camera, and a future upgrade to a laser induced breakdown spectroscopy quadruple mass spectrometer (LIBS-QMS). The MPEX experiments will generate diverse pre- and post-exposure measurement data of detailed material properties down to the crystal grain level in 3D for post-exposure assessment of PMI damage (e.g. cracking, melting, erosion and redeposition of the material). Physics models for the PMI, and how the material composition and manufacturing impact its performance under high energy plasma exposure, need to be validated with MPEX data to guide the selection of new candidate materials. Our vision for the MPEX AI Digital Twins project is to supply experimental and physics model simulation data to train Artificial Intelligence (AI) models for data processing, analysis, operational control, PMI and materials simulation to maximize the scientific output of the MPEX device. Ultimately, an AI digital twin of MPEX material assessment metrics for tested and synthetic material types with simulated PMI will be trained by the AI Modeling Teams on the experimental and physics simulation data submitted to the American Science Cloud by this project. A purely empirical search for the best material is inefficient given the finite number of samples that can be tested on MPEX. In order to expand the material properties database for training the MPEX Material Assessment AI Digital Twin, and to gain physics understanding of the PMI processes, physics models of the material properties and PMI processes are required. The physics simulations provide detailed simulation data, like impact angles for plasma ions, sputtering yields, transport of the ionized sputtered target material in the plasma, and redeposition locations. This simulation data expands the measurement data for deeper physics understanding. The experimental data is essential to validate the PMI and material structure simulation models. The validated models can then be used to generate new simulation data of MPEX material assessments for synthetic material compositions that have not been exposed in MPEX. These predictive simulations, plus the whole experimental dataset, will be used to train the MPEX Material Assessment AI Digital Twin allowing a rapid generative AI search for new materials with reduced PMI damage by interpolating the domain of the training set. These new optimum materials can be simulated with the physics codes and/or tested in MPEX. The ability of AI neural networks to interpolate multi-dimensional parameter spaces and generate virtual data is exploited for a more efficient search for optimum materials. The advent of the Transformational AI Models Consortium (TAIMC) is an opportunity to engage with state of the art private and public AI developers to achieve the goals of the AI digital twins and AI accelerated physics models proposed in this project. Our partners at ORNL from the Advance Scientific Computing Research (ASCR) organization will collaborate in accelerating the integrated plasma material interaction simulation framework. This simulation framework will provide a platform for generating simulation data across a range of physical fidelities, including hybrid methods that produce multi-fidelity results. This data will be leveraged for AI model development, both for generation of surrogates and the automation of simulation campaigns. A part of the research below will include collaborative efforts with the TAIMC to (i) adapt data storage approaches to ensure AI-readiness, (ii) provide a protypical exemplar to inform and exercise constructed workflows, and (iii) generate and share data, using the TAIMC unified AI data standard, for foundational models that will be trained from multiple sources across the DOE complex. We will also collaborate with the TAIMC, as well as the planned AI modeling teams, to develop approaches for reducing the cost of data generation. These include tailored multi-fidelity approaches as well as fine-tuning strategies to augment general, large-scale foundational models.
Conference presentation for 2023 International Freiberg Conference on Circular Carbon Technologies, Rotterdam, Netherlands, September 24–29, 2023. To assist in meeting the global graphite supply limitations, this study aims to investigate efficient ways to synthesize high-quality graphite from abundant coal and coal waste resources that exist in many areas around the world. A recently developed upgraded coal-to-products (UCP) process has shown great promise in the ability to reduce coal-borne impurities and produce a graphitizable product that yields good quality graphite for LIB applications. Preliminary results show that the quality of coal-derived graphite obtained by the UCP process is similar to that of commercial flake graphite. Available results are presented and discussed as well as maturation plans and flexibility of the UCP technology.
This project addresses the failure of conventional electrolytes and enables high-voltage operation of lithium-ion batteries (LIBs) by developing a novel organosulfur-based electrolyte system. To achieve this goal, we first designed and synthesized new organosulfur solvents that functionalized with strong electron-withdrawing groups such as fluoroalkyl and cyano substituents. Through regio-specific molecular engineering, supported by theoretical calculations, we lowered the highest occupied molecular orbital (HOMO) energy levels of these molecules to increase their anodic stability for high-voltage operation. We then optimized the formulation of the organosulfur-based electrolyte with additives, co-solvents and salts tailored to the newly synthesized solvent molecules. In parallel, we utilized advanced spectroscopic techniques—including in situ FTIR, EIS, and DEMS—to thoroughly elucidate the mechanisms of interaction between the electrolyte and electrode materials. Finally, we evaluated 2 Ah pouch cells under both normal and extreme conditions. Pouch cells with the newly developed electrolyte system demonstrated >90% capacity retention after 500 cycles under 4.5 V operating voltage, >80% capacity retention after 1000 cycles in coin cell level. In addition, the cells exhibited high safety and reliable operation capability over a wide temperature range from −30 °C to +45 °C.
This project supports the development of real time optical monitoring capabilities for molten salt reactor (MSR) environments by designing, testing, and refining a molten salt circulation loop suitable for combined laser induced breakdown spectroscopy (LIBS) and ultraviolet visible (UV Vis) absorption measurements. Online spectroscopic monitoring is increasingly important for nuclear safeguards, corrosion tracking, and material accountancy, yet MSR process fluids present substantial challenges due to their chemical complexity and hazards such as high temperatures and radiation. To address these needs, this work focuses on Phase I, the development of a room temperature aqueous circulation loop that serves as a surrogate platform for evaluating flow behavior, optical access, and component performance prior to high temperature salt operation. Initial testing identified several practical issues—including leaks, obstructions, and two-phase flow through the absorption cell—that were systematically resolved through hardware replacement, flow path redesign, and venturi pressure optimization. Relocating the flow cell upstream of the primary venturi enabled periods of stable single-phase flow, demonstrating the feasibility of integrating optical diagnostics into a circulation system. The results of Phase I provide essential design insight for Phase II, which will incorporate furnace compatible materials and LiCl KCl eutectic salt. Completion of the molten salt system will deliver a reusable testbed for evaluating multimodal spectroscopic techniques, advancing nondestructive, real time monitoring tools for future MSR and nuclear fuel cycle applications.
This data consists of simulations and experimental measurements of laser-induced breakdown spectroscopy (LIBS). The simulations are produced by ATOMIC, a general purpose plasma modeling and kinetics code that has been designed to compute emission (or absorption) spectra from plasmas [1]. Our overall suite of simulations contains 12 sets of simulations: training and validation sets of simulations for each of two resolutions of each of sodium, copper, and mixtures of the two. The training data were produced using a 500-run design that varies input parameters temperature (T), electron density (Ne), proportion of sodium (pNa), and proportion of copper (pCu). The latter two variables sum to one and are unused in the single-element simulations. The validation data was produced with a 25-run design. The coarse simulations produce spectra over a range of 240nm - 880nm that roughly mimics the range collected by the ChemCam instrument on the Mars rover Curiosity. The fine resolution simulations produce spectra over a range of 550nm to 600nm and were produced to mimic the included experimental results. The experimental results cover four mixtures of sodium and copper. All data sets are kept in zip files whose names indicate the elemental composition (NaCu, Na, or Cu), resolution (coarse or fine), and purpose (training or validation) with file names numbered to indicate the line in the design files used to produce the simulation. The designs are provided as text files with names indicating their purpose. The experimental data is provided as a CSV file. See attached abstract for figures.
This data consists of simulations and experimental measurements of laser-induced breakdown spectroscopy (LIBS). The simulations are produced by ATOMIC, a general purpose plasma modeling and kinetics code that has been designed to compute emission (or absorption) spectra from plasmas [2]. The makeup of the plasma was considered to be divided into some proportion water, some proportion Martian atmosphere (CO2), and some proportion target (from the rock or object impacted by the laser), where these proportions add to 1. Based on expert knowledge, the proportion of water was kept in the range [0.0,0.5] and the proportion of atmosphere was kept in the range [0.02, 0.9]. Our overall suite of simulations contains six sets of simulations that differ in which elements were considered to make up the target. Within each set, we used uniformly drawn temperatures and log mass densities within pre-specified ranges. The temperature range was [0.5,1.5] eV and the log (base 10) mass density range was [-7,-4]. The proportion of water, atmosphere, and target were drawn from a symmetric Dirichlet distribution, but draws in which the propor- tion of water or atmosphere exceeded the pre-specified limits were rejected from the design. Up to eleven constituent elements (Si, Al, Fe, Mg, Ca, O, Ti, Mn, Na, K, P) were considered for the target, as they are the most common elements found in basalt compounds and were used in [1]. For each run, the proportions of the constituent elements making up the target were drawn from a symmetric Dirichlet distribution. We ran 1,350 simulations that included nonzero proportions of all eleven elements. We also ran simulations which excluded some of these elements. In particular, we ran 1,000 simulations that only included nonzero proportions for the six most common elements (Si, Al, Fe, Mg, Ca, O). We also ran five sets, each with 500 simulations, that only included nonzero proportions for five of the six most common elements (but where all sets included O). Thus, we generated a total of 4,850 spectra representing basalt-like compounds in which the target was comprised of oxygen and between four and ten other elements. The ATOMIC code produced spectra over a range of 240nm - 880nm that roughly mimics the range collected by the ChemCam instrument on the Mars rover Curiosity. Each spectra had 32,000 wavelengths split across three spectrometer ranges (to mimic ChemCam). The experimental data, described in [1], measures a prepared basalt sample. All files are kept in directories whose names indicate the set of elements considered for the target with file names numbered to indicate the line in the design files used to produce the simulation. The designs are provided as text files with names indicating their purpose. The experimental data is provided as a CSV file which contains a header with measurement information, followed by a collection of 50 shots across a collection of wavelengths, along with the computed median and mean across shots.
Electrochemical impedance spectroscopy (EIS) is a valuable technique to detect the health status and aging phenomena in lithium-ion batteries (LiB). Equivalent circuit modeling (ECM) is conventionally used when interpreting EIS data and gaining physical insights into the aging mechanisms. However, performing ECM is resource intensive and expert-level of knowledge is usually required to select suitable models and fitting parameters. This article presents a quick and user-friendly data analysis algorithm as an alternative to ECM by mathematically fitting geometric features in Nyquist plots and obtaining the growth trends of the features. The evolving trends in the Nyquist plots, such as chord lengths of the arcs and interception points, are consistent with the growth of resistance components obtained using ECM with R 2 values from 0.67 to 0.99, and therefore can be used as indicators of battery aging. Our results show that the quick-fitting approach is suitable for analyzing a series of EIS data acquired during battery cycling and identifying the underlying aging mechanisms.
The ionome represents elemental composition in plant tissues and can be an indicator of nutrient status as well as overall plant performance. Thus, identifying genetic determinants governing elemental uptake and storage is an important goal for breeding and engineering biomass feedstocks with improved performance. In this study, we coupled high-throughput ionome characterization of leaf tissues with high-resolution genome-wide association studies (GWAS) to uncover genetic loci that modulate ionomic composition in leaves of poplar ( Populus trichocarpa ). Significant agreement was observed across the three ionomic profiling platforms tested: inductively coupled plasma-mass spectrometry (ICP-MS), neutron activation analysis (NAA) and laser-induced breakdown spectroscopy (LIBS). Relative quantification of 20 elements using ICP-MS across a population of 584 genotypes, revealed larger variation in micro-nutrients and trace elements content than for macro-nutrients across genotypes. The GWAS performed using a set of high-density (>8.2 million) single nucleotide polymorphisms, identified over 600 loci significantly associated with variations in these mineral elements, pointing to numerous uncharacterized candidate genes. A significant enrichment for genes related to ion homeostasis and transport was observed, including several members of the cation-proton antiporters (CPA) family and MATE efflux transporters, previously reported to be critical for plant growth and fitness in other species. Our results also included a polymorphic copy of the high-affinity molybdenum transporter MOT1 found directly associated to molybdenum content. For the first time in a perennial plant, our results provide evidence of genetic control of mineral content in a model tree species.
Low first-cycle Coulombic efficiency is especially poor for silicon (Si)-based anodes due to the high surface area of the Si-active material and extensive electrolyte decomposition during the initial cycles forming the solid electrolyte interphase (SEI). Therefore, developing successful prelithiation methods will greatly benefit the development of lithium-ion batteries (LiBs) utilizing Si anodes. In pursuit of this goal, in this study, lithium oxide (Li2O) was added to a LiNi0.6Mn0.2Co0.2O2 (NMC622) cathode using a scalable ball-milling approach to compensate for the initial Li loss at the anode. Different milling conditions were tested to evaluate the impact of particle morphology on the additive performance. In addition, Co3O4, a well-known oxygen evolution reaction catalyst, was introduced to facilitate the activation of Li2O. The Li2O + Co3O4 additives successfully delivered an additional capacity of 1116 mAh/gLi2O when charged up to 4.3 V in half cells and 1035 mAh/gLi2O when charged up to 4.1 V in full cells using Si anodes.
Ni-rich LiNixMnyCo1−x−yO2 (NMC) materials have been adopted in a range of applications, including electric vehicles. The recycled NMC material from a spent cell would be much more valuable if it could be upgraded to a Ni-rich, more energy-dense version of the material. This work demonstrates a simple, inexpensive, and facile method to upcycle LiNi1/3Mn1/3Co1/3O2 (NMC111, 160 mAh∙g−1), a cathode used in early generations of electric vehicle batteries, to LiNi0.8Mn0.1Co0.1O2 (NMC811, 190 mAh∙g−1), a more energy-dense cathode material. In this study, a preliminary investigation into a room-temperature eutectic synthesis of NMC811 is performed using NMC111, LiOH, and nickel nitrate as precursors. The synthesized material showed the desired crystal structure and stoichiometry, though the cycle life and Li diffusion coefficient need improvement when compared to commercially available NMC811. This study demonstrates an interesting proof of concept of the room-temperature eutectic synthesis process for LIB cathodes and could be improved by tuning the synthesis conditions.
High-entropy oxides (HEOs) have garnered significant interest as next-generation anode materials for lithium-ion batteries (LIBs) due to their high theoretical specific capacity and excellent structural stability. This study successfully synthesized spinel-structured (Al 0.2 Mn 0.2 Co 0.2 Ni 0.2 Zn 0.2 ) 3 O 4 HEO via a sol–gel method. The material was characterized by XRD, Raman and TEM, confirming a homogeneous single-phase spinel structure, with uniformly distributed elements-a hallmark of HEOs. Electrochemical tests demonstrated a stable cycling performance (438 mAh g −1 at 100 mA g −1 after 100 cycles and 350 mAh g −1 at 1 A g −1 after 1000 cycles) and rate capacity of 159 mAh g −1 at 2 A g −1 , The remarkable long-term cyclability and good rate capability highlight the potential of this HEO for practical applications in durable, high-power lithium-ion batteries. This work underscores the advantage of incorporating structurally stabilizing elements in HEOs for advanced energy storage.
The growing interest in sodium-ion batteries (SIBs) is driven by scarcity and the rising costs of lithium, coupled with the urgent need for scalable and sustainable energy storage solutions. Among various cathode materials, layered transition metal oxides have emerged as promising candidates due to their structural similarity to lithium-ion battery (LIB) counterparts and their potential to deliver high energy density at reduced costs. However, significant challenges remain, including limited capacity at high charge/discharge rates and structural instability during extended cycling. Addressing these issues is critical for advancing SIB technology toward industrial applications, particularly for large-scale energy storage systems. This review provides a comprehensive analysis of layered sodium transition metal oxides, focusing on their structural properties, electrochemical performance, and degradation mechanisms. Special attention is given to the intrinsic and extrinsic factors contributing to their instability, such as structural phase transitions, and cationic/anionic redox behavior. Additionally, recent advancements in material design strategies, including doping, surface modifications, and composite formation, are discussed to highlight the progress toward enhancing the stability and performance of these materials. This work aims to bridge the knowledge gaps and inspire further innovations in the development of high-performance cathodes for sodium-ion batteries.
The model of a graphene (Gr) sheet putting on a silicon (Si) substrate is used to simulate the structures of Si microparticles wrapped up in a graphene cage, which may be the anode of lithium-ion batteries (LIBS) to improve the high-volume expansion of Si anode materials. The common low-energy defective graphene (d–Gr) structures of DV5–8–5, DV555–777 and SV are studied and compared with perfect graphene (p–Gr). First-principles calculations are performed to confirm the stable structures before and after Li penetrating through the Gr sheet or graphene/Si-substrate (Gr/Si) slab. The climbing image nudged elastic band (CI-NEB) method is performed to evaluate the diffusion barrier and seek the saddle point. The calculation results reveal that the d–Gr greatly reduces the energy barriers for Li diffusion in Gr or Gr/Si. The energy stability, structural configuration, bond length between the atoms and layer distances of these structures are also discussed in detail.
Following the pulsation spectrum of a white dwarf through the heating and cooling involved in a dwarf nova outburst cycle provides a unique view of the changes to convective driving that take place on timescales of months versus millennia for nonaccreting white dwarfs. In 2019 January the dwarf nova V386 Ser (one of a small number containing an accreting, pulsating white dwarf) underwent a large-amplitude outburst. Hubble Space Telescope ultraviolet spectra were obtained 7 and 13 months after outburst along with optical ground-based photometry during this interval and high-speed photometry at 5.5 and 17 months after outburst. The resulting spectral and pulsational analysis shows a cooling of the white dwarf from 21,020 to 18,750 K (with a gravity $\mathrm{log}(g)=8.1$) between the two UV observations, along with the presence of strong pulsations evident in both UV and optical at a much shorter period after outburst than at quiescence. The pulsation periods consistently lengthened during the year following outburst, in agreement with pulsation theory. However, it remains to be seen if the behavior at longer times past outburst will mimic the unusual nonmonotonic cooling and long periods evident in the similar system GW Lib.
Benchmarks of Global Clean Energy Manufacturing provides an assessment of the global state of clean energy manufacturing over 3 years from 2014 to 2016. Four technologies were examined - wind turbine components (blade, tower, nacelle), crystalline silicon (c-Si) solar photovoltaic (PV) modules, light-duty vehicle (LDV) lithium-ion battery (LIB) cells, and light-emitting diode (LED) packages for lighting and other consumer products. The analysis looked along each technology's manufacturing supply chain, including processing raw materials, producing required subcomponents, and assembling final products. Manufacturing supply chains were evaluated across 13 economies that are the primary manufacturing hubs for these technologies. This Highlights summary report features key findings across the manufacturing supply chains.
A method for preparing a material composition comprising a hollow transition metal oxide nanoparticle supported upon a carbon material support includes a solution impregnation process step, followed by a thermal reduction process step and finally a thermal oxidation process step. The material composition, an electrode and an electrical component such as but not limited to a battery are all predicated at least in-part upon the material composition prepared in accord with the foregoing method. The foregoing material composition, electrode, battery and method may ultimately provide a LIB with enhanced performance.
Book Chapter discussing advanced LIBS measurements and calibration techniques