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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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1,709 records · Page 68
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Paleotribological models using preserved fossil tissue properties reveal functional significance of Eurasian mammoth dental evolution

Eurasian mammoths (Mammuthus) underwent substantial modifications in molar morphology as later-diverging species evolved progressively thinner enamel and increased enamel crest complexity. These features have been hypothesized to reduce whole-tooth wear and extend dental longevity as increasingly graze-dominated diets evolved within the lineage. This hypothesis has yet to be directly tested. Here, in this study, we developed an in-silico wear model using experimentally derived wear rates from fossil and extant proboscidean dental tissues. The models revealed that shifts in tissue topology do not affect whole-tooth wear rate, as inverse trends in lamellar frequency and enamel thickness preserve a consistent surface enamel area fraction; the determining factor of wear. Rather, topological shifts produce a wear-emergent secondary occlusal surface with greater numbers of triturating crests that create a regular, low-relief, file-like shearing pavement. These changes in occlusal architecture likely directly impacted the mastication capacity of Mammuthus dentitions, facilitating their dietary expansion to incorporate fibrous, lower-nutrient graze.

Dental wear↗
DOE OSTI2025

Do Households Adapt? Repeated Hurricane Exposure and the Purchasing of Bottled Water

Understanding how households adapt to hurricanes is increasingly important as these events become more frequent and severe. This paper examines how past hurricane exposure influences current household preparedness, focusing specifically on the stockpiling of bottled water. Leveraging scanner data on bottled water purchases for households in the Southeastern United States, we employ a difference-in-differences event study framework to analyze how repeated hurricane experiences affect consumer behavior. Our results indicate that households exposed to hurricane warnings do not increase their preparedness in the subsequent hurricane season, and those experiencing a landfall event underprepare. These results suggest limited learning from past events.

D12↗
DOE OSTI2026

Predicting Atomistic Transitions with Transformers

Accurate knowledge of the atomistic transition pathways in materials and material surfaces is crucial for many material science problems. However, conventional simulation techniques used to find these transitions are extremely computationally intensive. Even with large-scale, accelerated material simulations, the computational cost constrains the applicable domain in practice. Machine learning models, with the potential to learn the complex emergent behaviors governing atomistic transitions as a fast surrogate model, have great promise to predict transitions with a vastly reduced computational cost. Here, we demonstrate how transformers can be trained to predict atomistic transitions in nano-clusters. We show how we evaluate physical validity of the predictions and how a multitude of additional, different microstates can be generated by slightly varying the data provided to the model.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Recrystallization, cracking, and erosion of dispersoid-strengthened tungsten materials during exposure to divertor plasmas

In this study, we investigated the effects of combined intense particle and heat flux exposure on advanced tungsten plasma-facing materials within the DIII-D fusion facility. Our test matrix included two types of dispersoid-strengthened tungsten (containing either 100 nm diameter TiO 2 or Ni particles), along with high-purity polycrystalline tungsten as a reference. This experiment relied on a sample geometry angled at 15° relative to the divertor surface, thereby allowing the surfaces to intercept steady-state perpendicular heat fluxes (q ⟂ ) ranging from 10.1 to 19.6 MW/m 2 . During each shot, the samples were exposed to 42 Hz edge-localized modes (ELMs), allowing us to test the material response to transient heating. We correlated the exposure conditions with extensive post-test surface composition analysis and microscopy to determine how the plasma modified each surface. The angled specimens closest to the strike point received the highest combined heat and particle flux and melted midway through the experiment. EBSD analysis revealed they were completely recrystallized throughout, with an average grain size >100 µm. On the other hand, the specimens that received a lower steady state heat flux survived with more superficial surface damage. Whereas the high-purity polycrystalline tungsten exhibited a higher surface roughness, the dispersoid-strengthened material exhibited more extensive shallow inter-granular cracking. In addition, the surface was depleted of dispersoids following plasma exposure, possibly because of evaporation and/or sputtering. The results described here provide insights into the performance of these materials in a fusion environment which can guide further optimization for use in long-pulse devices.

Kolasinski, Robert D. [Sandia National Laboratorie↗
DOE OSTI2025

Review on Preprocessing Strategies, Deactivation, Thermal Safety, and Future Perspectives in Lithium-Ion Battery Recycling

The rapid growth in the use of lithium-ion batteries (LIBs) in electric vehicles, consumer electronics, and renewable energy storage has made effective end-of-life management essential. Recycling LIBs is critical not only for resource recovery and environmental protection but also for ensuring safety and economic viability. This review focuses on the preprocessing technologies that precede typical recovery processes, including disassembly, sorting, discharging, electrolyte removal, dismantling, thermal treatment, separation, and flotation. These steps play a foundational role in determining the efficiency, safety, and environmental impact of LIB recycling. LIBs pose substantial fire and explosion risks due to residual charge, flammable electrolytes, and reactive materials. The conditions and successive progression of the exothermic reactions which lead to thermal runaway has been discussed. It also explores secure deactivation techniques such as external circuit discharge, saline immersion, and thermomechanical methods, alongside fire prevention strategies including the use of flame retardants, elimination of oxidants, and reduction of heat generation and accumulation. Challenges and future directions are outlined, highlighting the need for standardized designs, automation, and safer, more sustainable recycling infrastructure. Furthermore, this review is distinguished by its focused analysis of preprocessing and deactivation steps, with particular attention to the thermal safety engineering aspects of LIB recycling.

Battery deactivation↗
DOE OSTI2026

A Unified Scaling Framework for Comparative Analysis of Major Electrical Machine Topologies

This paper presents a unified framework for comparing major electrical machine topologies under identical output and thermal constraints, with emphasis on supply-chain-aware selection among rare-earth-intensive, reduced-rare-earth, and rare-earth-free solutions. Using power factor and air-gap flux density as the principal descriptors, the framework links topology choice to relative size, copper demand, magnet dependence, cost sensitivity, and inertia. To support robust early-stage screening, the deterministic scaling model is combined with uncertainty representation, Monte Carlo scenario propagation, and hesitationaware ranking. The results show that rare-earth-rich machines remain compact and dense, whereas reduced-rare-earth and rare-earth-free alternatives become more attractive under specific material-risk and cost scenarios.

Kumar, Praveen [ORNL] (ORCID:0000000291877857)↗
DOE OSTI2026

Machine learning pipeline for denoising low signal-to-noise ratio and out-of-distribution transmission electron microscopy datasets

High-resolution transmission electron microscopy (HRTEM) is crucial for observing material’s structural and morphological evolution at Angstrom scales, but the electron beam can alter these processes. Devices such as CMOS-based direct-electron detectors operating in electron-counting mode can be utilized to substantially reduce the electron dosage. However, the resulting images often lead to a low signal-to-noise ratio, which requires frame integration that sacrifices temporal resolution. Several machine learning (ML) models have been recently developed to successfully denoise HRTEM images. Yet, these models are often computationally expensive, and their inference speeds on GPUs are outpaced by the imaging speed of advanced detectors, precluding in situ analysis. Furthermore, the performance of these denoising models on datasets with imaging conditions that deviate from the training datasets has not been evaluated. To mitigate these gaps, we propose a new self-supervised ML denoising pipeline specifically designed for time-series HRTEM images. This pipeline integrates a blind-spot convolution neural network with pre-processing and post-processing steps, including drift correction and low-pass filtering. Results demonstrate that our model outperforms various other ML and non-ML denoising methods in noise reduction and contrast enhancement, leading to improved visual clarity of atomic features. Additionally, the model is drastically faster than U-Net-based ML models and demonstrates excellent out-of-distribution generalization. The model’s computational inference speed is in the order of milliseconds per image, rendering it suitable for application in in-situ HRTEM experiments.

36 MATERIALS SCIENCE↗
DOE OSTI2026

A Reflection on the Evolution of Sodium/Metal Chloride (ZEBRA) Batteries and Lithium-Ion Cathode Materials (1975–2025): A Tribute to Johan Coetzer

This narrative summarizes, in retrospect, the enormous and quietly-conducted contribution of Dr Johan Coetzer, a South African scientist and entrepreneur, to the discovery, development and implementation of the high temperature sodium—metal chloride “ZEBRA” battery (Na/β-Al 2 O 3 , NaAlCl 4 /MCl 2 (M = Ni, Fe)). Here, this research activity was initiated in the mid 1970’s at the Council for Scientific and Industrial Research (CSIR) in South Africa and subsequently developed primarily in partnership with the Atomic Energy Research Establishment (AERE, Harwell, UK), Beta R&D (Derby, UK) and Daimler Benz (Germany), before being transferred to industry worldwide for electric vehicle and energy storage applications, albeit at a relatively low production rate. Coetzer’s wide-ranging, innovative and, at times, unconventional scientific approach also laid the foundation for the discovery and implementation of manganese-based spinel and layered metal oxide cathode materials for the Li-ion battery industry.

ZEBRA Battery↗
DOE OSTI2024

Real-space visualization of a defect-mediated charge density wave transition

Here, we study the coupled charge density wave (CDW) and insulator-to-metal transitions in the 2D quantum material 1T-TaS 2 . By applying in situ cryogenic 4D scanning transmission electron microscopy with in situ electrical resistance measurements, we directly visualize the CDW transition and establish that the transition is mediated by basal dislocations (stacking solitons). We find that dislocations can both nucleate and pin the transition and locally alter the transition temperature T c by nearly ~75 K. This finding was enabled by the application of unsupervised machine learning to cluster five-dimensional, terabyte scale datasets, which demonstrate a one-to-one correlation between resistance—a global property—and local CDW domain-dislocation dynamics, thereby linking the material microstructure to device properties. This work represents a major step toward defect-engineering of quantum materials, which will become increasingly important as we aim to utilize such materials in real devices.

4D-STEM↗
DOE OSTI2026

Topographic effects on reflected acoustic waves from the OSIRIS-REx reentry observed from stratospheric balloons

During long-distance sound propagation in planetary atmospheres, acoustic waves may reflect off the air/surface interface one or more times. For low sound frequencies and flat interfaces, the incident and reflected wave tend to be nearly identical. However, this may not be the case when the downgoing acoustic wave encounters topography. Here, we describe a set of direct and reflected acoustic signals recorded on free-flying balloons during the hypersonic entry of the OSIRIS-REx sample return capsule (SRC). In two of the three cases presented here, an impulsive reflected arrival similar in form to the direct sonic boom of the SRC is observed, followed by a diffuse coda. In contrast, one of the floating stations lacked an impulsive reflection entirely, with only the coda present. We use full waveform modeling to show how reflection in the presence of complex topography can explain coda seen in all three examples as well as the lack of impulsive arrival on the third. Our results indicate that the complex signals often observed in long range acoustic propagation could be due, in part, to interactions with topography during transmission.

Lees, Jonathan M. [University of North Carolina, C↗
DOE OSTI2025

Modeling phase transformations in Mn-rich disordered rocksalt cathodes with machine-learning interatomic potentials

Mn-rich disordered rocksalt (DRX) cathode materials exhibit a phase transformation from a disordered to a partially disordered spinel-like structure (δ-phase) during electrochemical cycling. Here, in this computational study, we use charge-informed molecular dynamics with a fine-tuned CHGNet foundation potential to investigate the phase transformation in LixMn 0.8 Ti 0.1 O 1.9 F 0.1 . Our results indicate that transition metal migration occurs and reorders to form the spinel-like ordering in an FCC anion framework. The transformed structure contains a higher concentration of nontransition metal (0-TM) face-sharing channels, which are known to improve Li transport kinetics. Analysis of the Mn valence distribution suggests that the appearance of tetrahedral Mn 2+ is a consequence of spinel-like ordering, rather than the trigger for cation migration as previously suggested. Calculated equilibrium intercalation voltage profiles demonstrate that the δ-phase, unlike the ordered spinel, exhibits solid-solution signatures at low voltage. A higher Li capacity is obtained than in the DRX phase. This study provides atomic insights into solid-state phase transformation and its relation to experimental electrochemistry, highlighting the potential of machine-learning interatomic potentials for understanding complex oxide materials.

Zhong, Peichen [University of California, Berkeley↗
DOE OSTI2026

Staged Z-pinch experiment at the double-EAGLE pulsed power facility

The staged Z-pinch is a potential high-energy gain fusion concept where a high atomic number liner implodes on a deuterium target using a pulsed multi-MA current source. Over the past several years this concept has been studied on 0.5–1.0 MA facilities using Ar and Kr gas puffs injected at R = 1.2 cm. Neutron yield up to (2.5 ± 0.34) x 10 10 was measured, Ruskov et al (2023 IEEE Trans. Plasma Sci. 51 3310–6). Here, in this study, we present experimental results from the 4 MA, 110 ns current rise time Double-EAGLE facility at L3Harris (currently, Fisica Inc.) where a larger radius nozzle created gas density profiles peaked at R = 2.5 cm. Modeling with the MACH2 and FLASH codes indicates that the larger radius allows stronger acceleration of the liner plasma and generation of shock waves that preheat a target plasma layer next to the liner to temperatures $T_i >$1 keV. The resulting counter thermal pressure on the liner plasma limits the growth of the Magneto-Rayleigh–Taylor (MRT) instability at the liner-vacuum boundary and the implosion proceeds in a relatively stable manner. Near bang time the enormous target plasma thermal pressure smoothens the MRT perturbations developed during the earlier implosion stages. Time integrated x-ray pinhole images with cutoff energy of 100 eV confirm that a long (∼3 cm), stable and uniform high energy density plasma column is formed in the final implosion stage. Consistent neutron yield in the 10 10 –10 11 range was measured for both Ar and Kr liners imploding on a deuterium target.

Physics - Plasma physics↗
DOE OSTI2026

Improving creep resistance of Al-0.27Zr-0.08Sn (wt%) via cold swaging while maintaining high electrical conductivity

This study investigates the effect of mechanical cold work (0, 50, and 90% cross-sectional area reduction via swaging) on the creep properties of cast aluminum alloys with high electrical conductivity including high-purity Al (HP-Al), Al-0.15Zr (Al-Zr), and Al-0.27Zr-0.08Sn (Al-Zr-Sn, wt%). The Al-Zr alloy is strengthened by Zr in solid solution while the Al-Zr-Sn alloy is additionally strengthened by Al3Zr nanoprecipitates (8 nm diameter). After 90% cold swaging, the alloys exhibit grains elongated along the swaging direction with their widths ranging between 8 and 152 μm perpendicular to the swaging direction. Creep testing at 200 °C shows that the minimum creep rate of all 90% swaged alloys shows high sensitivity to stress, which can be modeled via a threshold stress σth. Increasing swaging magnitude from 0 to 50 to 90% in Al-Zr-Sn improves the creep resistance without reducing electrical conductivity. The formation of subgrains, increased dislocation density, and columnar grain structure in swaged alloys all enhance creep resistance. HP-Al swaged to 90% exhibits much lower creep resistance (σth = 18 MPa) due to subgrain coarsening and the absence of precipitates compared to Al-Zr (σth = 40 MPa) and Al-Zr-Sn (σth = 40 MPa), which maintain stable subgrain structures and benefit from solid solution strengthening and Al3Zr nanoprecipitates, respectively. Although Al3Zr precipitates are known to stabilize the deformed microstructure by pinning grain-boundaries, this work demonstrates that Zr in solid solution alone can effectively stabilize the deformed microstructure resulting in enhanced creep resistance. This effect of Zr solute on stabilizing grain boundaries for creep performance was not previously well-defined in the literature. Despite similar creep performances of Al-Zr and Al-Zr-Sn, the latter shows 70% higher room-temperature microhardness and slightly improved electrical conductivity (56%IACS (International Annealed Copper Standard) vs. 57%IACS, respectively). This work provides new insights into creep mechanisms of cold-worked Al–Zr alloys that will guide the design of heat-resistant Al conductors for high-demand applications.

Coello ramirez, Ismael [Northwestern University,]↗
DOE OSTI2026

Divergent Rickettsia species exhibit distinct mechanisms of actin-based motility

Many Rickettsia species undergo actin-based motility to promote cell-cell spread during infection. Rickettsial genomes often encode two motility effectors, RickA and Sca2, which in the spotted fever group I species, Rickettsia parkeri act by activating the host Arp2/3 complex and by mimicking eukaryotic formins, respectively. The function of RickA and Sca2 orthologs in the distantly related species Rickettsia bellii was unclear. We report that R. bellii RickA activates the host Arp2/3 complex but has no discernible role in bacterial motility. The R. bellii Sca2 ortholog, Sca2/6, nucleates and elongates actin with a flexible structure and an unusual actin monomer-binding motif in a mechanism distinct from formins or other microbial actin nucleators. R. bellii motility is solely correlated with Sca2/6 localization and, compared with R. parkeri motility, is slow and meandering, generating distinctly organized actin tails. The evolutionary flexibility in the mechanism and regulation of rickettsial actin-based motility suggests similar adaptability for other microbes.

Bacher, Meghan C↗
DOE OSTI2026

Prime Time for Model-Predictive Control? Assessing the Technical and Market Readiness of Advanced Controls in Buildings

Despite three decades of extensive research and field testing that have consistently validated the benefits of Model Predictive Control (MPC) in building applications, the technology has seen limited market adoption. This paper evaluates the readiness of MPC for widespread deployment, showcases recent demonstrations and field tests across diverse building types, including residential, small commercial, large commercial, and campus settings. Our results demonstrate that MPC can optimize system operations to achieve load shifting, minimize curtailment of on-site generation, and reduce energy costs by up to 80 %, while maintaining or improving occupant comfort. We also show that MPC can effectively control large assets, such as MW-sized thermal storage systems, and respond to dynamic pricing signals. However, achieving scale remains difficult due to labor-intensive workflows, reliance on a “PhD-in-the-loop” for MPC design and maintenance, susceptibility to fragile data infrastructure, and persistent workforce education and acceptance barriers. To bridge this gap, we outline a transition from bespoke, labor intensive prototypes toward streamlined, segment-targeted deployment strategies that leverage model templates, semantic tools, and generative AI. By automating control configuration and reducing engineering effort, these recommendations provide a pathway for transforming successful research demonstrations into scalable, market ready solutions for MPC-based controls.

Pritoni, Marco↗
DOE OSTI2026

Feedstock Choices for Advancing the Bioeconomy in the US and Policy Implications

Biomass feedstocks will be critical for scaling up the bioeconomy in the United States to meet multiple demands for biofuels, sustainable aviation fuel, bioproducts, and biochemicals. There is a wide range of choices of feedstocks, including a variety of dedicated energy crops and crop residues. There are substantial differences in the yields, costs of production, and carbon intensity of these feedstocks and for each feedstock across locations. These feedstocks also differ in the trade-offs they offer among multiple environmental impacts. We discuss the economic factors that will influence the production of these feedstocks and the implications of alternative biofuel and low-carbon policies for the mix of feedstocks that will be incentivized.

Khanna, Madhu (ORCID:0000000349944451)↗