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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

An orbital strategy for regulating the Jahn–Teller effect

ABSTRACT The Jahn–Teller effect (JTE) arising from lattice–electron coupling is a fascinating phenomenon that profoundly affects important physical properties in a number of transition-metal compounds. Controlling JT distortions and their corresponding electronic structures is highly desirable to tailor the functionalities of materials. Here, we propose a local coordinate strategy to regulate the JTE through quantifying occupancy in the ${{d}_{{{z}^2}}}$ and ${{d}_{{{x}^2} - {{y}^2}}}$ orbitals of Mn and scrutinizing the symmetries of the ligand oxygen atoms in MnO6 octahedra in LiMn2O4 and Li0.5Mn2O4. The effectiveness of such a strategy has been demonstrated by constructing P2-type NaLixMn1–xO2 oxides with different Li/Mn ordering schemes. In addition, this strategy is also tenable for most 3d transition-metal compounds in spinel and perovskite frameworks, indicating the universality of local coordinate strategy and the tunability of the lattice–orbital coupling in transition-metal oxides. This work demonstrates a useful strategy to regulate JT distortion and provides useful guidelines for future design of functional materials with specific physical properties.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Spatial Heterogenous Redox Couples Degradation in Sodium-Ion Battery Cathode Materials and the Mitigation of Voltage Fade by Blocking Oxygen Release

The use of anionic redox has become a new paradigm for improving the energy density of rechargeable batteries, which is essential for improving the market competitiveness of sodium-ion batteries. However, issues such as voltage attenuation and cycling stability degradation persist in layered oxide anion redox cathode materials. Here, in this study, we systematically investigate the classic Na-ion cathode material Na 0.6 Li 0.2 Mn 0.8 O 2 , and the primary causes of voltage decay are identified as the activation of cations and the reduction in anion redox activity. In addition, the activation of cations is closely associated with anion reactions. Through the application of sophisticated multiscale synchrotron absorption spectroscopy and imaging techniques, we have identified a pronounced pattern of spatially dependent degradation in the evolution of redox couples, which is more evident from the material’s surface to its core. With this understanding, we introduced a surface fluorination approach that modulates the local chemical coordination environment. This strategy increases the formation energy of surface oxygen vacancies and locks transition metals oxide state. Consequently, it enables more reversible anionic redox reactions, which block the spatial progression of degradation and mitigates voltage decay.

25 ENERGY STORAGE↗
NASA NTRS2022

Working Toward A National Coordinated Soil Moisture Monitoring Network: Vision, Progress, and Future Directions

Soil moisture is a critical land surface variable, impacting the water, energy, and carbon cycles. While in situ soil moisture monitoring networks are still developing, there is no cohesive strategy or framework to coordinate, integrate, or disseminate these diverse data sources in a synergistic way that can improve our ability to understand climate variability at the national, state, and local levels. Thus, a national strategy is needed to guide network deployment, sustainable network operation, data integration and dissemination, and user-focused product development. The National Coordinated Soil Moisture Monitoring Network (NCSMMN) is a federally led, multi-institution effort that aims to address these needs by capitalizing on existing wide-ranging soil moisture monitoring activities, increasing the utility of observational data, and supporting their strategic application to the full range of decision-making needs. The goals of the NCSMMN are to 1) establish a national “network of networks” that effectively demonstrates data integration and operational coordination of diverse in situ networks; 2) build a community of practice around soil moisture measurement, interpretation, and application—a “network of people” that links data providers, researchers, and the public; and 3) support research and development (R&D) on techniques to merge in situ soil moisture data with remotely sensed and modeled hydrologic data to create user-friendly soil moisture maps and associated tools. The overarching mission of the NCSMMN is to provide coordinated high-quality, nationwide soil moisture information for the public good by supporting applications like drought and flood monitoring, water resource management, agricultural and forestry planning, and fire danger ratings.

C. Bruce Baker↗
NASA NTRS2020

PHALANX: Expendable Projectile Sensor Networks for Planetary Exploration

Technologies enabling long-term, wide-ranging measurement in hard-to-reach areas are a critical need for planetary science inquiry. Phenomena of interest include flows or variations in volatiles, gas composition or concentration, particulate density, or even simply temperature. Improved measurement of these processes enables understanding of exotic geologies and distributions or correlating indicators of trapped water or biological activity. However, such data is often needed in unsafe areas such as caves, lava tubes, or steep ravines not easily reached by current spacecraft and planetary robots. To address this capability gap, we have developed miniaturized, expendable sensors which can be ballistically lobbed from a robotic rover or static lander - or even dropped during a flyover. These projectiles can perform sensing during flight and after anchoring to terrain features. By augmenting exploration systems with these sensors, we can extend situational awareness, perform long-duration monitoring, and reduce utilization of primary mobility resources, all of which are crucial in surface missions. We call the integrated payload that includes a cold gas launcher, smart projectiles, planning software, network discovery, and science sensing: PHALANX. In this paper, we introduce the mission architecture for PHALANX and describe an exploration concept that pairs projectile sensors with a rover “mothership.” Science use cases explored include reconnaissance using ballistic cameras, volatiles detection, and building timelapse maps of temperature and illumination conditions. Strategies to autonomously coordinate constellations of deployed sensors to self-discover and localize with peer ranging (i.e. a “local GPS”) are summarized, thus providing communications infrastructure beyond-line-of-sight (BLOS) of the rover. Capabilities were demonstrated through both simulation and physical testing with a terrestrial prototype. The approach to developing a terrestrial prototype is discussed, including design of the launching mechanism, projectile optimization, micro-electronics fabrication, and sensor selection. Results from early testing and characterization of commercial-off-the-shelf (COTS) components are reported. Nodes were subjected to successful burn-in tests over 48 hours at full logging duty cycle. Integrated field tests were conducted in the Roverscape, a half-acre planetary analog environment at NASA Ames, where we tested up to 10 sensor nodes simultaneously coordinating with an exploration rover. Ranging accuracy has been demonstrated to be within +/-10cm over 20m using commodity radios when compared to high-resolution laser scanner ground truthing. Evolution of the design, including progressive miniaturization of the electronics and iterated modifications of the enclosure housing for streamlining and optimized radio performance are described. Finally, lessons learned to date, gaps toward eventual flight mission implementation, and continuing future development plans are discussed.

Dille, Michael↗
DOE OSTI2025

Population-level control of two manganese oxidases expands the niche for bacterial manganese biomineralization

Abstract The enzymatic oxidation of aqueous divalent manganese (Mn) is a widespread microbial trait that produces reactive Mn(III, IV) oxide minerals. These biominerals drive carbon, nutrient, and trace metal cycles, thus playing important environmental and ecological roles. However, the regulatory mechanisms and physiological functions of Mn biomineralization are unknown. This challenge arises from the common occurrence of multiple Mn oxidases within the same organism and the use of Mn oxides as indicators of combined gene activity. Through the detection of gene activation in individual cells, we discover that expression ofmnxGandmcoA, two Mn oxidase-encoding genes inPseudomonas putidaGB-1, is confined to subsets of cells within the population, with each gene showing distinct spatiotemporal patterns that reflect local microenvironments. These coordinated intra-population dynamics control Mn biomineralization and illuminate the strategies used by microbial communities to dictate the extent, location, and timing of biogeochemical transformations.

Biotechnology & Applied Microbiology↗
DOE OSTI2026

Online task-space motion control for positioner-coordinated multi-robot manufacturing systems

Incorporating multiple robotic manipulators into large-scale manufacturing systems enhances production efficiency and expands manufacturing capabilities beyond those of single-robot systems. Workpiece positioners in robotic manufacturing have demonstrated significant benefits for process optimization, but coordination strategies for multi-robot systems with shared positioners have received limited attention. This work presents a task-space coordinated trajectory-tracking control framework for multi-robot manufacturing systems, in which robots coordinate their motions within a shared, dynamic workpiece positioning frame. A workpiece positioner actively adjusts the pose of the manufactured component to enable greater operational concurrency and improve overall production efficiency. The proposed motion-coordination scheme employs a distributed and scalable architecture, supporting coordination across heterogeneous multi-robot systems. Two optimization methodologies are introduced to manage kinematic redundancies and maintain continuous, near-optimal operation throughout the manufacturing process. The first strategy exploits a task-space dimensionality reduction to achieve locally optimal configurations by leveraging symmetry-axis rotations of the tool. The second strategy utilizes the workpiece positioner to drive the coordinated robots toward stable and kinematically favorable configurations. For both optimization strategies, multiple objectives are defined to improve key performance metrics, including manipulability, configuration consistency, proximity to mechanical limits, and motion efficiency. Addressing a key limitation of existing coordination approaches, the framework is designed around online setpoint modification, allowing coordinated robots to respond effectively to in-situ process feedback. The proposed control framework is validated using the Robot Operating System (ROS) middleware on a combination of physical and simulated multi-robot system hardware.

Arbogast, Alex [ORNL] (ORCID:0000000154740723)↗
DOE OSTI2025

Cyber‐Resilient Distributed Energy Resource Control Algorithms for Smart Distribution Grids

ABSTRACT This paper focuses on the development of cyber‐resilient gradient‐based optimisation algorithms and theoretical proof for grid‐interactive distributed energy resource (DER) control to enable two grid services of virtual power plants (VPPs) dispatch and grid voltage regulation, considering the communication and security impacts. Firstly, the combined DER dispatch and voltage regulation as a real‐time gradient‐based optimisation problem is recapped. Thereafter, we consider a probabilistic traffic model to characterise packet delays and loss in a communication network, and study how the delays enter the process of information exchange among the grid measurement units, local DER controllers and the grid control centre that execute this control algorithm in a coordinated manner. Then, a strategy combining delay thresholds and message update rules is proposed to immunity the asynchrony resulting from the communications traffic and it avoids possible numerical instabilities and sensitivities of the power tracking and voltage regulation capabilities, resulting as cyber‐resilient DER control algorithms. Additionally, their convergence is theoretically proved. Effectiveness of proposed cyber‐resilient algorithms has been validated on the IEEE 37‐bus system in terms of convergence, VPP tracking and voltage regulation performance for smart distribution systems with high penetration of DERs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

An integrated in-situ coordination strategy enabling high-performance layered cathodes for sodium-ion batteries

O3-type layered transition metal oxide cathodes hold tremendous potential in sodium-ion batteries (SIBs) due to their low cost and high energy density. However, the structure instability associated with detrimental phase transitions and severe interface parasitic reactions exacerbate the material's electrochemical performance degradation. Herein, we develop an integrated in-situ coordination strategy via heteroatomic modulation inducing coherent epitaxial layer to collaboratively enhance the overall framework robustness from surface to bulk. The theoretical calculation and multiple in/ex-situ characterizations demonstrate the charge density around oxygen is redistributed, which promotes the electron localization, thus widening the NaO 2 lattice space and accelerating the Na + transport dynamics. Furthermore, the formed strengthened oxygen bond energy effectively distributes the long-range coordination of Mn 3+ O 6 octahedron, thereby alleviating Jahn-Teller distortion and local stress. Importantly, the in-situ formed conformal buffer layer dramatically relieves the adverse interface side reactions, facilitating the construction of robust cathode-electrolyte interface, which ameliorate the whole structure stability of designed materials. Consequently, the optimized NFMZ@NZO-1.0 exhibits the excellent cycling stability with 80.2% capacity retention after 300 cycles at 1C, and delivers a high discharge capacity of 107.1 mAh g −1 at 10C. In conclusion, this distinctive coupling strategy provides valuable insights for developing high-performance layered cathode materials in SIBs.

Coherent epitaxial layer↗
DOE OSTI2026

Hierarchical Reinforcement Learning of a Short-Range Bond-Order Potential for Silica: Analytic Embedding of Coordination with Classical Efficiency

Reinforcement learning (RL) has recently emerged as a data-efficient strategy to parametrize short-range interatomic potentials. Building on our past RL optimization of pairwise silica models, we extend the framework to a bond-order (Tersoff-type) potential that provides an analytic embedding of local coordination through a three-body term. A hierarchical RL workflow combining continuous-action Monte Carlo Tree Search and property-based rewards efficiently explores the 26-dimensional parameter space, sequentially optimizing lattice parameters, densities, angles, and cohesive energies of 21 silica polymorphs. The resulting models, Q-Tersoff and ML-Tersoff, reproduce the energetic ordering of low-energy phases and capture the angular correlations and amorphous structure factors of silica with improved fidelity over pairwise force fields, while remaining orders of magnitude faster than high-dimensional machine-learned potentials. Both models underperform for elastic constants and high-energy frameworks, delineating the limits of the current analytic form. The approach establishes a general and interpretable route to angle-aware, short-range potentials that bridge physics-based and machine-learned descriptions of silicate materials.

36 MATERIALS SCIENCE↗
DOE OSTI2024

An Efficient Checkpointing System for Large Machine Learning Model Training

As machine learning models increase in size and complexity rapidly, the cost of checkpointing in ML training became a bottleneck in storage and performance (time). For example, the latest GPT-4 model has massive parameters at the scale of 1.76 trillion. It is highly time and storage consuming to frequently writes the model to checkpoints with more than 1 trillion floating point values to storage. This work aims to understand and attempt to mitigate this problem. First, we characterize the checkpointing interface in a collection of representative large machine learning/language models with respect to storage consumption and performance overhead. Second, we propose the two optimizations: i) A periodic cleaning strategy that periodically cleans up outdated checkpoints to reduce the storage burden; ii) A data staging optimization that coordinates checkpoints between local and shared file systems for performance improvement.

machine learning, artificial intelligence↗
DOE OSTI2025

Mississippi's Strategic Resilience: A multi-systems approach to secure, reliable, and adaptable electric grid infrastructure

Mississippi’s electric grid resilience challenges are linked to an intersection of complex socioeconomic, ecological, technological, historical, and political challenges, exacerbated by increasing severe weather like flooding and tornado events. The state’s legacy of underinvestment in critical energy infrastructure, particularly in rural areas and vulnerable floodplains, have stressed an aging grid, creating long-lasting disruptions in electric service during weather-related outages. Effective emergency management and preparedness is further hampered by a lack of coordination across local, county, and regional scales. Using the TASTI-GRID platform and partnership with Oak Ridge National Laboratory (ORNL), Mississippi is developing a comprehensive regional resilience strategy to overcome energy security and reliability challenges, mitigating the impacts of natural hazards, and positioning Mississippi as a resilient and premier destination for residents, businesses, and economic development.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

SchrödingerNet: A Universal Neural Network Solver for the Schrödinger Equation

Recent advances in machine learning have facilitated numerically accurate solution of the electronic Schrödinger equation (SE) by integrating various neural network (NN)-based wave function ansatzes with variational Monte Carlo methods. Nevertheless, such NN-based methods are all based on the Born–Oppenheimer approximation (BOA) and require computationally expensive training for each nuclear configuration. In this work, we propose a novel NN architecture, SchrödingerNet, to solve the full electronic-nuclear SE by defining a loss function designed to equalize local energies across the system. This approach is based on a translationally, rotationally and permutationally symmetry-adapted total wave function ansatz that includes both nuclear and electronic coordinates. Furthermore, this strategy not only allows for an efficient and accurate generation of a continuous potential energy surface at any geometry within the well-sampled nuclear configuration space, but also incorporates non-BOA corrections, through a single training process. Comparison with benchmarks of atomic and small molecular systems demonstrates its accuracy and efficiency.

Chemical calculations↗
DOE OSTI2024

Enhancing the Reaction Kinetics and Stability of Co‐Free Li‐Rich Cathode Materials via a Multifunctional Strategy

Co-free Li-rich layered oxides (CFLLOs) with anionic redox activity are among the most promising cathode materials for high-energy-density and low-cost lithium-ion batteries (LIBs). However, irreversible oxygen release often causes severe structural deterioration, electrolyte decomposition, and the formation of unstable cathode-electrolyte interface (CEI) film with high impedance. Additionally, the elimination of cobalt elements further deteriorates the reaction kinetics, leading to reduced capacity and poor rate performance. Here, in this study, a multifunctional strategy is proposed, incorporating Li 2 MnO 3 phase content regulation, micro-nano structure design, and heteroatom substitution. The increased content of Li 2 MnO 3 phase enhances the capacity through oxygen redox. The smaller nanoscale primary particles induce greater tensile strain and introduce more grain boundaries, thereby improving the reaction kinetics and reactivity, while the larger micron-sized secondary particles help to reduce interfacial side reactions. Furthermore, Na⁺ doping modulates the local coordination environment of oxygen, stabilizing both the anion framework and the crystal structure. As a result, the designed cathode exhibits enhanced rate performance, delivering a capacity of 158 mAh g⁻¹ at 5.0 C and improved cyclic stability, with a high capacity retention of 99% after 400 cycles at 1.0 C. This multifunctional strategy holds great promise for advancing the practical application of CFLLOs in next-generation LIBs.

Co-free Li-rich layered oxide↗
DOE OSTI2025

Source Analysis of Ozone Pollution in Liaoyuan City’s Atmosphere Based on Machine Learning Models and HYSPLIT Clustering Method

Firstly, this study investigates the spatiotemporal distribution characteristics of the ozone (O 3 ) pollution in Liaoyuan City using monitoring data from 2015 to 2024. Then, three machine learning models (ML)—random forest (RF), support vector machine (SVM), and artificial neural network (ANN)—are employed to quantify the influence of meteorological and non-meteorological factors on O 3 concentrations. Finally, the HYSPLIT clustering method and CMAQ model are utilized to analyze inter-regional transport characteristics, identifying the causes of O 3 pollution. The results indicate that O 3 pollution in Liaoyuan exhibits a distinct seasonal pattern, with the highest concentrations found in spring and summer, peaking in the afternoon. Among the three ML models, the random forest model demonstrates the best predictive performance (R 2 = 0.9043). Feature importance identifies NO 2 as the primary driving factor, followed by meteorological conditions in the second quarter and land surface characteristics. Furthermore, regional transport significantly contributes to O 3 pollution, with approximately 80% of air mass trajectories in heavily polluted episodes originating from adjacent industrial areas and the sea. The combined effects of transboundary precursors and O 3 transport with local emissions and meteorological conditions further increase the O 3 pollution level. This study highlights the need to strengthen coordinated NO X and VOCs emission reductions and enhance regional joint prevention and control strategies in China.

HYSPLIT clustering↗
DOE OSTI2026

Instabilities and phase transitions in architected metamaterials: a gradient-enhanced continuum approach

Architected metamaterials such as foams and lattices exhibit a wide range of properties governed by microstructural instabilities and emerging phase transitions. Their macroscopic response–including energy dissipation during impact, large recoverable deformations, morphing between configurations, and auxetic behavior–remains difficult to capture with conventional continuum models, which often rely on discrete approaches that limit scalability. In this work, we propose a nonlocal continuum formulation that captures both stable and unstable responses of elastic architected metamaterials. The framework extends anisotropic hyperelasticity by introducing nonlocal variables and internal length scales reflective of microstructural features. Local polyconvex free-energy models are systematically augmented with two families of non-(poly)convex energies, enabling both metastable and bistable responses. Implementation in a finite element framework enables solution using a hybrid monolithic–staggered strategy. Simulations capture densification fronts, forward and reverse transitions, hysteresis loops, imperfection sensitivity, and globally coordinated auxetic modes. Overall, this framework provides a robust foundation for accelerated modeling of instability-driven phenomena in architected metamaterials, while enabling extensions to anisotropic, dissipative, and active systems as well as integration with data-driven and machine learning approaches.

42 ENGINEERING↗
DOE OSTI2026

Complex-Concentrated Anion Doping Enables Ultra-Stable Lattice Oxygen and Structural Integrity in Lithium-Rich Layered Oxide Cathodes

Lithium- and manganese-rich layered oxides (LMR) stand out as next-generation lithium-ion cathode chemistries, which harness both transition-metal and lattice-oxygen redox processes to deliver exceptional capacity and energy density. However, their full potential is hindered by intrinsic oxygen instability and structural degradation, resulting in pronounced voltage fade and capacity decay. Here, we present a complex-concentrated anion-doping paradigm in which multiple anions, F, Br, and S, are incorporated into the oxygen sublattice to enhance oxygen-redox and structural stability. X-ray absorption spectroscopy and aberration-corrected scanning transmission electron microscopy confirm ultra-stable local oxygen coordination environments during long-term cycling, with detrimental phase transformations and oxygen-loss-induced cavitation dramatically inhibited. Notably, we show that the characteristic LiTM6 transition metal (TM) honeycomb ordering is preserved even after electrochemical cycling. Concurrently, this strategy yields an unprecedented volume change of only 0.63% upon charging to 4.8 V vs. Li+/Li, achieving the first zero-strain LMR cathode. The resulting LMR cathode delivers ultralow voltage fade (1 mV per cycle during the first 100 cycles and becomes negligible in subsequent cycles) and outstanding energy retention (93% after 200 cycles) in a pouch cell configuration. Our complex-concentrated anion-doping concept establishes a broadly applicable strategy for resolving chemo-mechanical failure mechanisms in ceramic intercalation electrodes for next-generation energy storage.

Li-ion batteries↗
DOE OSTI2024

Pinellas County Clear Sky Assessment Process: Prioritizing Solar + Storage for Resilient Facilities & Communities

The Clear Sky Tampa Bay project was a 15-month collaborative research effort to support solar + storage deployment for community resilience in Florida. The Clear Sky Decision Support Toolkit is a collection of resources designed to support users in conducting solar + storage prioritization and feasibility screening assessments at critical facilities. The Tampa Bay Regional Planning Council worked with four local governments in the region to test and apply the Toolkit. This case study series describes how each partner government used the Toolkit and highlights key insights and lessons learned that other users could follow to replicate the process. Pinellas County applied the Clear Sky Decision Support Toolkit to improve interagency coordination and gather data to analyze solar + storage projects for its critical facilities. This case study examines energy resilience strategies for the Pinellas County Solid Waste-to-Energy Plant. The Toolkit's modular assessment process developed institutional capacity and knowledge within the county and will assist in the research and application of future solar energy projects.

14 SOLAR ENERGY↗
DOE OSTI2026

Enhancing the EVI-X National Framework to Address Emerging Energy Questions

This project advances the state-of-the-art in infrastructure analysis to better inform deployment strategies. It enhances NLR's EVI-X Suite, a set of tools supporting national network planning, local site design, and financial evaluation. These capabilities will position DOE to provide timely analysis and inform the strategic buildout of the national charging network. EVI-X development is closely coordinated with other DOE-funded efforts to ensure consistent, integrated use of key inputs and outputs, including EV adoption scenarios from NLR's TEMPO model.

24 POWER TRANSMISSION AND DISTRIBUTION↗