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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Refractory-based thermal energy storage for industrial process heat: one-dimensional modeling, control, and optimization

The variable and weather-dependent output of wind and solar power plants present a substantial challenge for planning and operating electricity-systems, particularly in the absence of cost-effective and dispatchable energy storage technologies. This study investigates a high-temperature, electrically heated, refractory-based thermal energy storage (RTES) system that stores electrical energy as sensible heat in dense ceramic bricks over the 950–1800 °C range. The stored heat can be discharged as a controlled hot-gas stream for industrial heating, fuel substitution in high-temperature processes, or electricity generation. The main novelty is a comprehensive modelling, control, mapping, and optimization framework that integrates one-dimensional transient gas–solid heat transfer, fan-assisted discharge, bypass-flow regulation, reheating logic, fan-power evaluation, insulation-loss assessment, and genetic-algorithm-based design optimization. The model uses feedback from outlet temperature and delivered power to regulate discharge, while a two-stage genetic algorithm optimizes brick-channel geometry, gas-flow operation, and multilayer insulation thicknesses. Storage capacities below 50 MWh and discharge powers of 5–30 MW are analyzed to evaluate hold time, thermal delivery, fan-power penalty, heat loss, state-of-charge evolution, and indicative capital cost. Results demonstrate that optimized and well-insulated refractory-based thermal energy storage units can provide stable, efficient, and repeatable heat delivery over multiple discharge cycles. The generated performance and cost maps support modular refractory thermal energy storage as a practical option for large-scale integration of wind and solar generation and for high-temperature industrial process heat.

25 ENERGY STORAGE↗
DOE OSTI2025

127 Xe quantification method development and intercomparison exercise

Monitoring of the atmosphere for fission products ( 131m Xe, 133m Xe, 133 Xe, and 135 Xe) is performed by various laboratories to detect nuclear explosions. Quantification of 127 Xe is not routinely performed by laboratories measuring atmospheric radioxenon because it is not a fission product. 127 Xe was recently detected by a ground-based beta-gamma air monitoring system. When measured using beta-gamma coincidence detector systems, such as those in use on the International Monitoring System (IMS) of the Comprehensive Nuclear-Test-Ban Treaty (CTBT), 127 Xe can interfere with the quantification of fission product radioxenon due to overlap of the 127 Xe beta-gamma coincidence signatures with those of fission product radioxenon. Here, this work demonstrates quantification of 127 Xe at different laboratories with different measurement techniques. Production and purification of 127 Xe was performed by neutron activation of enriched 126 Xe. The purified 127 Xe was then split between laboratories, and detection and quantification methods were developed. At Idaho National Laboratory, a quantification method involving high purity germanium detectors was devised that included self-attenuation correction. At AWE, a beta-gamma coincidence counting method, as used in support of the IMS, was modified to enable the measurement and analysis of the 127 Xe samples. Corrections were made for self-attenuation, which showed a strong xenon volume dependency, for some coincidence signatures. The gas sample activity concentration was used as the comparison metric and it showed excellent agreement between the methods.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2020

The potential application of VS 2 as an electrode material for Mg ion battery: A DFT study

Herein, by means of first-principle calculations based on density functional theory (DFT), the electrochemical properties of monolayer VS 2 (M-VS 2 ), double-layer VS 2 (D-VS 2 ) and bulk VS 2 (B-VS 2 ) as electrode materials for Mg-ion batteries (MIBs) were comprehensively explored. The computation results reveal that Mg atom can strongly bind with the three different forms of VS 2 . All of the Mg adsorbed VS 2 systems demonstrate metallic characteristics, which indicates a good electronic conductivity. In addition, crystal orbital hamiltonian population shows that the stability of V-S bond is weakened after adsorption of Mg atom. The low diffusion barriers of Mg give rise to the high rate performance of VS 2 in MIBs. More interestingly, the three types of VS 2 display same storage ability for Mg cations, which can adsorb 0.5 Mg atoms for VS 2 , producing maximum theoretical capacity 233 mA h g -1 for MIBs. Furthermore, the average working voltages results suggest that M-VS 2 can be employed as anode materials, while D-VS 2 , B-VS 2 can be used as cathode materials for MIBs.

25 ENERGY STORAGE↗
DOE OSTI2023

In-situ transmission electron microscopy investigation on surface oxides thermal stability of niobium

Niobium is commonly used for superconducting quantum systems as readout resonators, capacitors, and interconnects. Structural defects at the Nb/Si and air/Nb interface may be a major source of two-level systems (TLS), which are detrimental to the device's coherence time. Thus, identifying and understanding the microscopic origin of possible TLS in Nb-based devices and their relationship to processing is key to superconducting qubit performance improvement. Here this work studied the structure and thermal stability of surface oxide on physical vapor deposited Nb films on Si wafers, using aberration-corrected (scanning) transmission electron microscopy and spectroscopy. Here, all Nb films exhibit columnar growth with strong [110] textures. After in-situ heating of the heterostructure at 360 °C inside the microscope, the initial amorphous niobium surface oxides decompose into face-centered cubic Nb nanograins in the amorphous Nb-O matrix, which may reduce microwave dissipation. Despite changes in the microstructure and chemistry of the niobium oxide surface layer due to heat treatment, the interface between the Nb and the surface oxide layer remains almost unchanged. Our comprehensive study of the Nb surface oxide decomposition mechanism may guide future superconducting qubit device optimization through interfacial scattering center and TLS minimization.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Theoretical assessments of CO 2 activation and hydrogenation pathways on transition-metal surfaces

Carbon dioxide (CO 2 ) hydrogenation on transition-metal active sites offers a promising carbon utilization route toward mitigating greenhouse gas emissions. C 1 products are often formed in parallel during CO 2 hydrogenation, prompting investigations into the intrinsic properties of transition metals that drive activity and product selectivity. Here, in this work, close-packed surfaces of a selection of transition-metal catalysts (Ni, Co, Rh, Ru, Pd, and Pt) were studied with density functional theory (DFT) calculations to understand their fundamental reactivities for CO 2 transformation reactions. Results indicate that CO 2 conversion proceeds through CO* formation and hydrogenation to form C 1 products (* denotes an adsorbed species). Ni, Co, Rh, and Ru favor CO/CH 4 formation, while Pd and Pt favor CO/CH 3 OH formation. The ability of a metal to dissociate C-O bonds drives selectivity between CH 4 and CH 3 OH, while competition between CO* desorption and surface hydrogenation describes CO selectivities. The C-O bond dissociation steps often impose the highest barrier along CH 4 formation reaction profiles, suggesting their kinetic relevance for CH 4 formation rates. The provided DFT-derived data sets detail a comprehensive reaction network of elementary steps relevant to C 1 chemistries, ultimately offering a benchmark for insights into design strategies for materials that exploit transition-metal active sites in carbon capture or utilization processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Accommodating a hexagonal ζ- phase Mn 2 N film on a cubic MgO (001) substrate

The thin films of c -plane dominated hexagonal ζ- phase Mn 2 N were successfully grown on a cubic MgO (001) substrate directly using plasma-assisted molecular beam epitaxy. The surface was comprehensively studied through experimental and theoretical approaches. Reflection high energy electron diffraction revealed two pseudo-cubic domains along [100] MgO and [110] MgO , and one hexagonal domain, which is 30° apart from the [100] MgO direction. Scanning tunneling microscopy was used to image and resolve the high-quality surface, revealing a distorted hexagonal surface structure. Furthermore, atomic resolution of the hexagonal domain with a 2 × 2 reconstructed surface is presented. For c-plane surface, theoretical investigations were carried out using first principles studies to determine the surface formation energy for various reconstructed surfaces. The theoretical study shows that the nitrogen terminated 2 × 2 structure with a manganese adatom on the surface as the most stable reconstruction that reproduces the experimental results. A corresponding simulated scanning tunneling microscopy model is also presented, providing strong support for the experimentally observed in-plane lattice structures. Furthermore, the manganese: nitrogen stoichiometry within the bulk and surface is in good agreement with the expected ratio of 2:1.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Time-resolved electrical potential pump – X-ray photoelectron spectroscopy probe developments for investigating dynamic processes occurring at electrochemical interfaces

Electrode–electrolyte interfaces are of critical importance in several fields, including renewable energy, corrosion, and environmental chemistry. However, investigating these interfaces under operational conditions poses considerable challenges due to the limitations of the instrumentation employed. While recent advancements in in situ and operando techniques have enhanced our comprehension of the steady-state properties of solid-liquid interfaces, the dynamic behaviors of these systems remain inadequately explored. This study introduces a time-resolved X-ray photoelectron spectroscopy (XPS) technique designed to capture transient reaction intermediates and charging dynamics at electrified interfaces. The presented proof-of-principle study demonstrates that electrochemical processes, represented by an equivalent electrical circuit (EEC) model, can be probed and understood using square wave voltage pulses of a potentiostat synchronized to the modified data acquisition of an XPS setup. This method offers a valuable alternative to traditional pump–probe techniques, facilitating the investigation of a broader range of electrochemical systems. A dedicated software package for analyzing time- and energy-resolved XPS with a focus on extracting parameters of the EEC is geared towards benchmarking different EECs in future real-world electrochemical experiments.

Electrochemistry↗
DOE OSTI2022

Introduction to the special section on learning and security for multi-agent systems

This report features six articles that provide an overview of the emerging research topics at the intersection learning, security, and multi-agent systems. Recent years have witnessed a surge in the number of works at their intersections, and they have appeared in system and control communities as well as many other communities in artificial intelligence, cyber–physical systems, and economics. The articles in this special section give accessible and comprehensive tutorials and surveys for a broad systems and control audience, covering topics including adversarial machine learning, multi-agent reinforcement learning, cyber resilience, resilient control systems, and game design. It is hopeful that this special section will spawn future interest and cross-disciplinary collaborations in this emerging transdisciplinary research area.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

A critical review of cyber-physical security for building automation systems

Modern Building Automation Systems (BASs), as the brain that enable the smartness of a smart building, often require increased connectivity both among system components as well as with outside entities, such as the cloud, to enable low-cost remote management, optimized automation via outsourced cloud analytics, and increased building-grid integrations. As smart buildings move towards open communication technologies, providing access to BASs through the building's intranet, or even remotely through the Internet, has become a common practice. However, increased connectivity and accessibility come with increased cyber security threats. BASs were historically developed as closed environments with limited cyber-security considerations. As a result, BASs in many buildings are vulnerable to cyber-attacks that may cause adverse consequences, such as occupant discomfort, excessive energy usage, and unexpected equipment downtime. Therefore, there is a strong need to advance the state-of-the-art in cyber-physical security for BASs and provide practical solutions for attack mitigation in buildings. However, an inclusive and systematic review of BAS vulnerabilities, potential cyber-attacks with impact assessment, detection & defense approaches, and cyber resilient control strategies is currently lacking in the literature. This review paper fills the gap by providing a comprehensive up-to-date review of cyber-physical security for BASs at three levels in commercial buildings: management level, automation level, and field level. The general BASs vulnerabilities and protocol-specific vulnerabilities for the four dominant BAS protocols (i.e., BACnet, KNX, LonWorks, and Modbus) are reviewed, followed by a discussion on four attack targets and seven potential attack scenarios. Furthermore, the impact of cyber-attacks on BASs is summarized as signal corruption, signal delaying, and signal blocking. The typical cyber-attack detection and defense approaches are identified at the three levels. Cyber resilient control strategies for BASs under attack are categorized into passive and active resilient control schemes. Open challenges and future opportunities are finally discussed.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

How much information on precipitation is contained in satellite infrared imagery?

Satellite infrared (IR) brightness temperature providing information on the characteristics of cloud tops is one of the primary input data used for estimating precipitation from satellites. Thus, the natural questions to ask are: Does IR imagery contain more information about precipitation in some regions more than others? What are the factors that lead to such differences? Should we expect the amount of information provided by IR imagery to change with respect to temporal or spatial aggregation? Comprehensive analysis of the accuracy of satellite-based precipitation estimates obtained from any given algorithm may provide qualitative answers to the above questions. However, such an approach only offers conclusions within the limited context of the algorithm used to obtain precipitation estimates; that is, patterns caused by the inherent information content of IR imagery are inextricable from those induced by assumptions embedded in the precipitation estimation algorithm. Here, we address the abovementioned questions from a different perspective using an information-theoretic measure, free of structural assumptions and general to a wide range of relationships, to characterize the average and seasonal dependence between IR imagery provided by satellite sensors in the spectral range (10.7–11.5 μm) and precipitation rates in the contiguous United States (CONUS) across distinct temporal and spatial scales. We analyze a total of more than 1.3 billion pairs of IR and precipitation observations over CONUS, and we observe interesting patterns. First, we show that there is a strong inverse relationship (ρ = - 0.73) between the information content of IR data and the number of no-rain observations; however, its robustness varies regionally and seasonally with less significant correlation during the warm season. Second, we demonstrate that the intuitive relationship of increasing dependence between IR and precipitation as a result of temporal or spatial aggregation exhibits a diminishing returns behavior. For instance, temporal aggregation from 1 to 3 h increases the dependence approximately 7 times as much as temporal aggregation from 12 to 24 h. Furthermore, we quantitatively examine and re-confirm several statements previously reported in the literature such as the strong association between IR and precipitation in convective storms and the low association in orographic rainfall. Finally, we conclude by illustrating the potential of the analysis in diagnosis of operational algorithms for estimating precipitation from IR brightness temperature. The findings of this study pinpoint spatial domains and time scales at which IR is not an adequate proxy for estimating precipitation. Thus, they can potentially guide the development of operational algorithms that utilize satellite Infrared imagery for estimating, downscaling and data fusion of precipitation. Finally, the analysis presented here opens up the possibility of developing new methodologies for diagnosis of satellite-based precipitation estimation algorithms.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Quantitative evaluations of subtropical westerly jet simulations over East Asia based on multiple CMIP5 and CMIP6 GCMs

As a salient feature of the Asian monsoon system, the East Asian subtropical westerly jet (EASWJ) exerts significant impacts on weather and climate changes in China and even throughout East Asia. In this paper, we applied a new self-adaptive algorithm to detect the EASWJ, identify its boundaries, and then represent its characteristics by defining three indices: the intensity index, meridional displacement index, and width index. Compared to the reanalysis data, we carried out a comprehensive, objective, and quantitative EASWJ evaluation using historical experiments from multiple global climate models (GCMs) in the Coupled Model Intercomparison Project Phases 5 and 6 (CMIP5 and CMIP6). The results show that the multimodel ensemble mean (MME) of both CMIP5 and CMIP6 can simulate the characteristics of winter EASWJ well. While for the other three seasons, the MME of both phase models underestimate the 200-hPa zonal wind (U200) strength in the jet coverage area and overestimate the U200 outside the jet area, such simulation results weaken the meridional shear of the wind field. The EASWJ simulations from the CMIP5 GCMs had no consistent intensity or location characteristic tendencies, and most CMIP5 GCMs tended to simulate relatively wide-coverage jets. In contrast, most CMIP6 GCMs are inclined to simulate significantly weaker, wider, and more-northward jets. Compared to the predecessors in CMIP5, about half of CMIP6 GCMs significantly minimized the jet intensity bias, but remarkable errors were still observed in their jet location and coverage representations. Furthermore, the comparative analysis performed by classifying models based on their evaluated simulation results suggested that the simulated performance of the meridional temperature gradient was important for capturing the EASWJ characteristics. Further in-depth study of the causes of model differences is warranted to improve simulation results.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Analysis of the cyanobacterial amino acid metabolism with a precise genome-scale metabolic reconstruction of Anabaena sp. UTEX 2576

Filamentous cyanobacteria such as Anabaena sp. UTEX 2576 (a.k.a., Nostoc sp. PCC 7120) are a sustainable platform for commodity and specialty chemical production. Anabaena is a model cyanobacterium adopted to study production of nitrogen-containing metabolites useful for chemical, cosmetic, and pharmaceutical industries. Therefore, a precise description of the Anabaena metabolic network is desired to analyze their amino-acid metabolism and elucidate potential applications of these cyanobacteria as host organisms for biotechnological production. Secondary metabolite production depends on the metabolic availability of amino acids. We provide new insight on the biotechnological utilization of Anabaena after predicting phycocyanobilin and amino-acid production rates, using a genome-scale metabolic model (iDN1004). This metabolic reconstruction is a highly comprehensive representation of the global metabolism of Anabaena, which also contains experimental biomass equations and constraints under photoautotrophic and photodiazotrophic growth. Modelling results ranked proteinogenic amino acids based on predicted metabolic fluxes through amino-acid producing reactions. From these, l-aspartate, glycine, l-serine, l-valine, l-alanine, l-threonine, and l-leucine were selected as the best branching points to conduct metabolic engineering, where l-aspartate, l-serine, l-valine and glycine serve as potential precursors of the secondary metabolites Schizokinen (a siderophore), Sphingosine (a ceramide), Lyngbyatoxin A (an alkaloid), and Shinorine (a sunscreen).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Disturbance and diversity: Lichen species richness decreases with increasing anthropogenic disturbance

Anthropogenic disturbance is rapidly increasing through habitat degradation, development, and deforestation. Gaps remain in understanding the effects of this disturbance on diverse and ecologically important organisms such as lichens. In North America, studies have focused on epiphytic macrolichens and catastrophic disturbance, largely ignoring microlichens and less severe disturbances. The Intermediate Disturbance Hypothesis predicts these moderate disturbances will lead to higher species richness. Here we examine the effects of anthropogenic disturbance in the form of land management on overall lichen richness, including microlichens, and on the species richness of eight lichen functional groups. The study draws on a comprehensive data set of 872 species, in 208 one-hectare plots throughout the Southern Appalachian Mountains, a global biodiversity hotspot in eastern North America. A habitat quality index based on an established forestry metric was used as a proxy for anthropogenic disturbance and was quantified using a 10-part score including categories such as percent native tree canopy cover and degree of fragmentation. Linear models were used to compare habitat quality scores to overall species richness and to species richness of functional groups. Rather than following the Intermediate Disturbance Hypothesis, all groups uniformly follow a negative linear relationship: as disturbance increases, species richness decreases. This pattern held even for widely variable functional groups such as morphotype. Effective conservation of lichen richness should prioritize the maintenance of existing older, less-disturbed stands within large, contiguously forested areas.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Predicting the evolution of biomass bulk density through feedstock preprocessing: Discrete element modeling, regression analysis, and pilot-scale validation

Bulk density is an important material property of biomass feedstocks, influencing handling, storage, transport costs, and conversion efficiency. In this study, predictive regression models for loose and tapped bulk densities of Alamo and Cave-in-Rock switchgrass are developed using a comprehensive dataset generated via calibrated bonded-sphere discrete element method (DEM) simulations. Here, a key contribution of this study is the use of a DEM-based approach, which correlates density with moisture content and particle size distribution parameters and enables analysis across a continuous particle size range, overcoming limitations of purely experimental data. For comparison, regression models are also developed using only experimental data from pilot-scale runs at the Biomass Feedstock National User Facility at Idaho National Laboratory. Validation against pilot-scale data showed reasonable prediction accuracy for both model types, particularly for smaller particle sizes (post-secondary grinding). While the experimental model showed slightly better performance matching the validation data in some cases, the DEM-based model benefits from a much larger dataset, reduced predictor multicollinearity, and continuous parameter coverage, highlighting the utility of validated simulation models for developing robust predictive tools for biomass preprocessing applications.

09 - BIOMASS FUELS↗
DOE OSTI2025

Effect of particle size and moisture on flow performance of loblolly pine anatomical fractions: Experimental findings and model predictions

The rising energy demand has highlighted biomass as a promising next-generation energy source. However, commercializing biomass-derived energy faces challenges, particularly in handling biomass feedstock. Factors like particle size, shape, moisture content, and surface roughness significantly impact biomass flowability. This study addresses a crucial knowledge gap by examining the effects of particle size and moisture content on the flow behavior and shear properties of different anatomical fractions of loblolly pine (Pinus taeda). The bulk shear behavior was examined using a Schulze ring shear tester, while flow performance was tested through gravity-driven flow experiments in a variable wedge-shape hopper. Results were incorporated into empirical and machine learning-based flow prediction models to evaluate their accuracy and limitations. The study found that samples with higher moisture content show higher unconfined yield strength. The critical arching distance increased with particle size, e.g., from approximately 13 and 33 mm for 2- and 6-mm whole chips, respectively at a 32-degree inclination angle. Conversely, the flow rate decreased for a given hopper opening as particle size increased. For instance, at a 60-mm hopper opening and a 32-degree inclination angle, the mass flow rates for 2- and 6-mm whole chips were 7.83 and 6.42 tonne/h, respectively. The empirical model consistently overpredicted the mass flow rate for all anatomical fractions, while the machine learning model more accurately predicted the central tendency of flow rate but was insensitive to varying tissue proportions. These novel findings provide comprehensive characterization of anatomical fractions, reveal significant combined effects of particle size and moisture content on biomass flow behavior, and demonstrate a better predictive accuracy of a machine learning model, all of which are useful for optimizing material handling strategies and biomass utilization technologies in the industry.

09 - BIOMASS FUELS↗
DOE OSTI2022

Assessing the availability of two bamboo species for fermentable sugars by alkaline hydrogen peroxide pretreatment

We report this study comprehensively investigated two bamboo species (i.e. Neosinocalamus affinis and Phyllostachys edulis) in terms of their cell wall ultrastructure, chemical compositions, enzymatic saccharification, and lignin structure before and after alkaline hydrogen peroxide pretreatment (AHP). During AHP, Neosinocalamus affinis (NAB) had higher delignification than Phyllostachys edulis (PEB), and thus showed better enzymatic digestibility (93.05% vs 53.57% for glucan). The fundamental chemical behavior of the bamboo lignins was analyzed by fluorescence microscope (FM), confocal Raman microscope (CRM), molecular weight analysis, and 2D HSQC-NMR. Results indicated that the PEB has thicker cell wall and more concentrated lignin in its compound middle lamella and cell corner middle lamella than NAB. Moreover, PEB lignin contains more G units (S/G of 0.95), in evident contrast to that of NAB lignin (S/G of 1.30), which favor the formation of C–C linkages, thus impeding its degradation during the AHP.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Utilization of guaiacol-based deep eutectic solvent for achieving a sustainable biorefinery

This study proposed a renewable deep eutectic solvent (DES) pretreatment using lignin-derived guaiacol as the hydrogen bond donor. The DES showed excellent biomass fractionation efficiency after the incorporation of trace AlCl 3 as the reinforcer, which removed 79.1 % lignin while preserving more than 90 % glucan. The pretreated bamboo exhibited 96.2 % glucan enzymatic hydrolysis yield at only 110 °C. The physicochemical properties of the pretreated solids were comprehensively investigated to explain how the DES fractionation overcame the biomass recalcitrance. The regenerated lignin from the DES pretreatment was also analyzed, which revealed that lignin β-O-4 bond was significantly cleaved. In conclusion, this guaiacol-based DES could greatly contribute to establish a closed-loop biorefinery sequence with high lignin fractionation efficiency and great solvent recyclability.

09 BIOMASS FUELS↗