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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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Predictive model using artificial neural network to design phase change material-based ocean thermal energy harvesting systems for powering uncrewed underwater vehicles

Uncrewed Underwater Vehicles (UUVs) are a major beneficiary of the phase change material (PCM)-based ocean thermal energy harvesting technology for their mission needs. However, this technology relies on different parameters and energy conversion steps that could be critical to the general energy generation efficiency. Sea trials showed that the design performed lower than their laboratory design specifications. This underperformance results from different factors, mainly the UUV’s trajectory, travel time, underwater ocean currents, temperature fluctuations, and biofouling on the heat exchanger due to long term underwater operations. Therefore, there exists a need to continuously monitor the ambient energy harvesting system and predict system performance, for mission planning purposes. Two major parameters influencing the energy harvesting system include the final pressure inside the hydraulic energy storage vessel or accumulator, and the electrical load value. Here, this work focuses on the hydraulic to electric energy conversion system. Therefore, a combination of numerical model and experimental testing is used to develop a predictive model using artificial neural network using MATLAB. After validation with experimental testing, 1000 data samples obtained from the numerical model are used to train the ANN. Compared to the experimental results, the developed ANN model can predict in less than a second the designed benchtop system’s total efficiency with less than 15 percent maximum error range. This predictive model development represents a cost-effective way for optimization and a computational energy efficient mode aboard UUVs for mission planning for deployed UUVs using PCM-based ocean thermal energy harvesting technology.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2021

Free energy difference to create the M-OH* intermediate of the oxygen evolution reaction by time-resolved optical spectroscopy

Theoretical descriptors differentiate the catalytic activity of materials for the oxygen evolution reaction by the strength of oxygen binding in the reactive intermediate created upon electron transfer. Recently, time-resolved spectroscopy of a photo-electrochemically driven oxygen evolution reaction followed the vibrational and optical spectra of this intermediate, denoted M-OH*. However, these inherently kinetic experiments have not been connected to the relevant thermodynamic quantities. Here we discover that picosecond optical spectra of the Ti-OH* population on lightly doped SrTiO 3 are ordered by the surface hydroxylation. A Langmuir isotherm as a function of pH extracts an effective equilibrium constant relatable to the free energy difference of the first oxygen evolution reaction step. Thus, time-resolved spectroscopy of the catalytic surface reveals both kinetic and energetic information of elementary reaction steps, which provides a critical new connection between theory and experiment by which to tailor the pathway of water oxidation and other surface reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Single-atom molybdenum doping induces nickel oxide-to-hydroxide transformation for enhanced alkaline hydrogen evolution

NiMoO x compounds are widely regarded as among the most efficient non-noble metal catalysts for the hydrogen evolution reaction (HER). Nevertheless, understanding the structural evolution under in situ conditions and further enhancing their performance remain key challenges. Herein, we report that single-atom Mo doping in NiO significantly enhances its HER activity, reducing the overpotential to 131 mV at 10 mA cm −2 compared to undoped NiO. In situ X-ray absorption spectroscopy and Raman spectroscopy reveal that under catalytic conditions, Mo single atoms remain structurally stable, while Ni 2+ species in NiO are converted to Ni(OH) 2 in alkaline media under the applied working potential for HER. Notably, this transformation is absent in undoped NiO, indicating that Mo doping promotes the formation of active Ni(OH) 2 sites, which, in turn, accelerate the rate-limiting water dissociation step. These findings provide critical mechanistic insights into the structural evolution of NiMoO x during alkaline HER and highlight the importance of in situ studies in the development of highly efficient catalysts.

58 GEOSCIENCES↗
DOE OSTI2025

Software Tools Ecosystem Project (STEP) Midyear Report CY2025

This document provides a technical project report for the first six months of 2025 for the Software Tools Ecosystem Project (STEP). The mission of STEP is to enable critical software tools to proactively adapt to emerging platform technologies (such as new accelerators, storage devices, network technologies, and smart devices) and emerging application use cases (such as advanced machine learning and workflow frameworks) so that they continue to meet the needs of scientific computing and provide a strong foundation for future Advanced Scientific Computing Research activities. Our challenges include the wide breadth of our stakeholders and rapidly evolving platform technology dependencies.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Software Tools Ecosystem Project (STEP): CY2025 Annual Report

This document provides a technical project report for the Software Tools Ecosystem Project (STEP) during calendar year 2025. The mission of STEP is to enable critical software tools to proactively adapt to emerging platform technologies (such as new accelerators, storage devices, network technologies, and smart devices) and emerging application use cases (such as advanced machine learning and workflow frameworks) so that they continue to meet the needs of scientific computing and provide a strong foundation for future Advanced Scientific Computing Research activities.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Investigation of Correlation Methods for Use in Criticality Safety

Although their adoption by practitioners has been limited, the introduction of similarity indices in criticality safety was a major step forward in reducing the reliance on expert judgement in discerning applicable experiments for the validation of new appliations in criticality safety analyses. Similarity indices have been successfully employed in bias trending and data assimilation techniques, but it is often unclear which acceptance criteria should be used. In their 2004 paper, Broadhead et al. specify the most widely used similarity parameter, ck, as an acceptance cutoff at 0.9. (Broadhead et al., ”Sensitivity and Uncertainty-Based Criticality Safety Validation Techniques,” Nucl. Sci. Eng. 146, 340–366, 2004). Experiments with a ck < 0.9 are often not considered applicable for code validation. This heuristic is based on quantitative studies and engineering judgement, but in some cases, experiments with ck < 0.9 can be used to accurately estimate computational bias. This suggests that further analysis is needed to determine what components of ck are driving applicability and accuracy in bias estimation. For cases in which applicable experiments may not be available (as is the case with UF6 transport canisters), understanding what distinguishes experiments in providing adequate bias estimates aside from just the similarity index is particularly necessary. To further the goal to better interpret ck values, several visualization tools were developed to assist in the investigation of which components of ck are driving applicability.

ck↗
DOE OSTI2026

Recycling of Printed Circuit Boards to Recover Critical Materials

The printed circuit board (PCB), a central component of most electronic devices, represents a significant fraction of the electronic product waste stream. The complex composition of PCBs, consisting of metals, polymers, and fiberglass, requires specialized recovery steps to reclaim valuable and critical materials and the safe disposal of brominated compounds. In this review paper, we describe the current state of critical material recovery and traditional recycling technologies and identify key obstacles to large-scale implementation. Metals present at high concentrations, such as copper, lead, and iron, are conventionally recovered from PCBs using hydrometallurgical, pyrometallurgical, or electrometallurgical processes. Hydrometallurgical methods achieve high selectivity through chemical leaching but pose significant challenges for effluent and reagent recovery. Pyrometallurgical methods facilitate rapid metal separation through smelting but require substantial energy and may release harmful gases. Electrometallurgical techniques produce high-purity metals but are constrained by pretreatment requirements and the consumption of energy. The non-metallic fraction of PCB waste is recycled using thermochemical conversion, microwave-aided heating, and direct recycling of epoxy–fiberglass composites, enabling material or energy recovery. The recovered polymer from direct recycling may have reduced mechanical strength and poor compatibility with new polymer matrices, and the resulting products from the thermal conversion suffer from incomplete conversion, degradation of quality, and residual contamination, as compared to synthetic polymers. Recent process developments have focused on extracting rare earth and supply-critical materials present at lower concentrations in the waste stream. The literature on existing and emerging approaches for recycling PCB wastes is reviewed to identify sustainable, economically viable, and environmentally responsible strategies for the recovery and reuse of critical materials from waste streams.

36 MATERIALS SCIENCE↗
DOE OSTI2023

CRITICAL MINERAL PARTITIONING IN COAL-HOSTED CLAYS OF THE POWDER RIVER BASIN, WY DETERMINED BY SEQUENTIAL EXTRACTION

Increasing demand for a more robust domestic supply of rare earth elements (REE) and critical minerals (CM) has led to significant investigation into unconventional sources. Coal and coal byproducts from the Powder River Basin (PRB) of Wyoming are potential sources of REE and CM. The association between strategic metals and their mineral hosts has important implications for extractability. Samples of overburden, underclays, and clay-rich partings were selected for analysis from core and bucket samples from three PRB coal mines. Quartz, illite, and kaolinite-group minerals are abundant in clay-rich portions of the PRB coal strata. We performed a five-step sequential extraction to constrain critical metal partitioning in samples of overburden and underclays (n=10). Unlike the occurrences of REE in other clay deposits, insignificant amounts of total REE + Y (TREY) were recovered in the ion-exchangeable fraction (< 0.5 ppm). A significant amount of TREY was leached from the acid-soluble fraction by 0.1M HCl, suggesting REE may be tied up within crystal lattices rather than sorbed to clay surfaces. The acid-soluble fraction contained between 3 and 250 ppm TREY, with an average TREY concentration of 60 ppm. Relative standard deviations for each extraction step were generally < ±10%. Whole-rock samples (n=72) contained greater TREY enrichment in overburden than in underclays and partings, however, the opposite is true for other CM, such as Ti and V. Other locations in the PRB show different enrichment trends. Our findings supplement a broader effort to couple REE and CM extraction with existing domestic coal production and contribute to the fundamental understanding of how these metals concentrate in low-temperature basin environments.

Stuart, Sophia↗
DOE OSTI2023

Geothermal Play Fairway Analysis, Part 2: GIS methodology

Play Fairway Analysis (PFA) in geothermal exploration originates from a systematic methodology developed within the petroleum industry and is based on a geologic, geophysical, and hydrologic framework of identified geothermal systems. We tailored this methodology to study the geothermal resource potential of the Snake River Plain and surrounding region, but it can be adapted to other geothermal resource settings. We adapted the PFA approach to geothermal resource exploration by cataloging the critical elements controlling exploitable hydrothermal systems, establishing risk matrices that evaluate these elements in terms of both probability of success and level of knowledge, and building a code-based ‘processing model’ to process results. A geographic information system was used to compile a range of different data types, which we refer to as elements (e.g., faults, vents, heat flow, etc.), with distinct characteristics and measures of confidence. Discontinuous discrete data (points, lines, or polygons) for each element were transformed into continuous interpretive 2D grid surfaces called evidence layers. Because different data types have varying uncertainties, most evidence layers have an accompanying confidence layer which reflects spatial variations in these uncertainties. Risk layers, as defined here, are the product of evidence and confidence layers, and are the building blocks used to construct Common Risk Segment (CRS) maps for heat, permeability, and seal, using a weighted sum for permeability and heat, but a different approach with seal. CRS maps quantify the variable risk associated with each of these critical components. In a final step, the three CRS maps were combined into a Composite Common Risk Segment (CCRS) map, using a modified weighted sum, for results that reveal favorable areas for geothermal exploration. Additional maps are also presented that do not mix contributions from evidence and confidence (to allow an isolated view of evidence and confidence), as well as maps that calculate favorability using the product of components instead of a weighted sum (to highlight where all components are present). Our approach helped to identify areas of high geothermal favorability in the western and central Snake River Plain during the first phase of study and helped identify more precise local drilling targets during the second phase of work. By identifying favorable areas, this methodology can help to reduce uncertainty in geothermal energy exploration and development.

15 GEOTHERMAL ENERGY↗
DOE OSTI2025

Ab initio calculations of overlap integrals for μ → e conversion in nuclei

The rate for μ → e conversion in nuclei is set to provide the most stringent test of lepton-flavor symmetry and a window into physics beyond the Standard Model. However, to disentangle new lepton-flavor-violating interactions, in combination with information from μ → ey and μ → 3e, it is critical that uncertainties at each step of the analysis be controlled and fully quantified. In this regard, nuclear response functions related to the coupling to neutrons are notoriously problematic, since they are not directly constrained by experiment. We address these shortcomings by combining ab initio calculations with a recently improved determination of charge distributions from electron scattering by exploiting strong correlations among charge, point-proton, and point-neutron radii and densities. We present overlap integrals for 27 Al, 48 Ca, and 48 Ti including full covariance matrices, allowing, for the first time, for a comprehensive consideration of nuclear structure uncertainties in the interpretation of μ → e experiments.

ab initio calculations↗
DOE OSTI2023

Disruption event characterization and forecasting in tokamaks

Disruption prediction and avoidance is a critical need for next-step tokamaks, such as ITER. Disruption Event Characterization and Forecasting (DECAF) research fully automates analysis of tokamak data to determine chains of events that lead to disruptions and to forecast their evolution allowing sufficient time for mitigation or complete avoidance of the disruption. Disruption event chains related to local rotating or global magnetohydrodynamic (MHD) modes and vertical instability are examined with warnings issued for many off-normal physics events, including density limits, plasma dynamics, confinement transitions, and profile variations. Along with Greenwald density limit evaluation, a local radiative island power balance theory is evaluated and compared to the observation of island growth. Automated decomposition and analysis of rotating tearing modes produce physical event chains leading to disruptions. A total MHD state warning model comprised of 15 separate criteria produces a disruption forecast about 180 ms before a standard locked mode detector warning. Single DECAF event analyses have begun on KSTAR, MAST, and NSTX/-U databases with thousands of shot seconds of device operation using from 0.5 to 1 × 10 6 tested sample times per device. An initial multi-device database comparison illustrates a highly important result that plasma disruptivity does not need to increase as βN increases. Global MHD instabilities, such as resistive wall modes (RWMs), can give the briefest time period of warning before disruption compared to other physics events. In an NSTX database with unstable RWMs, the mode onset, loss of boundary and current control, and disruption event warnings are found in all cases and vertical displacement events are found in 91% of cases. An initial time-dependent reduced physics model of kinetic RWM stabilization created to forecast the disruption chain predicts instability 84% of the time for experimentally unstable cases with a relatively low false positive rate. Instances of the disruption event chain analysis illustrate dynamics including H–L back transitions for rotating MHD and global RWM triggering events. Furthermore, disruption warnings are issued with sufficient time before the disruption (on transport timescales) to potentially allow active profile control for disruption avoidance, active mode control, or mitigation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Estimating Critical Customer Outages Resulting from Extreme Hurricanes

US power outage data has been collected by organizations such as Oak Ridge National Laboratory (ORNL) through Environment for Analysis Geo-Located Energy Infrastructure (EAGLE-I: freely available) and poweroutage.us (commercial data: available to purchase). However, these sources do not provide information specific to outages of critical customers. Critical customers include entities, facilities, and individuals whose continuous access to electricity is essential for public safety, emergency response, disaster recovery, the well-being of vulnerable populations, public safety and order, and public utilities such as natural gas, communications, water and sanitation. Identification and geolocation of critical customers is crucial for understanding and addressing the effects of power outages on essential services and ensuring that necessary measures are taken to maintain their operations during power disruptions. This work is a first step towards estimating the occurrences of critical customer outages and developing a critical customer power outage data repository. This work estimates outage incidents of critical customers through spatiotemporal mapping of power outage data, weather data, building data, and critical infrastructure network data. Our results show that critical customer effects vary across different counties. We provide appropriate mathematical explanations and simplifications to define and systematize the proposed approach.

Bhusal, Narayan [ORNL] (ORCID:0000000222752145)↗
DOE OSTI2023

Selective Electrocatalytic Reduction of Nitrous Oxide to Dinitrogen with an Iron Porphyrin Complex

Nitrous oxide (N 2 O) is the third largest contributor to anthropogenic greenhouse gas emissions and plays a detrimental role in the depletion of ozone. Despite the contribution of N 2 O as an atmospheric pollutant, there are currently only a few examples of electrochemical N 2 O remediation to N 2 . Herein we report the electrocatalytic deoxygenation of N 2 O by iron tetraphenylporphyrin (FeTPP) to form N 2 with quantitative Faradaic efficiency and an observed rate of 1.91 s –1 . No degradation was observed after controlled potential electrolysis. Mechanistic investigation of the proposed catalytic steps determined that hydrogen-bond donors are critical for accelerating N 2 O activation and that proton transfer is involved in the rate-determining step.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

On the irreversible sodiation of tin disulfide

Tin disulfide is considered as a promising electrode material for sodium-ion batteries because of its two-dimensional layered structural characteristics allowing the intercalation of Na ions. Understanding the underlying reaction mechanisms and the decisive step of the reaction reversibility is critical for its applications. Herein, we investigate the sodiation and desodiation processes of SnS 2 by employing in situ transmission electron microscopy (TEM). After the initial intercalation reaction, a rock-salt Na y SnS 2 phase with disordering Na and Sn cations is observed, followed with a conversion reaction and an alloying reaction. Additionally, the disordering reaction occurs along <1-10> direction of pristine SnS 2 phase which is correlated with local bonding rearrangements induced by the exchange of Sn and Na cations. In-situ TEM studies and first-principles calculations indicate that the original 2D SnS 2 structure could not be recovered during desodiation. Instead, the disordered Na y SnS 2 phase is finally formed, which indicates that the irreversible disordering transition is the determining step of irreversible cycling. This work probes the structural evolution of sodiation, providing a fundamental understanding of the electrochemical properties of metal sulfides and inspiring rational designs of high performance electrodes for sodium-ion batteries.

25 ENERGY STORAGE↗
DOE OSTI2020

Revisiting Competing Paths in Electrochemical CO 2 Reduction on Copper via Embedded Correlated Wavefunction Theory

We re-evaluate two key steps in the mechanism of CO 2 reduction on copper at a higher level of theory capable of correcting inherent errors in density functional theory (DFT) approximations, namely, embedded correlated wavefunction (ECW) theory. Here, we consider the CO reduction step on Cu(111), which is critical to understanding reaction selectivity. Here, we optimize embedding potentials at the periodic plane-wave DFT level using density functional embedding theory (DFET). All possible adsorption sites (adsites) for each adsorbate then are screened with ECW theory at the catalytically active site to refine the local electronic structure. Unsurprisingly, DFT and ECW theory predict different adsite preferences, largely because of DFT’s inability to properly situate the CO 2π* level. Differing preferred adsites suggest that different reaction pathways could emerge from DFT versus ECW theory. Starting from these preferred ECW theory adsites, we then obtain reaction pathways at the plane-wave DFT level using the climbing-image nudged elastic band method to determine minimum energy paths. Thereafter, we perform ECW calculations at the catalytically active site to correct the energetics at each interpolated structure (image) along the reaction pathways. Via this approach, we confirm that the first step in CO reduction via hydrogen transfer on Cu(111) is to form hydroxymethylidyne (*COH) instead of formyl (*CHO). Although the prediction to preferentially form *COH is consistent with that of DFT, the two theories predict quite different structural and mechanistic behaviors, suggesting that verification is needed for other parts of the mechanism of CO 2 reduction, which is the subject of ongoing work.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2025

A Data Processing Pipeline To Extract A Knowledge Graph From Heterogeneous Data For Socio-technical Analysis Of Critical Infrastructure Influence

The code is written in Python and consists of the following pipeline that is implemented in Apache Airflow. This pipeline intends to understand the companies that are directly or indirectly involved with a type of critical infrastructure system at some point in that system's lifecycle. The pipeline takes a configuration file that specifies a list of initial companies to consider, a geographic region of interest, and a set of SEC form types as well as other data sources (e.g. CrunchBase) from which to extract entities and relations. There are four main components to this pipeline as currently implemented: Entity Extraction, Network Construction, Analysis, and Visualization. First, Entity Extraction, is implemented as the `topear-extract_organizations` Apache Airflow workflow. Given an initial query that specifies a geographic region of interest and a time interval, the software will extract CI facilities of interest and organizations that have a direct influence relationship to those facilities (e.g. ownership). During the course of the LDRD, we focused on Electric Vehicle charging stations and this information is available via the Department of Energy (DOE) database on fueling stations maintained by NREL. Within the context of the DOE CESER project, we have focused on Battery Energy Storage Systems (BESS). Second, the Network Extraction component will iteratively construct a social network graph given the set of organizations and people extracted in the previous step. Organizations (and eventually People if desired) are then fed as a query to the `topgear-construct_social_network` Apache Airflow workflow which given a set of initial companies and data sets (e.g. SEC EDGAR form types, OpenCorporates, Crunchbase). This Airflow workflow will iteratively query such data sources to discover relationships with new organizations and people. For example, this module can iteratively query SEC EDGAR for metadata that documents the number of each type of form for the given set of companies and their location. This forms metadata represents a catalog of data sources from SEC EDGAR for the extracted social network knowledge graph. The pipeline then downloads these forms from the website and saves them in a build directory for further processing. These documents are then parsed for entities and relations. Again, we note that in additional to SEC data sources, this step can also pull in information on organizations via API services such as CrunchBase and OpenCorporates or bulk data sources. At the end of this step, the resultant social network, the Critical Infrastructure network, and the edges that encode relationships between organizations and CI facilities, form the Adversarial Socio-Technical Network (ASTN) that informs the analysis. Third, the Analysis component processes these generated ASTN. Previously, that has included the ability to compare prevalence of different vendors for a given infrastructure component type across different regions as well as identify common public and private investors across those vendors. This was demonstrated for EV Charging Stations across several different metropolitan areas within an IEEE PES GridEdge publication. More recently, we have looked at ways to identify infrastructure owners and operators of BESS with the most nameplate capacity across different states as well as other indictors of risk resulting from changes in ownership over time. Finally, the Visualization component consists of an HTML/CSS/JS framework by which users can interact geospatial, operational, and organizational relationships across a given portfolio of Critical Infrastructure facilities. The objective is to provide a library of UI/UX modules that can be repurposed for stakeholder-specific dashboards. All of the modules are related via a common event model that enables UI actions in one view to percolate across the other views.

Weaver, Gabriel [Idaho National Laboratory (INL), ↗
DOE OSTI2020

Critical nuclei at hetero-phase interfaces

Two-step nucleation, in which a metastable intermediate phase acts as a precursor for nucleating a thermodynamically stable phase, has been widely observed in many materials systems and solid-state reactions. Among the advantages of two-step nucleation is that the stable phase may nucleate heterogeneously at the hetero-phase interface between the original and the precursory phases. Although heterogeneous nucleation (HN) theories for homo-phase grain boundaries and inert surfaces are well established, our understanding of HN at reactive hetero-phase interfaces remains incomplete. This deficiency stems from the discontinuity of the chemical potential driving force across the hetero-phase interface, which profoundly affects the fundamental properties of the nucleus in a way that is not properly accounted for in existing models. In this work, we incorporate these effects to extend the classical nucleation theory to HN at hetero-phase interfaces. Our extended model demonstrates that the nucleus shape along the minimum energy path is strongly size-dependent, and this additional degree of freedom can result in the reduction of the critical nucleus volume and associated activation energy barrier by orders of magnitude relative to conventional predictions. The simulation results are used to construct a sensitivity map in the parameter space of interfacial energy and bulk driving force ratios, which quantifies the difference in nucleation barriers predicted by different models.

36 MATERIALS SCIENCE↗
DOE OSTI2021

miRNAs: Critical mediators of breast cancer metastatic programming

Highlights: • This review highlights the crucial role played by miRNAs in the process of metastatic evolution of breast cancer. MicroRNA mediated aberrant gene regulation has been implicated in several diseases including cancer. Recent research has highlighted the role of epigenetic modulation of the complex process of breast cancer metastasis by miRNAs. miRNAs play a crucial role in the process of metastatic evolution by facilitating alterations in the phenotype of tumor cells and the tumor microenvironment that promote this process. They act as critical determinants of the multi-step progression starting from carcinogenesis all the way to organotropism. In this review, we focus on the current understanding of the compelling role of miRNAs in breast cancer metastasis.

60 APPLIED LIFE SCIENCES↗