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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Geometry-driven modeling of electron localization in InAs/GaAs double quantum dots

The coupled electronic states in two-dimensional (2D) and three-dimensional (3D) double quantum dot (DQD) systems are investigated using a phenomenological model applied to InAs/GaAs heterostructures. The single-band k • p effective potential approach previously proposed by our group is employed to numerically calculate the energy spectrum and spatial localization of a single electron, serving as an indicator of the coupling strength within the binary system. For identical quantum dots (QDs) in a DQD, the electronic states exhibit ideal coherence. We systematically vary the DQD geometry and the strength of the confinement potential (via an applied electric field) to examine the effects of symmetry breaking and the sensitivity of electron localization in both identical and nearly identical DQDs. Our results show that coherence in DQDs is highly sensitive to these subtle variations. This sensitivity can be harnessed to detect changes in the surrounding environment, such as fluctuations in chemical or electrical properties that affect the DQD system.

electron localization↗
DOE OSTI2024

Medial axis and local thickness computation using the Fast Sweeping Method

This report describes an efficient and robust voxel-based methodology for computing the medial axis, local thickness, and distance-to-skeleton of arbitrary three-dimensional geometries. It is assumed that the object can be represented by an exact or approximate signed distance function on a discrete grid. The gradient of such function is used to formulate a hyperbolic partial differential equation (PDE) that models the collapse of the position vector in space. By exploiting the causality property of the PDE, the Fast Sweeping Method is able to obtain the solution in a finite number of sweeps independent of the mesh resolution. The intersection of characteristic lines leads to the formation of shocks and a discrete bisector function is used to identify the medial axis. The same PDE approach is used to compute the local thickness inside the object and obtain the distance-to-skeleton field. Multiple examples are given in two and three dimensions along with a resolution study. The methodology has optimal complexity and yields subsecond computational times for geometries with over a million zones on a single core. The methodology is also capable of parallelization across shared and distributed memory architectures.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

The Workforce Readiness Index: A Local and Regional Assessment Tool for Energy Sector Preparedness

Building up a workforce that is properly trained and adequately sized is essential to ensuring that the deployment of energy generation sources in the United States meets future energy demand. Workforce development to support supply chain or large infrastructure investments typically occurs at a local level. However, there is a critical gap in understanding where and to what extent regional workforces are equipped to meet the needs of an energy industry. The Workforce Readiness Index ("the index") was developed to assess and compare energy sector workforce readiness across the United States at the county level to provide granular information to various stakeholders such as industry members, state decision makers, and training program developers. Workforce readiness is defined as the ability to recruit from the general labor market, transition workers with comparable skill sets, and train a workforce using scalable or existing training programs near a specific location. Therefore, the index evaluates readiness levels based on the likelihood that a county possesses the workforce development infrastructure needed to support the occupations required by an energy-related industry or sector. Furthermore, the index offers a standardized yet flexible approach that captures regional variations and highlights local strengths and challenges.

17 WIND ENERGY↗
DOE OSTI2026

Northwest Colorado Local Energy Analysis: October 2025 Results

The U.S. Department of Energy's (DOE) Communities Local Energy Action Program (Communities LEAP) provided customized technical assistance to the Northwest Colorado region to assist in developing strategies that facilitate long-term economic benefits through locally driven energy planning and development. The region sought technical assistance to model alternatives energy projects in response to the expected retirement of coal-fired powers plant and associated coal mines by 2030. Northwest Colorado faces a potential economic gap due to the loss of tax revenue, labor income, and jobs within the region due to the impending closure of the Craig and Hayden Power Stations and related mining operations at Trapper and Colowyo mines.

08 HYDROGEN↗
DOE OSTI2026

State, Local, and Tribal Program

NLR's State, Local, and Tribal Program delivers customized, data-driven support that strengthens local energy systems - expanding access to America's abundant energy resources, reducing costs, and supporting energy reliability across the country. NLR's world-class staff use a wide variety of cutting-edge energy tools and capabilities to deliver robust modeling, validation, and deployment support to hundreds of communities annually.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Selenium Migration and Local Structures in Cu‐Doped CdSeTe Solar Cells after Aging

Selenium grading plays a critical role in state-of-the-art Cadmium Telluride photovoltaic cells by enhancing long-wavelength absorption and extending minority carrier lifetimes —key to enabling the current performance record of 23.08%. However, very little is understood about selenium motion. In this study, a comprehensive, multimodal, and multiscale approach is employed to investigate Se migration and local structural changes in copper (Cu)-doped CdSeTe solar cells subjected to accelerated stress. X-ray fluorescence (XRF) microscopy shows unexpected levels of Se diffusion after 500 h under heat (75°C) and light (0.8 suns, 80 mW/cm 2 ), suggesting the coexistence of fast and slow diffusion channels even at low temperatures, with unexpectedly low activation energies (<0.85 eV). X-ray Absorption Near Edge Structure (XANES) analysis indicates a preferential migration of Se atoms to anionic lattice sites and a reduction in Se-Cl co-passivation at Te-terminated dislocation cores. Furthermore, these findings point to a reconfiguration of Se local environments and highlight the potential role of extended structural defects in enabling Se transport at low temperatures. Additionally, XANES results suggest that the presence of metallic Cu across the absorber layer may contribute to back-contact degradation and reduced hole density in both fresh and aged devices.

14 SOLAR ENERGY↗
DOE OSTI2025

Local Thermal Conductivity Patterning in Rotating Lattice Crystals of Anisotropic Sb 2 S 3

The ability to control material heat transport properties over space and time can drive advanced functionalities in thermal management for electronics and system-on-chip, and enable thermal circuits. Despite the technological relevance, there are limited demonstrations of local thermal property control. Rotating lattice single (RLS) crystals—formed via laser-induced crystallization of an amorphous substrate—offer a novel avenue for local crystal engineering, unlocking opportunities for microscale property patterning. Here, thermal conductivity (𝜅) imaging is applied to RLS crystals of Sb2S3 to resolve microscale 𝜅 variations across patterned regions. Amorphous areas exhibit 𝜅 as low as 0.6 Wm −1 K −1 , while crystalline regions display periodic 𝜅 variations from 0.7 to over 2.5 Wm −1 K −1 . These variations correspond to changes in crystal orientation, revealing marked 𝜅 anisotropy. The crystal out-of-plane direction (c axis)—featuring van der Waals bonds—shows amorphous-like transport, whereas in-plane directions (a, b axes) exhibit 3.5x and 1.7x larger 𝜅, respectively. First-principles calculations, in excellent agreement with experiments, suggest that the in-plane anisotropy originates from expressed Sb lone pairs, which impart a corrugation along the b axis affecting bond stiffness and 𝜅. These findings demonstrate microscale control of thermal properties via laser-processed metastructures, with significant implications for next-generation thermal management.

14 SOLAR ENERGY↗
DOE OSTI2024

Zero-Strain Metal-Insulator Transition by the Local Fluctuation of Cation Dimerization

The coupled electronic and structural transitions in metal-insulator transition (MIT) hinder ultrafast switching and ultimate endurance. Decoupling these transitions and achieving a zero-strain electronic MIT can overcome the fundamental limitations of MIT in solid materials. Here, this study demonstrates that iso-valent Ti dopants in supercooled VO 2 epitaxial films cause MIT with minimal hysteresis without changing unit-cell volume and crystal symmetry. The Ti dopants in the VO 2 lattice locally alter the configuration of V-V pairs, where the long-range ordering in V-V pairs is disrupted, and the nano-domains of V-V dimers are formed. Strikingly, these local V-V dimers persist even above the electronic transition temperature (T MI ), facilitating the zero-strain electronic MIT with nanoscale structural heterogeneity. The geometrically compatible interface between insulating and metallic phases drastically enhances switching speed and endurance during electrically and optically driven zero-strain MIT. In conclusion, this discovery offers a fresh perspective on the scientific understanding of MIT and the improved functionality in terms of device speed and reliability by decoupling electronic and structural transitions.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Local p‐ and n‐Type Doping of an Oxide Semiconductor via Electric‐Field‐Driven Defect Migration

Layered oxides exhibit high ionic mobility and chemical flexibility, attracting interest as cathode materials for lithium-ion batteries and the pairing of hydrogen production and carbon capture. Recently, layered oxides emerged as highly tunable semiconductors. For example, by introducing anti-Frenkel defects, the electronic hopping conductance in hexagonal manganites is increased locally by orders of magnitude. Here, local acceptor and donor doping in Er(Mn,Ti)O3 is demonstrated, facilitated by the controlled splitting of anti-Frenkel defects under applied d.c. voltage. By combining density functional theory calculations, scanning probe microscopy, atom probe tomography, and scanning transmission electron microscopy, it is shown that the oxygen defects can readily be moved through the layered crystal structure, leading to nano-sized interstitial-rich (p-type) and vacancy-rich (n-type) regions. The resulting pattern is comparable to dipolar npn-junctions and stable on the timescale of days. These findings reveal the possibility of temporarily functionalizing oxide semiconductors at the nanoscale, giving additional opportunities for the field of oxide electronics and the development of transient electronics in general.

He, Jiali↗
DOE OSTI2025

Examining the Impact of Local Constraint Violations on Energy Computations in DFT

ABSTRACT This work examines the impact of locally imposed constraints in Density Functional Theory (DFT). Using a metric referred to as the extent of violation index (EVI), we quantify how well exchange‐correlation functionals adhere to local constraints. Applying EVIs to a diverse set of molecules for GGA functionals reveals constraint violations, particularly for semi‐empirical functionals. We leverage EVIs to explore potential connections between these violations and errors in chemical properties. While no correlation is observed for atomization energies, a significant statistical correlation emerges between EVIs and total energies. Similarly, the analysis of reaction energies suggests weak positive correlations for specific constraints. However, definitive conclusions about error cancellation mechanisms cannot be made at this time. These observations revealed by EVIs may be useful for consideration when designing future generations of semilocal functionals.

Khanna, Vaibhav [Department of Chemistry Universit↗
DOE OSTI2025

Thermal Gradient Effects on Local Hotspot Ignition in 1,3,5,7‐Tetranitro‐1,3,5,7‐tetrazocane (HMX)

Understanding hotspot ignition, growth, and criticality, as well as the timescales of each, is crucial for parameterizing mesoscale and continuum‐level models that rely on a statistical understanding of hotspots. However, these models often consider hotspots to have uniform temperatures or for hotspots of a given temperature and size to always behave the same. Therefore, using molecular dynamics simulations, we assess the influence of thermal distribution effects on hotspot local ignition and time to ignition in 1,3,5,7‐tetranitro‐1,3,5,7‐tetrazocane (HMX) nanoscale hotspots. Finally, by assessing hotspots with a gradient driven from an initial two‐temperature core–shell setup, we show that small increases in the core temperature under a constant average temperature can lead to order‐of‐magnitude effects on reaction and local ignition timescales.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A Deep Learning Approach for Detection and Localization of Leaf Anomalies

The detection and localization of possible diseases in crops are usually automated by resorting to supervised deep learning approaches. In this work, we tackle these goals with unsupervised models, by applying three different types of autoencoders to a specific open-source dataset of healthy and unhealthy pepper and cherry leaf images. CAE, CVAE and VQ-VAE autoencoders are deployed to screen unlabeled images of such a dataset, and compared in terms of image reconstruction, anomaly removal, detection and localization. The vector-quantized variational architecture turns out to be the best performing one with respect to all these targets.

Calabro', Davide↗
DOE OSTI2024

On the relationship between precipitation extreme and local temperature over eastern China based on convection permitting simulations: roles of different moisture processes and precipitation types

The Clausius–Clapeyron (CC) scaling, which indicates a roughly 7% increase in saturated water vapor per 1 °C increase in temperature, can serve as a strong constraint linking the intensity of precipitation extremes and local temperature. However, the relationship between precipitation extreme and local temperature (referred to as the PE-T relationship) does not always follow the CC scaling and is highly dependent on climate regimes. In this study, we investigated the impacts of different moisture processes and precipitation types on the PE-T relationship over eastern China during the summertime based on convection-permitting model simulations. Consistent with observations, the simulated intensity of precipitation extremes increases with temperature at a rate close to CC (double-CC) scaling below (above) 20 °C. When the temperature exceeds 25 °C, precipitation intensity starts to drop. Precipitation extremes are mainly contributed by the stratiform, MCS (i.e., mesoscale convective system) convective, and non-MCS convective precipitation at low (< 20 °C), medium (20–25 °C), and high (> 25 °C) temperatures, respectively, suggesting that the double-CC scaling occurs when convective types become dominant, while the negative scaling at high temperatures is attributed to the reduced horizontal scale of convection. Corresponding to the reduced intensity of precipitation at high temperatures, there are stronger divergence and subsidence in the low-level atmosphere, which is probably caused by the net cooling associated with the enhanced melting and evaporation of falling hydrometeors due to the lower relative humidity in the low-level atmosphere. Overall, our findings contribute to a deeper understanding of the temperature dependence of precipitation extremes in eastern China.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Transfer learning for probabilistic localization of hidden cracks in concrete structures

Abstract The utility of discriminative supervised learning models built using multiple training-data sources is investigated for hidden crack localization in concrete. Feed-forward neural network (FFNN) is chosen as the model architecture, and transfer learning is used to assimilate the information obtained from different sources (computational physics simulations and laboratory experiments). The labeled training data consists of values of a damage index and the known locations of hidden cracks. The classification models need to learn how the presence of damage (hidden cracks) affects the damage index at different sensors for different test conditions. To this end, diagnostic FFNN models are built by sequentially adding and training new hidden layers to assimilate labeled information from computer models (different model geometries, test conditions, crack lengths, crack locations) and laboratory experiments on a plain cement slab. These transfer learning-based models are then used to localize damage in concrete specimens that reflect real-world conditions (i.e., specimens with steel reinforcement and randomly distributed aggregate). The actual damage state in these specimens is determined by extracting cores and performing petrographic studies on the extracted cores. The damage probability estimated by transfer learning-based models is compared with the petrographic damage rating index (DRI) to identify the most suitable approach to train the diagnostic models. The transfer learning-based diagnostic methodology shows promise and could be used in various structural health monitoring applications, where sufficient labeled data are typically not available from a single data source.

Miele, S.↗
DOE OSTI2025

Local chemical ordering of a neutron-irradiated CrFeMnNi compositionally complex alloy

While ion-irradiation studies are a critical first step in studying compositionally complex alloys (CCAs) for nuclear applications, they do not capture all the microstructural changes occurring under the low irradiation dose rates and different particles’ scattering patterns experienced in a nuclear reactor setting. To explore these phenomena in reactor-relevant conditions for the first time in CCA, the single-phase solid-solution Cr 10 Fe 30 Mn 30 Ni 30 was neutron irradiated up to 6.61 displacements per atom at 395 and 579 °C. Irradiation-enhanced local chemical ordering (LCO) well beyond the range of short range ordering was observed, and is predicted to be the precursor to the precipitation of a coherent Ni-Mn L1 0 phase and a Cr-rich α’ phase, though TEM analysis did not indicate the presence of either in any irradiation condition. The line density of faulted dislocation loops decreased from 6.47 to 1.69 ∙ 10 15 m -2 from 3.43 to 6.61 dpa at 579 °C despite no appreciable faulted loop content in the unirradiated material. LCO is expected to increase the complexity of the energy landscape within this alloy, restricting interstitial point defect mobility and creating local regions of greater stacking fault energy. These contribute to the negative correlation between irradiation dose and faulted dislocation loop density in this study, as well as the lack of void swelling observed.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Local heat transfer measurement in a volumetrically heated TPMS lattice using distributed optical fiber thermal sensing

As additive manufacturing continues to reduce design constraints on heat exchange geometries, methods for high-fidelity local heat transfer measurements in nonconventional channel geometries are critical to their continued development. This study presents a novel method for measuring local heat transfer performance in volumetrically heated lattices using a distributed optical fiber temperature sensor. A diamond-type triply periodic minimal surface (TPMS) lattice, 3D-printed from a conductive polymer, was Joule heated while it was convectively cooled with air. Temperature measurements were taken at the solid–fluid interface across 14 internal locations using a single optical fiber over the Reynolds number range 800–2750. The TPMS lattice achieved up to 312% higher heat transfer coefficients compared to developing flow in a straight tube. A Nusselt number correlation was developed for the diamond TPMS, which showed good agreement with data collected for comparable geometries available in literature. In conclusion, this study presents a robust and new method for experimental measurement of the heat transfer coefficient in complex geometries and helps to understand and quantify the exceptional performance of TPMS heat transfer geometries.

TPMS↗
DOE OSTI2025

Contrasting effects of land-use and local disturbance on plant and pollinator communities in wetlands

While pollinators and wetlands both provide important ecosystem services (e.g., the pollination of flowering plants and improving water quality), the relationship between the two is not well understood. Both biotic and abiotic effects can mediate the local wetland flower and pollinator community. In this study, we investigated how land use, including a land use gradient at five different radii, from 250 m to 2 km, along with anthropogenic disturbance affected pollinators in wetland ecosystems. We surveyed the abundance and diversity of plant-pollinator communities in fifteen different wetlands across two years. We also tested the relationship between water quality and temperature, and the abundance and diversity of flowering plants and pollinating insects. Our results suggest that increasing temperature, which was strongly associated with developed land use, had a negative effect on the floral display of wetland plants, as well as the abundance of all flower visitors and hover flies. Hover fly abundance was also positively associated with agricultural land use and total nitrogen in the water. Meanwhile, the abundance of female bees was affected by an interaction between temperature and disturbance: female bees were most abundant when temperatures were lower in areas of low disturbance. In contrast, pollinator species richness increased with temperature when developed land use was low, and floral diversity was strongly affected by several interactions between disturbance, land use, and water quality. Finally, the community composition of both plants and insects varied significantly among low, medium, and high disturbance categories, with weedier, non-native species being significantly associated with areas of higher disturbance and in sites with greater anthropogenic land use. We demonstrate that ecological communities shift significantly in response to anthropogenic change. Our work also illustrates the importance of quantifying interactions between land use and local disturbance with abiotic factors such as temperature and water quality on ecological systems.

Disturbance↗
DOE OSTI2026

Local reduced-order modeling for electrostatic plasmas by physics-informed solution manifold decomposition

Despite advancements in high-performance computing and modern numerical algorithms, computational cost remains prohibitive for multi-query kinetic plasma simulations. Here, in this work, we develop data-driven reduced-order models (ROMs) for collisionless electrostatic plasma dynamics, based on the kinetic Vlasov-Poisson equation. Our ROM approach projects the equation onto a linear subspace defined by the proper orthogonal decomposition (POD) modes. We introduce an efficient tensorial method to update the nonlinear term using a precomputed third-order tensor. We capture multiscale behavior with a minimal number of POD modes by decomposing the solution manifold into multiple time windows and creating temporally local ROMs. We consider two strategies for decomposition: one based on the physical time and the other based on the electric field energy. Applied to the 1D1V Vlasov–Poisson simulations, that is, prescribed E-field, Landau damping, and two-stream instability, we demonstrate that our ROMs accurately capture the total energy of the system both for parametric and time extrapolation cases. The temporally local ROMs are more efficient and accurate than the single ROM. In addition, in the two-stream instability case, we show that the energy-windowing reduced-order model (EW-ROM) is more efficient and accurate than the time-windowing reduced-order model (TW-ROM). With the tensorial approach, EW-ROM solves the equation approximately 90 times faster than Eulerian simulations while maintaining a maximum relative error of 7.5% for the training data and 11% for the testing data.

Electrostatic plasmas↗