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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

An AI-Based 3D Bat Movement Tracking System at Wind Energy Facilities Using Multi-Thermal Video Cameras

The poster at the 15th Wind Wildlife Research Meeting discusses how to leverage the potential of real-time thermal-imaging methodologies in quantifying nocturnal bat activities at wind turbines, using 3D computer vision techniques within a deep learning framework. This innovation enables the automatic detection and classification of bats, birds, and insects in thermal-imaging videos captured at wind turbine sites, facilitating efficient and accurate data analysis for enhanced understanding and mitigation of bat-wind turbine interactions.

AI↗
DOE OSTI2025

An AI-Based 3D Bat Movement Tracking System at Wind Energy Facilities Using Multi-Thermal Video Cameras

The talk at the NAWEA Wind Tech 2024 conference discusses how to leverage the potential of real-time thermal-imaging methodologies in quantifying nocturnal bat activities at wind turbines, using 3D computer vision techniques within a deep learning framework. This innovation enables the automatic detection and classification of bats, birds, and insects in thermal-imaging videos captured at wind turbine sites, facilitating efficient and accurate data analysis for enhanced understanding and mitigation of bat-wind turbine interactions.

AI↗
DOE OSTI2026

California Trees Seasonally Use Augmented Water Sources: Water Isotope Tracking in a Groundwater‐Dependent Ecosystem

Sustainable groundwater management must account for the needs of groundwater dependent ecosystems. To understand the relationship of ecosystems and seasonal water use, we studied the stable isotope composition (δ 18 O and δ 2 H) of water in streamside trees in a semi-arid streamside environment (Livermore, California, USA). We sampled seven trees at two sites every other month from April 2024 through April 2025 for tree xylem stable water isotope signatures. These data were compared to potential source waters: precipitation, imported surface water, soil water and regional groundwaters. Large daily precipitation events were found to be isotopically similar to regional groundwater and were thus treated as one water source. A Bayesian mixing model using stable water isotopes was used to determine the ratios of these three potential source waters (small daily precipitation events, groundwater/large daily precipitation events and imported water) present in tree xylem water. On average, tree water sources include 32% imported water (SD = 9%), 35% small daily precipitation events (SD = 10%) and 33% groundwater (SD = 3%), with significant seasonal variation (t summer-winter = 30.8, p < 0.01), particularly drawing more imported water (more than 55%) in the summer. While small daily precipitation events contribute only 10% of the total precipitation in our dataset, it represents a third of water used by trees. In addition, while these ecosystems are designated as groundwater dependent ecosystems, the trees use approximately one third imported water and even more during dry summer months. This approach provides water managers with a practical tool for quantifying ecosystem water needs, supporting data-driven decisions and regulatory compliance. While California's Sustainable Groundwater Management Act emphasizes supporting groundwater dependent ecosystems, it allows flexibility in demonstrating benefits. In conclusion, our methodology provides a way to document that management actions (such as managed aquifer recharge with imported water) deliver measurable co-benefits to GDEs.

Geosciences↗
DOE OSTI2025

Spatio-temporal multivariate cluster evolution analysis for detecting and tracking climate impacts

Recent years have seen a growing concern about climate change and its impacts. While Earth System Models (ESMs) can be invaluable tools for studying the impacts of climate change, the complex coupling processes encoded in ESMs and the large amounts of data produced by these models, together with the high internal variability of the Earth system, can obscure important source-to-impact relationships. Here, this paper presents a novel and efficient unsupervised data-driven approach for detecting statistically-significant impacts and tracing spatio-temporal source-impact pathways in the climate through a unique combination of ideas from anomaly detection, clustering and Natural Language Processing (NLP). Using as an exemplar the 1991 eruption of Mount Pinatubo in the Philippines, we demonstrate that the proposed approach is capable of detecting known post-eruption impacts/events. We additionally describe a methodology for extracting meaningful sequences of post-eruption impacts/events by using NLP to efficiently mine frequent multivariate cluster evolutions, which can be used to confirm or discover the chain of physical processes between a climate source and its impact(s).

Anomaly detection↗
DOE OSTI2025

Tracking Dendritic Growth in Hydrogen-Based Hematite Reduction via Computer Vision

The reduction of hematite to metallic iron using hydrogen (H2) as a reducing agent presents a promising pathway for decarbonizing steel production. In this study, we employ a combination of in situ confocal scanning laser microscopy (CSLM) and advanced computer vision techniques to quantitatively analyze dendritic growth of ferrite during H2-based reduction of iron oxide at high temperatures. A workflow integrating Watershed Image Segmentation (WIS) and Lucas-Kanade Optical Flow (LKOF) is developed to extract both global and local kinetic information from time-resolved micrograph sequences. H2 reduction experiments conducted at 1400 degrees C and 1500 degrees C demonstrate a clear correlation between temperature and reduction rate, as evidenced by accuracy of fitted Johnson-Mehl-Avrami-Kolmogorov (JMAK) parameters. Optical flow analysis further elucidates the anisotropic and branched nature of dendritic growth, providing spatially resolved velocity fields that correlate well with global transformation kinetics. The proposed methodology demonstrates strong agreement with experimental measurements and literature values, offering a robust framework for automated image-based analysis to study kinetics through microstructural evolution in the reduction of iron ore, and likely other reaction-diffusion phenomena.

08 HYDROGEN↗
DOE OSTI2025

yProv4ML: Effortless provenance tracking for machine learning systems

The rapid growth in interest in deep learning and foundation models (FMs) in particular, has attracted the attention of a diverse range of researchers thanks to their generalization ability. However, the advent of these techniques has also brought to light the lack of transparency and rigor in the way development is pursued. In particular, the inability to determine the number of epochs and other hyperparameters in advance presents challenges in identifying the best model. To address this challenge, machine learning frameworks such as MLFlow can automate the collection of this type of information. However, these tools capture data using proprietary formats and pose little attention to lineage. This paper proposes yProv4ML, a framework that captures provenance information generated during machine learning processes in PROV-JSON format, with minimal code modification.

Machine learning↗
DOE OSTI2026

Single-Molecule Tracking Measurements Reveal the Detailed Mechanisms of Molecular Diffusion in Solvent Mixtures under Nanoconfinement

Understanding mass transport mechanisms in nanopores is important for developing advanced materials for chemical separations, chemical sensing, and energy storage. This paper reports a novel imaging platform that is employed for the first time to investigate the detailed diffusion dynamics of single rhodamine B (RhB) dye molecules confined within solution-filled cylindrical anodic aluminum oxide (AAO) nanopores. The imaging platform relies on illumination of horizontally-oriented AAO nanopores in a highly inclined and laminated optical (HILO) light sheet microscopy geometry. The method was used to investigate the translational and orientational dynamics of single rhodamine B (RhB) molecules within horizontally-oriented 5- and 10-nm diameter AAO nanopores filled with water–ethanol mixtures. The established platform enabled the observation of one-dimensional motion along the pore axis involving occasional short- or long-term immobilization at the single-molecule level. Analysis of cumulative squared-displacement distributions revealed fast (5 – 30 µm²/s), intermediate (1 – 5 µm²/s), and slow (< 1 µm²/s) diffusion components. From the effects of mixture composition and pore size on the contributions of these three components, we inferred that the fast, intermediate, and slow components could be assigned to desorption-mediated hopping, crawling, and wiggling motions, respectively. The platform based on the horizontally-oriented AAO nanopores also permitted single-molecule emission polarization measurements that revealed the negligible steric confinement of individual diffusing RhB molecules within the AAO nanopores. The imaging platform based on AAO membranes and HILO microscopy provided a unique means to investigate how solvation-mediated surface interactions and nanoconfinement govern molecular transport in nanoporous environments.

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

In Situ Atomic Tracking on the Interfacial Etching and Reconfiguration of Cu-ReSe 2 Contact during Thermal Annealing

The Schottky barrier height can be greatly affected by the metal diffusion, reaction, and covalent bonding formation at the contact. Exploring novel methods and revealing the fundamental mechanisms for contact engineering are of vital importance for microelectronic devices. Here, in this study, the annealing induced interfacial reactions at Cu-ReSe 2 contact are dynamically revealed from the atomic scale. Accompanied by the diffusion of Se to Cu, ReSe 2 is gradually decomposed to a thin Re interlayer through a “chain-by-chain” manner. Theoretical calculations show that the Cu atoms can facilitate the chemical bond breaking of ReSe 2 , significantly lowering the Se diffusion energy barrier toward Cu. The formed Re/ReSe 2 heterostructure presents a metal-like band structure, which underscores the critical role of Cu in altering the interfacial chemistry and promoting carrier transport across the interface. Our results can provide vital insights into the contact properties of ReSe 2 and provide a possible method for fabricating high-performance ReSe 2 -based devices.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Nanoscale Tracking of the High-Temperature Spin-State Transition in LaCoO 3

The high-temperature spin and electronic transitions in LaCoO 3 have recently been leveraged to create neuromorphic (brain-inspired) devices. While these devices have shown the potential for impactful functionality in next-generation computing systems, the nanoscale dynamics of the spin and electronic transitions that underlie their operation are not well understood. Inhomogeneities related to interfaces, electrode contacts, strain, and crystal defects can all affect device performance, making nanoscale characterization of the transitions essential for producing consistent and reliable devices. Here, we demonstrate the first nanoscale in situ measurement of the spin transition in LaCoO 3 at device-relevant temperatures (25–325 °C) over length scales of tens of nanometers using STEM-EELS. This measurement is enabled by an Al 2 O 3 coating, which prevents unwanted reduction of the LaCoO 3 specimen at high temperature and vacuum. The detailed understanding of LaCoO 3 transition dynamics enabled by such measurements will be crucial for optimizing LaCoO 3 -based neuromorphic devices and increasing reliability for real-world application.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Tracking Thermal Transport in Colloidal Quantum Dot Films Using in Situ Time-Resolved X-ray Diffraction

Colloidal quantum dots (QDs) and their thin films are increasingly used in electronic and photonic devices replacing traditional bulk semiconductors. However, thermal properties of QDs remain underexplored relative to device development efforts. This study shows the use of time-resolved X-ray diffraction as a contact-free method to probe the thermal response of QDs in environments representative of the active layer in QD optoelectronic devices, providing in situ insights for future thermal management strategies. Through the extraction of Debye–Waller factors on a subnanosecond time scale, we directly capture the heating and cooling of core/shell CdSe/CdS QDs following pulsed optical excitation. In a QD thin film that actively provides optical gain, the thermal conductivity is found to be as low as 0.13 W m –1 K –1 , because of the poor heat flow between close-packed QD solids. For QDs dispersed in liquids, interfacial thermal conductance dominates thermal relaxation, with a conductance of 15 MW m –2 K –1 .

36 MATERIALS SCIENCE↗