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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Deep learning models map rapid plant species changes from citizen science and remote sensing data

Anthropogenic habitat destruction and climate change are reshaping the geographic distribution of plants worldwide. However, we are still unable to map species shifts at high spatial, temporal, and taxonomic resolution. Here, we develop a deep learning model trained using remote sensing images from California paired with half a million citizen science observations that can map the distribution of over 2,000 plant species. Our model— Deepbiosphere— not only outperforms many common species distribution modeling approaches (AUC 0.95 vs. 0.88) but can map species at up to a few meters resolution and finely delineate plant communities with high accuracy, including the pristine and clear-cut forests of Redwood National Park. These fine-scale predictions can further be used to map the intensity of habitat fragmentation and sharp ecosystem transitions across human-altered landscapes. In addition, from frequent collections of remote sensing data, Deepbiosphere can detect the rapid effects of severe wildfire on plant community composition across a 2-y time period. These findings demonstrate that integrating public earth observations and citizen science with deep learning can pave the way toward automated systems for monitoring biodiversity change in real-time worldwide.

Gillespie, Lauren E.↗
DOE OSTI2025

How transparent is graphene? A surface science perspective on remote epitaxy

Remote epitaxy is the synthesis of a single crystalline film on a graphene-covered substrate, where the film adopts epitaxial registry to the substrate as if the graphene is transparent. Despite many exciting applications for flexible electronics, strain engineering, and heterogeneous integration, an understanding of the fundamental synthesis mechanisms remains elusive. Here we offer a perspective on the synthesis mechanisms, focusing on the foundational assumption of graphene transparency. We identify challenges for quantifying the strength of the remote substrate potential that permeates through graphene, and propose Fourier and beating analysis as a bias-free method for decomposing the lattice potential contributions from the substrate, from graphene, and from surface reconstructions, each at different frequencies. We highlight the importance of graphene-induced reconstructions on epitaxial templating, drawing comparison to moiré epitaxy. We highlight the role of the remote potential in tuning surface diffusion and adatom kinetics on graphene, which are crucial for navigating the competition between remote epitaxy and defect-seeded mechanisms like pinhole epitaxy. In light of this weak remote potential, we re-evaluate the current state-of-the-art experimental evidence, highlighting why it remains challenging to experimentally validate a ‘remote’ epitaxy mechanism that cannot be explained by alternatives, such as pinhole-seeded epitaxy or serial van der Waals epitaxy. We end with one experimental example that, to out knowledge, cannot be explained by competing mechanisms: a different long-range epitaxial relationship for GdPtSb films grown on graphene/sapphire, compared to direct epitaxy on sapphire. We suggest for future experiments that directly measure the remote potential and impact of tuneable growth kinetics.

epitaxy↗
DOE OSTI2024

The 2024 “Hacking Limnology” Workshop Series and Virtual Summit: Increasing Inclusion, Participation, and Representation in the Aquatic Sciences

The 4th Aquatic Ecosystem MOdeling Network—Junior (AEMON-J) Hacking Limnology Workshop and 5th Virtual Summit: Incorporating Data Science and Open Science in the Aquatic Sciences (DSOS) convened 15–19 July 2024. During the week, these joint communities engaged in activities at the intersection of big data, open science, modeling, remote sensing, and the aquatic sciences. The weeklong event, with over 100 aquatic science practitioners and enthusiasts, followed a similar structure to previous years, comprising three days of workshops followed by two days of the virtual summit.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Unveiling the mechanism of remote epitaxy of crystalline semiconductors on 2D materials-coated substrates

Abstract Remote epitaxy has opened novel opportunities for advanced manufacturing and heterogeneous integration of two-dimensional (2D) materials and conventional (3D) materials. The lattice transparency as the fundamental principle of remote epitaxy has been studied and challenged by recent observations defying the concept. Understanding remote epitaxy requires an integrated approach of theoretical modeling and experimental validation at multi-scales because the phenomenon includes remote interactions of atoms across an atomically thin material and a few van der Waals gaps. The roles of atomically thin 2D material for the nucleation and growth of a 3D material have not been integrated into a framework of remote epitaxy research. Here, we summarize studies of remote epitaxy mechanisms with a comparison to other epitaxy techniques. In the end, we suggest the crucial topics of remote epitaxy research for basic science and applications. Graphical Abstract

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2023

High-Throughput Field Plant Phenotyping: A Self-Supervised Sequential CNN Method to Segment Overlapping Plants

High-throughput plant phenotyping—the use of imaging and remote sensing to record plant growth dynamics—is becoming more widely used. The first step in this process is typically plant segmentation, which requires a well-labeled training dataset to enable accurate segmentation of overlapping plants. However, preparing such training data is both time and labor intensive. To solve this problem, we propose a plant image processing pipeline using a self-supervised sequential convolutional neural network method for in-field phenotyping systems. This first step uses plant pixels from greenhouse images to segment nonoverlapping in-field plants in an early growth stage and then applies the segmentation results from those early-stage images as training data for the separation of plants at later growth stages. The proposed pipeline is efficient and self-supervising in the sense that no human-labeled data are needed. We then combine this approach with functional principal components analysis to reveal the relationship between the growth dynamics of plants and genotypes. We show that the proposed pipeline can accurately separate the pixels of foreground plants and estimate their heights when foreground and background plants overlap and can thus be used to efficiently assess the impact of treatments and genotypes on plant growth in a field environment by computer vision techniques. This approach should be useful for answering important scientific questions in the area of high-throughput phenotyping.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Interannual variability of spring and summer monsoon growing season carbon exchange at a semiarid savanna over nearly two decades

Eddy covariance measurements of land-atmosphere energy, carbon, and water exchange now span multiple decades at some sites, supporting an improved understanding of flux interannual variability (IAV) and its ecophysiological and physical controls. Most eddy covariance IAV studies have focused on temperate forest ecosystems, where carbon fluxes are large and flux records are longest – but also where IAV is much lower than in dryland regions, which have been identified as an essential driver of the trend and variability in the global terrestrial carbon sink. In this study, we leveraged 19 years of continuous micrometeorological measurements at the AmeriFlux US-SRM mesquite savanna site in southern Arizona, USA to quantify the IAV, trends, and drivers of carbon fluxes during the distinct spring and summer growing seasons. We also assessed the ability of modern satellite and land surface models to capture the IAV of seasonal water and carbon fluxes. Annual net ecosystem production (NEP) was small and highly variable (23 +/- 64 gC m –2 yr –1 ). Precipitation and associated measures of water availability determined most of the variability in NEP, largely through their influence on annual and seasonal gross ecosystem productivity (GEP) as opposed to ecosystem respiration (ER). Root-zone soil moisture captured between 73% (spring) and 85% (summer) of GEP variability and between 73% (spring) and 58% (summer) of ER variability. Throughout the study period, soil moisture and greenness increased with associated increases in GEP, ER and NEP. These trends were strongly influenced by very productive and wet summer growing seasons during the last two years, which were characterized by abundant understory grass cover. Typically, less than half of the variability in growing season GEP and evapotranspiration was captured by satellite-based estimates and land surface model simulations with local site forcing and calibration, highlighting the ongoing utility of long-term datasets to support careful model testing and improvement.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Automated Model for Improved Mapping of Country-Scale High-Resolution Coastal Bathymetry

Accurate and up-to-date maps of coastal bathymetry are critical for a variety of sectors from vessel navigation to port construction and are increasingly vital to inform coastal infrastructure management amid accelerating sea-level rise and more frequent and severe storm-surge events. The primary challenges to accurate and efficient bathymetric mapping from optical remote sensing are: accurately modeling light attenuation in both the atmosphere and water column; and inefficient data processing pipelines for highresolution satellite imagery. To address the effects of light attenuation within the water-column we have developed a novel physics-based bathymetry model that accounts for variations in water-column inherent optical properties on a pixel-by-pixel basis in optically-shallow aquatic environments, which represents a major advancement. For applications to satellite imagery, we have developed a software package that automatically applies the robust 6S atmospheric correction algorithm, estimates the bottom depth from the physics-based bathymetry model, which corrects for attenuation by suspended particulate matter and colored dissolved organic matter in the water column on a pixel-by-pixel basis, and leverages highperformance computing for rapid application to region-scale (e.g., CONUS) 2-meter resolution imagery datasets. Our approach is tailored to sensors that collect data at two-meter resolution with high return times for frequent updates. We mapped 591 WorldView satellite images for Florida, North Carolina, and Alaska and validated the maps against LiDAR-derived bathymetry data. Results show median RMSE of 1.75, 1.59, and 2.67 meters, respectively. By combining the strengths of Oak Ridge National Laboratory in high-performance computing and remote-sensing science with the water-column modeling expertise of Scripps Institution of Oceanography we advance the state of bathymetric mapping capability.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Large reductions in Permian Basin methane intensity shown in multi-year comparison of aerially-visible methane emissions

Spanning the US states of Texas and New Mexico, the Permian Basin has been a hotspot of methane emissions from oil and natural gas activity 1–4, although studies disagree over the magnitude of these emissions. The most comprehensive measurement campaigns published were conducted in 2019 1–5 .There have been large changes in the energy industry since then, including in the prices of oil and gas, both state and federal regulatory environments, investor and activist pressure over methane emissions, and the adoption of new technologies and policies by energy operators. Understanding how any or all of these might influence methane emissions is important for policy makers, oil and gas operators, and other stakeholders. We characterize the time evolution of Permian Basin methane emissions using a series of comprehensive aerial surveys conducted every year from 2020-2023 and compare them to the 2019 results cited above. To maintain comparability, all the data sets are from surveys using Insight M point source methane sensing technology. The scope of these surveys expanded over time: from 33-46% of wells, oil production, and gas production in 2020 to 60-65% in 2021, to 84% of wells and over 90% of both oil and gas production in 2023. These surveys by Insight M also include hundreds of gas processing plants and compressor stations as well as 1000s of km of gathering and transmission pipelines. Considering only the aerially detected portion of emissions (typically the majority of the total in such surveys 4), we find reductions of more than 70% in methane emissions intensity compared to the 2019 New Mexico-only Insight M survey, with variation depending on the year 3,4. Notably, although sources below 100 kg/hr contributed less than 10% of aerially measured emissions the 2019 New Mexico survey 3, these smaller sources constitute a larger proportion of total aerially measured emissions (although not the majority) in 2020-2023. Production facilities and gathering pipelines are responsible for the larges shares of total emissions, followed by compressor stations and gas processing plants. Permian methane emissions were also measured in a comprehensive 2019 Permian-wide survey by the Carbon Mapper team 2. That analysis led to a lower total emissions estimate at the time 4. These new Insight M-based emission rates are still roughly 30-70% lower than the aerially measured portion of the 2019 Carbon Mapper-based estimates 4. Further work is needed to harmonize these surveys in space and time to create the most intercomparable numbers possible 5. Additional analysis is needed to compare our findings to the more spatially constrained 2020, 2021, and 2023 Carbon Mapper surveys in the Permian 4,6. The evidence is strong from these two survey teams that emissions intensity has declined significantly since 2019. Reasons for this trend are currently unclear but point to possible success of emissions control programs. Future work investigating frequency, source, and operator-specific intensities could provide insights into the causes of this promising trend.

methane, oil and gas, data science, remote sensing↗
DOE OSTI2023

Editorial: Advances in observations and modeling of snow, forest-snow processes and snow hydrology

Seasonal snowpack plays a pivotal role in the regional water cycle. In Western mountainous regions, where precipitation predominantly occurs as snow during winter and is limited in the summer months when water demand peaks, snowpack serves as a critical water source essential for sustaining water supply, ecosystems, agriculture, and industries. Additionally, snowpack dynamically influences extreme events, such as floods, droughts, and wildfires, through intricate land-atmosphere feedback. Nevertheless, significant knowledge gaps persist within this field due to data limitations and the complexity of the physics involved in modeling snow and snow hydrology (i.e., snow acts as a critical upstream hydrological process). Here, this research topic presents a collection of manuscripts that address some of these important research gaps.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Leveraging Machine Learning and Geo-Tagged Citizen Science Data to Disentangle the Factors of Avian Mortality Events at the Species Level

Abrupt environmental changes can affect the population structures of living species and cause habitat loss and fragmentations in the ecosystem. During August–October 2020, remarkably high mortality events of avian species were reported across the western and central United States, likely resulting from winter storms and wildfires. However, the differences of mortality events among various species responding to the abrupt environmental changes remain poorly understood. In this study, we focused on three species, Wilson’s Warbler, Barn Owl, and Common Murre, with the highest mortality events that had been recorded by citizen scientists. We leveraged the citizen science data and multiple remotely sensed earth observations and employed the ensemble random forest models to disentangle the species responses to winter storm and wildfire. We found that the mortality events of Wilson’s Warbler were primarily impacted by early winter storms, with more deaths identified in areas with a higher average daily snow cover. The Barn Owl’s mortalities were more identified in places with severe wildfire-induced air pollution. Both winter storms and wildfire had relatively mild effects on the mortality of Common Murre, which might be more related to anomalously warm water. Our findings highlight the species-specific responses to environmental changes, which can provide significant insights into the resilience of ecosystems to environmental change and avian conservations. Additionally, the study emphasized the efficiency and effectiveness of monitoring large-scale abrupt environmental changes and conservation using remotely sensed and citizen science data.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Geophysical Observations of the 2023 September 24 OSIRIS-REx Sample Return Capsule Reentry

Sample return capsules (SRCs) entering Earth's atmosphere at hypervelocity from interplanetary space are a valuable resource for studying meteor phenomena. The 2023 September 24 arrival of the Origins, Spectral Interpretation, Resource Identification, and Security-Regolith Explorer SRC provided an unprecedented chance for geophysical observations of a well-characterized source with known parameters, including timing and trajectory. A collaborative effort involving researchers from 16 institutions executed a carefully planned geophysical observational campaign at strategically chosen locations, deploying over 400 ground-based sensors encompassing infrasound, seismic, distributed acoustic sensing, and Global Positioning System technologies. Additionally, balloons equipped with infrasound sensors were launched to capture signals at higher altitudes. This campaign (the largest of its kind so far) yielded a wealth of invaluable data anticipated to fuel scientific inquiry for years to come. The success of the observational campaign is evidenced by the near-universal detection of signals across instruments, both proximal and distal. This paper presents a comprehensive overview of the collective scientific effort, field deployment, and preliminary findings. The early findings have the potential to inform future space missions and terrestrial campaigns, contributing to our understanding of meteoroid interactions with planetary atmospheres. Furthermore, the data set collected during this campaign will improve entry and propagation models and augment the study of atmospheric dynamics and shock phenomena generated by meteoroids and similar sources.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Cyber Framework for Steering and Measurements Collection Over Instrument-Computing Ecosystems

We propose a framework to develop cyber solutions to support the remote steering of science instruments and measurements collection over instrument-computing ecosystems. It is based on provisioning separate data and control connections at the network level, and developing software modules consisting of Python wrappers for instrument commands and Pyro server-client codes that make them available across the ecosystem network. We demonstrate automated measurement transfers and remote steering operations in a microscopy use case for materials research over an ecosystem of Nion microscopes and computing platforms connected over site networks. The proposed framework is currently under further refinement and being adopted to science workflows with automated remote experiments steering for autonomous chemistry laboratories and smart energy grid simulations.

Al Najjar, Anees↗
DOE OSTI2019

Growth and opportunities in networked synthesis through AmeriFlux

Since its inception in 1996 with just 15 sites, the AmeriFlux network has grown to include over 300 sites, representing every major ecosystem type across the Americas. This grassroots coalition of the willing has for the past two decades continuously measured the exchange of carbon, water and energy between ecosystems and the atmosphere. Recent years in particular have seen remarkable growth in both the degree of coordination of activities within the AmeriFlux network, and the number of researchers involved. Through the AmeriFlux Management Project, the network has made public over 1500 site-years of observations. This project now represents over 5000 registered members, a quarter of whom have signed up in the past year, who use the observations for a range of applications, including ecosystem science, modeling, and remote sensing, but also education and outreach.

photosynthesis↗