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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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751 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Nuclear quantum effects in molecular liquids across chemical space

Abstract Nuclear quantum effects (NQEs) influence many physical and chemical phenomena, particularly those involving light atoms or occurring at low temperatures. However, their impact has been carefully quantified in few systems-like water-and is rarely considered more broadly. Here we use path-integral molecular dynamics to systematically investigate NQEs on thermophysical properties of 92 organic liquids at ambient conditions. Depending on chemical constitution, we find substantial impact across thermal expansivity, compressibility, dielectric constant, enthalpy of vaporization, and notably molar volume, which shows consistent, positive quantum-classical differences up to 5%; similar, less pronounced trends manifest as isotope effects from deuteration. Using data-driven analysis, we identify three features-molar mass, classical hydrogen density, and classical thermal expansivity-that accurately predict NQEs and facilitate understanding of how characteristics like branching and heteroatom content influence behavior. This work highlights the broad relevance of NQEs in molecular liquids, while also providing a conceptual and practical framework to anticipate their impact.

Science & Technology - Other Topics↗
DOE OSTI2025

Carbon Utilization and Storage Partnership of the Western United States

This technical report documents research conducted under DOE Award No. DE-FE0031837 focused on evaluating the feasibility of carbon capture, utilization, and storage (CCUS) systems in the central and western United States. The project integrated geologic characterization, reservoir simulation, infrastructure modeling, and economic analysis to assess CO₂ storage potential near industrial sources and develop strategies for transport and sequestration. The work included subsurface modeling, risk assessment, monitoring and verification (MRV) planning, and evaluation of regulatory pathways such as EPA Underground Injection Control (UIC) Class VI permitting and IRS 45Q tax credit eligibility. Results demonstrate the viability of multiple storage approaches, including saline formations, enhanced coalbed methane recovery, and basalt mineralization, supported by data-driven workflows and regional analyses. The project also produced permitting templates, technology transfer activities, and stakeholder engagement efforts to support deployment readiness. These findings contribute to the development of scalable, economically viable CCUS systems and provide a repeatable framework for future carbon management projects.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2026

U.S. ESCO Industry Report: Industry Size and Recent Market Trends, 2022- 2024

The latest edition of the U.S. Energy Service Company (ESCO) Industry Report by Lawrence Berkeley National Laboratory (LBNL) finds that the U.S. ESCO industry continues to show strong growth. The report draws from ESCO industry reported revenue data for the 2022-2024 period, detailing the current size and characteristics of the U.S. ESCO industry. Following 20 years of ESCO industry reports, the 2024 report explores significant revenue trends across market segments, geographic regions, ESCO size, financing structures, and business activities. New analysis in this report outlines customer priorities and non-energy benefit drivers of Energy Savings Performance Contract projects, adjusted revenue analysis detailing the impacts of inflation on industry growth, and project challenges by market segment.

Chelminski, Kathryn↗
DOE OSTI2024

Estradiol associations with brain functional connectivity in postmenopausal women

Abstract Objective Previous studies have found that estrogens play a role in functional connectivity in the brain; however, little research has been done regarding how estradiol is associated with functional connectivity in postmenopausal women. The purpose of this study was to examine the relationship between estradiol and functional connectivity in postmenopausal women. Methods Structural and blood oxygenation level–dependent resting-state magnetic resonance imaging scans of 88 cognitively healthy postmenopausal individuals were obtained along with blood samples collected the same day as the magnetic resonance imaging to assess hormone levels. We generated connectivity values in CONN toolbox version 20.b, an SPM-based software. Results A regression analysis was run using estradiol level and regions of interest (ROI), including the hippocampus, parahippocampus, dorsolateral prefrontal cortex, and precuneus. Estradiol level was found to enhance parahippocampal gyrus anterior division left functional connectivity during ROI-to-ROI regression analysis. Estradiol enhanced functional connectivity between the parahippocampal gyrus anterior division left and the precuneus as well as the parahippocampal gyrus anterior division left and parahippocampal gyrus posterior division right. An exploratory analysis showed that years since the final menstrual period was related to enhanced connectivity between regions within the frontoparietal network. Conclusions These results illustrated the relationship between estradiol level and functional connectivity in postmenopausal women. They have implications for understanding how the functioning of the brain changes for individuals after menopause that may eventually lead to changes in cognition and behavior in older ages.

Obstetrics & Gynecology↗
DOE OSTI2026

Explainable machine learning reveals that local structural motifs encode the thermodynamic state across the CuZr metallic glass-forming range

Metallic glasses derive their properties from the statistics of local atomic motifs rather than from long-range order, yet a quantitative, chemistry-specific link between motif populations and the underlying glassy state has remained elusive. In this work we combine large-scale molecular dynamics, Voronoi tessellation, deep neural networks, and SHapley Additive exPlanations (SHAP) to identify which local structural motifs define the glassy state of Cu—Zr metallic glasses. A dataset of 17,180 atomistic configurations spanning ten compositions (Cu 20 Zr 80 –Cu 80 Zr 20 ) and four quench rates (10 9 –10 12 K/s) is used to train a feed-forward neural network that regresses temperature across the 50–2000 K liquid–supercooled–glass range, achieving a mean absolute error of 19.89 K and R 2 = 0.9974, confirming that the local structural state is faithfully encoded in motif-level structure. SHAP analysis then reveals that a tightly coupled near-icosahedral family of motifs (coordination numbers (CN) 11–13, including the full icosahedron 001200 and its single-atom-perturbation sibling 10930) collectively encodes the thermodynamic state of the system across the full glass-forming range. The CN = 11–13 ordered members carry negative SHAP values at high populations, tracking the most deeply-quenched configurations, while 10930 shows the reversed signature consistent with its role as a soft-spot host whose population shrinks as the icosahedral network deepens. The analysis demonstrates that explainable machine learning can isolate the minimal motif vocabulary defining the glassy state and recovers the near-icosahedral building blocks previously identified by data-driven analyses of Cu—Zr. The approach provides a general, chemistry-specific route for characterizing the structural state of disordered materials.

36 MATERIALS SCIENCE↗
DOE OSTI1988

Nuclear Safety [Vol. 29, No. 3, July-September 1988]

Nuclear Safety is a review journal that covers significant developments in the field of nuclear safety. Its scope includes the analysis and control of hazards associated with nuclear energy, operations involving fissionable materials, and the products of nuclear fission and their effects on the environment. Primary emphasis is on safety in reactor design, construction, and operation; however, the safety aspects of the entire fuel cycle, including fuel fabrication, spent-fuel processing, nuclear waste disposal, handling of radioisotopes, and environmental effects of these operations, are also treated. Table of Contents for this issue follows. GENERAL SAFETY CONSIDERATIONS: 259 Fifteenth Water Reactor Safety Information Meeting by E. G. Silver; CONTROL AND INSTRUMENTATION: 284 Reliability Technology to Improve and/or Maintain Emergency Diesel Generator Performance by S. Karimian and J. H. Taylor, 293 A Noise Diagnostics System for Operator Advice by G. Hessel, P. Liewers, P. Schumann, W. Schmitt, and F.-P. Weiss; PLANT SAFETY FEATURES: 307 A Passive Containment System for Advanced Light-Water Reactors by O. B. Falls, Jr., and F. W. Kleimola; ENVIRONMENTAL EFFECTS: 318 Data Base Construction for a Computerized Radiological Risk Investigation System by L. M. Hively, J. E. Nyquist, J. L. Bledsoe, and A. L. Sjoreen, 326 Erratum to "Radiation Hormesis and Nuclear Safety," Vol. 29, No. 1; OPERATING EXPERIENCES: 327 Operational Safety Experience and Passive Safety Testing at the Fast Flux Text Facility by Q. L. Baird, J. L. Rathbun, D. D. Stepnewski, R. L. Stover, and A. E. Waltar, 344 Backfilling of Independent Residual Heat Removal Systems in West Germany and Switzerland by G. Eckert and Y. Salomon, 353 Reactor Shutdown Experience Compiled by J. W. Cletcher, 356 Selected Safety-Related Events Compiled by G. A. Murphy, 363 Operating U.S. Power Reactors Compiled by E. G. Silver; RECENT DEVELOPMENTS: 384 General Administrative Activities Compiled by E. G. Silver, 390 Reports, Standards, and Safety Guides by D. S. Queener, 395 Status of Power-Reactor Projects Undergoing Licensing Review Compiled by E. G. Silver, 400 Proposed Rule Changes as of Mar. 31,1988; ANNOUNCEMENTS: 283 International ENS/ANS Conference on Thermal Reactor Safety "NUCSAFE 88", 317 Northwestern University Short Course on Radiation Safety, 407 Second International Seminar on Small- and Medium-Sized Nuclear Reactors, 407 International Workshop on New Developments in Occupational Dose Control and ALARA Implementation at Nuclear Power Plants and Similar Facilities, 408 Fourth International Topical Meeting on Nuclear Reactor Thermal Hydraulics (NURETH-4), 404 The Authors.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Cost-effective valorization of 2,3-butanediol to high-value chemicals and jet fuel

Here, this work outlines an optimized process for converting 2,3-butanediol (BDO) into sustainable aviation fuel (SAF) and C4 chemicals. BDO is reactively separated from fermentation broth by forming dioxolanes, which are converted to isobutyraldehyde, methyl ethyl ketone (MEK), and 1,3-butadiene. These intermediates are reduced and dehydrated over Cu/ZSM-5 to form alkenes, which can be oligomerized and hydrotreated to jet-range alkanes. Previous BDO-dioxolane-alkene processes are limited by the requirement for a continuous aldehyde source for dioxolane formation. Brønsted acidic zeolites catalyze dioxolane deacetalization to form isobutyraldehyde and MEK in a >2:1 molar ratio, providing an internal, recyclable aldehyde source. Dioxolane formation optimization was performed to achieve >95% dioxolane yields over Amberlyst-15 and minimize isobutyraldehyde recycle. The overall BDO-dioxolane-fuel process yields an alkane mixture that enables at least a 50% v/v blend with Jet-A. Techno-economic analyses and life cycle assessments for this BDO-dioxolane-fuel process yield scenarios with <$2.50 per gallon gas equivalent and >58% reduction in CO2 emissions.

2,3-butanediol↗
DOE OSTI2026

Feedback, physics, and forecasts: The emerging paradigm of machine learning-driven battery research

Machine learning (ML) is reshaping how we understand, predict, and optimize electrochemical systems. In batteries, ML accelerates discovery across chemistry, design, and operation by transforming massive experimental and simulated datasets into predictive, interpretable models. This review consolidates a decade of progress in ML-driven battery innovation, from early-cycle feature extraction to operando image analysis and physics-informed modeling. We categorize approaches by data domain and physical fidelity, emphasizing interpretable ML for diagnostics, reinforcement learning for control, and multi-objective optimization for lifetime extension strategies. Additionally, we demonstrate how integrated models accelerate discovery, reduce testing time, and guide sustainable design. Economic analyses furthermore illustrate how these advances can lower cost per cycle and improve circularity. Together, these developments chart a path toward self-optimizing, sustainable battery technologies.

artificial intelligence↗
DOE OSTI2025

A Phenazine‐Based Two‐Dimensional Covalent Organic Framework for Photochemical CO 2 Reduction with Increased Selectivity for Two‐Carbon Products

Abstract The reduction of carbon dioxide (CO₂) into valuable products will contribute to sustainable carbon use. Here we report the photocatalytic reduction of CO₂ to carbon monoxide, formate, and oxalate ions using a redox‐active phenazine‐based 2D covalent organic framework (Phen‐COF) and its phenazine monomer. Under similar irradiation conditions,Phen‐COFproduced 2.9 times more CO, 11 times more formate, and 13 times more oxalate compared to equimolar amounts of the monomeric phenazine, demonstrating that the COF architecture enhances catalytic performance (TOF COF : 10 −7 s −1 CO, 10 −8 s −1 formate, and 10 −11 s −1 oxalate). Structural analysis, including X‐ray diffraction and N₂ porosimetry, confirmed the COF's long‐range order and porosity. Mechanistic studies suggest a sequential formate‐to‐oxalate pathway, with CO and formate acting as intermediates. These results demonstrate the potential of the COF architecture to improve the performance of metal‐free, redox‐active aromatic systems such as phenazines to facilitate efficient and selective CO₂ conversion under mild conditions.

Chemistry↗
DOE OSTI2026

A Novel Low-Profile High-Efficiency Three-Phase Matrix Transformer

High step-down isolated DC-DC conversion from an 800 V DC bus to low-voltage, high-current outputs is required in automotive auxiliary converters and data center power supplies. In such applications, conventional transformer-based converters require large turns ratios, which increase winding resistance, leakage inductance, and magnetic height. This paper proposes a novel low-profile three-phase matrix transformer that realizes a large effective voltage ratio through flux division among multiple secondary legs, without increasing the physical turns count of each winding. As a result, the proposed structure reduces copper usage and transformer height while preserving the voltage conversion capability of a conventional three-phase transformer. Finite element analysis shows that the proposed design reduces magnetic height by 27%, ferrite volume by 34%, and copper volume by 28%. Circuit-level simulations of an 800 V/12 V,3 kW CLLLC dual-active-bridge converter further show that the lower winding resistance reduces total system loss by 91% and increases DC-DC efficiency from 82.6% to 97.6% at 3 kW output.

Inoue, Shuntaro [ORNL] (ORCID:0000000262637627)↗
DOE OSTI2025

Ultra-sensitive radon assay using an electrostatic chamber in a recirculating system

Rare event searches such as neutrinoless double beta decay and Weakly Interacting Massive Particle detection require ultra-low background detectors. Radon contamination is a significant challenge for these experiments, which employ highly sensitive radon assay techniques to identify and select low-emission materials. This work presents the development of ultra-sensitive electrostatic chamber (ESC) instruments designed to measure radon emanation in a recirculating gas loop, for future lower background experiments. Unlike traditional methods that separate emanation and detection steps, this system allows continuous radon transport and detection. This is made possible with a custom-built recirculation pump. A Python-based analysis framework, PyDAn, was developed to process and fit time-dependent radon decay data. Radon emanation rates are given for various materials measured with this instrument. A radon source of known activity provides an absolute calibration, enabling statistically-limited minimal detectable activities of 20 µBq. These devices are powerful tools for screening materials in the development of low-background particle physics experiments.

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

Observed Land Surface Influence on Atmospheric Heat and Moisture Profiles During Interstorms

Land-atmospheric (L-A) feedbacks have historically been studied using models whose structure and parameterizations influence outcomes and insights. The representation of L-A feedbacks based on observations alone remains an ongoing challenge for understanding boundary layer development and precipitation. To address this gap, we use ground-based passive remote sensing and in-situ observations to present an analysis of the atmosphere during 103 interstorm soil moisture drydown events spanning nine warm seasons (2016–2024) in the U.S. Southern Great Plains region. By separating events based on local L-A coupling signals and characterizing the profiles of atmospheric heat and moisture to surface energy flux behavior, we investigate the physical mechanisms linking land surface processes to boundary layer development. We find that during interstorm drydowns, the atmospheric column follows a consistent pattern: moisture increases within the boundary layer, peaks near its top, and declines rapidly above, while warming occurs through the depth. Drydowns that shift toward evaporation produce stronger and deeper thermodynamic responses than cases dominated by sensible heating, which are weaker and shallower. Additionally, moisture is accumulated faster within the boundary layer during shorter drydowns, with longer drydowns representing slower, moisture-limited growth. Drydowns with wetter initial soil moisture will sustain stronger moistening within and above the boundary layer, accelerating buoyancy growth and convective potential toward the next storm. These results provide observational evidence linking surface flux evolution to boundary layer thermodynamics and offer a process-level benchmark for evaluating coupled L-A representations in models and demonstrating the influence of soil moisture on short-term weather forecasting skill.

Zhang, M. S. [Massachusetts Inst. of Technology (M↗
DOE OSTI2026

Validating a Dynamic PWR Safety and Security Model?

Nuclear power plants (NPPs) are assessed for safety and security using separate models that cannot capture how an attacker's decisions and a plant's response unfold together in real time, leaving regulators and operators without a complete picture of true plant vulnerability. Traditional probabilistic risk assessment (PRA) methods treat adversarial events as fixed initiators with predetermined outcomes, and are structurally incapable of representing the time-dependent interplay between physical security events, safety system response, and operator mitigative actions. At Idaho National Laboratory (INL), I contributed to the development and validation of Modeling and Analysis for Safety and Security using the Dynamic EMRALD Framework (MASS-DEF). Where static PRA relies on event-tree logic that cannot evolve mid-scenario, MASS-DEF couples a time-dependent dynamic PRA tool EMRALD (Event Modeling Risk Assessment using Linked Diagrams) with attack simulation software, allowing attacker behavior, plant system states, and operator actions to interact across time. My work focused on validating a general Pressurized Water Reactor (PWR) model. I traced model logic against PWR plant to identified errors in logic and confirm accuracy. I then built and tested attack scenarios against a general PWR model to verify that the model produced expected outcomes across all logical pathways. I also contributed a section to a related technical paper applying the same EMRALD platform to radiation dose modeling. Results show that MASS-DEF can quantitatively demonstrate that many plants exceed their regulatory security thresholds. This demonstrated margin provides a technically defensible basis for reducing the number of guards without compromising regulatory compliance. Physical security costs represent roughly 10% of annual operating budgets, making such reductions directly meaningful to INL's mission of sustaining existing commercial NPPs. This internship strengthened my understanding of nuclear systems, probabilistic modeling, and technical writing, and has solidified my pursuit of a career at a national laboratory.

98 - NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL↗
DOE OSTI2026

Thermal Reservoir Networks for Modularly Expandable Thermal Microgrids

The Department of Defense (DoD) faces the substantial challenge of cost-effectively retrofitting one to two installations per month, each comprising approximately 1,000 buildings, to improve resilience, reduce energy consumption, and enhance energy supply security. Achieving these objectives requires optimal system selection and effective risk mitigation during system integration. To address this need, we introduce Platform-Based Design (PBD), a structured, hierarchical methodology adapted from other industrial sectors to the domain of energy system retrofits. We demonstrate the effectiveness of PBD through a techno-economic feasibility study comparing geothermal-coupled thermal energy networks (TENs) with conventional energy systems for heating, cooling, and powering 17 buildings at Joint Base Andrews (JBA) in Maryland. Our analysis illustrates that the PBD approach enables rigorous, data-driven, sequential decision making, resulting in a family of Pareto-optimal systems, among which the TEN emerged as the most promising solution. The selected TEN design integrates geothermal borefields, heat recovery heat pumps, photovoltaic (PV) arrays, and battery storage. Compared to the baseline system – gas heating combined with air-source chillers – the proposed TEN reduces annual imported energy by 74% and peak electricity demand by 45%, achieves a levelized cost of energy of $\$0.210$/kWh, and substantially enhances resilience. Life-cycle costs increase by approximately 6%, and initial investment costs are about 2.5 times higher than the baseline. However, if central plant infrastructure, district loops, and utility-scale PV and battery systems are privately funded and operated, the initial investment would fall below the baseline system cost. Critical to achieving these significant performance improvements were detailed nonlinear dynamic simulations coupling geothermal heat transfer, energy system operation, and realistic feedback control logic. These simulations identified essential design modifications and control strategy refinements that substantially reduced energy use, peak demand, and compressor shortcycling, thereby improving durability and reliability—issues that would have been significantly more expensive to resolve during operation. Additionally, the verification step highlighted sensitivities to key design parameters that could reduce initial investment by approximately $\$2$ million and reduce annual life-cycle costs more than $\$300,000$. We recommend adopting the PBD methodology for future feasibility studies and TEN pilot projects to gain valuable operational experience. Furthermore, we recommend that DoD invest in transferring and scaling the PBD methodology to other installations. This entails developing standardized computational frameworks and component libraries as well as training industry in conducting PBD. Such investments would enable rapid, robust, reliable, and cost-effective retrofits, supporting DoD’s ambitious energy system modernization goals.

Wetter, Michael [Lawrence Berkeley National Labora↗
DOE OSTI2026

Operando microscopy for neuromorphic hardware

Microscopy techniques can uncover the physical properties and dynamic behaviours of materials, driving the discovery of emergent phenomena and guiding the design of next-generation computing hardware. As artificial intelligence becomes pervasive, the demand for high-performance materials to support sustainable information technologies is growing. Here, this Review highlights state-of-the-art imaging from electron and X-ray to optical techniques to probe the dynamics of neuromorphic materials, including operando characterization of devices. We examine design principles for neuromorphic materials, along with obstacles that hinder their development. Emphasis is placed on spatially and temporally resolved approaches that capture state changes including phase transitions, ferroic switching and spin-wave propagation that emulate biological components such as neurons, synapses and their connectivity. We discuss challenges in operando characterization and the integration of artificial intelligence-driven analysis for feedback-guided material discovery. Finally, we outline opportunities for real-time imaging of neuromorphic systems, paving the way towards adaptive, brain-inspired hardware.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

Magnetic structure of topological nodal-line semimetal EuSb 2

Here, we investigated the magnetic structure of the magnetic topological nodal-line semimetal EuSb 2 using x-ray resonant magnetic scattering at the Eu 𝐿 3 absorption edge. Forbidden magnetic reflections confirm antiferromagnetic ordering with propagation vector 𝐪 = (0.5,0,0) below 𝑇 N ≈ 27 K. Azimuthal-angle-dependent measurements reveal that the Eu moments are aligned along the monoclinic 𝑏 axis. Comparison between the measured 𝐐-dependent magnetic Bragg peak intensities and calculations based on representation analysis identifies the magnetic structure as the A-type antiferromagnetic 𝛤 4 representation with a (++−−) arrangement along the 𝑎 direction. These results establish the microscopic magnetic structure of EuSb 2 and provide a basis for understanding the interplay between antiferromagnetism and topological electronic states in this system.

36 MATERIALS SCIENCE↗
DOE OSTI2026

SAM Code Enhancements for Fission Product Tracking of Noble Gases and Metals in MSRs

This report documents fiscal year 2026 enhancements to the System Analysis Module (SAM) for modeling fission product transport in liquid-fueled molten salt reactors (MSRs). The work advances three principal areas: noble gas transport, noble metal deposition, and user interface improvements. The noble gas transport capability integrates drift-flux gas transport, Henry’s law two-film interphase mass transfer with pressure-based nucleation suppression, Knudsen-regime pore diffusion into porous graphite with a conjugate salt-graphite interface constraint, built-in material properties, five Sherwood-number mass transfer correlations including three derived from high-fidelity NekRS simulations, and xenon-135 reactivity feedback through SAM’s point-kinetics model. This work also presents a comprehensive verification test suite, including new analytically verified cases for pressure-dependent onset of interphase gas transfer in a stagnant vertical pipe, a postulated FLiBe-graphite Xe extraction permeator, a gravity riser with a fission-product source, and a descending pipe with gas redissolution driven by hydrostatic pressure. A machine learning framework for bubble rise velocity prediction in molten salt systems is developed and benchmarked on molten-salt and diverse aqueous bubble datasets. The best-performing fine-tuned transfer-learning networks achieve an 82% reduction in RMSE relative to the Clift correlation, and is implemented directly in SAM. The noble metal transport capability is developed, including a liquid-wall deposition model and a gas-surface flotation mechanism that transfers insoluble particles entrained by sparging gas to wetted structures. Verification tests and demonstration cases cover the surface deposition, flotation efflux, and flotation shedding. Finally, a new [SpeciesTransport] input structure replaces positional global vectors with selfcontained, order-independent, named species blocks, simplifies the specification of multiphase species and decay chains, and remains fully compatible with existing SAM input files. Together, these developments improve the physical fidelity, verification basis, and usability of SAM for system-level analyses of fissionproduct behavior in MSRs.

Mui, Travis (ORCID:0000000303736470)↗
DOE OSTI2024

Case study of UAS ignition of prescribed fire in a mixedwood on the William B. Bankhead National Forest, Alabama

Abstract Background For at least four decades, practitioners have recognized advantages of aerial versus ground ignition for maximizing the effectiveness of prescribed fires. For example, larger areas can be ignited in less time, or ignition energy may be variously targeted over an area in accordance with the uneven distribution of fuels. The maturation of wireless communication, geopositioning systems, and unmanned aerial systems (UAS) has enhanced those advantages, and UAS approaches also provide further advantages relative to helicopter ignitions, such as reduced risk to human safety, lower operating costs, and higher operational flexibility. In a long running study at the Bankhead National Forest in northcentral Alabama, prescribed fire has been used for nearly 20 years. Most of the burns have been hand-ignited via drip torches, while some have been aerially ignited via helicopter. In March 2022, for the first time, a UAS was used to ignite prescribed fires across a landscape that included a long-term research stand. This field note relates comparisons of both fire behavior and fuel consumption metrics for the UAS-ignited burn versus previous burns on the same stand, and versus burns of other research stands in the same year. Results The UAS-ignited prescribed fire experienced burn effects similar to those from ground-ignited prescribed fires on the same stand in previous years, as well as those from ground-ignited prescribed fires on other stands in the same year. Conclusion This post hoc analysis suggests that UAS ignition approaches may be sufficient for achieving prescribed burn goals, thereby enabling practitioners to realize the advantages offered by that ignition mode.

Environmental Sciences & Ecology↗