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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Hyperspectral radiance mapping and chromatic correction for temperature measurement in laser-heated diamond anvil cells

In laser-heated diamond anvil cell (DAC) experiments, the effective heated region typically decreases in size with increasing pressure, leading to steeper thermal gradients. Under these conditions, chromatic aberration in the optical path from sample to detector can significantly create bias in spectro-radiometric temperature measurement. We present a radiance-mapping approach using a hyperspectral camera that records 25 spectral channels spanning 605–875 nm at each pixel in a single exposure, providing spatially and spectrally resolved radiance in each frame. This enables chromatic effects to be recorded and corrected in data processing. We developed a procedure for hyperspectral mapping, involving per-camera calibration, crosstalk removal, measured spectral throughput functions, and optional sub-pixel co-registration to minimize chromatic distortion. The calibrated radiance maps are then used to derive temperature maps of the laser-heated hotspots. For smaller heating spots, the radiance mapping approach reveals chromatic shifts that conventional spectro-radiometric methods cannot quantify. Ambient-pressure heating experiments confirm accurate temperature retrieval. At high pressure, application of the hyperspectral system to a platinum-heating experiment at 12 GPa demonstrates stable temperature reconstruction under steep thermal gradients. Beyond mitigating chromatic aberrations, the ability to diagnose optical artifacts separately from emissivity variations during controlled test experiments or in situ suggests a path toward more rigorous spectral emissivity analysis and improved modeling of thermal transport in laser-heated DAC experiments.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

We Just Want to Pump…You Up! Forecasting Grid-Connected Heat Pump Water Heater Energy Savings and Load Shifting Potential for the Southeast U.S.

Heat pump water heaters (HPWH) can achieve energy savings of 60-70% compared to conventional electric-resistance water heaters. However, even with a favorable simple payback period within the typical product lifetime, HPWHs make up only 1% of all electric water heaters sold in the residential sector. Market adoption is challenged, in part, by the lack of effective energy efficiency programs in the U.S. region with the greatest amount of residential electric water heaters. The recent integration of connected functionality into HPWHs offers the capability to shift load without undue negative impact on customers. This capability can provide value to utilities with peak load constraints, motivating them to promote HPWHs for the first time. This paper will present a methodology to forecast connected HPWH energy use and extrapolate load shifting potential for the Southeast U.S. region. The methodology leverages data from a robust connected HPWH field study conducted in the Pacific Northwest. A coefficient of performance (COP) relationship for HPWHs was developed using ambient and inlet water temperature data to forecast HPWH performance on a month-by-month basis. Using the forecasted COP, HPWH operating hours were calculated for meeting load, which serve as the proxy to extrapolate load shifting potential from the Pacific Northwest to the Southeast. As a use case, analytical results are presented for a specific utility. This methodology, in combination with market analysis, facilitates the development of customized energy savings and load shifting forecasts to understand the potential impacts of launching connected HPWH programs in specific utility service territories.

heat pump water heater, energy savings, load shift↗
DOE OSTI2023

Integrated Quantum-Classical Protocol for the Realistic Description of Solvated Multinuclear Mixed-Valence Transition-Metal Complexes and Their Solvatochromic Properties

Linear cyanide-bridged polymetallic complexes, which undergo photoinduced metal-to-metal charge transfer, represent prototypical systems for studying long-range electron-transfer reactions and understanding the role played by specific solute–solvent interactions in modulating the excited-state dynamics. Here, to tackle this problem, while achieving a statistically meaningful description of the solvent and of its relaxation, one needs a computational approach capable of handling large polynuclear transition-metal complexes, both in their ground and excited states, as well as the ability to follow their dynamics in several environments up to nanosecond time scales. Here, we present a mixed quantum classical approach, which combines large-scale molecular dynamics (MD) simulations based on an accurate quantum mechanically derived force field (QMD-FF) and self-consistent QMD polarized point charges, with IR and UV–vis spectral calculations to model the solvation dynamics and optical properties of a cyano-bridged trinuclear mixed-valence compound (trans-[(NC) 5 Fe III (μ-CN)Ru II (pyridine) 4 (μ-NC)Fe III (CN) 5 ] 4– ). We demonstrate the reliability of the QMD-FF/MD approach in sampling the solute conformational space and capturing the local solute–solvent interactions by comparing the results with higher-level quantum mechanics/molecular mechanics (QM/MM) MD reference data. The IR spectra calculated along the classical MD trajectories in different solvents correctly predict the red shift of the CN stretching band in the aprotic medium (acetonitrile) and the subtle differences measured in water and methanol, respectively. By explicitly including the solvent molecules around the cyanide ligands and calculating the thermal averaged absorption spectra using time-dependent density functional theory calculations within the Tamm–Dancoff approximation, the experimental solvatochromic shift is quantitatively reproduced going from water to methanol, while it is overestimated for acetonitrile. This discrepancy can likely be traced back to the lack of important dispersion interactions between the solvent cyano groups and the pyridine substituents in our micro solvation model. The proposed protocol is applied to the ground state in water, methanol, and acetonitrile and can be flexibly generalized to study excited-state nonequilibrium solvation dynamics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Methane-cycling microbial communities from Amazon floodplains and upland forests respond differently to simulated climate change scenarios

Seasonal floodplains in the Amazon basin are important sources of methane (CH 4 ), while upland forests are known for their sink capacity. Climate change effects, including shifts in rainfall patterns and rising temperatures, may alter the functionality of soil microbial communities, leading to uncertain changes in CH 4 cycling dynamics. To investigate the microbial feedback under climate change scenarios, we performed a microcosm experiment using soils from two floodplains (i.e., Amazonas and Tapajós rivers) and one upland forest. We employed a two-factorial experimental design comprising flooding (with non-flooded control) and temperature (at 27 °C and 30 °C, representing a 3 °C increase) as variables. We assessed prokaryotic community dynamics over 30 days using 16S rRNA gene sequencing and qPCR. These data were integrated with chemical properties, CH 4 fluxes, and isotopic values and signatures. In the floodplains, temperature changes did not significantly affect the overall microbial composition and CH 4 fluxes. CH 4 emissions and uptake in response to flooding and non-flooding conditions, respectively, were observed in the floodplain soils. By contrast, in the upland forest, the higher temperature caused a sink-to-source shift under flooding conditions and reduced CH 4 sink capability under dry conditions. The upland soil microbial communities also changed in response to increased temperature, with a higher percentage of specialist microbes observed. Floodplains showed higher total and relative abundances of methanogenic and methanotrophic microbes compared to forest soils. Isotopic data from some flooded samples from the Amazonas river floodplain indicated CH 4 oxidation metabolism. This floodplain also showed a high relative abundance of aerobic and anaerobic CH 4 oxidizing Bacteria and Archaea. Taken together, our data indicate that CH 4 cycle dynamics and microbial communities in Amazonian floodplain and upland forest soils may respond differently to climate change effects. We also highlight the potential role of CH 4 oxidation pathways in mitigating CH 4 emissions in Amazonian floodplains.

16S rRNA sequencing↗
DOE OSTI2022

Understanding Novel Lewis Acid Doping Mechanisms in Organic Semiconductors

Recent studies supported by this DOE grant have provided a more detailed understanding of the doping mechanism of organic semiconductors by the Lewis acid, tris(pentafluorophenyl)borane (BCF). Our studies have examined the intermolecular semiconductor-dopant interactions as well as the thermodynamic feasibility of different doping mechanisms. Most notably, we found a different proposed doping scheme is much more thermodynamically favoured (exergonic) than our proposed two-step BCF doping mechanism. The state-of-the-art experimental and theoretical techniques of High-Field Multi-Dimensional Solid State NMR spectroscopy and Time-Dependent Density Functional theory (TD-DFT) and DFT were employed in this work. The data obtained helped identify the structural details and intermolecular interactions which impact the organic semiconductor doping efficiency for BCF and how these compare to the case of doping by the standard integer charge transfer dopant molecule F 4 TCNQ. We have, for the first time, assigned specific chemical shift values for the F 4 TCNQ molecules clustered outside of polymer chains as well as those intercalated between the polymer backbones. Further, we provide theoretical support for a novel doping mechanism which combines those proposed in previous literature involving the evolution of hydrogen gas along with a doping species more complex than the simple BCF·H 2 O. While our previously proposed doping mechanism was found to be highly thermodynamically unfavorable, the formation of large anion [BCF(OH)(OH 2 )BCF]- is the key change making the proposed mechanism exergonic while the elimination of gaseous H 2 helps drive the doping reaction.

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

CHESS 2025: Spectrometer orthorectified at-sensor radiance from NEON AOP imaging spectroscopy surveys

This dataset provides Level 1 (L1) orthorectified at-sensor radiance derived from measurements collected by the Imaging Spectrometer-1 (NIS-1) onboard the NEON (National Ecological Observatory Network) Airborne Observation Platform (AOP) for the 2025 Colorado Headwaters Ecological Spectroscopy Study (CHESS). NIS-1 captures light reflected from the Earth’s surface in 426 discrete wavelength bands as raw digital numbers (DNs; Level 0). These data are then calibrated to physical units (uW/cm²·sr·nm) following the processing steps described in the NEON Imaging Spectrometer Level 1B Calibrated Radiance Algorithm Theoretical Basis Document (ATBD; Gallery 2022). The data delivered here are the primary inputs for the surface reflectance product in “Custom surface reflectance, shade masks, and equivalent water thickness maps for the Colorado Headwaters Ecological Spectroscopy Study” (Carroll et al. 2026). For intertemporal comparison, the radiance data here are most directly relatable to the v2 radiance data in “NEON AOP Imaging Spectroscopy Survey of Upper East River Colorado Watersheds: Raw-Space Radiance and Observational Variable Dataset” (Goulden et al. 2018), to which the same processing methodology was applied. Together, the radiance and reflectance data enable users to exploit the unique reflection signatures of different surface objects for land cover classification, foliar trait mapping, plant vigor assessment, water content estimation, trace-element identification, and other scientific applications. The data were acquired over three study domains in the Upper Gunnison river basin: the upper East River watershed (CRBU); Almont Triangle and Taylor Canyon (ALMO); and Upper Taylor River watershed (UPTA) between 2025-06-13 and 2025-07-15. Within each domain, data are delivered by flightline as orthorectified and calibrated hyperspectral rasters in Hierarchical Data Format version 5 (HDF5) format, with radiance values provided in uW/cm²·sr·nm on a fixed, uniform Universal Transverse Mercator (UTM) grid at 1 meter spatial resolution. The radiance rasters include all 426 NIS-1 spectral bands, along with associated quality-assurance (QA) and diagnostic and ancillary layers needed for atmospheric correction workflows. Orthorectified radiance is produced from pushbroom spectrometer observations by applying NEON’s radiometric calibration (including bad pixel masking, dark subtract, dark pedestal shift correction, electronic panel ghost correction, grating ghost correction, deblur correction and flat-fielding) and spectral calibration (using spectral response function band centers and full-width at half-maximum intensity), followed by geolocation and regridding to the fixed grid. CHESS Project Description: The Colorado Headwaters Ecological Spectroscopy Study (CHESS) comprised a multi-week airborne remote sensing and field observation campaign in the Upper Gunnison Basin, Colorado, conducted in June and July of 2025. Airborne remote sensing was conducted by the National Ecological Observatory Network Airborne Observation Platform (NEON AOP), concurrent with a field campaign run by the Rocky Mountain Biological Laboratory (RMBL), the Lawrence Berkeley National Laboratory (LBNL) and SLAC National Accelerator Laboratory Watershed Function Science Focus Area (SFA), and NASA-JPL (Jet Propulsion Laboratory) Earth Surface Mineral Dust Source Investigation (EMIT) program. Between June 10 and July 18, 2025, the NEON AOP flight team collected high-resolution aerial imaging spectroscopy and Light Detection and Ranging (LiDAR) data over three domains: the Upper East River (CRBU), Almont Triangle (ALMO), and the Upper Taylor Basin (UPTA). In coordination with the flights, a field campaign acquired ground-truth observations, including observations of vegetation composition, foliar traits, forest demography, and subsurface properties in 18 core sampling areas within the domains. Additional surface water observations were taken at over 380 point locations. All CHESS campaign datasets can be found within the CHESS ESS-DIVE data portal: https://data.ess-dive.lbl.gov/portals/chess. Funding Acknowledgement: Field and remote-sensing data acquisition was performed under a grant from the National Aeronautics and Space Administration (80NSSC24K1005). This work was also supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

2018 NEON and 2025 CHESS Campaigns↗
DOE OSTI2023

Sensitivity measurements for a 250 MHz quartz shear-horizontal surface acoustic wave biosensor under liquid viscous loading

Surface acoustic wave (SAW) devices have been used in biochemical assays due to their high sensitivity. The device sensitivity is a function of changes in the density and viscosity of the liquid. Here, we studied the effect of fluid viscosity using a 250 MHz quartz shear-horizontal (SH)-SAW biosensor by monitoring different concentrations of binary aqueous/glycerol solutions. In this study, the sensitivity of the biosensor was determined by fitting the data to models derived from perturbation theory. Measurements in water were used as the reference. For a 0% to 50% glycerol solution, an 87°–204° separation in the phase shift was observed. The slope of the plot of the phase shift vs (ηρ)0.5 was used to indicate the sensor’s sensitivity. The sensitivity for our 250 MHz quartz SH-SAW sensors was calculated to be 3.7×10−3m2sKg. The corresponding mass sensitivity was determined to be 9.25 × 105m2Kg. The limit of detection was calculated to be 36 picograms (pg), while the limit of quantification or LOQ was calculated to be 109 pg. Traditionally, liquid phase measurements have been challenging for SAW devices because liquids dampen the vibrating sensors severely. This problem has been largely solved using a transverse (shear) wave instead of the more popular longitudinal or Rayleigh waves. Liquid measurements are now possible using transverse waves, also known as shear waves, because transverse waves are only minimally attenuated by liquids. Shear-horizontal SAW sensors (SH-SAW) show great promise as label-free biosensors because of their ability to handle liquid samples. However, the viscosity of the liquid still induces loading effects and can be measured when the liquid is loaded onto the SH-SAW propagating surface (delay line). When the liquid above the delay line is perturbed by physical or chemical changes, such as binding to a receptor, it alters the propagating acoustic wave. The SH-SAW device can measure these changes in liquid properties as a change in the wave’s phase compared to the original wave. The device’s phase shift was recorded as a function of the changes in the density and viscosity of the binary glycerol solution and used to determine the sensitivity in the linear dynamic range of responses.

Materials Science↗
DOE OSTI2025

Cross-functional transferability in foundation machine learning interatomic potentials

The rapid development of foundation potentials (FPs) in machine learning interatomic potentials demonstrates the possibility for generalizable learning of the universal potential energy surface. The accuracy of FPs can be further improved by bridging the model from lower-fidelity datasets to high-fidelity ones. In this work, we analyze the challenge of this transfer learning (TL) problem within the CHGNet framework. We show that significant energy scale shifts and poor correlations between GGA and r 2 SCAN hinder cross-functional transferability. By benchmarking different TL approaches on the MP-r 2 SCAN dataset, we demonstrate the importance of elemental energy referencing in the TL of FPs. By comparing the scaling law with and without the pre-training on a low-fidelity dataset, we show that significant data efficiency can still be achieved through TL, even with a target dataset of sub-million structures. We highlight the importance of proper TL and multi-fidelity learning in creating next-generation FPs on high-fidelity data.

Huang, Xu [University of California, Berkeley, CA ↗
DOE OSTI2023

Temporal and spatial resolution of distal protein motions that activate hydrogen tunneling in soybean lipoxygenase

The enzyme soybean lipoxygenase (SLO) provides a prototype for deep tunneling mechanisms in hydrogen transfer catalysis. This work combines room temperature X-ray studies with extended hydrogen–deuterium exchange experiments to define a catalytically-linked, radiating cone of aliphatic side chains that connects an active site iron center of SLO to the protein–solvent interface. Employing eight variants of SLO that have been appended with a fluorescent probe at the identified surface loop, nanosecond fluorescence Stokes shifts have been measured. We report a remarkable identity of the energies of activation ( E a ) for the Stokes shifts decay rates and the millisecond C–H bond cleavage step that is restricted to side chain mutants within an identified thermal network. These findings implicate a direct coupling of distal protein motions surrounding the exposed fluorescent probe to active site motions controlling catalysis. While the role of dynamics in enzyme function has been predominantly attributed to a distributed protein conformational landscape, the presented data implicate a thermally initiated, cooperative protein reorganization that occurs on a timescale faster than nanosecond and represents the enthalpic barrier to the reaction of SLO.

Science & Technology - Other Topics↗
DOE OSTI2021

Electron thermalization and relaxation in laser-heated nickel by few-femtosecond core-level transient absorption spectroscopy

Direct measurements of photoexcited carrier dynamics in nickel are made using few-femtosecond extreme ultraviolet (XUV) transient absorption spectroscopy at the nickel M 2,3 edge. It is observed that the core-level absorption line shape of photoexcited nickel can be described by a Gaussian broadening (σ) and a red shift (ω s ) of the ground-state absorption spectrum. Theory predicts and the experimental results verify that after initial rapid carrier thermalization, the electron temperature increase (ΔT ) is linearly proportional to the Gaussian broadening factor σ, providing quantitative real-time tracking of the relaxation of the electron temperature. Measurements reveal an electron cooling time for 50 nm thick polycrystalline nickel films of 640 ± 80 fs. With hot thermalized carriers, the spectral red shift exhibits a power-law relationship with the change in electron temperature of ω s ∝ ΔT 1.5 . Rapid electron thermalization via carrier-carrier scattering accompanies and follows the nominal 4-fs photoexcitation pulse until the carriers reach a quasithermal equilibrium. Entwined with a <6 fs instrument response function, carrier thermalization times ranging from 34 fs to 13 fs are estimated from experimental data acquired at different pump fluences and it is observed that the electron thermalization time decreases with increasing pump fluence. Here, the study provides an initial example of measuring electron temperature and thermalization in metals in real time with XUV light, and it lays a foundation for further investigation of photoinduced phase transitions and carrier transport in metals with core-level absorption spectroscopy.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Tunneling magnetoresistance in MgO tunnel junctions with Fe-based leads in empirically corrected density functional theory

The minority-spin Fe/MgO interface states are at the Fermi level in density functional theory (DFT), but experimental evidence and GW calculations place them slightly higher in energy. This small shift can strongly influence tunneling magnetoresistance (TMR) in junctions with a thin MgO barrier and its dependence on the concentration of Co in the electrodes. Here, in this study, an empirical potential correction to DFT is introduced to shift the interface states up to match the tunnel spectroscopy data. With this shift, TMR in Fe/MgO/Fe junctions exceeds 800% and 3000% at 3 and 4 monolayers (ML) of MgO, respectively. We further consider the effect of alloying of the Fe electrodes with up to 30% Co or 10% V, treating them in the coherent potential approximation (CPA). Alloying with Co broadens the interface states and brings a large incoherent minority-spin spectral weight to the Fermi level. Alloying with V brings the minority-spin resonant states close to the Fermi level. However, in both cases the minority-spin spectral weight at the Fermi level resides primarily at the periphery of the Brillouin zone, which is favorable for spin filtering. Using convolutions of k II -resolved barrier densities of states calculated in CPA, it is found that TMR is strongly reduced by alloying with Co or V but still remains above 500% at 4 ML of MgO up to 30% of Co or 5% V. At 5 ML, the TMR increases above 1000% in all systems considered. However, while TMR declines sharply with increasing bias up to 0.2 eV in the tunnel junctions with pure Fe leads, it remains almost constant up to 0.5 eV if leads are alloyed with Co.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2021

PNNL Soil Microbiome SFA

PNNL's Soil Microbiome Science Focus Area (SFA) is focused on understanding the basic biology underpinning how interactions among various soil microbial community members, across trophic levels, lead to the emergence of community functions. Moisture, in particular, drives microbial interactions and influences everything from cell function to substrate fate within soils. The group predicts this results in repeatable, predictable phenotypes. The sum of these phenotypes comprises the “soil metaphenome”. Understanding how the soil metaphenome shifts in response to moisture will provide a basis for modeling and predicting these shifts in reaction network responses. PNNL’s Soil Microbiome SFA project repository on DataHub allows for exploring and downloading integrated experimental omics data, experimental metadata, pre- and post-processed data files, and other associated materials directly related to experimental project publication data. Visit the PNNL Soil Microbiome Science Focus Area Program homepage for more information.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

MISPR : an open-source package for high-throughput multiscale molecular simulations

Computational tools provide a unique opportunity to study and design optimal materials by enhancing our ability to comprehend the connections between their atomistic structure and functional properties. However, designing materials with tailored functionalities is complicated due to the necessity to integrate various computational-chemistry software (not necessarily compatible with one another), the heterogeneous nature of the generated data, and the need to explore vast chemical and parameter spaces. The latter is especially important to avoid bias in scattered data points-based models and derive statistical trends only accessible by systematic datasets. Here, we introduce a robust high-throughput multi-scale computational infrastructure coined MISPR (Materials Informatics for Structure–Property Relationships) that seamlessly integrates classical molecular dynamics (MD) simulations with density functional theory (DFT). By enabling high-performance data analytics and coupling between different methods and scales, MISPR addresses critical challenges arising from the needs of automated workflow management and data provenance recording. The major features of MISPR include automated DFT and MD simulations, error handling, derivation of molecular and ensemble properties, and creation of output databases that organize results from individual calculations to enable reproducibility and transparency. In this work, we describe fully automated DFT workflows implemented in MISPR to compute various properties such as nuclear magnetic resonance chemical shift, binding energy, bond dissociation energy, and redox potential with support for multiple methods such as electron transfer and proton-coupled electron transfer reactions. The infrastructure also enables the characterization of large-scale ensemble properties by providing MD workflows that calculate a wide range of structural and dynamical properties in liquid solutions. MISPR employs the methodologies of materials informatics to facilitate understanding and prediction of phenomenological structure–property relationships, which are crucial to designing novel optimal materials for numerous scientific applications and engineering technologies.

36 MATERIALS SCIENCE↗
DOE OSTI2020

A spin-wave magnetometer with a positive feedback

In this work, we demonstrate experimentally the operation of a spin-wave magnetometer integrated into a circuit with a positive feedback. The circuit consists of the passive magnetic and active electric parts. The magnetic part includes a sensing element, which is a magnetic cross junction made of Y 3 Fe 2 (FeO 4 ) 3 . The electric part includes a non-linear amplifier and a phase shifter. The electric and magnetic parts are connected via micrometer size antennae. Spin waves are excited by two of these antennae while the output inductive voltage produced by the interfering spin waves is detected by the third antenna. Spin waves propagating in the orthogonal arms of the cross can accumulate significantly different phase shifts, depending on the direction and the strength of the external magnetic field. The output inductive voltage reaches its maximum in the case of constructive spin wave interference. The positive feedback provides further signal amplification. It appears possible to enhance the response function, compared to the passive circuits without a feedback, by a factor of ×100 without an increase in the noise level. The experimental data show a prominent response to the external magnetic field variation, exceeding 5 x 10 3 V/T. The intrinsic noise spectral density of the device can be as low as 10 -16 V 2 /Hz. The estimated sensitivity of the prototype device is 2 x 10 -12 T/√Hz at room temperature. We argue that spin-wave magnetometers can potentially be as sensitive as SQUIDs while operating at room temperature.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Investigation of coverage dependence of the stretching frequency of CO adsorbed on Pd surfaces at low coverage limits

The stretching frequency of the C—O bond is a sensitive probe of the local environment of a surface-bound CO molecule, including the adorption site and density, i.e. surface coverage. In this work, we extend our analysis beyond the frequency shift due to differences in adsorption configurations. Using density functional theory (DFT) calculations, we directly explore the correlations between surface coverage and the stretching frequency of adsorbed CO on Pd surfaces. Here we also perform constant pressure infrared reflection absorption measurements of CO on Pd(111) and use existing relations between pressure and coverage to derive coverage dependency. Both results are compared to previously reported experimental data. Our derived correlations of peak frequency and area with surface coverage can help interpret experimental IR spectra in real time and extract time-dependent concentration data from transient kinetic experiments.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2025

The hidden influence of terrestrial groundwater on salt marsh function and resilience

Salt marshes are hotspots of nutrient processing and carbon sequestration. So far, studies addressing spatiotemporal variability in and drivers of salt marsh biogeochemical function, carbon storage and resilience have focused on ocean-driven surface hydrologic influences, neglecting effects of terrestrial hydrology through subsurface connections. Here we evaluate drivers of salt marsh redox potential, a proxy for biogeochemical state, through wavelet analyses and information theory using data from seven marshes. The results point to terrestrial groundwater level as a dominant control on redox variability across all sites. Because redox is a key driver of biogeochemical processes, and specifically oxidation of organic matter that sequesters carbon and maintains marsh elevation, these terrestrial influences are critical to understanding marsh function and evolution. Further, the newly identified links between onshore groundwater levels and marsh redox conditions shift the traditional paradigm and suggest that terrestrial hydrology is a primary control on salt marsh carbon sequestration potential and resilience.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Comfort units and systems, methods, and devices for use thereof

Despite otherwise uncomfortable conditions in a surrounding environment, a customizable microenvironment can be created around a user to maintain a comfortable temperature and/or humidity level using a comfort unit. For example, the environment may be an office building where conditions are out of the comfortable range to save on energy or for other reasons, a factory/shop environment that is poorly conditioned, or an outdoor location with little to no conditioning. A sensing unit can monitor biometric and environmental data and can determine a comfort level of the user. The comfort unit can then dynamically respond to the determined comfort level and adjust the microenvironment to improve the user's comfort level. The comfort unit can follow the user as the user moves within the macro-environment, or can otherwise move within the macro-environment to achieve certain functions, such as recharging or spatial shifting of thermal load within the overall macro-environment.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

GIScience in the era of Artificial Intelligence: a research agenda towards Autonomous GIS

The advent of generative AI exemplified by large language models (LLMs) opens new ways to represent and compute geographic information and transcends the process of geographic knowledge production, driving geographic information systems (GIS) towards autonomous GIS. Leveraging LLMs as the decision core, autonomous GIS can independently generate and execute geoprocessing workflows to perform spatial analysis. In this vision paper, we further elaborate on the concept of autonomous GIS and present a conceptual framework that defines its five autonomous goals, five levels of autonomy, five core functions, and three operational scales. We demonstrate how autonomous GIS could perform geospatial data retrieval, spatial analysis, and map making with four proof-of-concept GIS agents. We conclude by identifying critical challenges and future research directions, including fine-tuning and self-growing decision-cores, autonomous modelling, and examining the societal and practical implications of autonomous GIS. By establishing the groundwork for a paradigm shift in GIScience, this paper envisions a future where GIS moves beyond traditional workflows to autonomously reason, derive, innovate, and advance geospatial solutions to pressing global challenges. Meanwhile, we emphasize that as we design and deploy increasingly intelligent geospatial systems, we carry a responsibility to ensure they are developed in socially responsible ways, serve the public good, and support the continued value of human geographic insight in an AI-augmented future.

Autonomous GI↗