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At least 1,099 records · Page 61
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

AutoBEM: A scalable framework for nationwide building energy simulation and retrofit evaluation in the United States

This paper presents AutoBEM, an integrated, automated framework for nationwide building energy modeling and retrofit evaluation in the United States. Unlike prior UBEM platforms that either rely primarily on representative stock sampling or operate at city scale, AutoBEM automates the generation of building-resolved, physics-based EnergyPlus/OpenStudio simulation models at national scale using GIS-derived geometry, prototype-based assumptions, and standardized scalable workflows. Leveraging the Model America dataset and high-performance computing, AutoBEM generates and simulates energy models for 122.9 million buildings, representing 97.8% of the U.S. building stock. These models are being made publicly and freely available as the Model America v1.0 (MAv1) dataset. AutoBEM supports detailed, building-level assessments of energy consumption, CO2 emissions, and post-processed anthropogenic heat emissions (AHE), and evaluates 151 energy conservation measures (ECMs) using localized utility pricing and building characteristics. In addition, AutoBEM incorporates both typical and future climate conditions through integration with Typical Meteorological Year (TMY) and Future TMY (fTMY) weather data derived from IPCC scenarios. In a case study of Phoenix, Arizona, AutoBEM identified several high-efficiency HVAC upgrades and selected envelope measures with short modeled payback periods (1.5 years) for certain building types and standards. Simulations under future climate scenarios (SSP5–RCP8.5) project an 11.3% increase in electricity use and a 32% reduction in natural gas demand by 2100, underscoring the need for climate-adaptive retrofit planning. By enabling reproducible, bottom-up, and location-specific analysis at scale, AutoBEM provides a step toward a national digital twin of the built environment and supports data-driven screening and planning for decarbonization, resilience, and energy equity.

Li, Hang [ORNL] (ORCID:0000000306001920)↗
DOE OSTI2026

Solid-State Syntheses, Crystallographic Spatial Disorders, Thermal Behaviors, and Bandgaps of Hybrid Organic-Inorganic Manganese Halides: A2Mn(Cl/Br)4 (A = NH4+, C(NH2)3+, & C3H4N2+)

By systematically optimizing solid-state synthesis via the concerted use of differential scanning calorimetry and in-situ variable-temperature X-ray diffraction, we report the discovery of four new hybrid organic-inorganic manganese halides A2Mn(Cl/Br)4 (A = NH4+, C(NH2)3+, C3H4N2+), with emphasis on how the organic fragment geometry, polarity, and electron-donating properties influence crystallographic spatial disorders, thermal behaviors, and optical band gaps. With a nonpolar tetrahedral cation, as in (NH4)2MnCl4 (P21/c, mP30) or (NH4)2MnBr4 (C2/c, mC180), the direct optical bandgaps (4.36–4.28 eV) are wider than those with an organic nonpolar planar geometry, as in (C(NH2)3)2MnBr4 (P21/c, mP300, 4.07 eV), or an organic polar planar geometry, as in (C3H4N2+)2MnBr4 (I41/a, tI384, 4.05 eV). Furthermore, the organic components affect the spatial arrangement and dimensionality of the resulting inorganic frameworks comprised of Mn(Cl/Br)6 octahedra, with varying distortions, or spatially disordered MnBr4 tetrahedra. These resulting trends, coupled with the systematic investigation into synthesis, and the motivation behind elucidating the nuanced role of the organic cation, altogether expand upon the phase-space of hybrid materials beyond perovskites and demonstrate the potential for a rational design of hybrid materials with tailored optoelectronic functionalities for advanced energy applications.

Lee, Shannon J.↗
DOE OSTI2025

Unveiling the lithium-ion transport mechanism in Li{sub 2}ZrCl{sub 6} Solid-State Electrolyte {ital via} deep learning-accelerated molecular dynamics simulations.

Lithium zirconium chlorides (LZCs) present a promising class of cost-effective solid electrolytes for next-generation all-solid-state batteries. The unique crystal structure of LZCs plays a crucial role in facilitating lithium-ion mobility, which further affects the electrochemical performance. To understand the underlying mechanism governing ion transport, we employed deep learning-accelerated molecular dynamics simulation on Li2ZrCl6 (trigonal alpha- and monoclinic beta-LZC), focusing specifically on the zirconium coordination environment. Our results reveal that disordered alpha-LZC exhibits the highest ionic conductivity, while beta-LZC demonstrates significantly lower conductivity, closely aligning with experimental findings. The study confirms that across all phases, lithium migration proceeds via the site-to-site hopping mechanism, where variations in site residence times critically impact the overall ionic conductivity. In alpha-LZCs, lithium ions prefer to anisotropically diffuse across interlayers as the result of a lower energy barrier, driven primarily by collective diffusion. In contrast, lithium ions in beta-LZC primarily isotropically diffuse within the intralayer, hindered by higher energy barriers and determined by individual diffusion. The variation in ZrCl6 2- octahedral unit softening, induced by the specific layered arrangement of zirconium atoms, emerges as a critical determinant of the energy barriers across the LZC phases. These atomic-scale insights into the transport processes provide valuable guidance for the rational design and optimization of LZCs-based electrolytes, accelerating their practical application in advanced energy storage technologies.

Guo, Hanzeng↗
DOE OSTI2025

AMOC Variability in Climate Models and Its Dependence on the Mean State

Abstract Understanding internal variability of the climate system is critical when isolating internal and anthropogenically forced signals. Here, we investigate the modes of Atlantic Meridional Overturning Circulation ( AMOC ) variability using perturbation experiments with the Institut Pierre‐Simon Laplace's (IPSL) coupled model and compare them to Coupled Model Intercomparison Project Phase 6 (CMIP6) pre‐industrial control simulations. We identify two characteristic modes of variability—decadal‐to‐multidecadal ( DMD var ) and centennial ( CEN var ). The former is driven largely by temperature anomalies in the subpolar North Atlantic, while the latter is driven by salinity in the western subpolar North Atlantic. The amplitude of each mode scales linearly with the mean AMOC strength in the IPSL experiments. The DMD var amplitude correlates well with the AMOC mean strength across CMIP6 models, while the CEN var mode does not. These findings suggest that the strength of DMD var depends robustly on the North Atlantic mean state, while the CEN var mode may be model‐dependent.

Ferster, Brady S. [LOCEAN‐IPSL Sorbonne Université↗
DOE OSTI2025

Allometric Scaling of Hyporheic Respiration Across Basins in the Pacific Northwest United States

Abstract Hyporheic zones regulate biogeochemical processes in streams and rivers, but high spatiotemporal heterogeneity makes it difficult to predict how these processes scale from individual reaches to river basins. Recent work applying allometric scaling (i.e., power‐law relationships between size and function) to river networks provides a new paradigm for understanding cumulative hyporheic biogeochemical processes. We used previously published model predictions of reach‐scale hyporheic aerobic respiration to explore patterns in allometric scaling across two climatically divergent basins with differing characteristics in the Pacific Northwest, United States. In the model, hydrologic exchange fluxes (HEFs) regulate hyporheic respiration, so we examined how HEFs might influence allometric scaling of respiration. We found consistent scaling behaviors where HEFs were either very low or very high, but differences between basins when HEFs were moderate. Our findings provide initial model‐generated hypotheses for factors influencing allometric scaling of hyporheic respiration. These hypotheses can be used to optimize new data generation efforts aimed at developing predictive understanding of allometries that can, in turn, be used to scale biogeochemical dynamics across watersheds.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Characterizing How Meteorological Forcing Selection and Parameter Uncertainty Influence Community Land Model Version 5 Hydrological Applications in the United States

Despite the increasing use of large-scale Land Surface Models (LSMs) in predicting hydrological responses in extreme conditions, there's a critical gap in understanding the uncertainties in these predictions. This study addresses this gap through a detailed diagnostic evaluation of the uncertainties arising from meteorological forcing selection and model parametrization in hydrological simulations of the Community Land Model version 5 (CLM5). CLM5 is configured at a spatial scale of about 12-km to simulate runoff processes for 464 headwater watersheds, selected from the Catchment Attributes for Large-Sample Studies (CAMELS) dataset to be representative of physiographic and climatic gradients across the conterminous United States. For each watershed, CLM5 is driven by five commonly used gridded forcing datasets in combination with a large ensemble (> 1200) of key CLM5 hydrologic parameters. Our results suggest that uncertainty in CLM5 runoff simulations resulting from both forcing and parametric sources is markedly higher in arid regions, e.g., Great Plains and Midwest regions. Uncertainty in low flow is dominated by parametric uncertainty, while the selection of meteorological forcing contributes more dominantly to high flow and seasonal flows during fall and spring. Our analysis also demonstrates that the selection of forcing datasets and the metrics used to calibrate CLM5 significantly impact the model’s predictive accuracy in extreme event severity for both floods and droughts. Overall, the results from this study highlight the need to understand and account for forcing and parametric uncertainties in CLM5 simulations, particularly for hazard and risk assessments addressing hydrologic extremes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Ensemble‐Based Spatially Distributed CLM5 Hydrological Parameter Estimation for the Continental United States

Abstract One of the major challenges in large‐domain hydrological modeling efforts lies in the estimation of spatially distributed hydrological parameters while simultaneously accounting for their associated uncertainties. Addressing this challenge is particularly difficult in ungauged locations. With growing societal demands for large‐scale streamflow projections to inform water resource management and long‐term planning, evaluating and constraining hydrological parameter uncertainty is increasingly vital. This study introduces a hybrid regionalization approach to enhance hydrological predictions of the Community Land Model version 5 (CLM5) across the Continental United States (CONUS), with a total of 50,629 1/8° grid cells. This hybrid method combines the strengths of two existing techniques: parameter regionalization and streamflow signature regionalization. It identifies ensemble behavioral parameters for each 1/8° grid cell across the CONUS domain, tailored to three distinct streamflow signatures focused on low flows, high flows, and annual water balance. Evaluating this hybrid method for 464 CAMELS (Catchment Attributes and Meteorology for Large‐sample Studies) basins demonstrates a significant improvement in CLM5 hydrological predictions, even in challenging arid regions. In CONUS applications, the derived spatially distributed parameter sets capture both spatial continuity and variation of parameters, highlighting their heterogeneous nature within specific regions. Overall, this hybrid regionalization approach offers a promising solution to the complex task of improving hydrological modeling over large domains for important hydrological applications.

CLM5↗
DOE OSTI2025

Evaluating How Climate Adaptation Measures Affect the Interconnected Water‐Energy Resource Systems of the Western United States

Abstract The Western US faces increasing water stress from the impacts of climate change, making it difficult to meet water demands for the region's cities, agriculture, and hydropower generators. Existing literature suggests that climate adaptation measures such as water conservation, cropland retirement, wastewater recycling, and managed aquifer recharge can alleviate some of these challenges. Few analyses, however, compare the relative efficacy and system‐wide effects of these adaptations under different climate projections across the entire Western United States. Here we use a Western US‐wide water systems model to evaluate, by sector and sub‐region, how the widespread implementation of these adaptive measures impacts water demands, water deliveries, and electricity use related to the water system for three different climate projections. We find that wastewater recycling has greater potential to lower unmet indoor water demands than urban indoor water conservation measures. However, when implemented at scale, indoor water conservation reduces electricity use by an average of 683 Terawatt hours while wastewater recycling increases energy use by an average of 721 Terawatt hours, cumulatively from 2020 to 2070. Cropland retirement and aquifer recharge adaptations increase the ability to meet agricultural water demand, increase groundwater storage, and reduce summertime electricity use. While most of these findings are consistent across different climate projections, the benefits of aquifer recharge are sensitive to spatial variation of precipitation. Given the limitations and tradeoffs of each individually, the results suggest that a portfolio of adaptation measures will be needed for a climate‐resilient water and energy future in the Western US. Plain Language Summary The Western US faces increased water stress from the impacts of climate change, making it difficult to meet demands for cities, agriculture, and hydropower facilities. Adaptation measures like water conservation, retiring agricultural lands, recycling wastewater, and storing water underground can address these challenges. However, there is little modeling to understand the impact of these adaptations if they were implemented across the entire Western US while also considering climate change. We use a Western US‐wide water systems model to evaluate how implementing adaptation measures impacts groundwater levels, the ability to meet water demands, and electricity use related to water in three different possible climate futures. We find that recycling wastewater to drinking water standards does a better job of meeting urban water demands than water conservation measures. However, indoor water conservation reduces energy use for water while recycling wastewater increases energy use for water. Retiring agricultural lands and storing water underground both increase the ability to meet agricultural water demands, increase underground water storage, and reduce summertime energy use. No adaptation measures provides benefits across every metric we track. Therefore, multiple adaptation measures will likely be needed to achieve a climate‐resilient future for energy and water in the Western US. Key Points Water‐related climate change adaptations have different benefits and tradeoffs for interconnected water‐energy systems in the Western U.S. Wastewater recycling most increases urban water coverage, but has a significant tradeoff in the form of greater electricity use Cropland retirement and aquifer recharge benefit water and electricity systems most in the summer when those systems are most stressed

Singhal, A↗
DOE OSTI2026

Root Dynamics Mitigate Warm and Dry Biases over the Central United States

The central United States frequently exhibits warm and dry biases in simulations of summertime conditions, a persistent feature that remains unresolved. While previous studies linked these biases to misrepresented surface energy exchanges, the role of belowground processes remains poorly understood. Here, we demonstrate that inadequate representation of root water uptake in land surface models contributes to this bias. Using both offline Noah-MP and coupled WRF-Noah-MP simulations with static and dynamic root water uptake schemes, we show that the inclusion of dynamic root processes reduces 2-m air temperature biases and enhances precipitation, primarily by increasing the rain rate of convective systems. Offline and coupled simulations further reveal that the cooling effects and precipitation increases are amplified through positive land-atmosphere feedback, active only in the coupled model. These findings highlight an important role of root in modulating land-atmosphere interactions and underscore the need to refine root-zone processes to improve regional atmospheric simulations.

Yang, Zhao (ORCID:0000000288027130)↗
DOE OSTI2025

Ligand efficacy shifts a nuclear receptor conformational ensemble between transcriptionally active and repressive states

Abstract Nuclear receptors (NRs) are thought to dynamically alternate between transcriptionally active and repressive conformations, which are stabilized upon ligand binding. Most NR ligand series exhibit limited bias, primarily consisting of transcriptionally active agonists or neutral antagonists, but not repressive inverse agonists—a limitation that restricts understanding of the functional NR conformational ensemble. Here, we report a NR ligand series for peroxisome proliferator-activated receptor gamma (PPARγ) that spans a pharmacological spectrum from repression (inverse agonism) to activation (agonism) where subtle structural modifications switch compound activity. While crystal structures provide snapshots of the fully repressive state, NMR spectroscopy and conformation-activity relationship analysis reveals that compounds within the series shift the PPARγ conformational ensemble between transcriptionally active and repressive conformations that are natively populated in the apo/ligand-free ensemble. Our findings reveal a molecular framework for minimal chemical modifications that enhance PPARγ inverse agonism and elucidate their influence on the dynamic PPARγ conformational ensemble.

Science & Technology - Other Topics↗
DOE OSTI2025

Long-lived photoinduced polar states in metal halide perovskites

Ferroic polarization in hybrid perovskites is crucial for enhancing photovoltaic performance and developing potential electronic applications. Controlling ferroic polarization with an optical field enables probing of ferroic polarization without the unwanted interface ionic effects caused by electronic contacts. This study employs ultrafast near-infrared photoexcitation to control dynamic structural transitions in soft single crystalline hybrid Cu (II) halide perovskites, achieving a long-lived polar state (beyond 104 s) at room temperature. We probe reversible long-lived polar domains under near-infrared photoexcitation using in-situ second harmonic generation microscopy. Theoretical calculation informs the polar lattice microstrain likely induced by anisotropic structure deformation in octahedral copper halide under near-infrared photoexcitation. The reversible slow structure deformation is further confirmed by in-situ photo-induced X-ray diffraction measurement. This work provides a material platform for understanding, controlling, and probing polarization under photoexcitation. Our methodology enables the identification of previously undiscovered polar phases in ferroelectric halide perovskites.

Dou, Yixuan↗
DOE OSTI2025

Graphene-driven correlated electronic states in one dimensional defects within WS2

Tomonaga-Luttinger liquid (TLL) behavior in one-dimensional systems has been predicted and shown to occur at semiconductor-to-metal transitions within two-dimensional materials. Reports of one-dimensional defects hosting a Fermi liquid or a TLL have suggested a dependence on the underlying substrate, however, unveiling the physical details of electronic contributions from the substrate require cross-correlative investigation. Here, we study TLL formation within defectively engineered WS2 atop graphene, where band structure and the atomic environment is visualized with nano angle-resolved photoelectron spectroscopy, scanning tunneling microscopy and spectroscopy, and non-contact atomic force microscopy. Correlations between the local density of states and electronic band dispersion elucidated the electron transfer from graphene into a TLL hosted by one-dimensional metal (1DM) defects. It appears that the vertical heterostructure with graphene and the induced charge transfer from graphene into the 1DM is critical for the formation of a TLL.

Rossi, Antonio↗
DOE OSTI2025

Phosphorylation toggles the SARS-CoV-2 nucleocapsid protein between two membrane-associated condensate states

Abstract The Nucleocapsid protein (N) of SARS-CoV-2 plays a critical role in the viral lifecycle by regulating RNA replication and by packaging the viral genome. N and RNA phase separate to form condensates that may be important for these functions. Both functions occur at membrane surfaces, but how N toggles between these two membrane-associated functional states is unclear. Here, we reveal that phosphorylation switches how N condensates interact with membranes, in part by modulating condensate material properties. Our studies also show that phosphorylation alters N’s interaction with viral membrane proteins. We gain mechanistic insight through structural analysis and molecular simulations, which suggest phosphorylation induces a conformational change in N that softens condensate material properties. Together, our findings identify membrane association as a key feature of N condensates and provide mechanistic insights into the regulatory role of phosphorylation. Understanding this mechanism suggests potential therapeutic targets for COVID infection.

Science & Technology - Other Topics↗
DOE OSTI2025

Electric transmission value and its drivers in United States power markets

Electric transmission infrastructure plays a vital role during extreme weather and supply disruptions and can enable low-cost electricity systems. This paper contributes to a more complete understanding of the value and cost-effectiveness of transmission, as well as barriers to its development. By studying wholesale energy market prices in the United States between 2012 and 2022, we find that additional transfer capacity between regions would have been especially valuable, with a median value of $116 million per GW per year. This capacity would often have provided balanced benefits to each region. The market value of transmission was highly influenced by a small fraction of time: 5% of hours typically captured at least 45% of the total value. These peak periods were primarily driven by unforeseen changes in conditions within one day of operations. Annualized transmission infrastructure cost estimates were lower than the average market value for most locations, including all links crossing regional seams, where the value-to-cost ratio was often greater than 4. This suggests that there are barriers to developing valuable grid infrastructure. These results complement forward-looking modeling studies and support efforts to improve modeling practices.

Energy economics↗
DOE OSTI2026

Organic carbon oxidation state shapes fermentative methanogenic microbiomes and controls greenhouse gas fluxes

Organic compounds with a negative nominal oxidation state of carbon (NOSC) are thermodynamically recalcitrant in anaerobic ecosystems, but few studies have measured the influence of NOSC on carbon degradation rates, gaseous product yields, or microbiome composition. We amended anaerobic rice paddy sediment microcosms with water-soluble monomeric organic carbon compounds varying in NOSC. Consistent with thermodynamic and stoichiometric predictions, negative NOSC compounds are catabolized more slowly but produce more methane per mole of carbon. Negative NOSC microbiomes have higher alpha diversity, more syntrophs and methanogens, and fewer fermentative bacteria. Strikingly, fermentative bacterial taxa display genomically encoded NOSC catabolic preferences both in the lab and field. Negative NOSC-preferring fermenters have longer predicted doubling times, consistent with the thermodynamic recalcitrance of their preferred substrates. We propose that microbial NOSC catabolic preferences may reflect the thermodynamic niche of microorganisms and we anticipate that extending research on microbial catabolic preferences to a greater variety of organic carbon substrates and diverse microbiomes will improve our understanding of microbial carbon cycling and trait evolution.

Hu, Ruiwen↗
DOE OSTI2024

Systematic determination of a material’s magnetic ground state from first principles

Abstract We present a self-consistent method based on first-principles calculations to determine the magnetic ground state of materials, regardless of their dimensionality. Our methodology is founded on satisfying the stability conditions derived from the linear spin wave theory (LSWT) by optimizing the magnetic structure iteratively. We demonstrate the effectiveness of our method by successfully predicting the experimental magnetic structures of NiO, FePS 3 , FeP, MnF 2 , FeCl 2 , and CuO. In each case, we compared our results with available experimental data and existing theoretical calculations reported in the literature. Finally, we discuss the validity of the method and the possible extensions.

Chemistry↗
DOE OSTI2026

Competition between excitonic insulators and quantum Hall states in correlated electron–hole bilayers

Excitonic insulators represent a unique quantum phase of matter that enables the study of exotic quantum bosonic states. Strongly coupled electron–hole bilayers, which host stable dipolar exciton fluids with an exciton density that can be adjusted electrostatically, offer an ideal platform to investigate correlated excitonic insulators. On the basis of electron–hole bilayers made of MoSe2/hexagonal boron nitride/WSe2 heterostructures, here we study the behaviour of excitonic insulators in a perpendicular magnetic field. We report the observation of excitonic quantum oscillations in both Coulomb drag signals and electrical resistance at low to medium magnetic fields. Under a strong magnetic field, we identify multiple quantum phase transitions between the excitonic insulator phase and the bilayer quantum Hall insulator phase. These findings underscore the interplay between the electron–hole interactions and Landau-level quantization, and enable further exploration of quantum phenomena in composite bosonic insulators.

Qi, Ruishi↗
DOE OSTI2025

A unified ensemble soil moisture dataset across the continental United States

Abstract A unified ensemble soil moisture (SM) package has been developed over the Continental United States (CONUS). The data package includes 19 products from land surface models, remote sensing, reanalysis, and machine learning models. All datasets are unified to a 0.25-degree and monthly spatiotemporal resolution, providing a comprehensive view of surface SM dynamics. The statistical analysis of the datasets leverages the Koppen-Geiger Climate Classification to explore surface SM’s spatiotemporal variabilities. The extracted SM characteristics highlight distinct patterns, with the western CONUS showing larger coefficient of variation values and the eastern CONUS exhibiting higher SM values. Remote sensing datasets tend to be drier, while reanalysis products present wetter conditions. In-situ SM observations serve as the basis for wavelet power spectrum analyses to explain discrepancies in temporal scales across datasets facilitating daily SM records. This study provides a comprehensive soil moisture data package and an analysis framework that can be used for Earth system model evaluations and uncertainty quantification, quantifying drought impacts and land–atmosphere interactions and making recommendations for drought response planning.

54 ENVIRONMENTAL SCIENCES↗