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DOE OSTI2025

Proximal remote sensing: an essential tool for bridging the gap between high‐resolution ecosystem monitoring and global ecology

Summary A new proliferation of optical instruments that can be attached to towers over or within ecosystems, or ‘proximal’ remote sensing, enables a comprehensive characterization of terrestrial ecosystem structure, function, and fluxes of energy, water, and carbon. Proximal remote sensing can bridge the gap between individual plants, site‐level eddy‐covariance fluxes, and airborne and spaceborne remote sensing by providing continuous data at a high‐spatiotemporal resolution. Here, we review recent advances in proximal remote sensing for improving our mechanistic understanding of plant and ecosystem processes, model development, and validation of current and upcoming satellite missions. We provide current best practices for data availability and metadata for proximal remote sensing: spectral reflectance, solar‐induced fluorescence, thermal infrared radiation, microwave backscatter, and LiDAR. Our paper outlines the steps necessary for making these data streams more widespread, accessible, interoperable, and information‐rich, enabling us to address key ecological questions unanswerable from space‐based observations alone and, ultimately, to demonstrate the feasibility of these technologies to address critical questions in local and global ecology.

Plant Sciences↗

DOE OSTI2022

ARIES: NREL Off-Road Decarbonization and Energy Systems Integration Workshop - Challenges and Opportunities

This presentation about ARIES was given at the NREL Off-Road Decarbonization and Energy Systems Integration Workshop - Challenges and Opportunities. ARIES was designed to fill a significant gap: there is no research platform that can support the nation's transition to a decarbonized energy system. ARIES will demonstrate and de-risk a future energy system with more than 50% renewable generation by 2030, that is just, affordable, flexible, clean, secure, resilient, and reliable, even in the off-road transportation sector.

ARIES↗

DOE OSTI2022

CeTaN 3 and CeNbN 3 : Prospective Nitride Perovskites with Optimal Photovoltaic Band Gaps

Perovskites constitute an exceptionally tunable materials family with diverse applications in electronics, optoelectronics, energy, and quantum technologies. Out of the thousands of known perovskites, the majority of compounds are oxides, halides, and chalcogenides. In contrast, only two nitride perovskites are currently known. In this work we perform a thorough ab initio computational screening of possible nitride perovskites, and we identify two new compounds, CeNbN 3 and CeTaN 3 , with band gaps in the near-infrared to visible range, depending on temperature. In their room-temperature orthorhombic phase, we predict that both compounds exhibit direct or quasidirect band gaps in the range 1.1–2.0 eV, with the Pnma phases matching the Shockley–Queisser limit for photovoltaic energy conversion efficiency. Further, these compounds are also predicted to be strong light absorbers, with absorption coefficients surpassing those of high-performance semiconductors such as GaAs and CH 3 NH 3 PbI 3 . The present findings reveal a potentially new class of nitride semiconductors with promise for electronics, optoelectronics, and light harvesting and for integration with existing nitride-based lighting technology.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Lattice-Mismatched van der Waals Epitaxy and Photoluminescence of Two-Dimensional GaxIn1-xSe Alloys on Si(111)

GaxIn1-xSe (GIS) alloys are two-dimensional (2D) layered materials with band gaps and lattice parameters of interest for many energy and electronic applications. They can be fabricated using van der Waals epitaxy, which is an emerging technique that offers unprecedented opportunities for 2D optoelectronic devices and epitaxy processes. This work has demonstrated van der Waals epitaxy of GIS alloys for the first time. Films with x compositions of 0, 0.062, 0.164, 0.680, 0.894, and 1 and tunable lattice constants were grown on Si(111) substrates, and characterized by X-ray diffraction pole figure and transmission electron microscope analysis. In spite of the lattice mismatches (InSe is 4.1% too large and GaSe is 2.8% too small), these alloys grow epitaxially, with Si(111) || GIS(001) and Si[1-10] || GIS[100] orientation. Photoluminescence was used to measure tunable band gaps in the absorber-relevant 1.3-2.0 eV range as a function of x composition and showed GIS did not degrade after capping with Se and prolonged storage. Therefore, GIS alloys exhibit a technologically advantageous combination of tunable band gap and photoluminescence with relaxed lattice parameter and rotational registry with the substrate.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Band Structure-Driven Design of a α-CsPbI 3 Ammonia Sensor for Industrial Applications

We investigate the defect-dependent electronic structure and gas-sensing potential of cubic α-CsPbI 3 using first-principles density functional theory and nonadiabatic molecular dynamics. Among the intrinsic defects, interstitials, vacancies, antisites, and switches studied, the I Pb and Pb I antisite defects exhibit transition energy levels near the middle of the band gap, thus functioning as deep traps. Short-term adsorption of ammonia selectively modifies the electronic structure, coordinating with Pb at Pb I sites and Cs at I Pb sites, significantly altering recombination pathways. Detailed analysis reveals that NH 3 reduces anharmonicity at I Pb defects, enabling enhanced recombination at elevated temperatures, while trap-assisted recombination dominates at room temperature. Other analytes, including CH 3 NH 2 and NO 2 , show negligible impact on the band gap or recombination dynamics, highlighting the potential selectivity of NH 3 interactions. Ab initio nonadiabatic molecular dynamics simulations at 300 K and 600 K further demonstrate temperature-dependent modulation of carrier lifetimes, with NH 3 accelerating recombination at ambient conditions and suppressing certain pathways at higher temperatures. These findings suggest that α-CsPbI 3 can serve as a selective and sensitive ammonia sensor over a broad temperature range and offer insights for ammonia detection under industrially relevant conditions.

ammonia sensor↗

DOE OSTI2026

Aliovalent gallium dopants remove Ti 3+ defects and improve photocatalytic and photoelectrochemical water oxidation properties of LaTiO 2 N

LaTiO 2 N is a promising semiconductor for the water splitting reaction due to its 2.1 eV band gap and stability against corrosion. However, its solar energy conversion is limited by Ti 3+ recombination defects introduced during ammonolysis. Here we show for the first time that Ti 3+ defects in LaTiO 2 N can be suppressed with incorporation of 2, 5, and 10% aliovalent gallium (Ga 3+ ) dopants during synthesis via the layered La 2 Ti 2 O 7 intermediate. Electron paramagnetic resonance (EPR) spectroscopy on the solid powders confirms a reduction in the Ti 3+ donor density from 2.97 × 10 17 cm −3 for the non-doped material to ∼6.24 × 10 16 cm −3 for 5% Ga-doped LaTiO 2 N. The remaining Ti 3+ defects are concentrated near the LaTiO 2 N surface, according to X-ray photoelectron spectroscopy. The defect reduction shifts the optical absorption edge from 2.02 to 2.09 eV and eliminates a broad absorption band at 1050 nm from the optical absorption spectra. It also removes a 1.0–1.7 eV sub-band gap photovoltage signal from surface photovoltage spectra. This suggests that empty Ti 3+ d-orbitals are located 1.0–1.7 eV above the LaTiO 2 N valence band edge. Removing these recombination states with increasing Ga 3+ content enhances the photoconversion efficiency of LaTiO 2 N during water oxidation. The optimized 2 wt% CoO x -loaded 5% Ga-doped LaTi O2 N material has a 16% AQE (400 nm) for O 2 production from aqueous silver nitrate solution and a ∼2.1 mA cm −2 water oxidation photocurrent at 1.23 V under 100 mW cm −2 Xe arc lamp illumination. The water oxidation photocurrent is stable during a 50 min test, and the Faraday efficiency for O 2 generation is 97%, confirming short-term corrosion stability of LaTiO 2 N. Altogether, these results provide a better understanding of the distribution, concentration, and impact of Ti 3+ defects on the optical, photovoltage, and photoelectrochemical properties of LaTiO 2 N. In combination with other defect control strategies, aliovalent Ga 3+ doping can help bring the solar energy conversion efficiency of LaTiO 2 N closer to the theoretical limit.

Wang, Li [University of California, Davis, CA (Uni↗

DOE OSTI2022

Effects of potassium treatment on SnO 2 electron transport layers for improvements of perovskite solar cells

SnO 2 has been studied intensively as an electron transport layer (ETL) for highly efficient metal halide perovskite solar cells. However, SnO 2 ETL frequently exhibits defect-related issues associated with the bulk SnO 2 and the perovskite/SnO 2 interface, and to passivate the defect states potassium ion has been used. In order to investigate the passivation effect of potassium ion, we carried out KCl treatment on the solution-processed SnO 2 ETL. It was found that KCl-treatment shifted up conduction band maximum and Fermi energy of SnO 2 , and reduced the band gap of perovskite absorber by K + diffusion, which resulted in a better conduction band alignment at perovskite/SnO 2 . Admittance spectroscopy revealed that diffused K + ions can passivate defects of the perovskite absorber layer. With the improvement of band alignment and defect passivation via the KCl treatment, the J-V hysteresis was almost eliminated and power conversion efficiency was much enhanced with improved open-circuit voltage and fill factor.

14 SOLAR ENERGY↗

DOE OSTI2026

Alaska Meteorology, Energy, and Transmission (MET) Toolkit

The Alaska MET (Meteorology, Energy, and Transmission) Toolkit is the National Laboratory of the Rockies' (NLR) new flagship atmospheric dataset, designed to support comprehensive long-term planning and operations across the entire power sector. Serving as the regional counterpart to CONUS-wide HRRR MET Toolkit, this dataset provides a comprehensive, high-fidelity meteorological record covering Alaska.The Alaska MET Toolkit is delivered at an hourly resolution on a standardized 2-km horizontal grid. This dataset is repackaged from the National Oceanic and Atmospheric Administration's (NOAA) operational High-Resolution Rapid Refresh for Alaska (HRRR-AK) forecasts. Spanning from 2019 to 2025, it overcomes the technical barriers of native weather models by providing spatial regridding from the native 3-km HRRR-AK horizontal resolution to a 2-km grid, temporal gap-filling, and vertical interpolation at key energy-relevant heights. By delivering highly accurate, validation-backed data across a comprehensive suite of atmospheric variables - including temperature, pressure, humidity, and wind characteristics - the Alaska MET Toolkit provides a highly accessible and strictly standardized foundation for modern power system modeling.

17 WIND ENERGY↗

DOE OSTI2024

Dark black holes in the mass gap

Abstract In the standard picture of stellar evolution, pair-instability — the energy loss in stellar cores due to electron-positron pair production — is predicted to prevent the collapse of massive stars into black holes with mass in the range between approximately 50 and 130 solar masses — a range known as the “black hole mass gap”. LIGO and Virgo detection of black hole binary mergers containing one or both black holes with masses in thismass gapthus challenges the standard picture, possibly pointing to an unexpected merger history, unanticipated or poorly understood astrophysical mechanisms, or new physics. Here, we entertain the possibility that a “dark sector” exists, consisting of dark electrons, dark protons, and electromagnetic-like interactions, but no nuclear forces. Dark stars would inevitably form given such dark sector constituents, possibly collapsing into black holes with masses within the mass gap. We study in detail the cooling processes necessary for successful stellar collapse in the dark sector and show that for suitable choices of the particle masses, we indeed predict populating the mass gap with dark sector black holes. In particular, we numerically find that the heavier of the two dark sector massive particles cannot be lighter than, approximately, the visible sector proton for the resulting dark sector black holes to have masses within the mass gap. We discuss constraints on this scenario and how to test it with future, larger black hole merger statistics.

Astronomy & Astrophysics↗

DOE OSTI2025

An Integrated ML/AI Framework for Digitizing, Structuring and Searching DOE U-TRU-Fuels Data with Gap Analysis of Non-DOE Records

The U.S. Department of Energy (DOE) Advanced Fuels Campaign (AFC) is advancing transmutation fuel technologies to reduce long-lived radioactive waste by converting minor actinides into shorter-lived or stable elements through irradiation in sodium-cooled fast reactors. Key experiments such as AFC-1, AFC-2, FUels for the transmutation of Trans-URanium elements In phéniX (FUTURIX)-Fortes Teneurs en Actinides (FTA), and Experimental Breeder Reactor-II (EBR-II) X501 have provided fuel fabrication, irradiation, and performance data on various transuranic-bearing fuel forms. This report documents the creation of an artificial-intelligence assisted database, which has consolidated all DOE-owned data related to Transuranic (TRU)-bearing fuel experiments and stored across it across both the Idaho National Laboratory (INL) Nuclear Data Management and Analysis System and the INL high performance computing (HPC) infrastructure. A dedicated webpage, hosted on the INL HPC system, has been developed to support role-based access and data interaction. The database architecture allows researchers to navigate large, heterogeneous archives with far greater speed and accuracy than manual search and lays the foundation for future expansion into multimodal nuclear materials analysis environments. The database represents a major step towards a nationally integrated fuels database utilizing artificial intelligence tools.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2020

Similarity of capacitive radio-frequency discharges in nonlocal regimes

Similarity transformations are essential for correlating discharges at different scales, which are mostly utilized with local field or local energy approximations. In this work, we report the fully kinetic results from particle-in-cell/Monte Carlo collision simulations that unambiguously demonstrate the similarity of radio frequency (rf) discharges in nonlocal regimes where the electron energy relaxation length is much larger than the gap dimension. It is found that at a constant rf voltage amplitude, discharges will be similar if the gas pressure, inverse of gap distance, and rf driving frequency are all changed by the same scaling factor. The scaling relations of fundamental parameters are illustrated for rf discharges in the alpha-mode with secondary electron emission ignored, and the temporal electron kinetics are shown to have invariance in similar discharges. The results explicitly validate the scaling laws in nonlocal kinetic regimes, indicating promising application potentials of the similarity transformations across a wide range of kinetic regimes.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2025

Bridging the Gap on Data, Metrics, and Analyses for Grid Resilience to Weather Events: Information that utilities can provide regulators, state energy offices, and other stakeholders

A growing number of states require regulated utilities to file resilience plans to improve the electric grid’s ability to anticipate, withstand, adapt to and recover from increasingly severe weather events. This report aims to help state regulators identify and request data, metrics, and analyses from utilities and use it in decisions on utility resilience plans and investments. The report reviews state requirements and utility plans focused on overall grid resilience, climate change resilience and vulnerabilities, infrastructure modernization, storm protection, and wildfire mitigation. It details types of data, metrics, and analyses across five categories--and provides examples of each from the utility plans. The first category is vulnerability assessments, or evaluations of the susceptibility of systems, communities, or assets to potential harm from identified hazards. The second is data on hazards and the exposure of utility assets and customers to these hazards. The third is attribute metrics, or system characteristics that contribute to or describe the resilience of a system. The fourth is performance metrics, which are impacts of resilience investments on system performance--typically a reduction of negative impacts from hazard events. Finally, evaluation and prioritization are analyses that utilities conduct to estimate impacts from resilience measures (evaluation) and prioritize measures based on costs and estimated impacts (prioritization). The report concludes with examples of key trends and emerging best practices for states and utilities, and identifies areas for further research.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

Optical response and band structure of LiCoO 2 including electron-hole interaction effects

The optical response functions and band structures of LiCoO 2 are studied at different levels of approximation, from density functional theory (DFT) in the generalized gradient approximation (GGA) to quasiparticle self-consistent QSGW (with G for Green's function and W for screened Coulomb interaction) without and with ladder diagrams ($QSG\hat{W}$) and the Bethe Salpeter Equation (BSE) approach. The QSGW method is found to strongly overestimate the band gap and electron-hole or excitonic effects are found to be important. They lower the quasiparticle gap by only about 11~\% but the lowest energy peaks in absorption are found to be excitonic in nature. The contributions from different band to band transitions and the relation of excitons to band-to-band transitions are analyzed. Finally, the excitons are found to be strongly localized. Finally, a comparison to experimental data is presented.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2024

Event-Based Energy Impact Tracking and Forecasting with Limited Measurements for Rooftop Units

Packaged air conditioning units and heat pumps, also known as rooftop units (RTUs), are responsible for almost 133 billion kWh of electricity usage annually on site for space cooling U.S. commercial buildings. In addition, the use of heat pumps is a trend we expect to accelerate as buildings transition from fossil fuel-based heating to electricity as a key step for decarbonizing the U.S. commercial buildings sector. However, the operation conditions and energy use of RTUs and heat pumps are usually not well monitored as they are not commonly integrated with building automation systems and lack exposed sensing and control points. To fill this gap, this paper proposes a framework for tracking and forecasting energy impacts resulting from degradation of performance and improved performance for unit servicing using limited data. The proposed framework makes use of a constrained dataset, specifically measurements of the outdoor air temperature and the power demand of individual RTUs, to track and forecast changes in energy use associated with changes in performance over various temporal horizons ranging from days to weeks. Following the detection of an RTU fault, performance degradation, or performance improvement, the framework employs a prediction model to assess the cumulative energy impact. We demonstrate the effectiveness of the method with field-collected data for servicing and degradation examples and compare the predicting accuracy of Gradient Boosting Decision Tree (GBDT) Regression models to Support Vector Regression and Linear Regression models. The results show that GBDT achieved the best accuracy for time-series validation datasets for the servicing and degradation cases, and the prediction model was able to track the cumulative energy impacts of events. The proposed framework can inform building owners of the cumulative change in energy usage of RTUs associated with performance degradation, performance improvement, or a fault.

packaged air conditioners, packaged heat pumps, ro↗

DOE OSTI2026

Fabrication, oxidation, and combustion of nanoscale magnesium diboride and tetraboride

The difficult ignition and low combustion efficiency of boron particles decrease the performance of boron-loaded, fuel-rich propellants for solid fuel ramjets and ducted rockets. One approach to solving this problem involves the use of magnesium diboride (MgB 2 ), which ignites easier than boron. Magnesium tetraboride (MgB 4 ) offers greater energy density owing to its higher boron content. However, the effect of B/Mg ratio on the ignition and combustion is unknown. Additionally, while nanoscale MgB₂ particles and quasi-2D structures are promising energetic additives, the oxidation and combustion properties of nanoscale MgB₄ have not been explored. To address these knowledge gaps, the present work included synthesis and high-energy ball milling of MgB 2 and MgB 4 powders, thermogravimetric analysis (TGA) of their oxidation, and combustion experiments with thin layers of the obtained powders. Comparison of two synthesis routes (a solid-state reaction in a tube furnace and combustion synthesis) has shown that the former is the superior method for producing magnesium borides. TGA has revealed that oxidation of both MgB 2 and MgB 4 results in a high conversion into the oxides (88–91 %), far exceeding the low conversion of boron (62.5 %). MgB 4 begins to oxidize rapidly at a much lower temperature (∼900 °C) than MgB 2 (∼1200 °C). The burning rates of milled MgB 2 and MgB 4 are about eight and five times, respectively, faster than that of submicron boron. Magnesium borides exhibit a stable, sustained boron flame, needed for high combustion efficiency, whereas physical Mg/B mixtures undergo Mg-driven "flash" combustion.

Boron↗

DOE OSTI2026

Conditional distribution estimation of building characteristics with diffusion models for urban energy modeling

Understanding current energy consumption behavior in communities is critical for informing future energy use decisions and enabling efficient energy management. Urban energy models, which are used to simulate these energy use patterns, require large datasets with detailed building characteristics for accurate outcomes. However, such detailed characteristics at the individual building level are often unknown and costly to acquire, or unavailable. Through this work, we propose using a generative modeling approach to generate realistic building attributes to fill in the data gaps and finally provide complete characteristics as inputs to energy models. Our model learns complex, building-level patterns from training on a large-scale residential building stock model containing 2.2 million buildings. We employ a tabular diffusion-based framework that is designed to handle heterogeneous (discrete and continuous) features in tabular building data, such as occupancy, floor area, heating, cooling, and other equipment details. We develop a capability for conditional diffusion, enabling the imputation of missing building characteristics conditioned on known attributes. We conduct a comprehensive validation of our conditional diffusion model, firstly by comparing the generated conditional distributions against the underlying data distribution, and secondly, by performing a case study for a Baltimore residential region, showing the practical utility of our approach. Our work is one of the first to demonstrate the potential of generative modeling to accelerate building energy modeling workflows.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2026

Discrete versus continuous: Enhancing battery optimization in capacity expansion models

This study compares two battery modeling approaches for capacity expansion models: discrete-duration and continuous-duration formulations. In the discrete approach, battery duration is fixed, and power capacity is optimized. In the continuous approach, both power and energy capacities are decision variables, allowing storage duration to be optimized endogenously. Although both discrete-duration and continuous-duration battery formulations are used in long-term power system planning models, the literature has provided limited direct, systematic comparisons of their implications within a common modeling framework. To address this gap, this study implements both approaches in the Regional Energy Deployment System (ReEDS TM ) capacity expansion model using two resource adequacy methods, across a range of future system conditions, and with varying battery cost projections. Results show continuous-duration and high-resolution discrete approaches produce similar capacity expansion outcomes. The continuous formulation achieves faster runtimes compared to discrete-duration runs with many discrete-duration options. However, the discrete-duration approach allows users to choose to have limited fidelity for storage duration options, which in some cases can outperform the continuous formulation. The continuous formulation has the lowest overall system costs, indicating its ability to fine-tune storage duration to better meet specific system needs. This study's findings provide a side-by-side evaluation of discrete and continuous battery modeling approaches and offer guidance for improving the representation of real-world systems, flexibility, and computational efficiency for representing energy storage in long-term power system planning models.

25 ENERGY STORAGE↗

DOE OSTI2024

North America’s Potential for an Environmentally Sustainable Nickel, Manganese, and Cobalt Battery Value Chain

The Detroit Big Three General Motors (GMs), Ford, and Stellantis predict that electric vehicle (EV) sales will comprise 40–50% of the annual vehicle sales by 2030. Among the key components of LIBs, the LiNixMnyCo1−x−yO2 cathode, which comprises nickel, manganese, and cobalt (NMC) in various stoichiometric ratios, is widely used in EV batteries. This review reveals NMC cathodes from laboratory research. Furthermore, this study examines the environmental effect of NMC cathode production for EV batteries (including coating technologies), encompassing aspects such as energy consumption, water usage, and air emissions. Although gaps persist in NMC cathode environmental assessments (NMC111, NMC532, NMC622, and NMC811), limited life cycle assessments “(LCA)” have been conducted. Most available data originate from Asia (primarily China), accounting for 85% of the production of EV LIB cathode materials. The concept of battery passports for data collection on LIB components has been proposed to facilitate material traceability as a system for ensuring a sustainable supply chain for critical minerals. The automotive industry’s shift to electrification necessitates a sustainable supply chain from mine to vehicle end-of-life. As the critical mineral supply moves from Asia to North America, environmentally friendly industrial methods must be studied to provide this supply chain direction.

25 ENERGY STORAGE↗