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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Model-Based Framework to Optimize Charger Station Deployment for Battery Electric Vehicles

The development of battery electric vehicles (BEVs) is accelerating due to their environmental advantages over gasoline and diesel-powered vehicles, including a decrease in air pollution and an increase in energy efficiency. The deployment of charging infrastructure will need to increase to keep pace with demand, especially for large commercial vehicles for which few public chargers currently exist. In this paper, a new flexible framework is proposed for optimizing the placement of charging stations for BEVs, within which different physical models and optimization techniques may be used. Furthermore, a set of metrics is suggested to help enforce complex constraints and facilitate direct comparison between different optimization techniques. Unlike many existing charger placement techniques, the proposed method directly considers the historical driving patterns on a vehicle-by-vehicle basis, using transparent models to assess impacts of candidate charger placements, thus improving the explainability of the results. In the developed framework, modeled BEVs are first generated along the road network to mimic historical traffic data and are simulated traveling along a given route according to a simplified vehicle model. During the simulation, the charger placement problem is initially relaxed to allow vehicles to charge at any node along the road network, and vehicle states are tracked to assess areas of high charging demand. Charging stations are then placed based on the results of the relaxed simulation, and suggested placements are evaluated via road network simulation with fixed charger locations. This proposed framework is applied to a sample problem of placing charging stations along five major highway corridors for Class 8 over-the-road electric trucks. A novel mixed integer programming (MIP) formulation is proposed to optimize charger placements based upon the expected charging demand. Constraints were imposed on the final placement results to limit expected wait times at each station and ensure a minimum threshold of trucking routes are viable for BEVs. The results demonstrate the flexibility and potential effectiveness of the developed model-based framework for scalable charger station deployment.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

SIX EPU Antiparallel Study: Estimating mechanical and magnetic performance of the distorted 3.5m EPU57 in antiparallel mode

The 3.5m long SIX EPU with 57 mm period shown schematically was manufactured to NSLS2 specification by Kyma of Italy. That specification called for operation to be limited to parallel mode. In parallel mode each of two diagonally opposing permanent magnet array quadrants drive in the same direction along its respective longitudinal axis by a half period relative to its adjacent fixed array quadrant. As such, at maximum shift the array pairs are only 180 degrees out of phase.

36 MATERIALS SCIENCE↗
DOE OSTI2022

ENIGMA: Ecosystems and Networks Integrated with Genes and Molecular Assemblies. Final Report

ENIGMA research is performed at a very large scale involving collaborations between multiple research groups to address two major driving concepts: For any microbe, it is possible to discover efficiently the genetic determinants of adaptation to life in dynamic environments in contact with other living members of its ecology and reveal hidden functional phenomena that are only possible by using a systems biology approach; and for any environment, it is possible to predict the temporal changes in geochemistry and accompanying system behavior, for some length of time, given biogeochemical and physical inputs. These driving concepts also map directly to grand challenges the ENIGMA team has outlined: “Define the levels of biological organization most relevant to scaling from single cells to ecosystems and global cycles; capture how that organization varies in time and space; and identify critical interactions that dictate rates of carbon, nutrient, and energy transformation in different environments.”

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Advanced Simulation and Computing: ASC FY24 Implementation Plan

The DOE National Nuclear Security Administration (NNSA) Stockpile Stewardship Program (SSP) is an integrated technical program for maintaining the safety, security, and reliability of the U.S. nuclear stockpile. The SSP incorporates nuclear test data, computational modeling and simulation, and experimental facilities to advance understanding of nuclear weapons. The suite of data analyzed comes from activities including previous nuclear tests, stockpile surveillance, experimental research, and development and engineering programs. This integrated national program requires the continued use of experimental facilities and the computational capabilities to support the SSP missions. These component parts, in addition to an appropriately scaled production capability, enable NNSA to support stockpile requirements. The ultimate goal of the SSP, and thus of the Advanced Simulation and Computing (ASC) program, is to ensure that the U.S. maintains a safe, secure, and effective strategic deterrent. The ASC program is a cornerstone of the SSP, providing simulation capabilities and computational resources to support the annual stockpile assessment and certification process, study advanced nuclear weapons design and manufacturing processes, analyze accident scenarios and weapons aging, and provide the tools to enable stockpile Life Extension Programs (LEPs) and the resolution of Significant Finding Investigations (SFIs). This work requires a balance of resources, including technical staff, hardware, simulation software, and computer science solutions. The ASC program focuses on increasing the predictive capabilities in a three-dimensional (3D) simulation environment while maintaining support to the SSP. The Program continues to improve its unique tools for understanding and solving progressively more difficult stockpile problems (sufficient resolution, dimensionality, and scientific details), and quantifying critical margins and uncertainties. Resolving each issue requires increasingly difficult analyses because the aging process has progressively moved the stockpile further from the original test base. While the focus remains on the U.S. nuclear weapons program, where possible, the Program also enables the use of high-performance computing (HPC) and simulation tools to address broader national security needs, such as foreign nuclear weapon assessments and nuclear counterterrorism. The 2022 Nuclear Posture Review (NPR) calls for NNSA to “deliver a modern, adaptive nuclear security enterprise based on an integrated strategy for risk management, production-based resilience, science and technology innovation, and workforce initiatives.” Furthermore, “NNSA will establish a Science and Technology Innovation Initiative to accelerate the integration of science and technology (S&T) throughout its activities.” Executing this strategy necessitates the continued emphasis on developing and sustaining high-quality scientific and engineering staff, as well as supporting computational and experimental capabilities. These components constitute the foundation of the nuclear weapons program. The continued success of the SSP and LEPs is predicated upon the ability to credibly certify the stockpile, without a return to underground nuclear tests (UGTs). Shortly after the nuclear test moratorium entered into force in 1992, the Accelerated Strategic Computing Initiative (ASCI) was established to provide an extensive simulation capability to underpin stockpile certification. While computing and simulation have always been essential to the success of the nuclear weapons program, the program goal of ASCI was to execute NNSA’s vision of using these tools in support of the stockpile stewardship mission. The ASCI program was essential to the successful demonstration of the SSP, providing critical nuclear weapons simulation and modeling capabilities. ASCI officially evolved into the ASC program in fiscal year (FY) 2005, but the mission remains essentially the same: provide the simulation and computational capabilities that underpin the ability to maintain a safe, secure, effective nuclear weapon stockpile, without returning to underground nuclear testing. The capabilities that the ASC program provides at the national laboratories play a vital role in the nuclear security enterprise and are necessary for fulfilling the stockpile stewardship and life extension requirements outlined for NNSA. The Program develops modern simulation tools that provide insights into stockpile aging issues, provide the computational and simulation tools that enable designers and analysts to certify the current stockpile and life-extended nuclear weapons, and inform the decision-making process when any modifications in nuclear warheads or the associated manufacturing processes are deemed necessary. Furthermore, ASC is enhancing the predictive simulation capabilities that are essential to evaluate weapons effects, design experiments, and ensure test readiness. The ASC program continues to improve its unique tools to solve stockpile problems— with a focus on sufficient resolution, dimensionality, and scientific detail—to enable Quantification of Margins and Uncertainties (QMU) and to resolve the increasingly difficult analyses needed for stockpile stewardship. The needs of the Stockpile Management and Production Modernization programs (formerly Directed Stockpile Work) also drive the requirements for simulation and computational resources. These requirements include planned LEPs, stockpile support activities, and mitigation efforts against the potential for technical surprise. All of the weapons within the current stockpile are in some stage of the life extension process. The simulation and computational capabilities are crucial for successful execution of these life extensions and for ensuring NNSA can certify these life-extended weapons without conducting a UGT.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Comparative feedstock analysis in Setaria viridis L. as a model for C 4 bioenergy grasses and panicoid crop species

Second generation feedstocks for bioethanol will likely include a sizable proportion of perennial C4 grasses, principally in the Panicoideae clade. The Panicoideae contain agronomically important annual grasses including Zea mays L. (maize), Sorghum bicolor (L.) Moench (sorghum), and Saccharum officinarum L. (sugar cane) as well as promising second generation perennial feedstocks including Miscanthus × giganteus and Panicum virgatum L. (switchgrass). The underlying complexity of these polyploid grass genomes is a major limitation for their direct manipulation and thus driving a need for rapidly cycling comparative model. Setaria viridis (green millet) is a rapid cycling C4 panicoid grass with a relatively small and sequenced diploid genome and abundant seed production. Stable, transient, and protoplast transformation technologies have also been developed for Setaria viridis making it a potentially excellent model for other C4 bioenergy grasses. Here, the lignocellulosic feedstock composition, cellulose biosynthesis inhibitor response and saccharification dynamics of Setaria viridis are compared with the annual sorghum and maize and the perennial switchgrass bioenergy crops as a baseline study into the applicability for translational research. A genome-wide systematic investigation of the cellulose synthase-A genes was performed identifying eight candidate sequences. Two developmental stages; (a) metabolically active young tissue and (b) metabolically plateaued (mature) material are examined to compare biomass performance metrics.

09 BIOMASS FUELS↗
DOE OSTI2020

Drive-pressure optimization in ramp-wave compression experiments through differential evolution

Ramp-wave dynamic-compression experiments are used to examine quasi-isentropic loading paths in materials. The gradual and continuous increase in pressure created by ramp waves make these types of experiments ideal for studying nonequilibrium material behavior, such as solidification kinetics. In ramp-wave compression experiments, the input drive pressure to the experimental setup may be exerted through one of a number of different mechanisms (e.g., magnetic fields, gas-gun-driven impactors, or high-energy lasers) and is generally required for simulating such experiments. Yet, regardless of the specific mechanism, this drive pressure cannot be measured directly (measurements are generally taken at a location near the back of the experimental setup through a transparent window), leading to an inverse problem where one must determine the drive pressure at the front of the experimental setup (i.e., the input) that corresponds to the particle velocity (the output) measured near the back of the experimental setup. Furthermore, we solve this inverse problem using a heuristic optimization algorithm, known as differential evolution, coupled with a multiphysics, hydrodynamics code that simulates the compression of the experimental setup. By running many rounds of forward simulations of the experimental setup, our optimization process iteratively searches for a drive pressure that is optimized to closely reproduce the experimentally measured particle velocity near the back of the experimental setup. While our optimization methodology requires a significant number of hydrodynamics simulations to be conducted, many of these can be performed in parallel, which greatly reduces the time cost of our methodology. One novel aspect of our method for determining the drive pressure is that it does not require physical modeling of the drive mechanism and can thus be broadly applied to many types of ramp-compression experiments, regardless of the drive mechanism.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

Adaptive Cybersecurity for Distributed Energy Resources (AdCyDER): Online Reinforcement Learning with Stackelberg-Optimized Defenses — Pipeline Architecture, Evaluation Methodology, and Findings from a Synthetic-Data Evaluation

This report documents the design and evaluation of an integrated online-learning pipeline developed within the AdCyDER project for Distributed Energy Resource (DER) cybersecurity. The pipeline couples a Reinforcement Learning (RL) attack classifier — which produces an attack-type probability distribution — with a Stackelberg game-theoretic (GT) defense selector that consumes those distributions alongside SME-encoded priors over (defense, attack) effectiveness pairings and perdefense costs to choose grid-health-preserving defenses. The objective is not attack classification per se but production of distributions that drive effective defense selection through the Stackelberg layer, learned from delayed grid-health feedback rather than labeled attack data. AdCyDER as a whole is broader than the work presented here; this report covers the specific RL/GT loop integration and its evaluation. We present the integrated pipeline (SCADA telemetry with Fronius inverter physics, Suricata IDS, time-windowed aggregation, per-facility LSTM classifier, Stackelberg optimizer, OpenC2 actuators), an experimental campaign of 28 eight-hour iterations across three baseline modes, and a pipeline-ordered diagnostic protocol. The protocol identifies two distinct failure modes within the loop: paired supervised ceilings on the same features establish that the deployed online RL classifier (macro F1 ≈ 0.07) sits at least 4.7× below a same-architecture supervised LSTM (≈ 0.34) and 10–11× below a linear feature-signal ceiling (≈ 0.70–0.79 depending on per-facility isolation), localizing the dominant failure to the training procedure; and the reward signal driving online updates carries weak directional coupling with classifier correctness in the methodology-expected direction (multi-lens convergent: top-decile P(true) records produce more frequent state changes and slightly larger improvements, top-vs-bot Cohen’s 𝑑 ≈ −0.19), but at effect magnitudes too small to drive gradient-based learning at the campaign sample size. The original learning hypothesis is not supported by the data. The primary contributions are the diagnostic methodology — proposed as a transferable falsification protocol for online RL/GT defense pipelines learning from delayed environmental reward — and the open, reproducible experimental infrastructure. We outline reward reformulation as the highest-priority aspirational next step given the underpowered-but-aligned Q6 reading, with hardware-in-the-loop evaluation as the broadest scope-expansion option.

Blakely, Benjamin [Argonne National Laboratory (AN↗
DOE OSTI2024

Curves, Coriolis, and Cross-Channel Circulation in the Hudson River Estuary

Abstract Despite its relatively small magnitude, cross-channel circulation in estuaries can influence the along-channel momentum balance, dispersion, and transport. We investigate spatial and temporal variation in cross-channel circulation at two contrasting sites in the Hudson River estuary. The two sites differ in the relative strength and direction of Coriolis and curvature forcing. We contrast the patterns and magnitudes of flow at the two sites during varying conditions in stratification driven by tidal amplitude and river discharge. We found well-defined flows during flood tides at both sites, characterized by mainly two-layer structures when the water column was more homogeneous and structures with three or more layers when the water column was more stratified. Ebb tides had generally weaker and less definite flows, except at one site where curvature and Coriolis reinforced each other during spring tide ebbs. Cross-channel currents had similar patterns, but were oppositely directed at the two sites, demonstrating the importance of curvature even in channels with relatively gradual curves. Coriolis and curvature dominated the measured terms in the cross-channel momentum balance. Their combination was generally consistent with driving the observed patterns and directions of flow, but local acceleration and cross-channel advection made some notable contributions. A large residual in the momentum balance indicates that some combination of vertical stress divergence, baroclinic pressure gradients, and along-channel and vertical advection must play an essential role, but data limitations prevented an accurate estimation of these terms. Cross-channel advection affected the along-channel momentum balance at times, with implications for the exchange flow’s strength. Significance Statement Currents that flow across the channel in an estuary move slower than those flowing along the channel, but they can transport materials and change water properties in important ways, affecting human uses of estuaries such as shipping, aquaculture, and recreation. We wanted to better understand cross-channel currents in the Hudson River estuary. We found that larger tides produced the strongest cross-channel currents with a two-layer pattern, compared to weaker currents with three layers during smaller tides. Higher or lower river flow also affected current strength. Comparing two locations, we saw cross-channel currents moving in opposite directions because of differences in the curvature of the river channel. Our results show how channel curvature and Earth’s rotation combine to produce cross-channel currents.

Conley, Margaret M.↗
DOE OSTI2022

Process-informed adsorbent design guidelines for direct air capture

Direct air capture using solid adsorbents is a proven technology critical to reducing our net greenhouse gas emissions to zero and beyond. Currently, academic research into the technology mainly focuses on the development of new adsorbents. However, there is a discord between the adsorbent design and process performance. Many materials scientists focus on maximising metrics such as the CO 2 capacity of their adsorbent. Here, we combine detailed process modelling, machine learning, and extensive global sensitivity analysis, which entails varying all of the model parameters together, on a direct air capture process to show that the dry CO 2 adsorption capacity does not influence process performance for an amine-functionalised adsorbent operating in a temperature vacuum swing adsorption (TVSA) process, while it is important in a steam-assisted TVSA (S-TVSA) process. In fact, adsorption kinetics, density, and thermal conductivity are all critical attributes to obtaining a low energy penalty and reduced costs. The analysis also highlights the importance of heat transfer, directing process engineers to (alternative) adsorber designs that maximise this. By an in-depth evaluation of how process performance indicators are affected by materials properties and process operating parameters, this work provides guidance to both material scientists and process engineers towards the design of a “unicorn adsorbent” and intensified DAC processes. This will improve the performance of solid adsorbent direct air capture and help drive down the costs of this vital technology to avert the worst impacts of climate change.

42 ENGINEERING↗
DOE OSTI2022

Drive-Leg Kinematics During the Windup and Pushoff Is Associated With Pitching Kinetics at Later Phases of the Pitch

Background: Inconsistent findings exist between drive-leg ground-reaction forces (GRFs) and pitching mechanics. Previous literature has largely reported drive-leg mechanics and GRFs at the start of the pushoff phase for their role in initiating force development. Little research has assessed drive-leg kinematics that includes a pitcher’s windup motion to determine its effects on subsequent phases in the pitching motion. Purpose/Hypothesis: The primary aim was to analyze the relationship between drive-leg knee valgus angle during the windup and subsequent pitching mechanics. We hypothesized that the drive-leg knee valgus angle during the early portion of the pitching motion would alter later phases’ pitching mechanics. A secondary aim was to assess GRFs to determine if the drive-leg knee valgus angle was associated with changes in force. We hypothesized that an increased drive-leg knee valgus angle would increase GRFs during the pitching motion. Study Design: Descriptive laboratory study. Methods: A total of 17 high school baseball pitchers (mean age, 16.1 ± 0.9 years; mean height, 180.0 ± 4.8 cm; mean weight, 75.5 ± 7.5 kg) volunteered for the study. Kinematic data and GRFs were collected using an electromagnetic tracking system and force plates. Pitchers threw maximal-effort fastballs from a mound at regulation distance. The drive-leg knee valgus angle was analyzed during the windup and pushoff phases of the pitch to determine its effects on other biomechanical variables throughout the pitching motion. Results: There was a significant relationship between drive-leg knee valgus angle during the windup ( Fchange 1,12) = 16.13; P = .002; R 2 = 0.695) and lateral GRF in the arm-cocking phase. Additionally, there was a significant relationship between drive-leg knee valgus angle during pushoff ( Fchange(2,11) = 10.21; P = .003; R 2 = 0.716) and lateral GRF in the arm-cocking phase and pitching-elbow valgus moment in the acceleration phase. Conclusion: Drive-leg knee valgus angle during the windup and pushoff had a significant relationship with drive-leg GRF and pitching-elbow valgus moment at later stages of the pitching cycle. Clinical Relevance: Assessments of drive-leg kinematics during the windup and pushoff may be useful in identifying inefficient movement patterns that can have an effect on the direction of a pitcher’s drive-leg force contribution, which can lead to increased forces on the throwing elbow.

Orthopedics↗
DOE OSTI2021

Guided skyrmion motion along pinning array interfaces

We examine ac driven skyrmions interacting with the interface between two different obstacle array structures. We consider drive amplitudes at which skyrmions in a bulk obstacle lattice undergo only localized motion and show that when an obstacle lattice interface is introduced, directed skyrmion transport can occur along the interface. The skyrmions can be guided by a straight interface and can also turn corners to follow the interface. For a square obstacle lattice embedded in a square pinning array with a different obstacle radius, we find that skyrmions can undergo transport in all four primary symmetry directions under the same fixed ac drive. We map where localized or translating motion occurs as a function of the ac driving parameters. Our results suggest a new method for controlling skyrmion motion based on transport along obstacle lattice interfaces.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Determination of the regeneration energy of direct air capture solvents/sorbents using calorimetric methods

Regeneration energy and recyclability are important parameters that dictate the viability of a CO 2 direct air capture (DAC) process. In this study, differential scanning calorimetry (DSC) is used in conjunction with thermogravimetric analysis (TGA) and Fourier Transform Infrared Spectroscopy (FTIR) to evaluate the regeneration energy required for CO 2 -loaded 3 M aqueous potassium sarcosinate (K-SAR) solvent and crystalline methyl-glyoxal-bisiminoguanidine (MGBIG) sorbent. Based on calorimetric measurements, for aqueous K-SAR, the sensible heat amounts to 1.5 GJ/tCO 2 and the enthalpy of desorption is estimated at 3.68 GJ/tCO 2 . The total energy of regeneration will also include the enthalpy of solvent vaporization, which will depend on the thermodynamic conditions and the level of regeneration. For MGBIG, the total regeneration energy required was measured at approximately 7.0 GJ/tCO 2 . Further, FTIR measurements were used to observe CO 2 and H 2 O release during the thermal regeneration process. For K-SAR, CO 2 release is seen to take place at temperatures greater than 80 °C and, for MGBIG, the CO 2 release takes place at temperatures greater than 100 °C. The moderate temperatures required for K-SAR and MGBIG regenerations compared to other DAC solvents/sorbents suggest that low-cost sources of heat, such as geothermal heat, could potentially be used for regeneration to drive down the cost of direct air capture.

42 ENGINEERING↗
DOE OSTI2024

Electron/hole selectivity in organic semiconductor contacts for solar energy conversion (Final Report)

Four major and accomplishments for the project "Electron/hole selectivity in organic semiconductor contacts for solar energy conversion.'' are reported. The first is a development of a model describing the contact-determined behavior of a solar cell. The most basic solar cell consists of an intrinsic (pure) semiconductor that acts as an absorber to which contacts are made that provide the asymmetry needed to create a driving force (voltage) for the directional flow of electrons (current), in other words, to convert sunlight into electrical energy. The asymmetry at the contacts comes from the different rate at which electrons and holes, the charge carriers generated by illumination, are collected. We developed a model that describes the ideal current-voltage, and hence energy converting properties, of an ideal photovoltaic that is entirely determined by the kinetics for these charge collection processes. Second, we measured how organic semiconductor interfacial layers impact contact electron and hole transfer rates at semiconductor interfaces and described how these concepts do or do not determine the open-circuit voltage of a solar cell. The work clearly controverts common general misconceptions about the action of contact interfacial layers, such as the idea that improved selectivity for one carrier over the other results from decreased recombination, and quantitatively demonstrates how specific interfacial layer materials act to improve the efficiency of a solar cell. Third, we measured the sub-band gap external quantum efficiency (EQE) of a series of organometal halide perovskite (“perovskite”) solar cells. These measurements quantified band-tailing and revealed defect states, which can cause recombination, that correlate with composition, performance, and hysteresis. Finally, we developed a semiconductor bipolar membrane that uses light to pump ions. This structure is unique among systems that drive ion gradients using light in that it is designed to pump salt rather than one sign of ion; it is a photochemical salt pump.

14 SOLAR ENERGY↗
DOE OSTI2023

Innovation in complementary energy technologies from renewable energy policies

Complementary renewable technologies support renewable energy use as they can help balance the intermittency of solar and wind generation. Previous research has shown that environmental policies directly targeting renewable energy can drive innovation in solar PV and wind technology. This study explores the impact of renewable policies on innovation in complementary renewable technology that assists with integration, including combustion with mitigation potential, efficient power transmission or distribution, and enabling technologies. We use negative binomial models and a panel of 25 OECD countries from 1997 to 2015 to evaluate these relationships. We are not able to find evidence that renewable policies incentivize innovation in complementary combustion or transmission and distribution technologies, and only limited evidence that demand-pull instruments are associated with increased innovation in smart grid technology. Technology-push policies, such as public research and development funds for renewable energy, have had limited impact on grid-supporting energy storage innovation. Our findings suggest that policymakers wishing to accelerate these complementary technologies need to go beyond policies targeting renewable energy in order to drive innovation in complementary fields.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Spatial access and resource limitations control carbon mineralization in soils

Core-scale soil carbon fluxes are ultimately regulated by pore-scale dynamics of substrate availability and microbial access. These are constrained by physicochemical and biochemical phenomena (e.g. spatial access and hydrologic connectivity, physical occlusion, adsorption-desorption with mineral surfaces, nutrient and resource limitations). We conducted an experiment to determine how spatial access and resource limitations influence core-scale SOM mineralization, and how these are regulated by antecedent moisture conditions. Intact soil cores were incubated at field-moist vs. drought conditions, after which they were saturated from above (to simulate precipitation) or below (to simulate groundwater recharge). Soluble C (acetate) and N (nitrate) forms were added to some cores during the rewetting process to alleviate potential nutrient limitations. Respiration showed evidence of C-limitation, as C amendments increased the cumulative CO 2 evolved. Drought and rewetting increased soil respiration, and these soils also exhibited increased complex aromatic molecules in porewater. This newly available substrate appeared to alleviate nutrient limitations on respiration, because there were no further respiration increases with subsequent C and N amendments. We expected that respiration would be influenced by wetting direction, as simulated precipitation would mobilize C from the surface. However, as a main effect, this response was seen only in the C-amended soils, indicating that surface-C may not have been bioavailable. At the pore scale (porewater samples), compared to the baseline soils, drought and the C, N amendments caused a net loss of identified molecules when the soils were rewet from below, whereas wetting from above caused a net increase in identified molecules. This indicates that as soils were wet from below, the fresh inputs simulated the C-and N-limited microbial populations present deeper in the soil profile. Furthermore, our experiment highlights the complex and interactive role of antecedent moisture conditions, wetting direction, and resource limitations in driving core-scale C fluxes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

p-Type BiVO 4 for Solar O 2 Reduction to H 2 O 2

Photoelectrochemical cells (PECs) can directly utilize solar energy to drive chemical reactions to produce fuels and chemicals. Oxide-based photoelectrodes in general exhibit enhanced stability against photocorrosion, which is a critical advantage for building a sustainable PEC. However, most oxide-based semiconductors are n-type, and p-type oxides that can be used as photocathodes are limited. In this study, we report the synthesis, characterization, and application of p-type BiVO 4 with a monoclinic scheelite (ms) structure. ms-BiVO 4 is inherently n-type, and it has been investigated only as a photoanode to date. In this study, we prepared p-type ms-BiVO 4 (bandgap of 2.4 eV) via atomic doping of Ca 2+ at the Bi 3+ site under an O 2 -rich environment and examined its performance as a photocathode. We then demonstrated that the Ca-doped ms-BiVO 4 photocathode can be used for solar O 2 reduction to H 2 O 2 when coupled with appropriate catalysts. Our computational investigation using hybrid density functional theory revealed that holes are stable as polarons in ms-BiVO 4 and have a low self-trapping energy, that may lead to free carriers in the valence band at finite temperature. Our calculations also show that Ca is an effective shallow acceptor dopant with low formation energy and thermal ionization energy leading to p-type conductivity. In conclusion, our joint experimental and computational results provide critical insights into the design of p-type ms-BiVO 4 , enabling its use as a polaronic oxide photocathode.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

A data-driven global soil heterotrophic respiration dataset and the drivers of its inter-annual variability

Soil heterotrophic respiration (SHR), one of the primary carbon fluxes from terrestrial ecosystems to the atmosphere, is important for carbon-climate feedbacks because of its sensitivity to available litter and soil carbon, climatic conditions, and nutrient availability. However, until recently limited SHR data were available, and most published global SHR estimates have either a short time span, coarse spatial resolution, or reply on overly-simple model formulations. To better understand and quantify the global distribution of SHR and its sensitivity to climate variability, we produced a new global SHR dataset using Random Forest algorithms, up-scaling 455 point data from the Global Soil Respiration Database (SRDB 4.0) with gridded fields of climatic, edaphic and productivity as explanatory variables. We estimated a global total SHR of 46.8 Pg C yr-1 over 1985-2013 (95% confidence interval: 38.6-56.3 Pg C yr-1), with a significant increasing trend of 0.03 Pg C yr-2 during this period. We found that the choice of soil moisture datasets contributes more to the difference among these data-driven SHR members rather than that of productivity, temperature and precipitation data sources. We also analyzed the influence of climatic variables on the inter-annual variability (IAV) of our SHR product. Water availability was the dominant driver of IAV at global scales, although the inferred sensitivity depends on the choice of the soil moisture gridded dataset. At the ecosystem scale, temperature strongly controls the IAV of SHR in tropical forests, while water availability dominates in extra-tropical forest and semi-arid regions. Our machine-learning gridded SHR dataset and outputs from process-based land surface models (TRENDYv6) show agreement for a strong association between water variability and SHR IAV at the global scale, but the two approaches lead to different temporal trend globally and different controlling variables for IAV at the ecosystem scale. Our study provides evidence for the pervasive and important role of water availability in driving SHR, indicating both a direct effect limiting decomposition rates and an indirect effect through the amount of fresh organic matter made available to SHR from productivity. In consideration of potential limitations and uncertainties remaining in our data-driven SHR datasets, we call for a more scientifically designed observation network for SHR, more observation data compilation, and increased use of deep learning methods making maximum use of observation data in hand. This will benefit process-based models, and improve our understanding of SHR response to future anomalous environmental conditions.

Yao, Yitong↗
DOE OSTI2026

Scalings of laser-driven MeV electron sources with relativistic multi-picosecond laser pulses

We investigate the generation of MeV electrons in relativistic multi-picosecond laser–solid interactions, using two-dimensional particle-in-cell simulations. Scanning a parameter space of intensities from 10 18 to 10 20 W/cm 2 and pulse durations between 100 fs and 10 ps, we discuss scalings of the effective hot electron temperature and MeV electron dose relevant to applications, as well as the direct laser acceleration mechanism that drives electrons to energies much higher than the ponderomotive potential of the laser pulse.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗