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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Stochastic symplectic reduced-order modeling for model-form uncertainty quantification in molecular dynamics simulations in various statistical ensembles

Here, this work focuses on the representation of model-form uncertainties in molecular dynamics simulations in various statistical ensembles. In prior contributions, the modeling of such uncertainties was formalized and applied to quantify the impact of, and the error generated by, pair-potential selection in the microcanonical ensemble (NVE). In this work, we extend this formulation and present a linear-subspace reduced-order model for the canonical (NVT) and isobaric (NPT) ensembles. The symplectic reduced-order basis is randomized on the tangent space of the Stiefel manifold to provide topological relationships and capture model-form uncertainty. Using the Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS), we assess the relevance of these stochastic reduced-order atomistic models on canonical problems involving a Lennard-Jones fluid and an argon crystal melt.

42 ENGINEERING↗
DOE OSTI2026

Local reduced-order modeling for electrostatic plasmas by physics-informed solution manifold decomposition

Despite advancements in high-performance computing and modern numerical algorithms, computational cost remains prohibitive for multi-query kinetic plasma simulations. Here, in this work, we develop data-driven reduced-order models (ROMs) for collisionless electrostatic plasma dynamics, based on the kinetic Vlasov-Poisson equation. Our ROM approach projects the equation onto a linear subspace defined by the proper orthogonal decomposition (POD) modes. We introduce an efficient tensorial method to update the nonlinear term using a precomputed third-order tensor. We capture multiscale behavior with a minimal number of POD modes by decomposing the solution manifold into multiple time windows and creating temporally local ROMs. We consider two strategies for decomposition: one based on the physical time and the other based on the electric field energy. Applied to the 1D1V Vlasov–Poisson simulations, that is, prescribed E-field, Landau damping, and two-stream instability, we demonstrate that our ROMs accurately capture the total energy of the system both for parametric and time extrapolation cases. The temporally local ROMs are more efficient and accurate than the single ROM. In addition, in the two-stream instability case, we show that the energy-windowing reduced-order model (EW-ROM) is more efficient and accurate than the time-windowing reduced-order model (TW-ROM). With the tensorial approach, EW-ROM solves the equation approximately 90 times faster than Eulerian simulations while maintaining a maximum relative error of 7.5% for the training data and 11% for the testing data.

Electrostatic plasmas↗
DOE OSTI2026

Parametric reduced order models for graded lattice structures

Graded lattice structures, characterized by smoothly varying mechanical properties, hold significant promise for optimizing material distribution in advanced engineering applications. However, accurately modeling these structures poses substantial computational challenges due to the continuous geometric variations within their unit cells. Here, to address these challenges, this paper introduces a novel Efficient Reduced Order Model (EROM) that integrates the Matrix Discrete Empirical Interpolation Method (MDEIM) and Discrete Empirical Interpolation Method (DEIM) with polynomial regression to efficiently manage geometric parametrization in lattice structures. Unlike traditional reduced order models (ROMs) that require extensive precomputed libraries for each geometric configuration, our approach enables continuous geometric variations through a flexible algebraic formulation, significantly reducing computational costs while preserving high accuracy. The method constructs projection matrices for individual unit cells that can be efficiently assembled into global systems, leveraging the repetitive nature of lattice structures. Numerical studies demonstrate that our EROM achieves displacement errors below 1% and von Mises stress prediction errors below 4%, coupled with computational speedups exceeding two orders of magnitude compared to full-order simulations. The proposed method's modularity and scalability make it particularly suitable for design optimization and real-time simulation of functionally graded lattice structures, with applications spanning aerospace to biomedical engineering.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Joint state-parameter estimation for the reduced fracture model via the united filter

Here, in this paper, we introduce an effective United Filter method for jointly estimating the solution state and physical parameters in flow and transport problems within fractured porous media. Fluid flow and transport in fractured porous media are critical in subsurface hydrology, geophysics, and reservoir geomechanics. Reduced fracture models, which represent fractures as lower-dimensional interfaces, enable efficient multi-scale simulations. However, reduced fracture models also face accuracy challenges due to modeling errors and uncertainties in physical parameters such as permeability and fracture geometry. To address these challenges, we propose a United Filter method, which integrates the Ensemble Score Filter (EnSF) for state estimation with the Direct Filter for parameter estimation. EnSF, based on a score-based diffusion model framework, produces ensemble representations of the state distribution without deep learning. Meanwhile, the Direct Filter, a recursive Bayesian inference method, estimates parameters directly from state observations. The United Filter combines these methods iteratively: EnSF estimates are used to refine parameter values, which are then fed back to improve state estimation. Numerical experiments demonstrate that the United Filter method surpasses the state-of-the-art Augmented Ensemble Kalman Filter, delivering more accurate state and parameter estimation for reduced fracture models. This framework also provides a robust and efficient solution for PDE-constrained inverse problems with uncertainties and sparse observations.

Bayesian inference↗
DOE OSTI2024

In situ oxidation of reduced graphene oxide membranes by peracetic acid for dye desalination

Graphene oxide (GO) membranes with tunable interlayer spacings are of interest for dye removal from salty textile wastewater, and the membranes are often reduced to improve their stability, which inevitably lowers water permeance. Herein, we demonstrate that reduced GO (rGO) membranes can be facilely modified using peracetic acid (PAA) in situ to dramatically enhance water permeance while retaining dye rejection. Specifically, PAA-modified membranes (PrGO) are synthesized by vacuum-filtering hydrazine-reduced rGO nanosheets onto Nylon substrate and then exposing them to PAA solutions. The effects of the rGO layer thickness, PAA content, and PAA exposure time on the membrane chemistry, nanostructures, and salt/dye separation properties are thoroughly examined. For example, the PAA oxidation of a 100 nm-thick rGO membrane for 10 min increases water permeance by 180 %, from 35 to 93 Liter m −2 h −1 bar −1 , and decreases Na 2 SO 4 rejection from 10 % to 3.3 % while retaining the rejection of Congo red at ≈99.7 %. The PrGO membranes exhibit stable water permeance and >99 % dye rejection in multi-cycle tests in a crossflow system, surpassing state-of-the-art GO membranes and showcasing their potential for practical applications.

Dye desalination↗
DOE OSTI2024

Utilization of Ultrasonication as a Method of Reducing Organic and Inorganic Contamination in Post‐Consumer Plastic Film Waste

Post-consumer plastic film waste often carries organic and inorganic contaminants that challenge recycling processes and affect the quality of recycled products. An effective contaminant removal procedure through washing such single-used plastic films (SUPFs) can address environmental and waste management concerns. This study compares the efficiency of different washing techniques in reducing SUPF contamination. To evaluate the efficacy of each washing technique, film samples collected from material recovery facilities are individually exposed to friction, ultrasonic-assisted, and a combination of both washes. Thermal analysis indicates that the polymers' melting temperature, crystallization temperature, and crystallinity remain unaffected by the washing methods, demonstrating method aptness. Confocal laser scanning microscope images show that washing results in a cleaner sample surface. 91% ash reduction during the combined wash treatment indicates a high method efficiency compared to the individual friction and ultrasonic wash procedures. This is further validated by reducing characteristic contaminant IR bands (3600–3000, 1750–1600, and 1100–1000 cm −1 ). Elements of concern such as Cd, Cr, Hg, and Pb in SUPFs after each washing technique applied conform with regulations (<100 ppm) for packaging products. This research shows the novel ultrasonic washing reduces more contamination than friction with shorter wash times and no surfactants.

42 ENGINEERING↗
DOE OSTI2025

Phosphate-modulated transformation of Sb(V)-bearing ferrihydrite under microbial iron- and sulfate-reducing conditions

Antimony (Sb) is a toxic metalloid that poses environmental risks in terrestrial and aquatic systems. The fate of the Sb(V) oxyanion, Sb(OH) 6 − , is governed by complex biogeochemical processes, including immobilization by ferric (Fe(III)) oxides, reduction by sulfide, and the less-explored competitive adsorption with other anions such as phosphate (PO 4 3− ). Here, this study investigates the interplay between such mechanisms in controlling the behavior of Sb(V) associated with ferrihydrite (Fh) under Fe(III)- and sulfate-reducing conditions, with a particular emphasis on the role of phosphate in influencing Sb(V) mobility and transformation. Anoxic reactors that contained Sb(V)-coprecipitated Fh, varying PO 4 3− concentrations (0, 0.2, and 2 mM), and sulfate, were inoculated with a microbial community sourced from Sb-contaminated soil. Additionally, abiotic reactors with either Sb(V)-adsorbed or Sb(V)-coprecipitated Fh and different PO 4 3− loadings (0–100 mM) were created to investigate the competitive adsorption mechanisms in the absence of microbial activity. Results from the abiotic reactors suggest that Sb(V) is likely incorporated into the Fh structure, with only minor amounts remaining surface-bound and extractable by PO 4 3− . In the biotic reactors, microbial Fe(III) and sulfate reduction were more extensive in the presence of PO 4 3− . At 0.2 mM PO 4 3− , microbial activity transformed Fh into siderite and led to the complete reduction of Sb(V) to Sb(III) as stibnite (Sb 2 S 3 ). At 2 mM PO 4 3− , the greater coverage by PO 4 3− stabilized Fh and decreased the extent of both Fe(III) and Sb(V) reduction, and shifted the reduced products to mackinawite and Sb(III) adsorbed onto Fh, in addition to stibnite formation. This study demonstrates that while PO 4 3− may not directly compete with Sb(V) for sorption sites, it can influence Sb mobility in Fe(III)- and sulfate-reducing environments by enhancing microbial activity and altering the mineralization pathways.

Microbial Fe(III) and sulfate reduction↗
DOE OSTI2026

The effectiveness of D 2 pellet and gas injection in reducing intra-ELM tungsten erosion and heat flux in the DIII-D small angle slot divertor

Edge localized modes (ELMs) in H-mode plasmas can melt and erode plasma-facing components (PFCs) and lead to impurities in the core, reducing confinement. This study analyzes the use of D 2 pellet and gas injection for ELM mitigation on the DIII-D tokamak during the 2022 Small Angle Slot V-shaped Tungsten (W) (SAS-VW) divertor campaign, reducing W erosion and heat flux during ELMs. D α (656 nm) and WI (400.9 nm) filterscopes and Langmuir probes provide photon emission and electron density/temperature to estimate W atom erosion using the S/XB method, while surface eroding thermocouples measured ELM peak heat flux at the outer strike point (OSP). Thomson Scattering measurements of pedestal T e and n e provided input to predict W divertor erosion and heat flux during ELMs via the Free-Streaming plus Recycling Model (FSRM). While a greater D 2 mass injection rate decreased the ELM peak heat flux, the impact on W erosion was not monotonic. The average ‘large’ intra-ELM W erosion was lower for plasma shots with D 2 mass injection compared to the plasma shots without any D 2 mass injection in the SAS-VW divertor. However, plasma shots did not see significant changes in ‘large’ intra-ELM W divertor erosion as the D 2 mass injection rate increased. On average, the FSRM overestimated SAS-VW experimental intra-ELM W erosion by a factor of 6.9, but the overestimation is reduced to a factor of 3.6 with the implication of C deposition effects. Generally, experimentally measured and predicted quantities were worse for plasma shots with a lower D 2 mass injection rate and corresponding higher plasma carbon (C) impurity percentage (f C ). The discrepancies are postulated to be due to C/W material mixing, for which a simple analytic mixed-material model is presented. These results highlight the importance of incorporating and improving the robustness of a mixed-material layer model in the analysis of PFC erosion on present and future tokamak devices.

Carbon (C)↗
DOE OSTI2026

Oxidation of biogenic U(IV) mediated by iron-bearing clay minerals, iron-reducing bacteria, and organic ligands

Bioreduction of hexavalent uranium (U(VI)) to tetravalent uranium (U(IV)) by dissimilatory metal-reducing bacteria (DMRB) is considered an effective strategy for uranium immobilization in contaminated environments. However, U(IV) can be reoxidized to U(VI) under fluctuating redox conditions and remobilized. This work investigates the oxidation behavior of biogenic U(IV) in the presence of bioreduced iron-bearing clay minerals (rNAu-2), iron-reducing bacteria (Shewanella putrefaciens CN32), and organic ligands (ethylenediaminetetraacetic acid (EDTA) and citrate). Results demonstrate that the presence of CN32 significantly inhibits U(IV) oxidation. rNAu-2 exerted a context-dependent influence on U(IV) oxidation: its effect was masked by bicarbonate-promoted U(VI) mobilization in the absence of active CN32, but became detectable when CN32-mediated microbial protection slowed U(IV) oxidation. EDTA and citrate markedly accelerate U(IV) oxidation via formation of soluble U(IV)-ligand complexes, changing U(IV) redox potentials, and by promoting clay mineral dissolution that enhances Fe(II)/Fe(III) redox cycling. Collectively, our findings constrain the roles that clay minerals, iron-reducing bacteria, and organic ligands play in governing U(IV) stability, emphasizing the need to account for these factors in developing robust bioremediation strategies.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2024

Electrochemically Assisted Single Crystal Growth of Reduced Preyssler Polyoxometalates Decorated with M 2+ ( M = Co, Ni) and Cubane–Like Ni 4 O 4 Units

Polyoxometalates (POMs) are of great interest to the scientific community, and their reduction and nucleation have been well–established by multi–step techniques. The present study develops an electrochemical approach for simultaneous reduction and nucleation of polyoxometalate–containing solids. Herein we report crystal growth of reduced Preyssler polyoxotungstate–based (anionic formula [NaP 5 W 30 O 110 ] 14– ) new crystalline solids made of Preyssler anions interlinked by Co 2+ and Ni 2+ ions. Crystal nucleation and in situ reduction were achieved at room temperature using a two silver wire electrode setup in various aqueous solutions under constant applied potentials. The POM material was deposited on the cathode, and its structure was characterized by X–ray diffraction techniques. The primary structure type observed involves POMs decorated by disordered Co 2+ /Ni 2+ octahedra and fused into 1–D pillars by additional Co 2+ /Ni 2+ octahedra. Additionally, a secondary phase was observed in the Ni–based reactions, where reduced Preyssler anions are decorated by Ni 4 O 4 cubane–like units. To understand the electrochemical process, polarization curves of the electrolyte solutions are presented, suggesting an applied potential best suited for crystal growth. The work highlights the effectiveness of an electrochemical pathway where nucleation and simultaneous reduction of POMs can make novel reduced POM solids.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Unravelling Adsorbate-Metal-Oxide Interactions: Water Vapor Chemistry on the Growth and Sintering of Ni over Reducible CeO2(111) Thin Films

The role of water in the growth and sintering of Ni particles over well-ordered CeOx(111) (1.5 < x < 2) thin films was investigated through scanning tunneling microscopy (STM) and X-ray photoelectron spectroscopy (XPS) studies, considering ceria-supported Ni attracts great attention as a promising catalyst for reactions such as steam reforming of ethanol and water gas shift reaction, in which water vapor is used as a key reactant. In the study, both fully oxidized CeO2 and partially reduced CeO1.75 thin films were prepared to examine the effect of the oxygen vacancies/Ce3+ sites in ceria supports. Our STM results revealed that dosing water before or after Ni deposition over the CeOx(111) surfaces at room temperature influenced the sintering behavior of Ni nanoparticles with further heating. Exposure of water to Ni nanoparticles that were deposited over both CeO2 and CeO1.75 at 300 K causes the formation of flatter particles with significantly reduced height when heating to the same temperatures compared to Ni/ceria with no water adsorbates. The flatter Ni particles were also observed when water was first dosed over CeO2 at 300 K followed by Ni deposition at room temperature and further heating. Over a partially reduced CeO1.75 surface with predosed water at 300 K, there is an extensive decrease in the particle density upon subsequent Ni deposition at room temperature and a significant increase in the height for Ni nanoparticles with further heating to higher temperatures compared to Ni over a pristine CeO1.75 surface. This is due to the filling of oxygen vacancies caused by the dissociation of water. This creates fewer nucleation sites for Ni on ceria, weakening the metal-oxide interaction and causing significant metal sintering. Our experimental findings suggest distinct adsorbate-metal-oxide interactions are key to the tuning of sintering of Ni nanoparticles over the CeOx(111) surface caused by water exposure. Such interactions are essential for the further modification of Ni-based catalysts for improved reactivity and stability.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Nanoscopic Structure of the Interface between Reduced TiO 2– x (110) and Water Vapor

We investigate the interaction between a reduced rutile TiO 2–x (110)-(1×4) surface and water vapor at ambient pressures using atomic force microscopy and X-ray photoelectron spectroscopy (AP-AFM and AP-XPS). Our results reveal that water molecules strongly interact with the reduced surface, leading to hydroxylation and localized clustering of water molecules. In defect-rich regions, AFM tip-induced restructuring causes removal of the topmost surface layer, highlighting the lowered cohesive energy of the surface atoms upon hydroxylation. These findings provide new insights into the water adsorption and restructuring mechanisms on reducible transition metal oxides, relevant for catalytic and environmental applications.

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

Is the Matrix Completion of Reduced Density Matrices Unique?

Reduced density matrices are central to describing observables in many-body quantum systems. In electronic structure theory, the two-particle reduced density matrix (2-RDM) suffices to determine the energy and other key properties. Recent work has used matrix completion, leveraging the low-rank structure of RDMs and approximate theoretical models, to reconstruct the 2-RDM from partial data and thus reduce the computational cost. However, matrix completion is, in general, an under-determined problem. Revisiting Rosina’s theorem (Rosina, M. Queen’s Papers on Pure and Applied Mathematics , 1968, No. 11, 369), we here show that the matrix completion is unique under certain conditions, identifying the subset of 2-RDM elements that enables its exact reconstruction from incomplete information. Building on this, we introduce a hybrid quantum–stochastic algorithm that achieves exact matrix completion, demonstrated through applications to the Fermi–Hubbard model.

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

Formation of Bimetallic Nanoparticles via Exsolution Using a Reducible Metal Oxide Capping Layer

Bimetallic nanoparticles are promising catalysts that can improve performance in heterogeneous catalysis and solid-state electrochemistry. Exsolution is a useful method for forming such nanoparticles; however, it is limited by the elements present within the host oxide lattice. Here, in this work, we develop and demonstrate a strategy to form bimetallic particles from La 0.5 Sr 0.5 Ti 0.94 Ni 0.06 O 3 (LSTN) exsolution and using a reducible SnO 2 capping layer, expanding the range of elements available for bimetallic nanoparticle formation. Using this capping layer strategy, we formed nickel–tin (Ni 0 –Sn 0 ) bimetallic nanoparticles via exsolution. We used in situ near-ambient pressure X-ray photoelectron spectroscopy to monitor surface chemical changes during exsolution, showing that first, SnO 2 volatilized. This SnO 2 loss exposed the perovskite surface of LSTN to reducing conditions, which induced Ni exsolution, and compounded with SnO 2 reduction led to the formation of bimetallic Ni 0 –Sn 0 particles. To evaluate the associated microstructural evolution, we measured grazing incidence small-angle X-ray scattering (GISAXS), which confirmed the loss of the SnO 2 capping layer, and scattering simulations suggested the formation of bimetallic particles. We confirmed the bimetallic nanoparticle composition and morphology by Auger spectroscopy and scanning transmission electron microscopy. The resulting bimetallic nanoparticles were smaller and more thermally stable than the monometallic Ni counterparts on LSTN. This capping layer and exsolution approach allow synthesizing multimetallic nanoparticles and can be applied to other reducible metal oxides and perovskite hosts, broadening the compositional space for advanced catalytic materials.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Can Restoring Tidal Wetlands Reduce Estuarine Nuisance Flooding of Coasts Under Future Sea‐Level Rise?

Wetland restoration is an increasingly popular nature‐based method for flood risk mitigation in coastal communities. In this study, we present a novel method using hydrodynamic modeling and harmonic analysis to quantify wetlands' ability to reduce future nuisance flooding. The method leverages a hydrodynamic model calibrated to present day data and was run for a range of future sea‐level rise (SLR) and wetland restoration scenarios to quantify changes to tidal harmonic amplitudes and phases. The harmonic constituents are used to generate water surface elevations over a time period of interest (e.g., one year) and compared to critical exceedance thresholds such as levee elevations. Then, changes to nuisance flooding are calculated by counting the number of hours critical thresholds are exceeded under different SLR and wetland restoration scenarios. We applied the method to Coos Bay, Oregon, USA as a test case. We found restoration reduces the number of hours nuisance flooding occurs in downtown Coos Bay from 15 hr (present day conditions) to 0 hr (fully restored condition) under median SLR (82 cm by 2100). Restoration had spatially variable impacts on reducing peak flood elevations with minimal impacts near the estuary mouth and greatest impact 32 km inland. The effectiveness of restoration was heavily dependent on future SLR. Restoration was maximally effective in 2050 under all SLR scenarios, less effective in 2100 under median SLR, and not effective under high SLR. Modeling results suggest increased tidal prism and accommodation space are driving restoration‐associated reductions in tidal amplitudes.

Brand, Matthew W. [Louisiana State Univ., Baton Ro↗
DOE OSTI2025

Reducing Long‐Standing Surface Ozone Overestimation in Earth System Modeling by High‐Resolution Simulation and Dry Deposition Improvement

The overestimation of surface ozone concentration in low‐resolution global atmospheric chemistry and climate models has been a long‐standing issue. We first update the ozone dry deposition scheme in both high‐ (0.25°) and low‐resolution (1°) Community Earth System Model (CESM) version 1.3 runs, by adding the effects of leaf area index and correcting the sunlit and shaded fractions of stomatal resistances. With this update, 5‐year‐long summer simulations (2015–2019) using the low‐resolution CESM still exhibit substantial ozone overestimation (by 6.0–16.2 ppbv) over the U.S., Europe, eastern China, and ozone pollution hotspots. The ozone dry deposition scheme is further improved by adjusting the leaf cuticle conductance, reducing the mean ozone bias by 19%, and increasing the model resolution further reduces the ozone overestimation by 43%. We elucidate the mechanism by which model grid spacing influences simulated ozone, revealing distinctive pathways in urban versus rural areas. In rural areas, grid spacing mainly affects daytime ozone levels, where additional NO x emissions from nearby urban areas result in an ozone boost and overestimation in low‐resolution simulations. In contrast, over urban areas, daytime ozone overestimation follows a similar mechanism due to the influence of volatile organic compounds from surrounding rural areas. However, nighttime ozone overestimation is closely linked to weakened NO titration owing to the redistribution of urban NO x to rural areas. Additionally, stratosphere‐troposphere exchange may also contribute to reducing ozone bias in high‐resolution simulations, warranting further investigation. This optimized high‐resolution CESM may enhance understanding of ozone formation mechanisms, sources, and changes in a warming climate.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Thermal Adaptation of Enzyme‐Mediated Processes Reduces Simulated Soil CO2 Fluxes Upon Soil Warming

Abstract Understanding factors influencing carbon effluxes from soils to the atmosphere is important in a world experiencing climatic change. Two important uncertainties related to soil organic carbon (SOC) stock responses to a changing climate are (a) whether soil microbial communities acclimate or adapt to changes in soil temperature and (b) how to represent this process in SOC models. To further explore these issues, we included thermal adaptation of enzyme‐mediated processes in a mechanistic SOC model (ReSOM) using the macromolecular rate theory. Thermal adaptation is defined here to encompass all potential responses of soil microbes and microbial communities following a change in temperature. To assess the effects of thermal adaptation of enzyme‐mediated processes on simulated SOC losses, ReSOM was applied to data collected from a 13‐year soil warming experiment. Results show that a model omitting thermal adaptation of enzyme‐mediated processes substantially overestimates observed CO 2 effluxes during the initial years of soil warming. The bias against observed CO 2 effluxes was lower for models including thermal adaptation of enzyme‐mediated processes. In addition, for a simulated linear 3°C soil warming over 100 years, models including thermal adaptation of enzyme‐mediated processes simulated SOC losses of a factor of three smaller than models omitting this process. As thermal adaptation of microbial community characteristics is generally not included in models simulating feedback between the soil, biosphere and atmosphere, we encourage future studies to assess the potential impact that microbial adaptation has on soil carbon – climate feedback representations in models. Plain Language Summary A major uncertainty in projecting how much soil organic carbon (SOC) will be converted to CO 2 as a consequence of climate change is related to how soil microbes may adapt to increasing soil temperatures. While this “microbial thermal adaptation” has been shown to occur in short‐term lab incubation experiments, its effect on SOC cycling on a decadal timescale is not clear. To address this knowledge gap, a mechanistic SOC model was used to simulate data collected from a 13‐year soil warming experiment, to assess how microbial thermal adaptation affects predicted SOC losses upon soil warming. The model results show that incorporating microbial thermal adaptation into the model led to reduced CO 2 effluxes from the soil to the atmosphere compared to the common approach of omitting this mechanism. Our results imply that projected SOC losses for the decades to come may be reduced when this mechanism is incorporated in land models. We therefore advocate for more research on the mechanisms controlling microbial thermal adaptation, and how to implement this mechanism in SOC models. Key Points A crucial aspect of soil organic carbon (SOC) models is the representation of soil microbes Predicted soil CO 2 fluxes upon soil warming are reduced when accounting for microbial thermal adaptation On a centennial time scale, this thermal adaptation results in up to a factor of three lower predicted SOC loss

Van de Broek, Marijn↗
DOE OSTI2024

Potential of artificial intelligence in reducing energy and carbon emissions of commercial buildings at scale

Artificial intelligence has emerged as a technology to enhance productivity and improve life quality. However, its role in building energy efficiency and carbon emission reduction has not been systematically studied. This study evaluated artificial intelligence’s potential in the building sector, focusing on medium office buildings in the United States. A methodology was developed to assess and quantify potential emissions reductions. Key areas identified were equipment, occupancy influence, control and operation, and design and construction. Six scenarios were used to estimate energy and emissions savings across representative climate zones. Here we show that artificial intelligence could reduce cost premiums, enhancing high energy efficiency and net zero building penetration. Adopting artificial intelligence could reduce energy consumption and carbon emissions by approximately 8% to 19% in 2050. Combining with energy policy and low-carbon power generation could approximately reduce energy consumption by 40% and carbon emissions by 90% compared to business-as-usual scenarios in 2050.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗