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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 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Observation of laser ablation of silicon as a function of pulse length at constant fluence via time-resolved x-ray spectroscopy

We investigate the ablation of silicon as a function of laser pulse length at a constant fluence using time-resolved x-ray spectroscopy data obtained from OMEGA EP experiments at the University of Rochester's Laboratory for Laser Energetics. Our targets consisted of three-layer planar structures composed of Si (50 μm), Cu (25 μm), and SiO 2 (500 μm) layers. The Si layer was irradiated by a 351-nm laser with varying pulse widths of 250 ps, 500 ps, 1 ns, and 10 ns while maintaining a constant fluence of ~27.9 kJ/cm 2 . Electron temperatures and densities of the ablated plasma were determined by analyzing the time-resolved x-ray spectroscopy data through a comparison of experimental measurements with synthetic results obtained from Si atomic calculations in a steady state and non-local thermodynamic equilibrium. These calculations were computed using PrismSPECT. Additionally, radiation-hydrodynamics simulations with FLASH are used to generate simulated plasma-density and plasma-temperature profiles, which are then compared with the experimental measurements. Our analyses reveal that increasing the laser pulse length at a constant fluence results in a decrease in electron temperatures and densities. Furthermore, the longer pulses with lower intensities lead to deeper ablation regions before reaching the peak ablation but lower ionization balances in the silicon layer. Furthermore, these findings emphasize the critical role of laser pulse length in plasma ablation and shock generation for laser-impulse studies.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Effect of workpiece curvature on the tool influence function during hemispherical sub-aperture tool glass polishing

The influence of workpiece curvature on the tool influence function spot during polishing of fused silica glass with cerium oxide slurry, while using a rotating hemispherical pad-foam tool for a wide variety of process conditions (tool displacement, inclination angle, and rotation rate), has been investigated. (Workpiece curvature ranged from 500 mm radius concave to 43 mm radius convex.) The TIF spot decreases in diameter and increases in the peak removal rate on more convex workpieces. In contrast, the TIF spot increases both in diameter and peak removal rate on more concave workpieces. For the range of workpiece curvatures investigated, both the spot size and the peak removal rate changed significantly, as much as 2 times. An elastic sphere–sphere contact mechanics model, which utilizes both a modified displacement (that leads to a change in the applied load) as well as a mismatch factor (that influences the pressure distribution shape), has been developed. Furthermore, the model was validated using both offline load-displacement measurements and finite-element analysis simulations. The model quantitatively describes the measured change in the relative contact diameter and relative pressure distribution, as well as semiquantitively describes the change in the relative volumetric removal rate on a large variety of TIF spots. The change in the volumetric removal rate for convex workpieces is a result of the balance between a decreasing spot size (reducing removal) and an increasing peak pressure (increasing removal), which usually results in relatively small changes in volumetric removal. In the case of concave workpieces, the volumetric removal rate change is also governed by a similar balance, but the spot size increase contribution dominates, resulting in a significant increase in volumetric removal rate. Understanding these trends can enable methods to add greater determinism during the fabrication of freeform optics by adjusting polishing parameters (such as dwell time) while the tool translates along a workpiece surface with different local curvatures.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Grid-Integrated Production of Fischer-Tropsch Synfuels from Nuclear Power

Idaho National Laboratory (INL) investigates the relative economic profitability of an integrated energy system (IES) coupling an NPP with a synfuel production process at selected case study locations across the United States. In the synfuel IES, a high-temperature steam electrolysis (HTSE) plant is thermally and electrically coupled with an NPP to produce zero-carbon hydrogen. The synthetic fuel is produced from this H 2 combined with a CO 2 supply using the reverse water gas shift process followed by the Fischer-Tropsch (FT) reaction. This analysis considers a system in which the CO 2 is sourced from regional CO 2 emitters via the construction and operation of pipeline-based CO 2 supply networks. Locating the FT plant at the same site as the NPP and HTSE plants enables the NPP to provide zero-carbon heat and power to the HTSE plant and zero-carbon power to the FT plant as well as avoid the requirement for long-distance H 2 product transport from the HTSE plant to the FT plant. Hydrogen storage is used to enable the NPP to dispatch power to the electrical grid (instead of the HTSE plant) when grid demand increases, thus enabling the FT plant to continue to operate in a steady-state production mode. The ability to cease hydrogen production for several hours within each day enables the NPP to provide power to the grid to balance the electricity market during peak periods and maximize revenues for the nuclear synfuel IES. The FT process design considered has a 99% carbon conversion efficiency. The use of nuclear energy and nuclear energy-derived hydrogen enables synfuel production to achieve this high level of carbon utilization. Additionally, the life-cycle carbon emissions of the nuclear-based synfuel production process are very low, with WTW emissions of approximately 25 gCO 2 e/MJ, including steam credits (generated from FT process excess heat), and approximately 7 gCO 2 e/MJ, if steam credits are excluded. This compares favorably with the WTW emissions of 90.5 gCO 2 e/MJ for a compression-ignition, direct injection (CIDI) vehicle with a fuel economy of 31.6 miles per gallon gasoline equivalent (MPGGE), using low-sulfur diesel produced using conventional petroleum production and refining processes. Several NPPs in various regions of the U.S. are considered as case study analyses. Supply locations and transportation via pipeline of the CO 2 feedstock to the NPP site are analyzed through the National Energy Technology Laboratory (NETL) CO 2 Transport Cost model. The team finds that the amount of CO 2 generated by different sectors is sufficient for the synfuel production process at all locations considered. The CO 2 transportation costs are functions of the distance of the source to the NPP location, the CO 2 capture cost at the source, and the quantity of CO 2 transported. Historical electricity prices for the NPP case study locations are collected and analyzed. Monthly average prices, price range, and duration of negative-price periods vary among these locations. For each location, an auto-regressive moving average (ARMA) model is trained on historical electricity price data. ARMA validation is done to ensure the synthetic price distributions represent one of historical prices with high fidelity. Synthetic time series from these ARMA models are used in a coupled dispatch and system optimization in the Holistic Energy Resource Optimization Network (HERON) to compute the differential net present value (NPV) of the IES. The team finds that this econometric is positive, ranging from $14M–1.3bn (2020) depending on the location. The optimal synfuel IES configuration to obtain this increase in NPV often maximizes the size of the synfuel production process with regards to the size of the NPP. However, the team shows that the NPP still plays a stabilizing role for the grid: In periods of high prices and high loads, more electricity from the NPP is sent to the grid. A high variability of electricity prices and extreme maximum prices tend to drive up electricity production. While it requires significant investment, the synfuel IES could increase the economic profitability for the existing fleet of LWRs across the country while still maintaining the grid stabilizer role of NPPs. During its lifetime, the main costs for the nuclear synfuel IES are the carbon feedstock transportation costs, followed by the capital expenses (CAPEX) and operation and maintenance (O&M) costs while the revenue comes first from the IRA H 2 production tax credit (PTC) and then from the sales of synfuel products. The profitability of the synfuel IES is most sensitive to the value of the hydrogen PTC and the synfuel products as well as the cost of the carbon feedstock, highlighting the importance of governmental incentives regarding hydrogen, carbon emissions, and synfuel in driving the deployment of future nuclear synfuel IESs.

08 HYDROGEN↗
DOE OSTI2021

Research and Development of a Ventilation-Integrated Comfort System

From an indoor air quality perspective, the best residential ventilation strategies include filtering outdoor air and distributing that air to all occupied parts of a home. From an energy standpoint, it is desirable that energy be transferred from the exhaust air to the incoming outdoor air to limit heating and cooling impacts. Heat or energy recovery ventilators (HRVs or ERVs) can provide these functions, but researchers have seen many poor installations related to design, installation, and operation and maintenance. More robust ventilation systems may involve an ERV with a dedicated duct distribution system and controls. Such a duct system can be costly to install, and many builders reduce these costs by connecting an ERV to a central heating and cooling duct system. Although this can sometimes be done effectively, researchers have seen consistent challenges with low, inconsistent, or imbalanced flow rates; high electricity consumption; and—of greatest concern—outdoor air short-circuiting or not being delivered to occupied spaces at all. Most ERVs are designed to operate with their own duct system; they are not designed as an add-on to much larger heating, ventilating, and air-conditioning (HVAC) systems. The ventilation-integrated comfort system (VICS) is expressly designed to integrate with low-capacity, efficient, ducted heating and cooling systems. Overall, the latest VICS prototype consumed 40–75 watts (W), including the air handler power, to deliver 50–120 cfm of whole-dwelling ventilation. The large, cross-flow ERV core performed to match manufacturer values (73% winter sensible effectiveness, 64% summer total effectiveness), but further improvements are possible. The VICS system researched and tested during this project will provide efficient, controllable, balanced energy recovery ventilation that is integrated with heating and cooling systems. The integration reduces space and ductwork needed for separate ventilation systems, and there are no compromises to heating, cooling, or ventilation performance. The integrated nature of the device also reduces risks for improper installation and commissioning. Even when using the air handler blower to distribute outdoor air, the total power consumption is lower than that of most available ERV products in the same airflow range. This system has the potential to offer very high-performance ventilation with much smoother and simpler installation than conventional systems.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Filtering, averaging, and scale dependency in homogeneous variable density turbulence

We investigate relationships between statistics obtained from filtering and from ensemble or Reynolds-averaging turbulence flow fields as a function of length scale. Generalized central moments in the filtering approach are expressed as inner products of generalized fluctuating quantities, q ' ( ξ , x ) = q ( ξ ) - q ¯ ( x ) , representing fluctuations of a field q ( ξ ) , at any point ξ, with respect to its filtered value at x. For positive-definite filter kernels, these expressions provide a scale-resolving framework, with statistics and realizability conditions at any length scale. In the small-scale limit, scale-resolving statistics become zero. In the large-scale limit, scale-resolving statistics and realizability conditions are the same as in the Reynolds-averaged description. Using direct numerical simulations (DNS) of homogeneous variable density turbulence, we diagnose Reynolds stresses, T i j , resolved kinetic energy, kr, turbulent mass-flux velocity, a i , and density-specific volume covariance, b, defined in the scale-resolving framework. These variables, and terms in their governing equations, vary smoothly between zero and their Reynolds-averaged definitions at the small and large scale limits, respectively. At intermediate scales, the governing equations exhibit interactions between terms that are not active in the Reynolds-averaged limit. For example, in the Reynolds-averaged limit, b follows a decaying process driven by a destruction term; at intermediate length scales, it is a balance between production, redistribution, destruction, and transport, where b grows as the density spectrum develops and then decays when mixing becomes strong enough. This work supports the notion of a generalized, length-scale adaptive model that converges to DNS at high resolutions and to Reynolds-averaged statistics at coarse resolutions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Exploiting bacterial effector proteins to uncover evolutionarily conserved antiviral host machinery

Arboviruses are a diverse group of insect-transmitted pathogens that pose global public health challenges. Identifying evolutionarily conserved host factors that combat arbovirus replication in disparate eukaryotic hosts is important as they may tip the balance between productive and abortive viral replication, and thus determine virus host range. Here, we exploit naturally abortive arbovirus infections that we identified in lepidopteran cells and use bacterial effector proteins to uncover host factors restricting arbovirus replication. Bacterial effectors are proteins secreted by pathogenic bacteria into eukaryotic hosts cells that can inhibit antimicrobial defenses. Since bacteria and viruses can encounter common host defenses, we hypothesized that some bacterial effectors may inhibit host factors that restrict arbovirus replication in lepidopteran cells. Thus, we used bacterial effectors as molecular tools to identify host factors that restrict four distinct arboviruses in lepidopteran cells. By screening 210 effectors encoded by seven different bacterial pathogens, we identify several effectors that individually rescue the replication of all four arboviruses. We show that these effectors encode diverse enzymatic activities that are required to break arbovirus restriction. We further characterize Shigella flexneri-encoded IpaH4 as an E3 ubiquitin ligase that directly ubiquitinates two evolutionarily conserved proteins, SHOC2 and PSMC1, promoting their degradation in insect and human cells. We show that depletion of either SHOC2 or PSMC1 in insect or human cells promotes arbovirus replication, indicating that these are ancient virus restriction factors conserved across invertebrate and vertebrate hosts. Collectively, our study reveals a novel pathogen-guided approach to identify conserved antimicrobial machinery, new effector functions, and conserved roles for SHOC2 and PSMC1 in virus restriction.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Understanding how minority relativistic electron populations may dominate charge state balance and radiative cooling of a post-thermal quench tokamak plasma

Minority relativistic electron populations can occur in a range of complex plasmas. Of specific interest is when runaway electrons form among the presence of high-atomic-number ion species in a tokamak plasma discharge. It has been recently demonstrated that ion charge state distributions and radiation losses at low bulk electron temperatures can be dominated by relativistic electrons, even though their density is orders of magnitude lower. Furthermore, this was attributed to the relativistic enhancement of electron impact inelastic cross sections. In this work, we provide a closer inspection of the atomic physics underpinning this effect. We also demonstrate the consequences of runaway enhanced scattering on post-disruption tokamak fusion discharges with neon and argon impurities present. Effects on charge state distributions, radiation and spectral characteristics, and reduced-order modeling considerations are discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Synergistic double-atom catalysts of metal-boron anchored on g-C 2 N for electrochemical nitrogen reduction: Mechanistic insight and catalyst screening

The rational design of a novel catalytic center with a sound basis remains both challenging and rewarding for the electrochemical reduction of N 2 (eNRR), which has provided a feasible route for achieving clean and sustainable NH 3 production under ambient conditions. Herein, using density functional theory calculations, we demonstrate that hybrid metal (M)-boron (B) double-atom catalysts (DACs) embedded in g-C 2 N substrate (M-B@C 2 N, M = 3d, 4d and 5d transition metals) can achieve both high catalytic activity and high selectivity in eNRR. The proposed M-B@C 2 N DACs have exhibited impressive feasibility and stability thanks to the resilient and robust C 2 N substrate with abundant pyridinic N atoms distributed among right-sized pore structures. Our results reveal that like the metal center, the embedded B atom can actively involve in Ntriple bondN bond activation via π*-backdonation mechanism concomitant with the substantial charge transfer to adsorbed *N 2 , leading to sizable Nsingle bondN bond elongation. Accordingly, both adsorption energy and Nsingle bondN bond length of *N 2 can be employed as catalytic descriptors for predicting eNRR activity in terms of the limiting potentials (UL). Using high-throughput screening method, we found that six M-B@C 2 N candidates have stood out as the outstanding electrocatalysts for driving eNRR, namely, M = Ti (U L = 0 V), Mo (U L = 0 V), Nb (U L = -0.04 V), W (U L = -0.23 V), Zr (U L = -0.26 V), V (U L = -0.28 V). The underlying origin is attributed to the balanced and constrained N-affinity of M-B dual site working in synergy, which can thus be used as one important guide of catalyst design.

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

Finding the order in complexity: The electronic structure of 14-1-11 zintl compounds

Yb 14 MnSb 11 and Yb 14 MgSb 11 have rapidly risen to prominence as high-performing p-type thermoelectric materials. However, the fairly complex crystal structure of A 14 MX 11 Zintl compounds renders the interpretation of the electronic band structure obscure, making it difficult to chemically guide band engineering and optimization efforts. In this work, we delineate the valence-balanced Zintl chemistry of A 14 MX 11 compounds using the molecular orbital theory. By analyzing the electronic band structures of Yb 14 MgSb 11 and Yb 14 AlSb 11 , we show that the conduction band minimum is composed of either an antibonding molecular orbital originating from the (Sb 3 ) 7– trimer or a mix of atomic orbitals of A, M, and X. The singly degenerate valence band is comprised of non-bonding Sb pz orbitals primarily from the Sb atoms in the (MSb 4 ) m– tetrahedra and of isolated Sb atoms distributed throughout the unit cell. Such a chemical understanding of the electronic structure enables strategies to engineer electronic properties (e.g., the bandgap) of A 14 MX 11 compounds.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Microbial community diversity changes during voltage reversal repair in a 12-unit microbial fuel cell

Microbial fuel cell stacks (MFC-Stack) are often confronted with voltage reversals, likely due to an interplay between microbial community dynamics and insufficient electric circuit balancing. Herein, we provide new insight into voltage reversals by examining the microbiomes of twelve MFC units of a 12-liter Pilot-MFC-Stack during repair. Different biofilm repair methods (self-healing, electrostimulation, and re-acclimatization upon cross-inoculation) were used to evaluate the microbial community response. In addition, MFC-Stack simulation was performed based on Kirchhoff’s Second Law to predict values for source potentials and post-evaluate internal resistances. Analysis of the 16S rRNA amplicon sequencing data suggests that the biofilm repair methods could slowly heal damaged biofilms. Notably, severely voltage reversed MFC units had low electrogen relative abundances (18%) and positive anode potentials, while strong bioanodes and contained more than 50% electrogens and had negative anode potentials. Between-community analyses (beta diversity ordination and multinomial regression) of the voltage reversed MFC units revealed differences among biofilms in contrast to healthy/strong MFC units. Permutational multivariate analysis of variance (PERMANOVA) confirmed that reversed biofilms were, indeed, significantly (p < 0.05) different from stronger ones. Overall, these analyses demonstrated the utility of combining electrotechnical and microbial community analyses, especially beta diversity ordination and multinomial regression, to understand problematic MFC units and the potential success of a biofilm repair method. Finally, thicker biofilms were usually healthier and stronger, although thickness was no guarantee for proper structure and power function as all factors were interdependent. There was an evolutionary trend that strong anodes became stronger/healthier and others weaker. This spontaneous trend has to be considered to avoid irreversible voltage reversals and to repair electrogenic biofilms in an MFC-Stack.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Site-Differentiated Iron–Sulfur Cluster Ligation Affects Flavin-Based Electron Bifurcation Activity

Electron bifurcation is an elegant mechanism of biological energy conversion that effectively couples three different physiologically relevant substrates. As such, enzymes that perform this function often play critical roles in modulating cellular redox metabolism. One such enzyme is NADH-dependent reduced-ferredoxin: NADP+ oxidoreductase (NfnSL), which couples the thermodynamically favorable reduction of NAD+ to drive the unfavorable reduction of ferredoxin from NADPH. The interaction of NfnSL with its substrates is constrained to strict stoichiometric conditions, which ensures minimal energy losses from non-productive intramolecular electron transfer reactions. However, the determinants for this are not well understood. One curious feature of NfnSL is that both initial acceptors of bifurcated electrons are unique iron–sulfur (FeS) clusters containing one non-cysteinyl ligand each. The biochemical impact and mechanistic roles of site-differentiated FeS ligands are enigmatic, despite their incidence in many redox active enzymes. Herein, we describe the biochemical study of wild-type NfnSL and a variant in which one of the site-differentiated ligands has been replaced with a cysteine. Results of dye-based steady-state kinetics experiments, substrate-binding measurements, biochemical activity assays, and assessments of electron distribution across the enzyme indicate that this site-differentiated ligand in NfnSL plays a role in maintaining fidelity of the coordinated reactions performed by the two electron transfer pathways. Given the commonality of these cofactors, our findings have broad implications beyond electron bifurcation and mechanistic biochemistry and may inform on means of modulating the redox balance of the cell for targeted metabolic engineering approaches.

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

Ca X ML: Chemistry‐informed machine learning explains mutual changes between protein conformations and calcium ions in calcium‐binding proteins using structural and topological features

Proteins' flexibility is a feature in communicating changes in cell signaling instigated by binding with secondary messengers, such as calcium ions, associated with the coordination of muscle contraction, neurotransmitter release, and gene expression. When binding with the disordered parts of a protein, calcium ions must balance their charge states with the shape of calcium-binding proteins and their versatile pool of partners depending on the circumstances they transmit. Accurately determining the ionic charges of those ions is essential for understanding their role in such processes. However, it is unclear whether the limited experimental data available can be effectively used to train models to accurately predict the charges of calcium-binding protein variants. Here, we developed a chemistry-informed, machine-learning algorithm that implements a game theoretic approach to explain the output of a machine-learning model without the prerequisite of an excessively large database for high-performance prediction of atomic charges. We used the ab initio electronic structure data representing calcium ions and the structures of the disordered segments of calcium-binding peptides with surrounding water molecules to train several explainable models. Network theory was used to extract the topological features of atomic interactions in the structurally complex data dictated by the coordination chemistry of a calcium ion, a potent indicator of its charge state in protein. Our design created a computational tool of Ca X ML, which provided a framework of explainable machine learning model to annotate ionic charges of calcium ions in calcium-binding proteins in response to the chemical changes in an environment. Our framework will provide new insights into protein design for engineering functionality based on the limited size of scientific data in a genome space.

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

The role of AdhE mutations in Thermoanaerobacterium saccharolyticum

ABSTRACT Thermoanaerobacterium saccharolyticum is a thermophilic anaerobic bacterium that natively ferments a variety of hemicellulose substrates to organic acids and alcohols. It has recently been engineered to produce ethanol at high yield and titer; however, it uses a unique metabolic pathway for ethanol production that is poorly characterized. One of the distinctive aspects of this pathway is the presence of acetyl-CoA as an intermediate metabolite. In this organism, acetyl-CoA is converted to ethanol by a bifunctional AdhE enzyme. This enzyme has been a frequent target for mutations, and in many cases, the function of these mutations was unknown. Using a combination of genetic modifications, enzyme assays, and computational analysis, we have developed a better understanding of how mutations in AdhE affect ethanol production in the engineered homoethanologen strain. We identify a set of approximately interchangeable AdhE mutations (G544D, T597K, T597I, and T605I), whose function is to disrupt the activity of the alcohol dehydrogenase (ADH) domain of AdhE. This reduces NADH-linked ADH activity, which dramatically increases ethanol tolerance and changes the overall stoichiometry of acetaldehyde to ethanol conversion. Furthermore, our improved understanding of the function of these AdhE mutations calls into question a proposed feature of AdhE enzymes known as substrate channeling—direct transfer of acetaldehyde between the two domains of the AdhE enzyme. This improved the understanding of the role of AdhE mutations in T. saccharolyticum and provides deeper insights into the function of the unique ethanol production pathway in this organism. IMPORTANCE Many anaerobic bacteria maintain redox equilibrium by producing reduced organic compounds such as ethanol. The final two steps of ethanol production are mediated by a bifunctional enzyme, AdhE, and this enzyme is a frequent target of mutations in strains engineered for increased ethanol production. Paradoxically, these mutations increase ethanol production by eliminating the activity of one domain of the AdhE enzyme (the ADH domain). This provides additional support for a redox-imbalance theory of alcohol tolerance, which challenges the prevailing hypothesis that alcohol tolerance is associated with cell membrane effects.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Magnetocaloric Effect in Lightly‐Doped Fe 5 Si 3 Single Crystals

Abstract Development of promising new materials for above room temperature magnetic cooling applications relies on careful balancing of structure and composition to maximize accessible metastable phases that can drive a strong magnetocaloric effect (MCE). However, the working temperatures of these materials may fall outside of desired application windows. In this work, it is shown that it is possible to control metastable phase stability temperatures of Fe 5 Si 3 through selection of appropriate spin and charge doping. Here, the parent material's desired structure appears only within a narrow temperature range from 1098 to 1303 K. Doping with Mn and P is shown to allow stabilization of the parent's high temperature phase and resulting MCE to room temperature. The structural and magnetic properties, and the magnetocaloric effect of single crystal Fe 4.83 Mn 0.16 Si 2.91 P 0.09 (FMSP) are investigated experimentally and theoretically. A first‐order magneto‐elastic transition is observed at 348 K, where magnetic onset is accompanied by a change in lattice volume without an apparent change in crystal symmetry. Although the trace Mn and P doping are found to decrease the T C , the maximum magnetic entropy change Δ S Max ( T ) and the relative cooling power (RCP) of FMSP are enhanced compared to polycrystalline Fe 5 Si 3 . As a result, an intrinsically broader entropy change over a larger temperature span is generated in the lightly doped single crystal of Fe 5 Si 3 . The magnetic moment of the system is also enhanced. Density functional theory (DFT) calculations are performed to gain microscopic insights into the experimental findings. The results suggest that the hexagonal Fe 5 Si 3 is a new giant room temperature MCE material that is on par with La–Fe–Si and Fe‐Mn‐P‐Si systems.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Assessing the potential of deep learning for protein–ligand docking

The effects of ligand binding on protein structures and their in vivo functions carry numerous implications for modern biomedical research and biotechnology development efforts such as drug discovery. Although several deep learning (DL) methods and benchmarks designed for protein–ligand docking have recently been introduced, so far no previous works have systematically studied the behaviour of the latest docking and structure prediction methods within the broadly applicable context of: (1) using predicted (apo) protein structures for docking (for example, for applicability to new proteins); (2) binding multiple (cofactor) ligands concurrently to a given target protein (for example, for enzyme design); and (3) having no previous knowledge of binding pockets (for example, for generalization to unknown pockets). To enable a deeper understanding of the real-world utility of docking methods, we introduce PoseBench, a comprehensive benchmark for broadly applicable protein–ligand docking. PoseBench enables researchers to rigorously and systematically evaluate DL methods for apo-to-holo protein–ligand docking and protein–ligand structure prediction using both primary ligand and multiligand benchmark datasets, the latter of which we introduce to the DL community. Empirically, using PoseBench, we find that: (1) DL cofolding methods generally outperform comparable conventional and DL docking baseline algorithms, but popular methods such as AlphaFold 3 are still challenged by prediction targets with new protein–ligand binding poses; (2) certain DL cofolding methods are highly sensitive to their input multiple sequence alignments, whereas others are not; and (3) DL methods struggle to strike a balance between structural accuracy and chemical specificity when predicting new or multiligand protein targets.

Morehead, Alex [Lawrence Berkeley National Laborat↗
DOE OSTI2024

Photosynthetic responses to temperature across the tropics: a meta-analytic approach

Background and Aims Tropical forests exchange more carbon dioxide (CO 2 ) with the atmosphere than any other terrestrial biome. Yet, uncertainty in the projected carbon balance over the next century is roughly three times greater for the tropics than other for ecosystems. Our limited knowledge of tropical plant physiological responses, including photosynthetic, to climate change is a substantial source of uncertainty in our ability to forecast the global terrestrial carbon sink. Methods Here, we used a meta-analytic approach, focusing on tropical photosynthetic temperature responses, to address this knowledge gap. Our dataset, gleaned from 18 independent studies, included leaf-level light-saturated photosynthetic (A sat ) temperature responses from 108 woody species, with additional temperature parameters (35 species) and rates (250 species) of both maximum rates of electron transport (J max ) and Rubisco carboxylation (V cmax ). We investigated how these parameters responded to mean annual temperature (MAT), temperature variability, aridity and elevation, as well as also how responses differed among successional strategy, leaf habit and light environment. Key Results Optimum temperatures for A sat (T optA ) and J max (T optJ ) increased with MAT but not for V cmax (T optV ). Although photosynthetic rates were higher for ‘light’ than ‘shaded’ leaves, light conditions did not generate differences in temperature response parameters. T optA did not differ with successional strategy, but early successional species had ~4 °C wider thermal niches than mid/late species. Semi-deciduous species had ~1 °C higher T optA than broadleaf evergreen species. Most global modelling efforts consider all tropical forests as a single ‘broadleaf evergreen’ functional type, but our data show that tropical species with different leaf habits display distinct temperature responses that should be included in modelling efforts. Conclusions This novel research will inform modelling efforts to quantify tropical ecosystem carbon cycling and provide more accurate representations of how these key ecosystems will respond to altered temperature patterns in the face of climate warming.

Carter, Kelsey R. [Oak Ridge National Laboratory (↗
DOE OSTI2024

The Transactive Energy Network Template Metamodel

While transactive energy, which is defined as an allocation of electricity based on dynamically discovered values or prices, has been extensively studied, its uptake and use has been slow. This report describes a tool, the transactive network template, which should hasten the creation and uptake of transactive energy networks. Some basic principles of transactive energy are familiar from existing wholesale electricity markets. Locational prices are calculated today for zones within bulk electric transmission systems. Locational prices differ while accounting for the locational costs of electricity generation and the losses and constraints incurred when electricity is transmitted from generators and distributed to consumers. A transactive energy network might include these transmission zones. However, current research strives to apply transactive energy also in electricity distribution circuits, buildings, and even for individual generating and consuming devices. At the same time, researchers explore how to apply transactive energy in real time during increasingly shorter time intervals. Automated computational agents become necessary as transactive energy becomes applied to smaller circuit zones and at faster dynamic timescales. A transactive energy network is an example of a multi-agent system. Each zone in the network is represented by its transactive agent, which makes decisions for and acts on behalf of a business entity that is responsible for and manages one of the circuit regions. A transactive energy network is also an example of a decentralized, distributed control system. Control decisions and responsibilities are distributed among the network’s transactive agents. The transactive agents are independent; that is, there typically is no centralized authority or oversight function. Instead, transactive agents exchange transactive signals and thereby negotiate the prices and quantities of electricity that they will exchange. Initially, the circuit regions and responsibilities of transactive agents appear to be very dissimilar. Each circuit region may comprise transmission, distribution, or building-level circuits. Each has a unique position and electrical connectivity within the transactive energy network. Each possesses unique assets that either generate or consume electricity, and these (e.g., renewable energy generator, diesel generator, aggregate utility load, building load, space conditioning, refrigerator, etc.) may further differ in their price flexibility and in their strategies for responding to dynamic electricity prices. Given such diversity, an implementer’s first inclination might be to start from scratch to define all these devices and to engineer their seemingly unique interactions. Given that each implementer’s perspective may be narrow within a transactive energy network, it is unlikely that uniquely engineered systems would interact well. This is where the transactive network template is applicable. The transactive network template is a metamodel that has been developed to guide implementers as they configure their own transactive agent within a network of such agents. The object-oriented design of the transactive network template provides basic code object types that may be used and extended by implementers to represent each of the assets in their circuit region. These objects further facilitate the transactive agent’s necessary computations, which are divided among responsibilities to schedule power usage, balance electric supply and demand, and coordinate the exchange of electricity with the other transactive agents. This report addresses the conceptual transactive network template design. Implementers are directed to more formal design documents and reference implementations. A Python™-based1 reference implementation of the transactive network template has been coded, and three implementations have been configured to represent a national laboratory and two university campuses. Version 2 of the transactive node template generalizes the market class and its methods to facilitate multiple, and more diverse market coordination mechanisms than were facilitated by and demonstrated using Version 1. Version 3 includes new Appendix B, which addresses the designs of methods that would make dynamic prices track approved electricity rates. In the future, the author wishes to make the transactive network template more generally applicable to networks that require more accurate power flow. Development of the transactive network template is jointly funded by the U.S. Department of Energy (DOE) Energy Efficiency and Renewable Energy and the DOE Office of Electricity. In late 2015, one of the first projects to be funded by the DOE Grid Laboratory Modernization Laboratory Consortium was the Clean Energy and Transactive Campus project, led by Pacific Northwest National Laboratory. DOE funds were matched by an investment by the Washington Department of Commerce through its Clean Energy Fund. The transactive network template was developed to guide the implementation of transactive energy networks within this project’s scope.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Mechanistic Studies of an Iron-Catalyzed Intermolecular C–H Amination Reaction under Catalytic Conditions and Having a Large KIE

The conversion of C–H bonds into amines by nitrene insertion is an attractive transformation since it is both atom- and step-economical, and provides a direct route to functionalizing hydrocarbons. Using an iron catalyst [{( tBu pyrr) 2 pyr}Fe(OEt 2 )] (1-OEt 2 ) (( tBu pyrr) 2 pyr 2– = 3,5- t Bu 2 -bis(pyrrolyl)pyridine), we recently demonstrated the catalytic conversion of weak C–H bonds into secondary amines using aryl azides as the nitrene source [Zars, E.; Angew. Chem., Int. Ed. 2023, 62, e202311749]. Here, we describe detailed mechanistic studies of this intermolecular C–H amination reaction under catalytic conditions. We find by Variable Time Normalization Analysis (VTNA) that the conversion of xanthene (2-H 2 ) and 2,4,6-trimethyl-phenyl azide ( Me 3) catalyzed by 1-OEt 2 is an overall 3/2 order process, being 1 st order in 2-H 2 and half order in Me 3. A kinetic isotope effect study (KIE) using 2-d 2 results in a significant decrease in the rate (KIE = 61(15)), which clearly implicates the C–H insertion step as rate-determining. Furthermore, treatment of 1-OEt 2 with one equivalent of N 3 -2,6- i Pr 2 –C 6 H 3 yields the mixed-valence C–N coupled product [( tBu pyrr) 2 pyrFe-N═C(2,6 i Pr 2 –Ph)═N-(2,6 i Pr 2 –Ph))Fe tBu pyrrpyr(2-H-pyrr)] (5 iPr ). Quantum chemical calculations confirm the electronic structure of the mixed-valence dimer in 5 iPr and rationalize the Hammett correlation by a delicate balance in the dinuclearization of the catalytically active monomers. Calculations further indicate significant tunneling for the pivotal H atom abstraction by the iron-imidyl complex. Combining all these results allows us to propose a mechanism consisting of imido formation in equilibrium with a radical-coupled diiron system, followed by stepwise C–H insertion via a linear H atom abstraction transition state and subsequent radical rebound.

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