Search NASA⌕ Search

SEARCH · Search NASA

Results for “climbing”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Additively-manufactured Al-0.3Zr-0.2Ce-0.2Cu alloy with high creep resistance and electrical conductivity

Here, a new, solute-lean Al-0.3Zr-0.2Ce-0.2Cu (wt.%) alloy is developed for additive manufacturing that overcomes the classical tradeoff between conductivity and creep resistance. The rapid-cooling-enabled supersaturation of Zr, and its uniform distribution in α-Al matrix, along with formation of submicron (Ce,Cu)-rich intermetallic particles on solidification lead to unusually high creep resistance at 200 °C. Near-zero secondary creep rates are achieved up to the alloy yield stress (YS) of 65 MPa at 200 °C in as-fabricated state. The Zr-solute-induced dislocation-climb suppression mechanism underlying this improvement also restricts dynamic recovery above YS, as noted from appreciable primary creep and its transitioning to near-zero secondary creep rates. A combination of relatively coarse, epitaxially-grown α-Al grains, low Zr concentration in α-Al, and the impurity-scavenging effect of Ce to purify α-Al matrix produces high electrical conductivity of ∼48 %IACS. Aging precipitation of L1 2 -Al 3 Zr nanoprecipitates doubles the YS (to ∼150 MPa) at room temperature and increases alloy conductivity to ∼58 %IACS, but loss of solid-solution Zr out of α-Al matrix leads to activation of dislocation climb, degrading the creep properties as compared to the supersaturated Al-Zr solid solution in the as-fabricated state. Compared to L1 2 -Al 3 Zr nanoprecipitates, submicron (Ce,Cu)-rich particles formed on solidification are more effective at impeding dislocation climb, producing a threshold stress for dislocation creep of ∼ 50 MPa at 200 °C. The new alloy design concepts, especially solute-induced dislocation-climb suppression for creep resistance, explored here may pave way for the design of new metallic alloys for thermal/electrical conductors and other high-temperature applications.

Additive Manufacturing↗
DOE OSTI2025

Demonstrate new plasticity models for doped UO 2 that capture dislocation mechanisms

In light water reactors, fuel vendors are investigating the use of dopants to modify the properties of UO 2 pellets, with the goal of improving pellet-cladding mechanical interactions during operation. Dopants are expected to ‘soften’ the pellets; that is, the doped pellets have higher plastic deformation than conventional UO 2 . This leads to a reduction in the severity of mechanical pellet-cladding interactions, helping to reduce the hoop strain on the cladding. By minimizing the strain exerted by the pellet on the cladding, it is anticipated that cladding performance under accident conditions can be enhanced (i.e., lowering the risk of burst during a LOCA). Dopants such as chromium (Cr) promote grain growth during pellet fabrication, leading to larger grains; therefore, understanding the link between chemistry, microstructure and mechanical deformation (enhanced creep rates) behavior of UO 2 is critical to helping operators further substantiate the benefits of doping UO 2 . Historically, the nuclear energy industry has relied on empirical models to make assessments of performance. Compared to empirical models, mechanistic physics-based models provide benefits, such as, fewer data points for validation and better extrapolation where experimental data is scarce or non-existent. In this report, Bayesian inference techniques have been applied to a previously developed lower length-scale-informed diffusional creep model. The objective is to i) infer lower-length-scale parameter distributions from available experiment and then ii) determine the uncertainties in the measurable quantity (in this case creep rates) after propagating the inferred lower length scale parameter uncertainties. The approach requires many evaluations of the model, which becomes computationally insurmountable; therefore, a neural-network model is trained to data obtained by sampling the full model over the most important parameters. This neural-network is then used in the Bayesian inference approach to determine probability distributions in the parameter values that represent the uncertainty in the model given what is known from the experiments (posterior). A significant reduction compared to conservative initial (prior) uncertainties is achieved through inference against the experimental data, demonstrating the efficacy of this approach. Furthermore, by accounting for uncertainties in the experimental conditions and sample non-stoichiometry, it is possible to resolve apparent discrepancies in experimental measurements within a self-consistent grain boundary (Coble) creep model that is sensitive to chemistry. This work has been written up and submitted to Nuclear Technology for a special issue on accelerated fuel qualification (AFQ). This uncertainty quantification (UQ) work not only improves the diffusional model, while accounting for uncertainty, but also establishes a framework which can readily be applied to the mechanistic models of dislocation deformation developed in this study. The most likely values from the Bayesian analysis are incorporated into our UO 2 diffusional creep model and a lower length scale-informed irradiation UO 2 creep mechanistic model to generate a dataset. This dataset has been provided to our INL collaborators for training an artificial neural network surrogate model, which will be implemented in the BISON fuel performance code to assess how the results differ from those currently obtained using a fully empirical model and that of using the nominal (uncalibrated) atomic scale parameters in our mechanistic model. Plastic deformation (creep and glide) in UO 2 is a complex phenomenon, governed by multiple underlying processes such as local defect concentrations, applied stresses, and microstructural characteristics. Consequently, there is a need for a meso-scale model with polycrystalline resolution capable of extrapolating to large grain sizes applicable to doped UO 2 , where data is limited and the model can help bridge the knowledge gap. By integrating atomistic data into the polycrystal LApx code, it becomes possible to predict dislocation climb and glide plasticity that simple analytical models cannot accurately represent. The application of atomic-scale data within LApx demonstrated the importance of climb and glide mechanisms in reproducing high-stress UO 2 behavior. Behaviors such as this are crucial to capture and implement in BISON, as parts of the fuel pellet can reach temperatures where glide can occur before pellet cracking. This model which captures dislocation based mechanisms for UO 2 is then used to stand up the doped model accounting for larger grain sizes. It was found that larger grain sizes can lead to enhanced deformation rates in the glide regime, and therefore can help with the pellet cladding mechanical interaction. Therefore if the fuel pellet reaches conditions (stress/temperature) where glide is active, the enhanced creep rates for larger grains in the glide regime (doped UO 2 ) can help with pellet cladding mechanical interactions. Plastic deformation in UO 2 involves multiple mechanisms, including diffusional creep, dislocation climb, and glide. This milestone contains two parts: (1) UQ of a pre-existing lower length scale informed mechanistic diffusional creep model, and (2) development of a new LApx based model for dislocation-mediated creep mechanisms in UO 2 , with application to large-grain doped UO 2 .

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Coupled cluster and dislocation dynamics modeling of microstructure evolution in irradiated materials

We develop here a coupled cluster and dislocation dynamics framework to study the microstructure evolution of irradiated materials. The framework not only accounts for the three dimensional diffusion of radiation-generated clusters, but also their interaction with dislocation networks and the resultant climb motion of discrete dislocations within finite crystals. The framework is solved with a superposition solution scheme, and is applied to investigate the evolution of the irradiation-induced dislocation loops in zirconium (Zr), considering the effects of various bias factors including the diffusion anisotropy difference (DAD) of interstitials and interstitial clusters, the dislocation bias of defects to discrete dislocation segments, and the production bias of defects from the radiation cascade. We find that the DAD is the most critical factor influencing the kinetics of the loop evolution in Zr, while the recombination/interaction of mobile defects can induce a strong spatial dependence of the loop evolution together with the DAD. Here, the method is also adopted to study the evolution of interstitial $\langle$a$\rangle$ and vacancy $\langle$c$\rangle$ dislocation loop ensembles consistent with the microstructure observed during irradiation-induced growth of Zr. Our findings not only reveal the spatial dependence of the size and ellipticity of the dislocation loops, but also suggest a limit on the anisotropy factor of interstitials to reproduce the co-growth of $\langle$a$\rangle$ and $\langle$c$\rangle$ loops in zirconium, in good agreement with experimental observations and other simulation results.

Bias factors↗
DOE OSTI2025

Direct Imaging of Hydrogen‐Driven Dislocation and Strain Field Evolution in a Stainless Steel Grain

Hydrogen embrittlement (HE) poses a significant challenge to the durability of materials used in hydrogen production and utilization. Disentangling the competing nanoscale mechanisms driving HE often relies on simulations and electron-transparent sample techniques, limiting experimental insights into hydrogen-induced dislocation behavior in bulk materials. This study employs in situ Bragg coherent X-ray diffraction imaging to track three-dimensional (3D) dislocation and strain field evolution during hydrogen charging in a bulk grain of austenitic 316 stainless steel. Tracking a single dislocation reveals hydrogen-enhanced mobility and relaxation, consistent with dislocation dynamics simulations. Subsequent observations reveal dislocation unpinning and climb processes, likely driven by osmotic forces. Additionally, nanoscale strain analysis around the dislocation core directly measures hydrogen-induced elastic shielding. These findings experimentally validate theoretical predictions and offer mechanistic insights into hydrogen-driven dislocation behavior. The quantified nanoscale phenomena serve as critical inputs for multiscale modeling frameworks to predict bulk material responses and accelerate the development of HE-resistant alloys.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

An energetic link between order and strength in metals: A nanocrystalline strength limit in high-entropy alloys and intermetallic compounds

The metallurgy and materials communities have long understood and exploited fundamental links between chemical and structural ordering in metallic solids to tailor their mechanical properties. We extend these ideas to include prediction of the nanocrystalline strength limit in high-entropy alloys and intermetallic compounds, where a breakdown occurs in the classical Hall-Petch strengthening behavior. The highest reported strength achievable through alloying has rapidly climbed and given rise to new classifications of materials with extraordinary properties, with a notable case being nanocrystalline metals. High-entropy alloys (chemically disordered, concentrated solid solutions) and intermetallic compounds are two boundary cases of how tailored order can be used to manipulate mechanical behavior. Here, we show that the complex electronic-structure mechanisms governing the peak strength of alloys and pure metals can be reduced to a few physically meaningful parameters based on their atomic arrangements and used – with no fitting parameters – to predict the maximum strength of these materials. This includes a generalized energy-based accounting for the degree of structural and chemical ordering that allows for rapid and reasonably accurate prediction of peak strength (validated in the nanocrystalline limit) as a function of temperature. Predictions of maximum strength based on the activation energy (with all materials properties derived from DFT calculations or experiments) for a stress-driven transition to an amorphous state is shown to accurately describe the breakdown in Hall-Petch behavior at the smallest crystallite sizes for pure metals, intermetallic compounds, high-entropy alloys, and metallic glasses. Further, this activation energy is also shown to be directly proportional to interstitial electronic charge density, which is a good predictor of ductility, stiffness (moduli), and phase stability in high-entropy alloys and solid metals generally. The proposed framework suggests the possibility of coupling ordering and intrinsic strength to mechanisms like dislocation nucleation, hydrogen embrittlement, and transport properties, such as through correlations between the activation energies for amorphization with stacking-fault and grain boundary energies. It additionally opens the prospect for greatly accelerated structural materials design and development to address materials challenges limiting more sustainable and efficient use of energy.

36 MATERIALS SCIENCE↗
DOE OSTI2025

High-temperature nanoindentation creep studies on castable and sintered nanostructured low-activation ferritic-martensitic alloys

In this article, we present the creep characteristics of two reduced activation ferritic-martensitic steels of identical starting compositions formed by different fabrication routes: a nanostructured ferritic alloy commonly referred to as a castable nanostructured alloy (CNA) and a sintered nanostructured alloy (SNA) variant. Through a series of nanoindentation experiments spanning a temperature range of 25 °C to 650 °C, with a maximum load of 100 mN, we find creep behaviors in the cast and sintered materials to be remarkably similar. The creep stress exponent (n) for CNA and SNA were found to be in the range of 8–35 and the activation volume was ∼14–42b 3 , underscoring a dominance of dislocation-mediated mechanisms in both alloys. Notably, we observed a decline in the creep stress exponent with increasing temperature, attributable to the heightened influence of thermally activated dislocations. This phenomenon suggests a potential transition in the deformation mechanism towards a thermally activated dislocation climb process, significantly impacting the observed creep behavior.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Co-, Ni- and Fe-rich grain-boundary phases enhance creep resistance in θ'-strengthened Al-Cu alloys

Here, microstructural evolution and creep response were investigated in the cast Al-5.0Cu-0.3Mn-0.2Zr (wt.%) alloy with and without addition of slow-diffusing, intermetallic-forming elements Fe, Ni, or Co. Baseline Al-5.0Cu-0.3Mn-0.2Zr alloy exhibits high creep resistance at 300 °C, up to ~75 MPa, which is attributed to high-aspect-ratio, intragranular θ'-Al 2 Cu precipitates that effectively suppress dislocation climb. However, θ'-Al 2 Cu precipitate-free zones form along grain boundaries upon heat treatment, whose extent is amplified during subsequent creep. Such weak regions experience dislocation creep, leading to strain localization and acceleration of grain-boundary sliding. Adding Ni and Co, individually or in combination, leads to the formation of grain-boundary precipitates (Al 9 Co 2 , Al 3 Ni 2 ) which are resistant to coarsening, thus suppressing the formation of θ'-Al 2 Cu precipitate-free zones. This microstructure provides high creep resistance at stresses up to 75–80 MPa, with strain rates much lower than in unmodified Al-5.0Cu-0.3Mn-0.2Zr. Adding Fe, which results in extensive decoration of grain boundaries with coarsening-resistant Al 7 Cu 2 Fe, and then increasing the Cu content to compensate for the Cu loss to this new phase, leads to a new Al-7.4Cu-1.6Fe-0.3Mn-0.2Zr alloy with creep resistance at 300 °C that surpasses known cast aluminum alloys. Adding Fe to improve the creep resistance of Al-Cu alloys is both cost-effective and sustainable. Our findings offer guidelines applicable to various alloy systems on controlling the evolution of precipitate-free zones and its ensuing effects on creep deformation.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Force-Free Identification of Minimum-Energy Pathways and Transition States for Stochastic Electronic Structure Theories

Here, the accurate mapping of potential energy surfaces (PESs) is crucial to our understanding of the numerous physical and chemical processes mediated by atomic rearrangements, such as conformational changes and chemical reactions, and the thermodynamic and kinetic feasibility of these processes. Stochastic electronic structure theories, e.g., Quantum Monte Carlo (QMC) methods, enable highly accurate total energy calculations that in principle can be used to construct the PES. However, their stochastic nature poses a challenge to the computation and use of forces and Hessians, which are typically required in algorithms for minimum-energy pathway (MEP) and transition state (TS) identification, such as the nudged elastic band (NEB) algorithm and its climbing image formulation. Here, we present strategies that utilize the surrogate Hessian line-search method, previously developed for QMC structural optimization, to efficiently identify MEP and TS structures without requiring force calculations at the level of the stochastic electronic structure theory. By modifying the surrogate Hessian algorithm to operate in path-orthogonal subspaces and at saddle points, we show that it is possible to identify MEPs and TSs by using a force-free QMC approach. We demonstrate these strategies via two examples, the inversion of the ammonia (NH 3 ) molecule and the nucleophilic substitution (S N 2) reaction F – + CH 3 F → FCH 3 + F – . We validate our results using Density Functional Theory (DFT)- and Coupled Cluster (CCSD, CCSD(T))-based NEB calculations. We then introduce a hybrid DFT-QMC approach to compute thermodynamic and kinetic quantities, free energy differences, rate constants, and equilibrium constants that incorporates stochastically optimized structures and their energies, and show that this scheme improves upon DFT accuracy. Our methods generalize straightforwardly to other systems and other high-accuracy theories that similarly face challenges computing energy gradients, paving the way for highly accurate PES mapping, transition state determination, and thermodynamic and kinetic calculations at significantly reduced computational expense.

Iyer, Gopal R.↗
DOE OSTI2025

Energy Barriers for H 2 Uptake and Release by Defects in Boron Nitride

Density functional theory simulations (DFT) have been used in combination with the climbing image nudged elastic band method (CI-NEB) to determine the energy barriers required to dissociate H 2 at four types of h-BN defects and evaluate the potential for reacted H species to hop to adjacent available sites. The defects were selected based on previous work in which ab initio thermodynamics was used to identify specific defects with optimal thermodynamics for reversible H 2 storage, that is, the defects would dissociate molecular H 2 while not binding H species too strongly so that hydrogen release is favorable. The four defects investigated are the N and B monovacancies, which only offer either B or N defective sites respectively, as well as larger cluster vacancy defects named 3V(1B2N) and hexagonal 6V(3B3N), which present a mixture of B and N defect sites available for H binding. While homogeneous H 2 dissociation by B and N monovacancies have energy barriers larger than 0.4 eV, we found that mixed BN terminated defects have energy barrier lower than 0.4 eV for H 2 dissociation. In particular, H 2 dissociation by the hexagonal 6V(3B3N) defect, exclusively made of Frustrated Lewis Pairs (FLPs), is almost barrierless. The energy barrier for subsequent H hopping to available adjacent B or N sites of the defect were also calculated. It was found that the hopping of H species generally involves high energy barriers ranging from 0.26 eV to 2.57 eV. In conclusion, this work completes previous thermodynamic theoretical investigations and provides a more comprehensive picture of H 2 reaction with defective h-BN for potential H 2 storage and recovery.

Sassi, Michel J. [Pacific Northwest National Labor↗
DOE OSTI2025

Tests of the DFT Ladder for the Fulminic Acid Challenge

Properties of the historically pivotal fulminic acid (HCNO) molecule have been computed with a panoply of 473 density functionals of all varieties, providing a snapshot of the performance of contemporary density functional theory (DFT) for a challenging chemical system. Exhaustive tabulations and statistical analyses have been carried out for geometric parameters, vibrational frequencies, barriers to linearity, and the HCN–O dissociation energy. As the DFT ladder is climbed, confusion rather than consensus ensues regarding the details of the distinctive, extremely flat H–C–N bending potential of fulminic acid and whether the equilibrium structure is linear or bent. While high-ranking DFT functionals produce the smallest errors for the HCN + O( 3 P) → HCNO reaction energy, lower rungs emerge as the best performers for many of the bond distances and harmonic vibrational frequencies. This research shows that the current DFT zoo of approximations does not constitute a transparent ladder of increasingly accurate methods that consistently converges on definitive predictions for various properties of HCNO. Additional analyses are performed on the side effects of popular dispersion corrections on the covalently bonded properties and thermochemistry of HCNO.

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

Natural nanoparticle complexes at water-water interfaces

Aqueous two-phase systems (ATPSs) with multifunctional attributes have significant promise as biomimetic materials, but current approaches do not harness their full potential. Here, we show that ATPSs can be stabilized to form microcapsules by the interfacial assembly of chitin nanofibers (ChNF) and rod-like cellulose nanocrystals (CNC). The high structural stability of the ChNF/CNC complexes integrates permeability and transport across the membrane at the liquid/liquid interface. Driven by density and osmotic stress gradients, the microcapsules show switchable motility, including cyclic meniscus-climbing and subsurface transport. These observations demonstrate a self-regulating system with potential for cargo transfer, cell biomimicry, as well as ATPSs-based microreactors and microrobots.

Bioinspired materials↗
DOE OSTI2025

Life cycle greenhouse gas emissions and carbon intensity of U.S. fuel use and projection for the next 10 years-based on built capacity and expansion plans

The U.S. Inflation Reduction Act of 2022 supports biofuel production expansion through the 45Z clean fuel production tax credit, replacing previous 40A and 40B credits. This follows on the Renewable Fuel Standard from the Energy Policy Act of 2005 and its expansion in 2007. States like California, Oregon, and Washington also offer clean fuel credits. Meanwhile, federal agencies, including the U.S. Department of Energy, have advanced alternative fuel technologies through research and development funding. The surging interest in the biofuel industry has spurred the demand for biofuel supplies in the markets, although achieving profitability for advanced biofuels and low-carbon e-fuels remains challenging. This study aims to track U.S. alternative fuel production capacity expansion plans over the next 10 years and estimate impacts on greenhouse gas (GHG) emissions. By tracking built capacity and industry announcements of planned expansion, this study complements other studies which use models to predict changes in energy technologies and the associated GHG implications. Modeled projections of future technologies are often criticized for over or underestimating the cost and potential role of new technologies. The study focuses on sustainable aviation fuel, renewable diesel, ethanol, biodiesel, and renewable natural gas. Using facility-level data, we conducted a bottom-up analysis linking biofuel production pathways with corresponding pathways and parameterizations in the Argonne R&D GREET model. Results indicate that biofuel capacity could reach 3.8 exajoules in 2035, potentially reducing U.S. GHG emissions by 179 million tonnes, including the full life cycle. This corresponds to a 20% reduction in transportation and 5% in industry sector emissions by 2035, or a 3.6% reduction in economy-wide emissions. Overall, this study shows that while biofuel production capacity in the U.S. is expanding, the capacities remain limited compared to fuel demand. Uncertainty regarding the durability and extension of incentives may be dampening the pace of growth. Meanwhile, demonstrating the commercial potential for alternative fuels and climbing the learning curve for new technologies could lead to an increased pace of expansion in later years. This study offers insights for bioenergy stakeholders, highlighting biofuel technologies' contribution to U.S. energy system and emissions reduction over time based on producers' plans.

Biofuel Producers↗
DOE OSTI2025

Resolving electrochemically triggered topological defect dynamics and structural degradation in layered oxides

Understanding topological defects-controlled structural degradation of layered oxides—a key cathode material for high-performance lithium-ion batteries—plays a critical role in developing next-generation cathode materials. Here, by constructing a nanobattery in an electron microscope enabling atomic-scale monitoring of electrochemcial reactions, we captured the electrochemically driven atomistic dynamics and evolution of dislocations—a most important topological defect in material. We deciphered how dislocations nucleate, move, and annihilate within layered cathodes at the atomic scale. Specifically, we found two types of dislocation configurations, i.e., single dislocations and dislocation dipoles. Both pure dislocation glide/climb and mixed motions were captured, and the dislocation glide and climb velocities were first experimentally measured. Moreover, dislocation activity-mediated structural degradation such as crack nucleation, phase transformation, and lattice reorientation was unraveled. Our work provides deep insights into the atomistic dynamics of electrochemically driven dislocation activities in layered oxides.

Wang, Chunyang (ORCID:0000000184613952)↗
DOE OSTI2025

The revised elastic field of an edge dislocation

We modify the traditional linear-elastic field of an edge dislocation. The modifications stem from symmetry and energy requirements imposed in terms of embedded (deformed) coordinates. These requirements are satisfied if a line force is added to the dislocation field. The modification to the stress field is expressed by coefficients that are a function only of Poisson’s ratio. Qualitatively, the field of the dislocation is increased in the glide direction and decreased in the climb direction. There are small changes to the field of a screw dislocation that do not entail the addition of a line force. Effects of nonlinearity, anisotropic elasticity, and image forces are briefly considered.

Hirth, J. P.↗
DOE OSTI2024

Artificial Intelligence for Climate Change Mitigation Roadmap (Second Edition)

The first ICEF Artificial Intelligence for Climate Change Mitigation Roadmap was released in December 2023. Since that time, attention to artificial intelligence (AI) has continued to grow at a rapid pace. Tens of billions of dollars have poured into AI projects, policymakers around the world have considered new AI policies, and OpenAI reports that each month more than 200 million people now use ChatGPT. Signs of a changing climate continue to grow as well. Based on global average temperatures, July 22, 2024 was the warmest day ever recorded; 2023 was the warmest year ever recorded; and the 10 warmest years on record are the past 10 years. Yet global emissions of greenhouse gases continue to climb. Can AI help cut emissions of greenhouse gases? This Roadmap explores that question. In this second edition of the Artificial Intelligence for Climate Change Mitigation Roadmap, a team of 25 co-authors builds on last year’s roadmap—comprehensively updating all old chapters, adding six new chapters and offering 5–10 specific, actionable recommendations in each chapter. Our goal is to provide a useful resource for experts and non-experts alike. In Part I of this Roadmap, we provide brief introductions to both AI and climate change. In Part II, we explore eight sectors in which AI is helping respond to climate change and could do much more. In Part III, we explore crosscutting issues. We close with findings and recommendations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Analysis of RNA viral function from metatranscriptomic reads in drought simulated soils

Soil viruses have received increased interest in recent years because of their abundance and unelucidated potential as drivers for organic carbon derived from fungal and bacterial necromass. With decreasing levels of rainfall and climbing instances of unseasonal conditions, it becomes crucial to our goals for negative carbon emissions to understand how soil carbon flux is affected. Here we leveraged metatranscriptomic data from a section of research plot of Hopland Research and Extension in northern California with a suite of viral detection tools: VirSorter, DRAMv, and VContact2. We aimed to cross analyze moisture regiments with viral populations. We find that viral diversity is driven by site, like bacteria. We found that viral diversity at face value showed some differentiation but did not significantly differ by legacy moisture content. Additionally, there was detection of auxiliary metabolic genes in a viral sequence which may further support virus’s direct input into the soil carbon pool.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Implementation of WBG devices in circuits - Electric Drive Technologies Project (Final Technical Report)

The objective of the project is to ensure that SiC devices are reliable and rugged as required in automotive applications for operational life of 300,000 hrs and create new device designs to address various weaknesses in currently available commercial devices. OSU has worked closely with SUNY Polytechnic. OSU has carried out the reliability and ruggedness evaluations of commercial devices as well as those fabricated by SUNY Polytechnic, discussed the results with SUNY Poly, and collaborated with the PI at SUNY Poly to improve the designs with respect to reliability/ruggedness. OSU work focused on reliability/ruggedness evaluation of SiC devices by individually testing them and then evaluate them in a 10 kW, 3 phase inverter system built with a specific purpose of stressing devices using realistic drive cycles such as a 10-minute hill climb. It should be noted that the primary purpose of the 10 kW inverter is to provide a platform for stressing the SiC devices under accelerated but realistic drive conditions.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Experimental and Numerical Characterization of High Temperature Deformation Behavior of 347H Stainless Steel

This study investigates how temperature affects the plasticity and thermal creep behavior of 347H stainless steel under uniaxial tension. The research combined experimental testing with advanced computational modeling. Two types of experiments were conducted: uniaxial tensile tests at temperatures from 100°C to 750°C using strain rates of ~10⁻⁴ s⁻¹, and creep tests at temperatures between 600°C and 750°C under various stress levels. These experimental results were used to develop and validate a new integrated mechanistic model that can predict material behavior under any loading condition while accounting for both stress and temperature effects. The model was implemented using a polycrystalline microstructure simulation framework based on elasto-viscoplastic Fast Fourier Transform (EVPFFT). It incorporates three key deformation mechanisms: thermally activated dislocation glide, dislocation climb, and vacancy diffusional creep. The model accounts for internal stress distribution within single crystals and considers how precipitates and solute atoms (both interstitial and substitutional) affect dislocation movement. After validation against experimental data, the model was used to generate Ashby-Weertman deformation mechanism maps for 347H steel, providing new insights into how microstructure influences the activation of different creep mechanisms.

Joy, Jobin K.↗