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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 1,063 records · Page 59
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Arabidopsis ACYL CARRIER PROTEIN4 and RHOMBOID LIKE10 act independently in chloroplast phosphatidate synthesis

Abstract ACYL CARRIER PROTEIN4 (ACP4) is the most abundant ACP isoform in Arabidopsis (Arabidopsis thaliana) leaves and acts as a scaffold for de novo fatty acid biosynthesis and as a substrate for acyl-ACP-utilizing enzymes. Recently, ACP4 was found to interact with a protein-designated plastid RHOMBOID LIKE10 (RBL10) that affects chloroplast monogalactosyldiacylglycerol (MGDG) biosynthesis, but the cellular function of this interaction remains to be explored. Here, we generated and characterized acp4 rbl10 double mutants to explore whether ACP4 and RBL10 directly interact in influencing chloroplast lipid metabolism. Alterations in the content and molecular species of chloroplast lipids such as MGDG and phosphatidylglycerol were observed in the acp4 and rbl10 mutants, which are likely associated with the changes in the size and profiles of diacylglycerol (DAG), phosphatidic acid (PA), and acyl-ACP precursor pools. ACP4 contributed to the size and profile of the acyl-ACP pool and interacted with acyl-ACP-utilizing enzymes, as expected for its role in fatty acid biosynthesis and chloroplast lipid assembly. RBL10 appeared to be involved in the conversion of PA to DAG precursors for MGDG biosynthesis as evidenced by the increased 34:x PA and decreased 34:x DAG in the rbl10 mutant and the slow turnover of radiolabeled PA in isolated chloroplasts fed with [14C] acetate. Interestingly, the impaired PA turnover in rbl10 was partially reversed in the acp4 rbl10 double mutant. Collectively, this study shows that ACP4 and RBL10 affect chloroplast lipid biosynthesis by modulating substrate precursor pools and appear to act independently.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Surrogate-constructed scalable-circuits adaptive variational quantum eigensolver in the Schwinger model

Inspired by recent advancements in simulating periodic systems on quantum computers, we develop an approach to further advance the simulation of these systems, named (SC) 2 -ADAPT-VQE. Our approach extends the scalable-circuits ADAPT-VQE framework, which builds an ansatz from a pool of coordinate-invariant operators defined for arbitrarily large, though not arbitrarily small, volumes. Our method uses a classically tractable “surrogate constructed” method to remove irrelevant operators from the pool, reducing the minimum size for which the scalable circuits are defined. Bringing together the scalable circuits and the surrogate constructed approaches forms the core of the (SC) 2 methodology. Our approach allows for a wider set of classical computations on small volumes, which can be used for a more robust extrapolation protocol. While developed in the context of lattice models, the surrogate construction portion is applicable to a wide variety of problems where information about the relative importance of operators in the pool is available. As an example, we use it to compute the properties of the Schwinger model—quantum electrodynamics for a single, massive fermion in 1 +1 dimensions—and show that our method can be used to accurately extrapolate to the continuum limit.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Laser melting modes in metal powder bed fusion additive manufacturing

In laser powder bed fusion additive manufacturing of metals, extreme thermal conditions create many highly dynamic physical phenomena such as vaporization and recoil, Marangoni convection, and protrusion and keyhole instability. Collectively however, the full set of phenomena is too complicated for practical applications and, in reality, the melting modes are used as a guideline for printing. With increasing local material temperature beyond the boiling point, the mode can change from conduction to keyhole. These mode designations ignore laser-matter interaction details but in many cases are adequate to determine the approximate microstructures and hence the properties of the build. To date, no consistent, common, and coherent definitions have been agreed upon because of historic limitations in melt pool and vapor depression morphology measurements. Here, we distinguish process-based definitions of different melting modes from those based on postmortem evidence. The latter are mainly derived from the transverse cross-sections of the fusion zone, whereas the former come directly from time-resolved x-ray imaging of melt pool and vapor depression morphologies. These process-based definitions are more strict and physically sound, and they offer new guidelines for laser additive manufacturing practices and create new research directions. Further, we highlight the significance of the keyhole, which substantially enhances the laser energy absorption by the melt pool. Recent studies strongly suggest that stable-keyhole laser melting enables efficient, sustainable, and robust additive manufacturing. The realization of this scenario demands the development of multiphysics models, signal translations from morphology to other feasible signals, and in-process metrology across platforms and scales.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

Community detection robustness of graph neural networks

Graph neural networks (GNNs) are increasingly widely used for community detection in attributed networks. They combine structural topology with node attributes through message passing and pooling. However, their robustness or lack thereof with respect to different perturbations and targeted attacks in conjunction with community detection tasks is not well understood. To shed light on latent mechanisms behind GNN sensitivity on community detection tasks, we conduct a systematic computational evaluation of six widely adopted GNN architectures graph convolutional network, graph attention network, graph sample and aggregate (GraphSAGE), differentiable pooling (DiffPool), minimum cut pooling (MinCUT), and deep modularity networks (DMoN). The analysis covers three perturbation categories: node attribute manipulations, edge topology distortions, and adversarial attacks. We use element-centric similarity as the evaluation metric on synthetic benchmarks and real-world citation networks. Our findings indicate that supervised GNNs tend to achieve higher baseline accuracy, while unsupervised methods, particularly DMoN, maintain stronger resilience under targeted and adversarial perturbations. Furthermore, robustness appears to be strongly influenced by community strength, with well-defined communities reducing performance loss. Across all models, node attribute perturbations associated with targeted edge deletions and shifts in attribute distributions tend to cause the largest degradation in community recovery. These findings highlight important trade-offs between accuracy and robustness in GNN-based community detection and offer insights into selecting architectures resilient to noise and adversarial attacks.

Goel, Jaidev [Virginia Polytechnic Inst. and State↗
DOE OSTI2017

Matrix approach to land carbon cycle modeling: A case study with the Community Land Model

The terrestrial carbon (C) cycle has been commonly represented by a series of C balance equations to track C influxes into and effluxes out of individual pools in earth system models (ESMs). This representation matches our understanding of C cycle processes well but makes it difficult to track model behaviors. It is also computationally expensive, limiting the ability to conduct comprehensive parametric sensitivity analyses. To overcome these challenges, we have developed a matrix approach, which reorganizes the C balance equations in the original ESM into one matrix equation without changing any modeled C cycle processes and mechanisms. We applied the matrix approach to the Community Land Model (CLM4.5) with vertically-resolved biogeochemistry. The matrix equation exactly reproduces litter and soil organic carbon (SOC) dynamics of the standard CLM4.5 across different spatial-temporal scales. The matrix approach enables effective diagnosis of system properties such as C residence time and attribution of global change impacts to relevant processes. We illustrated, for example, the impacts of CO 2 fertilization on litter and SOC dynamics can be easily decomposed into the relative contributions from C input, allocation of external C into different C pools, nitrogen regulation, altered soil environmental conditions, and vertical mixing along the soil profile. In addition, the matrix tool can accelerate model spin-up, permit thorough parametric sensitivity tests, enable pool-based data assimilation, and facilitate tracking and benchmarking of model behaviors. Altogether, the matrix approach can make a broad range of future modeling activities more efficient and effective.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Biological mechanisms may contribute to soil carbon saturation patterns

Increasing soil organic carbon (SOC) storage is a key strategy to mitigate rising atmospheric CO 2 , yet SOC pools often appear to saturate, or increase at a declining rate, as carbon (C) inputs increase. Soil C saturation is commonly hypothesized to result from the finite amount of reactive mineral surface area available for retaining SOC, and is accordingly represented in SOC models as a physicochemically determined SOC upper limit. However, mineral-associated SOC is largely microbially generated. In this perspective, we present the hypothesis that apparent SOC saturation patterns could emerge as a result of ecological constraints on microbial biomass—for example, via competition or predation—leading to reduced C flow through microbes and a reduced rate of mineral-associated SOC formation as soil C inputs increase. Microbially explicit SOC models offer an opportunity to explore this hypothesis, yet most of these models predict linear microbial biomass increases with C inputs and insensitivity of SOC to input rates. Synthesis of 54 C addition studies revealed constraints on microbial biomass as C inputs increase. Different hypotheses limiting microbial density were embedded in a three-pool SOC model without explicit limits on mineral surface area. As inputs increased, the model demonstrated either no change, linear, or apparently saturating increases in mineral-associated and particulate SOC pools. Taken together, our results suggest that microbial constraints are common and could lead to reduced mineral-associated SOC formation as input rates increase. We conclude that SOC responses to altered C inputs—or any environmental change—are influenced by the ecological factors that limit microbial populations, allowing for a wider range of potential SOC responses to stimuli. Understanding how biotic versus abiotic factors contribute to these patterns will better enable us to predict and manage soil C dynamics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Land‐based climate solutions for the United States

Abstract Meeting end‐of‐century global warming targets requires aggressive action on multiple fronts. Recent reports note the futility of addressing mitigation goals without fully engaging the agricultural sector, yet no available assessments combine both nature‐based solutions (reforestation, grassland and wetland protection, and agricultural practice change) and cellulosic bioenergy for a single geographic region. Collectively, these solutions might offer a suite of climate, biodiversity, and other benefits greater than either alone. Nature‐based solutions are largely constrained by the duration of carbon accrual in soils and forest biomass; each of these carbon pools will eventually saturate. Bioenergy solutions can last indefinitely but carry significant environmental risk if carelessly deployed. We detail a simplified scenario for the United States that illustrates the benefits of combining approaches. We assign a portion of non‐forested former cropland to bioenergy sufficient to meet projected mid‐century transportation needs, with the remainder assigned to nature‐based solutions such as reforestation. Bottom‐up mitigation potentials for the aggregate contributions of crop, grazing, forest, and bioenergy lands are assessed by including in a Monte Carlo model conservative ranges for cost‐effective local mitigation capacities, together with ranges for (a) areal extents that avoid double counting and include realistic adoption rates and (b) the projected duration of different carbon sinks. The projected duration illustrates the net effect of eventually saturating soil carbon pools in the case of most strategies, and additionally saturating biomass carbon pools in the case of forest management. Results show a conservative end‐of‐century mitigation capacity of 110 (57–178) Gt CO 2 e for the U.S., ~50% higher than existing estimates that prioritize nature‐based or bioenergy solutions separately. Further research is needed to shrink uncertainties, but there is sufficient confidence in the general magnitude and direction of a combined approach to plan for deployment now.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Belowground impacts of perennial grass cultivation for sustainable biofuel feedstock production in the tropics

Abstract Perennial grasses can sequester soil organic carbon ( SOC ) in sustainably managed biofuel systems, directly mitigating atmospheric CO 2 concentrations while simultaneously generating biomass for renewable energy. The objective of this study was to quantify SOC accumulation and identify the primary drivers of belowground C dynamics in a zero‐tillage production system of tropical perennial C4 grasses grown for biofuel feedstock in Hawaii. Specifically, the quantity, quality, and fate of soil C inputs were determined for eight grass accessions – four varieties each of napier grass and guinea grass. Carbon fluxes (soil CO 2 efflux, aboveground net primary productivity, litterfall, total belowground carbon flux, root decay constant), C pools ( SOC pool and root biomass), and C quality (root chemistry, C and nitrogen concentrations, and ratios) were measured through three harvest cycles following conversion of a fallow field to cultivated perennial grasses. A wide range of SOC accumulation occurred, with both significant species and accession effects. Aboveground biomass yield was greater, and root lignin concentration was lower for napier grass than guinea grass. Structural equation modeling revealed that root lignin concentration was the most important driver of SOC pool: varieties with low root lignin concentration, which was significantly related to rapid root decomposition, accumulated the greatest amount of SOC . Roots with low lignin concentration decomposed rapidly, but the residue and associated microbial biomass/by‐products accumulated as SOC . In general, napier grass was better suited for promoting soil C sequestration in this system. Further, high‐yielding varieties with low root lignin concentration provided the greatest climate change mitigation potential in a ratoon system. Understanding the factors affecting SOC accumulation and the net greenhouse gas trade‐offs within a biofuel production system will aid in crop selection to meet multiple goals toward environmental and economic sustainability.

09 BIOMASS FUELS↗
DOE OSTI2017

Cover crop root contributions to soil carbon in a no‐till corn bioenergy cropping system

Abstract Crop residues are potential biofuel feedstocks, but residue removal may reduce soil carbon (C). The inclusion of a cover crop in a corn bioenergy system could provide additional biomass, mitigating the negative effects of residue removal by adding to stable soil C pools. In a no‐till continuous corn bioenergy system in the northern US Corn Belt, we used 13 CO 2 pulse labeling to trace plant C from a winter rye ( Secale cereale ) cover crop into different soil C pools for 2 years following rye cover crop termination. Corn stover left as residue (30% of total stover) contributed 66, corn roots 57, rye shoots 61, rye roots 50, and rye rhizodeposits 25 g C m −2 to soil. Five months following cover crop termination, belowground cover crop inputs were three times more likely to remain in soil C pools than were aboveground inputs, and much of the root‐derived C was in mineral‐associated soil fractions. After 2 years, both above‐ and belowground inputs had declined substantially, indicating that the majority of both root and shoot inputs are eventually mineralized. Our results underscore the importance of cover crop roots vs. shoots and the importance of cover crop rhizodeposition (33% of total belowground cover crop C inputs) as a source of soil C. However, the eventual loss of most cover crop C from these soils indicates that cover crops will likely need to be included every year in rotations to accumulate soil C.

13CO2↗
DOE OSTI2020

Associative nitrogen fixation linked with three perennial bioenergy grasses in field and greenhouse experiments

Abstract Associative nitrogen (N 2 )‐fixation (ANF) by bacteria in the root‐zone of perennial bioenergy grasses has the potential to replace or supplement N fertilizer and support sustainable production of biomass, but its application in marginal ecosystems requires further evaluation. In this study, we first combined both greenhouse and field experiments, to explore the N 2 fixation effects of three temperate feedstocks Miscanthus × giganteus (giant miscanthus, Freedom), Panicum virgatum (switchgrass, Alamo), and Saccharum sp. (energycane, Ho 02‐147). In field studies across three growing seasons, plant and soil pools of candidate feedstocks were partially composed of N derived from the atmosphere (Ndfa). Energycane, giant miscanthus, and switchgrass were estimated to derive >30%, %Ndfa. Greenhouse studies were also performed to trace isotopically labeled 15 N 2 into plant biomass and soil pools. Evidence for Ndfa was detected in all three feedstock grasses (using reference 15 N of soil, chicory, and sorghum, δ 15 N~+7.0). Isotopically labeled 15 N 2 was traced into biomass (during grass elongation stage) and soil pools. Extrapolation of rates during the 24 hr labeling period to 50 days estimated 30%–55% of plant Ndfa, with the greatest Ndfa for energycane. The findings of the field natural abundance and greenhouse 15 N 2 feeding experiments provided complementary evidence that perennial bioenergy grasses have the potential to support relatively high rates of ANF, and accumulate diazotroph‐derived N into biomass when grown on non‐fertilized soil.

09 BIOMASS FUELS↗
DOE OSTI2012

Soil carbon and nitrogen cycling and storage throughout the soil profile in a sweetgum plantation after 11 years of CO2-enrichment

Increased partitioning of carbon (C) to fine roots under elevated [CO2], especially deep in the soil profile, could alter soil C and nitrogen (N) cycling in forests. After more than 11 years of free-Air CO2 enrichment in a Liquidambar styraciflua L. (sweetgum) plantation in Oak Ridge, TN, USA, greater inputs of fine roots resulted in the incorporation of new C (i.e., C with a depleted 13C) into root-derived particulate organic matter (POM) pools to 90-cm depth. Even though production in the sweetgum stand was limited by soil N availability, soil C and N content increased over time, and were greater throughout the soil profile under elevated [CO2] at the conclusion of the experiment. However, greater C inputs under elevated [CO2] did not result in increased net N immobilization or C mineralization rates in long-term laboratory incubations, and did not appear to prime the decomposition of older SOM. The 13CO2 of the C mineralized from the incubated soil closely tracked the 13C of the labile POM pool in the elevated [CO2] treatment, especially in shallower soil, and did not indicate the decomposition of older (i.e., pre-experiment) SOM. While potential C mineralization rates were positively and linearly related to total soil organic matter (SOM) C content in the top 30 cm of soil, this relationship did not hold in deeper soil. Taken together with an increased mean residence time of C in deeper soil pools, these findings indicate that C inputs from relatively deep roots under elevated [CO2] may have increased potential for long-term storage. Expanded representation of biogeochemical cycling throughout the soil profile may improve model projections of future forest responses to rising atmospheric [CO2].

13C↗
DOE OSTI2025

Mitigation of Boiling-Induced Thermal Degradation Using Microporous Nickel Inverse Opals Structures

Engineered microporous structures have received much attention in high-heat-flux electronics cooling due to their high thermal conductivity and permeability, and large surface area for heat transfer, but are susceptible to boiling-induced thermal degradation. Here, this study investigates the efficacy of nickel inverse opals (NiIOs) in mitigating structural degradation caused by corrosion-assisted erosion during pool boiling with water as the working fluid. First, we compared the reliability of NiIOs to copper inverse opals (CuIOs) for a 3-day pool boiling test at constant heat flux. The NiIOs demonstrated superior resistance to thermal degradation due to their inherent corrosion resistance and mechanical strength. Subsequently, we conducted a more controlled experiment to show the effect of heat flux on the degradation of the NiIOs while excluding the effect of temperature variations. Pool boiling tests of 20-μm-thickness NiIOs covering an area of ∼11 × 11 mm 2 with a 2.5 × 2.5 mm 2 heater at the center were conducted at heat flux levels of 20%, 40%, and 60% of the critical heat flux (CHF) for 3 days. The NiIOs subjected to heat flux levels of 20% and 40% CHF showed minimal degradation, while the sample subjected to 60% CHF showed erosion on the top surface due to higher bubble formation and departure rate. These results show the potential of NiIOs as a promising solution for long-term thermal management in high-power electronic devices, although design considerations for maximum allowable heat flux are necessary for reliable operation.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Accelerating Large-Format Metal Additive Manufacturing: How Controls R&D is Driving Speed, Scale, and Efficiency

This article highlights work at Oak Ridge National Laboratory’s Manufacturing Demonstration Facility to develop closed-loop, feedback control for laser-wire based Directed Energy Deposition, a form of metal Big Area Additive Manufacturing (m-BAAM), a process being developed in partnership with GKN Aerospace specifically for the production of Ti-6Al-4V pre-forms for aerospace components. A large-scale structural demonstrator component is presented as a case-study in which not just control, but the entire 3D printing workflow for m-BAAM is discussed in detail, including design principles for large-format metal AM, toolpath generation, parameter development, process control, and system operation, as well as post-print net-shape geometric analysis and finish machining. In terms of control, a multi-sensor approach has been utilized to measure both layer height and melt pool size, and multiple modes of closed-loop control have been developed to manipulate process parameters (laser power, print speed, deposition rate) to control these variables. Layer height control and melt pool size control have yielded excellent local (intralayer) and global (component-level) geometry control, and the impact of melt pool size control in particular on thermal gradients and material properties is the subject of continuing research. Further, these modes of control have allowed the process to advance to higher deposition rates (exceeding 7.5 lb/hr), larger parts (1-meter scale), shorter build times, and higher overall efficiency. The control modes are examined individually, highlighting their development, demonstration, and lessons learned, and it is shown how they operate concurrently to enable the printing of a large-scale, near net shape Ti-6Al-4V component.

Gibson, Brian↗
DOE OSTI2022

SynBio QC-Library QC (LibQC) v2.0.0

This software is a pipeline used to identify the distribution of user-specified sequences in oligo pools that have been sequenced on the MiSeq platform for quality control purposes. The software counts instances of user-specified sequences (inserts or spacers) identified in sequencing data, returning the distribution of sequences in each pool and the length distribution of all the sequences. Among other types similar types of projects, this can be used to assess the quality of a guideRNA library once it has been inserted into the vector of choice to ensure that there is an even distribution of all the individual protospacers in the pool. This pipeline uses many freely available open source libraries, the value added is that in our application the steps of the pipeline are defined in Workflow Description Language (WDL) and run through the Cromwell workflow engine in Docker containers, for easy distribution and set up.

Simirenko, Lisa↗
DOE OSTI2021

Vegetable intake and the risk of bladder cancer in the BLadder Cancer Epidemiology and Nutritional Determinants (BLEND) international study

Although a potential inverse association between vegetable intake and bladder cancer risk has been reported, epidemiological evidence is inconsistent. This research aimed to elucidate the association between vegetable intake and bladder cancer risk by conducting a pooled analysis of data from prospective cohort studies. Vegetable intake in relation to bladder cancer risk was examined by pooling individual-level data from 13 cohort studies, comprising 3203 cases among a total of 555,685 participants. Pooled multivariate hazard ratios (HRs), with corresponding 95% confidence intervals (CIs), were estimated using Cox proportional hazards regression models stratified by cohort for intakes of total vegetable, vegetable subtypes (i.e. non-starchy, starchy, green leafy and cruciferous vegetables) and individual vegetable types. In addition, a diet diversity score was used to assess the association of the varied types of vegetable intake on bladder cancer risk. The association between vegetable intake and bladder cancer risk differed by sex ( P -interaction = 0.011) and smoking status ( P -interaction = 0.038); therefore, analyses were stratified by sex and smoking status. With adjustment of age, sex, smoking, energy intake, ethnicity and other potential dietary factors, we found that higher intake of total and non-starchy vegetables were inversely associated with the risk of bladder cancer among women (comparing the highest with lowest intake tertile: HR = 0.79, 95% CI = 0.64–0.98, P = 0.037 for trend, HR per 1 SD increment = 0.89, 95% CI = 0.81–0.99; HR = 0.78, 95% CI = 0.63–0.97, P = 0.034 for trend, HR per 1 SD increment = 0.88, 95% CI = 0.79–0.98, respectively). However, no evidence of association was observed among men, and the intake of vegetable was not found to be associated with bladder cancer when stratified by smoking status. Moreover, we found no evidence of association for diet diversity with bladder cancer risk. Higher intakes of total and non-starchy vegetable are associated with reduced risk of bladder cancer for women. Further studies are needed to clarify whether these results reflect causal processes and potential underlying mechanisms.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Characterization of resistance to a potent D -peptide HIV entry inhibitor

Background: PIE12-trimer is a highly potent D-peptide HIV-1 entry inhibitor that broadly targets group M isolates. It specifically binds the three identical conserved hydrophobic pockets at the base of the gp41 N-trimer with sub-femtomolar affinity. This extremely high affinity for the transiently exposed gp41 trimer provides a reserve of binding energy (resistance capacitor) to prevent the viral resistance pathway of stepwise accumulation of modest affinity-disrupting mutations. Such modest mutations would not affect PIE12-trimer potency and therefore not confer a selective advantage. Viral passaging in the presence of escalating PIE12-trimer concentrations ultimately selected for PIE12-trimer resistant populations, but required an extremely extended timeframe (> 1 year) in comparison to other entry inhibitors. Eventually, HIV developed resistance to PIE12-trimer by mutating Q577 in the gp41 pocket. Results: Using deep sequence analysis, we identified three mutations at Q577 (R, N and K) in our two PIE12-trimer resistant pools. Each point mutant is capable of conferring the majority of PIE12-trimer resistance seen in the polyclonal pools. Surface plasmon resonance studies demonstrated substantial affinity loss between PIE12-trimer and the Q577R-mutated gp41 pocket. A high-resolution X-ray crystal structure of PIE12 bound to the Q577R pocket revealed the loss of two hydrogen bonds, the repositioning of neighboring residues, and a small decrease in buried surface area. The Q577 mutations in an NL4-3 backbone decreased viral growth rates. Fitness was ultimately rescued in resistant viral pools by a suite of compensatory mutations in gp120 and gp41, of which we identified seven candidates from our sequencing data. Conclusions: These data show that PIE12-trimer exhibits a high barrier to resistance, as extended passaging was required to develop resistant virus with normal growth rates. The primary resistance mutation, Q577R/N/K, found in the conserved gp41 pocket, substantially decreases inhibitor affinity but also damages viral fitness, and candidate compensatory mutations in gp160 have been identified.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Multitask graph neural networks for elastoplastic response prediction in dual-phase polycrystals

Microstructure-sensitive prediction of elastoplastic response remains a recurring bottleneck in multiscale damage and fatigue modeling, where large ensembles of statistically distinct polycrystals are required to quantify variability and extreme-value behavior. In this work, we develop a multitask graph neural network (GNN) surrogate that maps dual-phase ferrite–martensite polycrystal microstructures to Statistical Volume Element (SVE)-level elastoplastic Quantities of Interest (QoIs). Each SVE is represented as a grain-adjacency graph, with node features encoding phase, geometry, and crystallographic orientation, and edge features encoding relative misorientation. A message-passing graph convolution generates node embeddings, which are pooled into a graph representation and passed to a multitask regression head that jointly predicts 10 scalar QoIs and vector-valued stress–strain responses in orthogonal loading directions across multiple martensite volume fractions and SVE sizes. Results show high accuracy for scalar QoIs and strong agreement for full stress–strain trajectories, with population envelopes reproducing both median behavior and finite-SVE variability across compositions and partition scales. A unified model trained on pooled volume-fraction data preserves most within-regime accuracy relative to regime-specific models while also capturing the broader cross-regime variation reflected in the pooled test set. Distributional comparisons further demonstrate that the surrogate preserves heterogeneity under SVE partitioning, enabling statistically consistent block-wise random-field construction for mesoscale analyses. Overall, the proposed grain-graph surrogate provides a practical pathway to accelerate ensemble-based studies of SVE-level constitutive variability in dual-phase polycrystals.

Crystal plasticity↗
DOE OSTI2024

Effects of fire and fire-induced changes in soil properties on post-burn soil respiration

Boreal forests cover vast areas of land in the northern hemisphere and store large amounts of carbon (C) both aboveground and belowground. Wildfires, which are a primary ecosystem disturbance of boreal forests, affect soil C via combustion and transformation of organic matter during the fire itself and via changes in plant growth and microbial activity post-fire. Wildfire regimes in many areas of the boreal forests of North America are shifting towards more frequent and severe fires driven by changing climate. As wildfire regimes shift and the effects of fire on belowground microbial community composition are becoming clearer, there is a need to link fire-induced changes in soil properties to changes in microbial functions, such as respiration, in order to better predict the impact of future fires on C cycling. We used laboratory burns to simulate boreal crown fires on both organic-rich and sandy soil cores collected from Wood Buffalo National Park, Alberta, Canada, to measure the effects of burning on soil properties including pH, total C, and total nitrogen (N). We used 70-day soil incubations and two-pool exponential decay models to characterize the impacts of burning and its resulting changes in soil properties on soil respiration. Laboratory burns successfully captured a range of soil temperatures that were realistic for natural wildfire events. We found that burning increased pH and caused small decreases in C:N in organic soil. Overall, respiration per gram total (post-burn) C in burned soil cores was 16% lower than in corresponding unburned control cores, indicating that soil C lost during a burn may be partially offset by burn-induced decreases in respiration rates. Simultaneously, burning altered how remaining C cycled, causing an increase in the proportion of C represented in the modeled slow-cycling vs. fast-cycling C pool as well as an increase in fast-cycling C decomposition rates. Together, our findings imply that C storage in boreal forests following wildfires will be driven by the combination of C losses during the fire itself as well as fire-induced changes to the soil C pool that modulate post-fire respiration rates. Moving forward, we will pair these results with soil microbial community data to understand how fire-induced changes in microbial community composition may influence respiration.

54 ENVIRONMENTAL SCIENCES↗