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All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Development of SAM Code Capabilities for Safety Analysis of GCR Air-ingress Events

Air-ingress following a depressurized loss-of-forced-cooling (DLOFC) event is a challenging, multiphysics safety scenario for High-Temperature Gas-Cooled Reactors (HTGRs), involving coupled gas composition transport, buoyancy-driven flow redistribution, graphite oxidation, and structural heat-up. Despite its importance — air ingress is a key scenario identified in the PIRT process for the HTGRs — existing system-level safety codes have lacked the integrated capability to simulate the complete event sequence with high confidence. This report documents the development, validation, and demonstration of three new capabilities in the SAM code to address this gap: (1) a multi-component gas mixture flow model with binary diffusion to track the helium-air composition and its effect on system density and flow; (2) a 0-D graphite oxidation model based on the Roes correlation, including oxygen consumption and exothermic heat release; and (3) an isentropic critical flow model for accurate representation of primary system depressurization through a break. These capabilities are validated against two benchmark experiments. The NSTF heavy-gas ingress experiment validates the multi-component flow model: SAM correctly reproduces the rapid buoyancydriven flow stagnation and subsequent natural circulation recovery driven by composition-dependent density changes. The NACOK graphite oxidation experiment validates the oxidation model: SAM predicts a bottom-level graphite weight loss of 25%, in close agreement with the measured 24%, and reproduces the strong axial nonuniformity and block-geometry dependence of oxidation, at a level comparable to the SPECTRA and TINTE codes. The validated capabilities are then exercised together in an integrated, reactor-scale simulation of a DLOFC air-ingress transient in a simplified HTR-PM pebble-bed reactor. In a single calculation spanning approximately 8 days, SAM reproduces the complete accident sequence: rapid depressurization, densityand diffusion-driven air ingress over ˜15 hours, onset of buoyancy-driven natural circulation, exothermic graphite oxidation with a peak fuel temperature at ˜62 hours, and eventual passive cooldown. These results demonstrate that SAM now provides the nuclear community with a preliminarily validated, modern systemlevel tool for HTGR air-ingress safety analysis, filling a recognized capability gap. Future extensions to broaden species tracking, improve oxidation chemistry, and refine the reactor model are discussed.

Yang, Gang↗
DOE OSTI2026

Beyond microbial abundance: metadata integration enhances disease prediction in human microbiome studies

Multiple studies have highlighted the interaction of the human microbiome with physiological systems such as the gut, immune, liver, and skin, via key axes. Advances in sequencing technologies and high-performance computing have enabled the analysis of large-scale metagenomic data, facilitating the use of machine learning to predict disease likelihood from microbiome profiles. However, challenges such as compositionality, high dimensionality, sparsity, and limited sample sizes have hindered the development of actionable models. One strategy to improve these models is by incorporating key metadata from both the human host and sample collection/processing protocols. This remains challenging due to sparsity and inconsistency in metadata annotation and availability. In this paper, we introduce a machine learning-based pipeline for predicting human disease states by integrating host and protocol metadata with microbiome abundance profiles from 68 different studies, processed through a consistent pipeline. Our findings indicate that metadata can enhance machine learning predictions, particularly at higher taxonomic ranks like Kingdom and Phylum, though this effect diminishes at lower ranks. Our study leverages a large collection of microbiome datasets comprising 11,208 samples, therefore enhancing the robustness and statistical confidence of our findings. This work is a critical step toward utilizing microbiome and metadata for predicting diseases such as gastrointestinal infections, diabetes, cancer, and neurological disorders.

Mathematics and Computing↗
DOE OSTI2020

Characterization of Tank 11H samples from tank closure cesium removal (TCCR) Batch 3 - intermediate and final samples

Savannah River Remediation (SRR) is currently operating the Tank Closure Cesium Removal (TCCR) process to remove 137 Cs from tank waste supernate using an ion exchange process. The TCCR unit processes dissolved salt from Tank 10H through a series of ion exchange columns containing crystalline silicotitanate (CST) and the effluent is then discharged to Tank 11H. Four interim samples pulled from Tank 11H during and just after the completion of processing of Batch 3 through the TCCR process have been analyzed for 137 Cs activity and density. The 137 Cs activity was found to decrease with each subsequent sample, which is consistent with the addition of decontaminated solution to Tank 11H. When compared to the expected composition from mixing the Tank 10H Batch 3 feed with the material already present in Tank 11H, the bulk chemical composition was as expected. A corrosion control sample collected from Tank 11H in June 2020 showed changes in the chemical composition and 137 Cs activity when compared to the composition measured at the end of Batch 2 processing. As there were no additions made to the tank during this period, these changes were attributed to leaching of the solids present in Tank 11H. Revision 1 of this report contains additional analyses of the fourth interim sample including inductively coupled plasma – mass spectrometry (ICP-MS) results and activities of other radionuclides. These results are consistent with the previously reported results, showing leaching from the Tank 11H heel. Notably, the 90 Sr activity was about 2.7x higher than calculated from a mixture of the original Tank 11H supernate and the Tank 10H supernate as treated by TCCR, suggesting additional leaching of Sr from the Tank 11H heel solids. In addition, Revision 1 includes analysis results for the Batch 3 Post-Production surface and variable depth samples collected in October of 2020. The Post-Production surface sample was similar in composition to the fourth interim surface sample, except for the increased Cs-137 and oxalate concentrations that were presumably associated with leaching of the Tank 11H heel solids.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Development of gas chromatographic pattern recognition and classification tools for compliance and forensic analyses of fuels: A review

Gas chromatography (GC) is undoubtedly the analytical technique of choice for analyzing the composition of petroleum-based fuels. Over the past twenty years, as comprehensive two-dimensional gas chromatography (GC×GC) has evolved, fuel analysis has often been highlighted in scientific reports, as their complexity allows for illustration of the impressive peak capacity gains afforded by GC×GC. Indeed, several research groups in recent years have applied GC×GC and chemometrics to demonstrate the potential of these analytical tools to address important compliance (tax evasion, tax credits, physical quality standards) and forensic (arson investigations, oil spills) applications involving fuels. None the less, routine use of GC×GC in forensic laboratories has been limited largely by (1) legal and regulatory guidelines, (2) lack of chemometrics training, and (3) concerns about the reproducibility of GC×GC. The goal of this review is to highlight recent advances in one-dimensional GC (1D-GC) and GC×GC analyses of fuels for compliance and forensic applications, in an effort to assist scientists in overcoming the aforementioned hindrances. An introduction to 1D-GC principles, GC×GC technology (column stationary phases and modulators) and several chemometric techniques will be provided. More specifically, chemometric techniques will be broken down into (1) signal pre-processing, (2) peak decomposition, identification and quantification, and (3) classification and pattern recognition. Examples of compliance and forensic applications will be discussed, with particular emphasis on the demonstrated success of the employed chemometric techniques. Overall, this review will hopefully make 1D-GC and GC×GC coupled with chemometric data analysis tools more accessible to the larger scientific community, and aid in eventual widespread standardization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Selenium interaction with iron minerals: Quantitative comparison of sorption and coprecipitation impacts on mobility

Given the significance of selenium (Se) as a micronutrient, the radioactive nature of some of its isotopes, and its affinity to iron (Fe) minerals, extensive research has been conducted on the sorption mechanisms between Se and these minerals. Here, in this study, we employ sorption data sourced from the L-SCIE database and coprecipitation data from available literature to achieve the following objectives: i) establish coherence between adsorption and coprecipitation processes, ii) quantitatively evaluate the importance of these processes in nuclear waste repository science, and iii) propose a forward-looking approach for integrating coprecipitation into reactive transport models. Our findings indicate that a correlation between Se adsorption and coprecipitation can be established using the λ formalism. The comparable log(λ Se(IV) /λ Se(VI) ) ratios derived from adsorption and coprecipitation experiments suggest that these processes can be quantitatively compared and evaluated using our numerical approach. Across all iron oxide phases examined, coprecipitation leads to significantly greater immobilization of Se compared to adsorption. Specifically, for hydrous ferric oxide, hematite, and goethite, coprecipitation is predicted to result in 100–1000 times more Se immobilization compared to adsorption, irrespective of the Se oxidation state (Se(IV) or Se(VI)); notably stronger immobilization potential via coprecipitation was observed for magnetite. The modeling approach and quantitative analysis presented herein clearly highlight the importance of including coprecipitation processes when simulating Se (and other elements) transport, particularly under conditions where mineral compositions are transient or evolving with time. Neglecting coprecipitation in models is likely to lead to significant overestimates of migration.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2021

Combustion in the ZrF 4 -Mg-Si and ZrF 4 -Al-Si systems for preparation of zirconium silicides

The exothermic reactions in the ZrF 4 –Mg-Si and ZrF 4 -Al-Si systems are investigated by a fast temperature recording (thermocouple) technique, differential scanning calorimetry (DSC), and thermogravimetric analysis (TGA). A quenching method is used to arrest the combustion process and conduct a layer-by-layer analysis of the products by x-ray diffraction (XRD) and electron microscopy. Two seemingly similar reactive systems exhibited considerably different combustion characteristics, composition, and morphology. Based on these investigations, we propose and discuss phase formation mechanisms at the early stages for each system. Three different pathways involving the reaction of ZrF 4 with other reagents and the Mg 2 Si intermediate are identified to occur in the ZrF 4 –Mg-Si system. Contrary to the complex mechanism in the ZrF 4 –Mg-Si system, the early stage of the combustion process for the ZrF 4 -Al-Si system involves the interaction of ZrF 4 with Al-Si eutectic melt. The exothermic reaction between reduced solid Zr and Si melt is the primary heat-generating step for both systems in spite of substantial differences in the early stages of the reactions. The silicon content in the reactive mixtures governs the phase composition of products. The ZrSi 2 phase, with a high growth rate, forms first on the Zr particle surfaces and then grows by a reactive diffusion mechanism. The ZrSi 2+ Zr reaction produces silicon-lean phases (e.g., ZrSi) when the silicon supply is limited. The combustion temperature also has a considerable influence on the phase compositions of the products. High combustion temperature in the ZrF 4 +2Mg+Si mixture enables the formation of multiphase products (α-ZrSi and β-ZrSi), whereas the relatively lower temperatures in the 3ZrF 4 +4Al+3Si mixture yields a single-phase α-ZrSi. As a result, lower combustion temperatures also make the ZrF 4 -Al-Si system more advantageous for the preparation of zirconium silicides.

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

Automated phase segmentation and quantification of high-resolution TEM image for alloy design

In the alloy design and development process, a wealth of atomically resolved structural high-resolution transmission electron microscopy (HRTEM) images are produced. Identifying the different nano-precipitate phases and tracking their evolution under various compositions and during manufacturing or post-processing requires hundreds of HRTEM images and thousands of precipitates. The nanoscopic phase information labeling and analysis purely relies on humans are prohibitively costly and time-consuming, sometimes not reliable because of the lack of authoritative knowledge. Here, in this work, we develop a novel unsupervised machine learning approach coupled with adaptive computer vision techniques with features in the Fourier space to automatically determine the number of phases and segment/quantify the phases with nanoscale resolution, allowing for quantitative correlation between nanostructure formation, processing and functional properties. To automate the phase extraction/quantification and ascertain its applicability, we have applied the developed framework to the HRTEM images from several alloy systems, processing conditions, image magnifications, and phase types and morphologies (precipitates, nano-twins, stacking faults, crystalline matrix, and amorphous structures) for verification. This study paves the road for compression, visualization, and translation of raw image structural data into physically relevant information in real-time with minimal human supervision. It shows the promise of enabling high-throughput materials characterization for the acceleration of alloy manufacturing and design.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Native Void Space for Maximum Volumetric Capacity in Silicon-Based Anodes

Volumetric energy density is considered a primary factor in developing high-energy batteries. Despite its significance, less efforts have been devoted to its improvement. Silicon-based materials have emerged as next-generation anodes for lithium-ion batteries due to their high specific capacity. However, their volumetric capacities are limited by the volume expansion rate of silicon, which restricts mass loading in the electrodes. To address this challenge, we introduce porous silicon templated from earth-abundant minerals with native internal voids, capable of alleviating volumetric expansion during repeated cycles. In situ transmission electron microscopy analysis allows the precise determination of the expansion rate of silicon, thus presenting an analytical model for finding the optimal content in silicon/graphite composites. The inner pores in silicon reduce problems associated with its expansion and allow higher silicon loading of 42% beyond the conventional limitations of 13–14%. Consequently, the anode designed in this work can deliver a volumetric capacity of 978 mAh cc–1. Thus, suppressing volume expansion with natural abundant template-assisted materials opens new avenues for cost-effective fabrication of high volumetric capacity batteries.

Yeom, Su Jeong↗
DOE OSTI2021

Gut microbiome partially mediates and coordinates the effects of genetics on anxiety-like behavior in Collaborative Cross mice

Abstract Growing evidence suggests that the gut microbiome (GM) plays a critical role in health and disease. However, the contribution of GM to psychiatric disorders, especially anxiety, remains unclear. We used the Collaborative Cross (CC) mouse population-based model to identify anxiety associated host genetic and GM factors. Anxiety-like behavior of 445 mice across 30 CC strains was measured using the light/dark box assay and documented by video. A custom tracking system was developed to quantify seven anxiety-related phenotypes based on video. Mice were assigned to a low or high anxiety group by consensus clustering using seven anxiety-related phenotypes. Genome-wide association analysis (GWAS) identified 141 genes (264 SNPs) significantly enriched for anxiety and depression related functions. In the same CC cohort, we measured GM composition and identified five families that differ between high and low anxiety mice. Anxiety level was predicted with 79% accuracy and an AUC of 0.81. Mediation analyses revealed that the genetic contribution to anxiety was partially mediated by the GM. Our findings indicate that GM partially mediates and coordinates the effects of genetics on anxiety.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

High pressure, high flow rate batch mixing apparatus for high throughput experiments

An automated, high pressure, high flow rate batch mixing apparatus has been designed and constructed for rapid, stable, and repeatable mixing of multiple gases and vapors. The apparatus operates as an intermittent batch mixer with cycles of topping off fresh mixture to maintain pressure in an accumulator tank until consumed in an experimental apparatus. At high duty cycles, the apparatus can also function at steady state. This style of mixing is suitable for experiments such as high repetition rate shock tubes and other devices with intermittent flow demands. It is compact and portable, facilitating use in locations such as synchrotron light sources. The entire apparatus is heated to permit the mixing of vapors from species with low volatilities. The apparatus is fully automated and runs for extended periods with the only intervention being to refresh reagent supplies. Here, the accuracy and repeatability of the apparatus were verified by periodic gas sampling and analysis with gas chromatography. Multi-component mixtures spanning a wide range of complexity, dilution, and volatility of constituents have been prepared. The compositions of the majority of the mixture were found to be stable over several filling cycles, repeatable, and with the proper calibration of set-point conditions, accurate. Challenges were encountered preparing a mixture from multi-component liquids, and potential solutions are discussed.

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

Competing magnetic phases in Cr 3+𝛿 ⁢Te 4 are spatially segregated

Cr 1+𝑥⁢ Te 2 is a self-intercalated van der Waals system that is of current interest for its room-temperature room-temperature ferromagnetic (FM) phases and tunable topological properties. In bulk samples, the strain from the interstitial Cr ions leads to distinct structural phases for different ranges of 𝑥. Early neutron powder diffraction (NPD) measurements on the monoclinic phase Cr 3 ⁢Te 4 (𝑥=0.5) presented evidence for competing FM and antiferromagnetic (AFM) phases. Here we apply neutron diffraction to a single crystal of Cr 3+𝛿 ⁢Te 4 with 𝛿=−0.10 and discover that it consists of two distinct monoclinic phases, one with FM order below 𝑇 C ≈321 K and another that develops AFM order below 𝑇 N ≈86 K. In contrast, we find that a crystal with 𝛿=−0.26 exhibits only FM order below 𝑇 C ≈285 K. The single-crystal analysis is complemented by results obtained with NPD, x-ray powder diffraction, and transmission electron microscopy (TEM) measurements on the 𝛿=−0.10 composition. From observations of spontaneous magnetostriction of opposite sign at 𝑇 C and 𝑇 N , along with the TEM evidence for both monoclinic phases in a single thin ( ≈100 nm) grain, we conclude that the two phases must have a fine-grained ( ≲100 nm) intergrowth character, as might occur from high-temperature spinodal decomposition during the growth process. Calculations of the relaxed lattice structures for the FM and AFM phases with density functional theory provide a rationalization of the observed spontaneous magnetostrictions. Correlations between the magnitude and orientation of the magnetic moments with lattice parameter variation demonstrate that the magnetic orders are sensitive to strain, thus explaining why magnetic ordering temperatures and anisotropies can be different between bulk and thin-film samples, when the latter are subject to epitaxial strain. Our results point to the need to investigate the supposed coexistence FM and AFM phases reported elsewhere in the Cr 1+𝑥 ⁢Te 2 system, such as in the Cr 5 ⁢Te 8 phase (𝑥=0.25).

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Development and validation of time‐domain 1 H‐NMR relaxometry correlation for high‐throughput phenotyping method for lipid contents of lignocellulosic feedstocks

Abstract The bioenergy crops such as energycane, miscanthus, and sorghum are being genetically modified using state of the art synthetic biotechnology techniques to accumulate energy‐rich molecules such as triacylglycerides (TAGs) in their vegetative cells to enhance their utility for biofuel production. During the initial genetic developmental phase, many hundreds of transgenic phenotypes are produced. The efficiency of the production pipeline requires early and minimally destructive determination of oil content in individuals. Current screening methods require time‐intensive sample preparation and extraction with chemical solvents for each plant tissue. A rapid screen will also be needed for developing industrial extraction as these crops become available. In the present study, we have devised a proton relaxation nuclear magnetic resonance ( 1 H‐NMR) method for single‐step, non‐invasive, and chemical‐free characterization of in‐situ lipids in untreated and pretreated lignocellulosic biomass. The systematic evaluation of NMR relaxation time distribution provided insight into the proton environment associated with the lipids in the biomass. It resolved two distinct lipid‐associated subpopulations of proton nuclei that characterize total in‐situ lipids into bound and free oil based on their “molecular tumbling” rate. The T1T2 correlation spectra also facilitated the resolution of the influence of various pretreatment procedures on the chemical composition of molecular and local 1 H population in each sample. Furthermore, we show that hydrothermally pretreated biomass is suitable for direct NMR analysis unlike dilute acid and alkaline pretreated biomass which needs an additional step for neutralization.

pretreatment↗
DOE OSTI2021

The Development of Catalysts for Upgrading of Pyrolysis Vapor for Refinery Feedstocks and Intermediates: Cooperative Research and Development, CRADA Number CRD-12-00497 (Final Report)

Fast pyrolysis of biomass with vapor phase upgrading (VPU) can produce refinery feedstocks or intermediates that can meet the Department of Energy’s goal of cost-competitive hydrocarbon fuels by 2017. A key technical barrier for this technology is the lack of selective, cost effective catalysts that can produce high yields of fuel-appropriate hydrocarbons from the pyrolysis vapors. In overcoming this barrier, it will be important to engage leading catalyst development companies to devote their resources and expertise to the development of these materials. Thus, we propose a Cooperative Research and Development Agreement (CRADA) between the National Renewable Energy Laboratory (NREL), a world leader in biomass pyrolysis research and Johnson Matthey (JM), a world leader in the production of advanced catalyst materials to develop and test novel catalysts for efficient VPU. Through its Intercat Inc. subsidiary in Savannah, Ga., Johnson Matthey is internationally recognized as a leader in zeolite-based vapor phase upgrading in refinery duties and an emerging developer of biomass conversion technologies. The research and development efforts described in the proposed work will build upon existing collaborations between NREL and JM and play to the strengths of both institutions. NREL will analyze the composition of pyrolysis vapors as an input to catalyst design, screen and test catalysts, characterize the resulting oil and conduct techno-economic analysis. Catalyst samples will be produced and funded by JM. JM will design and synthesize catalysts, characterize fresh and used catalysts and develop catalyst supports needed to achieve commercially meaningful lifetimes. The project will span catalyst development and testing from the fundamental stage using quantum mechanical modeling and chemical reaction analysis to catalyst screening to integrated pilot studies.

09 BIOMASS FUELS↗
DOE OSTI2023

Field Laboratory for Emerging Stacked Unconventional Plays in Central Appalachia

The goal of the Field Laboratory for Emerging Stacked Unconventional Plays (ESUP) in Central Appalachia project was to investigate and characterize the resource potential for multi-play production of emerging unconventional reservoirs in Central Appalachia. Project activities included drilling, logging and coring of a vertical characterization well drilled to basement to approximately 15,000 feet in depth. The data from drilling and well logs as well recovered core samples were used by the research team to support characterization of the geology and potential pay zones within the Nora Gas Field of southwestern Virginia and the greater Central Appalachian Basin. This project was led by Dr. Nino Ripepi of the Virginia Center for Coal and Energy Research (VCCER) in close collaboration with EnerVest Operating LLC (EnerVest). VCCER is housed in the Department of Mining and Minerals Engineering at Virginia Tech and was created by an Act of the Virginia General Assembly on March 30, 1977, as an interdisciplinary study, research, information, and resource facility for the Commonwealth of Virginia. EnerVest is a top tier, low-cost oil and natural gas company with a long history of traditional operating relationships with institutional investors as well as public and private companies. This report summarizes two major research activities: 1) Log and Core Analysis and 2) Numerical Modeling. Core analysis comprises the characterization efforts of the ESUP Field Laboratory and includes a discussion of the well logs run in the deep characterization wells, an initial analysis of those, the number, size and location of cores recovered, core testing and analysis done to date as well as plans for future analysis. Numerical modeling is comprised of seven major modeling efforts, including (1) Multiphysics shale transport modeling work, (2) the developed in-house compositional simulator studies, (3) reservoir modeling studies using GEM software, (4) fracture modeling work using EFRAC3D software and (5) numerical modeling efforts with ABAQUS software, (6) Numerical modeling efforts using FLAC3D and PFC3D, and (7) Automatic Machine Learning (AutoML) Studies.

02 PETROLEUM↗
DOE OSTI2024

Hear It? – New Physics Calls For a Healthy Target!

Nowadays, when the attention of the physics community is drawn to muon collider prospects and neutrino projects, a target as the primary source of such exotic particles is a key component of a particle physics experiment. The extreme conditions placed on the target, though, decrease its functionality and threaten the future of high-power targetry. Subject to superb magnetic fields, extreme temperatures, and radiation damage, the target is constantly at risk of unexpected failures. The Target Health Monitor (THM) aims to enable the continuous analysis of the target state throughout the experiment. Based on the optical concept of Brewster s angle and the reflectivity variation with the compositional changes in the target material, the THM will record and evaluate the radiation-caused transmutations in the target to foresee its malfunction before it affects the experimental results. The first steps in validating our THM concept have been made this summer. Continuing reflectivity measurements of the prospective target materials, we anticipate proving the THM potential to monitor target health effectively.

Havryshchuk, Kateryna↗
DOE OSTI2024

Particle Image Velocimetry and Total Temperature Characterization of Arc-Heated Mach 4.5 Free Jet

Particle image velocimetry (PIV) measurements were conducted in the Arc-Heated Combustion Tunnel (ACT-II) on a high-enthalpy Mach 4.5 nozzle flow. The primary motivation for the current work is to establish the feasibility of PIV as a high-quality flow diagnostic technique in hypersonic arc-heated flows and produce a high-resolution hypersonic nozzle flow characterization, including nozzle free jet shear layer velocity profiles. Due to the uncertain nature of the gas composition in the flowfield of interest, PIV measurements of a supersonic wedge flow were used to couple the flow velocities to the oblique shock relations. This enabled a PIV-derived total temperature calculation that does not require a priori assumptions of the exact gas composition. A PIV expansion module was developed for this study, and proper seed sizing and material were selected for the present flow. An analysis of the seed particle response from the PIV measurements provided an initial validation of the seed performance while revealing potential issues with consistent seed sizing. These measurements and derived conditions represent a means of acquiring high-resolution velocimetry and temperature datasets that consider uncertainties in the experimental generation of hypersonic high-enthalpy flows.

Engineering↗
DOE OSTI2026

Integrative Modeling and Analysis of Fungal Central Carbon Metabolism

Over a thousand fungal genomes have been sequenced, yet manually curated genome-scale metabolic models (GEMs) are available for only a limited number of species. Moreover, these models have often been developed independently, leading to inconsistencies in namespaces, compartment definitions, and pathway representations that hinder comparative analysis, the systematic reuse of prior curation efforts, and the integration of consolidated metabolic knowledge. Here, we present the Consolidated Fungal Core Metabolism Model (CFCMM), constructed by integrating thirteen published fungal models spanning Ascomycota, Mucoromycota, and both Crabtree-positive and Crabtree-negative yeasts. We harmonized metabolites and reactions into a non-redundant shared ModelSEED ontological space, standardized compartmentalization, and refined gene–protein–reaction (GPR) rules. Using pathway-level visualization and systematic gap detection, we further improved the integrated network through literature-guided curation to correct stoichiometry, stereospecificity, and pathway architecture. Orthologous protein family reconstruction and functional annotation workflows were used to validate and inform GPR associations, with particular emphasis on ambiguous enzyme superfamilies and membrane-associated components. Using the resulting CFCMM, we built high-quality central carbon core models for each fungus and performed flux balance analysis to quantify ATP-yield variation under aerobic and anaerobic conditions, explicitly evaluating scenarios driven by differences in electron transport chain (ETC) composition. Simulations reproduced the expected fermentative yield of approximately 2 mmol ATP per mmol glucose under anaerobic conditions and separated the thirteen fungi into two bioenergetic groups under aerobic respiration based on Complex I status, with predicted yields of approximately 30 versus 22 mmol ATP per mmol glucose. Forcing flux through the alternative oxidase bypass further reduced ATP yields to approximately 12 and 4 mmol ATP per mmol glucose in Complex I-containing and Complex I-lacking fungi, respectively. Collectively, this work provides a manually curated, ModelSEED-consistent, and extensible fungal core metabolic template, deployed in DOE KBase as a resource for automated reconstruction of central carbon core models from any sequenced fungal genome. In addition, the CFCMM provides modular components for developing GEMs with more accurate energy predictions and enables robust comparative analyses of fungal bioenergetics and core metabolic diversity

59 BASIC BIOLOGICAL SCIENCES↗