Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “enrichment”

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 1,297 records · Page 72
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Multi-Objective Optimization of Uranium Target Assembly–3: A Comparison of Genetic and Traditional Methods

Commonly produced as a byproduct of uranium fission, 99 Mo is a key medical isotope that is in high demand in the United States. An international goal is to switch from medical isotope production technologies that require highly enriched uranium to medical isotope production technologies that require only low-enriched uranium. Niowave Inc. is contributing to this goal by developing an accelerator-driven subcritical assembly called the Uranium Target Assembly (UTA). This work compares the performance of Dakota’s Multi-Objective Genetic Algorithm (MOGA) against traditional sensitivity analysis in the neutronic optimization of the UTA-3 system. The design objectives are k-eigenvalue (k eff ) and natural uranium fission power, which are directly correlated with the amount of 99 Mo produced. Dakota:MOGA did not perform as well as human engineering ingenuity in optimization studies with high numbers of input parameters, such as fuel rod type selection and fuel rod placement. However, Dakota:MOGA did outperform traditional sensitivity analysis in optimization studies with fewer than 20 parameters and revealed the degree to which each parameter influences the optimal design space for k eff and natural uranium fission power (to a lesser extent). As the design model became more complex in the final stage of design, the computational resources required to calculate the design objective values in the Monte Carlo N-Particle transport code from selected input parameter combinations limited Dakota:MOGA’s performance, and, unfortunately, human intervention was required to discern the optimal design space. In conclusion, future work will attempt to reduce computational resource constraints by incorporating areduced-order neutronics model into the optimization cycle.

Accelerator-driven systems↗
DOE OSTI2026

Deimos: HALEU TRISO Heated Critical Experiment Data

Deimos was the first critical experiment using high-assay low-enriched uranium (HALEU) TRistructural ISOtropic (TRISO) fuel in over 40 years. HALEU TRISO is the desired fuel form for many of the advanced reactor designs in development; however, very little experimental data are available for this fuel type. Deimos was designed to utilize existing HALEU TRISO fuel in a large graphite moderator to obtain nuclear and reactor physics data to fill the gaps surrounding this fuel type and enrichment. In addition to cold critical data, three separate heated experiments were conducted to measure the temperature reactivity coefficient for this type of system. These measured coefficients were then compared to simulated coefficients to a first level order of fidelity. This comparison showed very good agreement for the experiment where only the inner core was heated and good agreement for the other two configurations, which included heating portions of the outer core. Less agreement when the outer core was heated is attributed to potential heating in the beryllium reflector, which has a positive temperature reactivity coefficient and was unaccounted for in the first-order models. Future heated experiments with Deimos will include temperature monitoring of the beryllium reflector to account for beryllium heating in the simulations.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

PWR Core Analysis for Cycle Extension and Uprates with LEU+ Accident Tolerant Fuel and 80 GWd/Tonne Burnup Limit

The U.S. Nuclear Regulatory Commission has recently drafted a rule enabling fuel burnup increase in light water reactors up to 80 GWd/t. In conjunction with use of fuel enrichment up to 10%, and accident tolerant fuel (ATF), this is anticipated to facilitate 24-month cycles in PWRs, along with further power uprates. In this paper, PWR core analysis is performed for 20% increased PWR power output along with cycle extension up to 24 months, in combination with use of chromia-doped fuel and chromium-coated clad, considered to be the most near-term ATF concepts. In combination, these lead to challenging conditions with a core average discharge burnup of up to ~74 GWd/t, challenging even the 80 GWd/t burnup limit. Analysis is performed using the 2-step method with POLARIS (within SCALE) used for the lattice calculations and PARCS for the core calculations. Core designs are first baselined for current operating conditions (LEU, 62 GWd/t discharge burnup limit) and then derived that meet cycle constraints on power distribution and the updated lead pin discharge burnup limit while maintaining at least two batches of fuel in the core. Gadolina loadings in fuel pins of up to 8% are used, with enrichment zoning both within the core and, to a limited extent, within assemblies. Here, doped fuel with coated cladding can utilize the same core designs as the reference UOX cores, exhibiting slightly lower burnup due to higher fuel density, which also offsets the slight reactivity penalty from the doping and coating. For the analysis performed here, doped fuel enabled a core with 24-month cycle and 20% uprate to stay within the 80 GWd/t lead pin discharge burnup limit.

LEU+↗
DOE OSTI2026

Evaluation of Sandia NCS Benchmark Suite Updates

The Sandia Nuclear Criticality Safety (NCS) program’s benchmark suite was recently updated. This suite is used to ensure that NCS calculations using computer-based neutron transportation codes have an established baseline comparison of calculated versus known experimental results. The Evaluated Nuclear Data File (ENDF) version used for the MCNP models in the suite was changed from ENDF/B-VII.1 to ENDF/B-VIII.0. Additionally, relevant thermal scattering law data libraries (TSLs) were updated. The sensitivity of the calculational bias of each benchmark model to these changes is discussed. Implementation of the ENDF/B-VIII.0 library and updated TSLs results in improvements to bias distribution in the intermediate enriched uranium, plutonium, and mixed uranium–plutonium (IEU, PU, and MIX) fissionable material benchmark categories, but a small bias increase in low- and high-enriched uranium categories (LEU and HEU, respectively). The results also highlight the sensitivity of the benchmarks, with average lethargy of neutrons causing fission energies (EALF) in the intermediate energy range to ENDF/B library changes. The most numerous bias changes were observed in the thermal energy region when transitioning from ENDF/B-VII.1 to ENDF/B-VIII.0. In conclusion, most of the unique bias changes observed in MCNP 6.3.0 between the two nuclear data libraries were in the LEU-COMP-THERM evaluation subset.

ICSBEP↗
DOE OSTI2023

Extraction of Neptunium, Plutonium, Americium, Zirconium, and Technetium by Di-(2-Ethylhexyl)- Iso -Butyramide (DEH i BA) at High Metal Loadings

Increased focus on carbon neutral energy has generated a resurgence of interest in nuclear power, and in particular advanced reactors which are likely to utilize high assay low enriched uranium (HALEU). This in turn could increase the economic attractiveness of recovering still partially enriched uranium from used nuclear fuel. Concomitant to development of advanced reactors, advanced reprocessing schemes should be developed which address the disadvantages to well established reprocessing schemes. The present study focuses on using di-(2-ethylhexyl)-iso-butyramide (DEHiBA) under high metal loading conditions for the reprocessing of used nuclear fuel. The elements examined in the study include the dominant transuranic actinides (Np, Pu, Am) as well as the often-problematic Tc and Zr. Further, by increasing the concentration of the extractant from the more commonly reported 1.0 M – 1.5 M, the extraction of hexavalent actinides is substantially increased, while maintaining effective rejection of tri, tetra, and pentavalent actinides, particularly in the presence of high loadings of uranium. In conclusion, the extraction of Zr by 1.5 M DEHiBA is noted to be negligible by comparison to tributyl phosphate (TBP), however the coextraction of Tc with U is observed to be nominally twice the quantity that is extracted by TBP indicating a need for effective Tc management.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Initial Neutronics Investigation of a Chlorine Salt-Based Breeder Blanket

Tritium breeding blankets within D-T-fueled fusion reactors contain lithium compounds and typically require neutron multiplier materials to achieve a tritium breeding ratio (TBR) consistent with self-sustaining operation. Liquid breeder blankets have some advantages over solid blankets, and previous blanket studies have investigated liquid metal as well as liquid salt–based blankets. Liquid salts have reduced magnetohydrodynamic effects as compared to liquid metals, but typically have a lower TBR. Recently, advanced fission reactor concepts have considered chloride-based salts in their design, and there is a significant amount of research work occurring to study these salts. Chloride salts have previously been considered for fusion reactors, but studies have typically found lower breeding ratios than for fluoride salts, such as 2(LiF)-BeF 2 (flibe) so they have not been further developed. In this work, we use a one-dimensional cylindrical radiation transport model of a conceptual tokamak fusion reactor to investigate the neutronics feasibility of using a chloride salt–based blanket that uses chlorine enriched in 37 Cl, which has both a low capture cross section and a substantial (n,2n) cross section. It is found that chloride salts (LiCl mixed with BeCl 2 and/or PbCl 2 ) can potentially achieve a ~3% to 5% higher TBR than fluoride molten salts, notably flibe, in the absence of a solid multiplier. Including a solid multiplier, however, does narrow this advantage, with TBRs estimated within ~1% of flibe with a 2-cm Be multiplier. Chloride salts can also reach lower melting points than flibe, potentially improving the scope for the use of reduced activation ferritic-martensitic steel as a structural material. There is substantial uncertainty in the calculations driven by limited thermochemical data for the Cl salts, plus cross-section uncertainties. The production of 36 Cl through 35 Cl(n,g) and 37 Cl(n,2n) has the potential to challenge the waste disposal rating of the blanket. Calculations indicate that, while this is not an immediate showstopper, this case depends upon the exact waste disposal rating criteria used for 36 Cl. Further work could reduce these uncertainties with improved thermochemical data, higher-fidelity modeling for downselected salts, and more refined waste disposal calculations and regulatory guidance. Lastly, it must be recognized that, as for all molten salts, corrosion and chemistry can present appreciable technical challenges that require further assessment in developing a practical blanket concept, and also that the enrichment of chlorine presents an additional technical and supply chain challenge.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Engineering a tumor-selective prodrug T-cell engager bispecific antibody for safer immunotherapy

T-cell engaging (TCE) bispecific antibodies are potent drugs that trigger the immune system to eliminate cancer cells, but administration can be accompanied by toxic side effects that limit dosing. TCEs function by binding to cell surface receptors on T cells, frequently CD3, with one arm of the bispecific antibody while the other arm binds to cell surface antigens on cancer cells. On-target, off-tumor toxicity can arise when the target antigen is also present on healthy cells. The toxicity of TCEs may be ameliorated through the use of pro-drug forms of the TCE, which are not fully functional until recruited to the tumor microenvironment. This can be accomplished by masking the anti-CD3 arm of the TCE with an autoinhibitory motif that is released by tumor-enriched proteases. Here, we solve the crystal structure of the antigen-binding fragment of a novel anti-CD3 antibody, E10, in complex with its epitope from CD3 and use this information to engineer a masked form of the antibody that can activate by the tumor-enriched protease matrix metalloproteinase 2 (MMP-2). We demonstrate with binding experiments and in vitro T-cell activation and killing assays that our designed prodrug TCE is capable of tumor-selective T-cell activity that is dependent upon MMP-2. Furthermore, we demonstrate that a similar masking strategy can be used to create a pro-drug form of the frequently used anti-CD3 antibody SP34. This study showcases an approach to developing immune-modulating therapeutics that prioritizes safety and has the potential to advance cancer immunotherapy treatment strategies.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

PROSPECT-II physics opportunities

We report the precision reactor oscillation and spectrum experiment, PROSPECT, has made world-leading measurements of reactor antineutrinos at short baselines. In its first phase, conducted at the high flux isotope reactor (HFIR) at Oak Ridge National Laboratory, PROSPECT produced some of the strongest limits on eV-scale sterile neutrinos, made a precision measurement of the reactor antineutrino spectrum from 235 U, and demonstrated the observation of reactor antineutrinos in an aboveground detector with good energy resolution and well-controlled backgrounds. The PROSPECT collaboration is now preparing an upgraded detector, PROSPECT-II, to probe yet unexplored parameter space for sterile neutrinos and contribute to a full resolution of the reactor antineutrino anomaly, a longstanding puzzle in neutrino physics. By pressing forward on the world’s most precise measurement of the 235 U antineutrino spectrum and measuring the absolute flux of antineutrinos from 235 U, PROSPECT-II will sharpen a tool with potential value for basic neutrino science, nuclear data validation, and nuclear security applications. Following a two-year deployment at HFIR, an additional PROSPECT-II deployment at a low enriched uranium reactor could make complementary measurements of the neutrino yield from other fission isotopes. PROSPECT-II provides a unique opportunity to continue the study of reactor antineutrinos at short baselines, taking advantage of demonstrated elements of the original PROSPECT design and close access to a highly enriched uranium reactor core.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Evaluation of silicon carbide as a divertor armor material in DIII-D H-mode discharges

Silicon carbide (SiC) represents a promising but largely untested plasma-facing material (PFM) for next-step fusion devices. In this work, an analytic mixed-material erosion model is developed by calculating the physical (via SDTrimSP) and chemical (via empirical scalings) sputtering yield from SiC, Si, and C. The Si content in the near-surface SiC layer is predicted to increase during D plasma bombardment due to more efficient physical and chemical sputtering of C relative to Si. Silicon erosion from SiC thereby occurs primarily from sputtering of the enriched Si layer, rather than directly from the SiC itself. SiC coatings on ATJ graphite, manufactured via chemical vapor deposition, were exposed to repeated H-mode plasma discharges in the DIII-D tokamak to test this model. The qualitative trends from analytic modeling are reproduced by the experimental measurements, obtained via spectroscopic inference using the S/XB method. Quantitatively the model slightly under-predicts measured erosion rates, which is attributed to uncertainties in the ion impact angle distribution, as well as the effect of edge-localized modes. After exposure, minimal changes to the macroscopic or microscopic surface morphology of the SiC coatings were observed. Compositional analysis reveals Si enrichment of about 10%, in line with expectations from the erosion model. Extrapolating to a DEMO-type device, an order-of-magnitude decrease in impurity sourcing, and up to a factor of 2 decrease in impurity radiation, is expected with SiC walls, relative to graphite, if low C plasma impurity content can be achieved. Furthermore, these favorable erosion properties motivate further investigations of SiC as a low-Z, non-metallic PFM.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Impurity leakage and radiative cooling in the first nitrogen and neon seeding study in the closed DIII-D SAS configuration

A comparative study of nitrogen versus neon has been carried out to analyze the impact of the two radiative species on power dissipation, SOL impurity distribution, divertor and pedestal characteristics. The experimental results show that N remains compressed in the divertor, thereby providing high radiative losses without affecting the pedestal profiles and displacing carbon as dominant radiator. Neon, instead, radiates more upstream than N thus reducing the power flux through the separatrix leading to a reduced ELM frequency and compression in the divertor. A significant amount of neon is measured in the plasma core leading to a steeper density gradient. The different behavior between the two impurities is confirmed by SOLPS-ITER modeling which for the first time at DIII-D includes multiple impurity species and a treatment of full drifts, currents and neutral–neutral collisions. The impurity transport in the SOL is studied in terms of the parallel momentum balance showing that N is mostly retained in the divertor whereas Ne leaks out consistent with its higher ionization potential and longer mean free path. This is also in agreement with the enrichment factor calculations which indicate lower divertor enrichment for neon. The strong ionization source characterizing the SAS divertor causes a reversal of the main ions and impurity flows. The flow reversal together with plasma drifts and the effect of the thermal force contribute significantly in the shift of the impurity stagnation point affecting impurity leakage. This work provides a demonstration of the impurity leakage mechanism in a closed divertor structure and the consequent impact on pedestal. Since carbon is an intrinsic radiator at DIII-D, in this paper we have also demonstrated the different role of carbon in the N vs Ne seeded cases both in the experiments and in the numerical modeling. Here, carbon contributes more when neon seeding is injected compared to when nitrogen is used. Finally, the results highlight the importance of accompanying experimental studies with numerical modeling of plasma flows, drifts and ionization profile to determine the details of the SOL impurity transport as the latter may vary with changes in divertor regime and geometry. In the cases presented here, plasma drifts and flow reversal caused by high level of closure in the slot upper divertor at DIII-D play an important role in the underlined mechanism.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Deuterium plasma induced preferential erosion in ultra-high temperature ceramics TiB 2 and ZrB 2 *

Abstract Steady-state deuterium plasma exposures were performed on ultra-high temperature ceramics titanium diboride (TiB 2 ) and zirconium diboride (ZrB 2 ) using the PISCES-RF linear plasma device (LPD) as early screening for first wall, plasma-facing applications. Deuterium plasma exposures were performed using 40 eV ion energies at 240, 525, and 800 °C sample temperatures and 90 eV ion energies at 240 °C sample temperatures to analyze TiB 2 and ZrB 2 surface morphology and chemistry evolution behavior. Post-plasma exposure chemistry characterization of the near surface ( < 50 nm) region of the samples all show transition metal enrichment, indicating boron preferential erosion. Transition metal to boron fractions vary with plasma exposure temperature under the 40 eV ion energy; metal enrichment is maximized at 800 °C and then minimized at 525 °C. SEM micrographs of all plasma exposed sample surfaces show no significant or noticeable plasma induced damage from cracking or blistering.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Improving streamflow predictions across CONUS by integrating advanced machine learning models and diverse data

Accurate streamflow prediction is crucial to understand climate impacts on water resources and develop effective adaption strategies. A global long short-term memory (LSTM) model, using data from multiple basins, can enhance streamflow prediction, yet acquiring detailed basin attributes remains a challenge. To overcome this, we introduce the Geo-vision transformer (ViT)-LSTM model, a novel approach that enriches LSTM predictions by integrating basin attributes derived from remote sensing with a ViT architecture. Applied to 531 basins across the Contiguous United States, our method demonstrated superior prediction accuracy in both temporal and spatiotemporal extrapolation scenarios. Geo-ViT-LSTM marks a significant advancement in land surface modeling, providing a more comprehensive and effective tool for better understanding the environment responses to climate change.

Tayal, Kshitij↗
DOE OSTI2025

Machine learning-powered data cleaning for LEGEND: a semi-supervised approach using affinity propagation and support vector machines

Neutrinoless double-beta decay ($0\nu\beta\beta$) is a rare nuclear process that, if observed, will provide insight into the nature of neutrinos and help explain the matter-antimatter asymmetry in the Universe. The large enriched germanium experiment for neutrinoless double-beta decay (LEGEND) will operate in two phases to search for $0\nu\beta\beta$. The first (second) stage will employ 200 (1000) kg of High-Purity Germanium (HPGe) enriched in 76 Ge to achieve a half-life sensitivity of 10 27 (10 28 ) years. In this study, we present a semi-supervised data-driven approach to remove non-physical events captured by HPGe detectors powered by a novel artificial intelligence model. We utilize affinity propagation to cluster waveform signals based on their shape and a support vector machine to classify them into different categories. We train, optimize, and test our model on data taken from a natural abundance HPGe detector installed in the Full Chain Test experimental stand at the University of North Carolina at Chapel Hill. We demonstrate that our model yields a maximum sacrifice of physics events of $0.024 ^{+0.004}_{-0.003} \%$ after data cleaning. Our model is being used to accelerate data cleaning development for LEGEND-200 and will serve to improve data cleaning procedures for LEGEND-1000.

artificial intelligence↗
DOE OSTI2024

Genome-resolved analysis of Serratia marcescens strain SMTT infers niche specialization as a hydrocarbon-degrader

Abstract Bacteria that are chronically exposed to high levels of pollutants demonstrate genomic and corresponding metabolic diversity that complement their strategies for adaptation to hydrocarbon-rich environments. Whole genome sequencing was carried out to infer functional traits of Serratia marcescens strain SMTT recovered from soil contaminated with crude oil. The genome size (Mb) was 5,013,981 with a total gene count of 4,842. Comparative analyses with carefully selected S. marcescens strains, 2 of which are associated with contaminated soil, show conservation of central metabolic pathways in addition to intra-specific genetic diversity and metabolic flexibility. Genome comparisons also indicated an enrichment of genes associated with multidrug resistance and efflux pumps for SMTT. The SMTT genome contained genes that enable the catabolism of aromatic compounds via the protocatechuate para-degradation pathway, in addition to meta-cleavage of catechol (meta-cleavage pathway II); gene enrichment for aromatic compound degradation was markedly higher for SMTT compared to the other S. marcescens strains analysed. Our data presents a valuable genetic inventory for future studies on strains of S. marcescens and provides insights into those genomic features of SMTT with industrial potential.

Genetics & Heredity↗
DOE OSTI2020

Insights into community of photosynthetic microorganisms from permafrost

ABSTRACT This work integrates cultivation studies of Siberian permafrost and analyses of metagenomes from different locations in the Arctic with the aim of obtaining insights into the community of photosynthetic microorganisms in perennially frozen deposits. Cyanobacteria and microalgae have been described in Arctic aquatic and surface soil environments, but their diversity and ability to withstand harsh conditions within the permafrost are still largely unknown. Community structure of photosynthetic organisms in permafrost sediments was explored using Arctic metagenomes available through the MG-RAST. Sequences affiliated with cyanobacteria represented from 0.25 to 3.03% of total sequences, followed by sequences affiliated with Streptophyta (algae and vascular plants) 0.01–0.45% and Chlorophyta (green algae) 0.01–0.1%. Enrichment and cultivation approaches revealed that cyanobacteria and green algae survive in permafrost and they could be revived during prolonged incubation at low light intensity. Among photosynthetic microorganisms isolated from permafrost, the filamentous Oscillatoria-like cyanobacteria and unicellular green algae of the genus Chlorella were dominant. Our findings suggest that permafrost cyanobacteria and green algae are expected to be effective members of the re-assembled community after permafrost thawing and soil collapse.

Vishnivetskaya, Tatiana A.↗
DOE OSTI2021

Democratization of fungal highway columns as a tool to investigate bacteria associated with soil fungi

ABSTRACT Bacteria–fungi interactions (BFIs) are essential in ecosystem functioning. These interactions are modulated not only by local nutritional conditions but also by the physicochemical constraints and 3D structure of the environmental niche. In soils, the unsaturated and complex nature of the substrate restricts the dispersal and activity of bacteria. Under unsaturated conditions, some bacteria engage with filamentous fungi in an interaction (fungal highways) in which they use fungal hyphae to disperse. Based on a previous experimental device to enrich pairs of organisms engaging in this interaction in soils, we present here the design and validation of a modified version of this sampling system constructed using additive printing. The 3D printed devices were tested using a novel application in which a target fungus, the common coprophilous fungus Coprinopsis cinerea, was used as bait to recruit and identify bacterial partners using its mycelium for dispersal. Bacteria of the genera Pseudomonas, Sphingobacterium and Stenotrophomonas were highly enriched in association with C. cinerea. Developing and producing these new easy-to-use tools to investigate how bacteria overcome dispersal limitations in cooperation with fungi is important to unravel the mechanisms by which BFIs affect processes at an ecosystem scale in soils and other unsaturated environments.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

¡Viva la mitochondria!: harnessing yeast mitochondria for chemical production

ABSTRACT The mitochondria, often referred to as the powerhouse of the cell, offer a unique physicochemical environment enriched with a distinct set of enzymes, metabolites and cofactors ready to be exploited for metabolic engineering. In this review, we discuss how the mitochondrion has been engineered in the traditional sense of metabolic engineering or completely bypassed for chemical production. We then describe the more recent approach of harnessing the mitochondria to compartmentalize engineered metabolic pathways, including for the production of alcohols, terpenoids, sterols, organic acids and other valuable products. We explain the different mechanisms by which mitochondrial compartmentalization benefits engineered metabolic pathways to boost chemical production. Finally, we discuss the key challenges that need to be overcome to expand the applicability of mitochondrial engineering and reach the full potential of this emerging field.

Biotechnology & Applied Microbiology↗
DOE OSTI2024

Harnessing the predicted maize pan-interactome for putative gene function prediction and prioritization of candidate genes for important traits

Abstract The recent assembly and annotation of the 26 maize nested association mapping population founder inbreds have enabled large-scale pan-genomic comparative studies. These studies have expanded our understanding of agronomically important traits by integrating pan-transcriptomic data with trait-specific gene candidates from previous association mapping results. In contrast to the availability of pan-transcriptomic data, obtaining reliable protein–protein interaction (PPI) data has remained a challenge due to its high cost and complexity. We generated predicted PPI networks for each of the 26 genomes using the established STRING database. The individual genome-interactomes were then integrated to generate core- and pan-interactomes. We deployed the PPI clustering algorithm ClusterONE to identify numerous PPI clusters that were functionally annotated using gene ontology (GO) functional enrichment, demonstrating a diverse range of enriched GO terms across different clusters. Additional cluster annotations were generated by integrating gene coexpression data and gene description annotations, providing additional useful information. We show that the functionally annotated PPI clusters establish a useful framework for protein function prediction and prioritization of candidate genes of interest. Our study not only provides a comprehensive resource of predicted PPI networks for 26 maize genomes but also offers annotated interactome clusters for predicting protein functions and prioritizing gene candidates. The source code for the Python implementation of the analysis workflow and a standalone web application for accessing the analysis results are available at https://github.com/eporetsky/PanPPI.

Genetics & Heredity↗