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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 163 records · Page 9

Thermo-Hydro-Mechanical Modeling of Brine Migration in a Heated Borehole Test in Bedded Salt

Abstract This research paper focuses on the thermo-hydro-mechanical (THM) modeling of brine migration in a heated borehole test conducted as part of the ongoing Brine Availability Test in Salt (BATS) at the Waste Isolation Pilot Plant (WIPP) in New Mexico. It is a component of the international collaboration project DECOVALEX-2023 (DEvelopment of COupled models and their VALidation against EXperiments), which aims to understand the THM processes governing brine flow in heated rock salt repositories through collaborative analysis by multiple research teams. Using the TOUGH–FLAC simulator, THM simulations were performed and compared with data from the BATS phase 1a. This experiment involved two identical horizontal-borehole arrays, one heated and one serving as a control, both equipped with sensor arrays. Analysis of measurements revealed water flow rate surges during heater power transitions, with the highest jump observed during cooling. Acoustic emission activity exhibited distinct patterns in response to heater power changes, suggesting that damage to rock salt is particularly pronounced during the cooling phase. The THM simulations successfully captured these phenomena, highlighting the significance of thermal effects, brine migration, and mechanical behavior in predicting brine availability in heated and damaged rock salt. Our modeling also revealed the critical interplay between heating and cooling-induced damage and its influence on flow properties, particularly affecting brine inflow estimation. Notably, we found that cooling-induced brine inflow spikes result from increased permeability due to tensile dilatancy. These findings have important implications for the development of robust containment strategies and enhance our understanding of the complex processes involved in repository performance.

58 GEOSCIENCES↗

Development of The DOME Shield Model For The NRIC Virtual Test Bed

As several advanced reactor concepts are maturing, test beds are needed to accelerate the demonstration and deployment of these advanced nuclear technologies. The National Reactor Innovation Center (NRIC) is building new or enhancing existing US Department of Energy infrastructure to support testing of components and systems. Demonstration of Microreactor Experiments (DOME) will utilize the Experimental Breeder Reactor-II (EBR-II) dome containment structure to host reactor demonstrations. A reactor supplemental shielding is needed so that DOME dose requirements are met. To accelerate the confirmatory analysis required for the reactor demonstration, the NRIC Virtual Test Bed (VTB) is developing a virtual model of the DOME shield that will be made available on the VTB public repository. This will allow developers to leverage advanced modeling and simulation tools to ensure their reactor demonstration concept will meet dose requirement and the limit concrete temperature in the shield during steady state and transient operation conditions. This paper presents the model developed for the DOME shield using open-source tools: MOOSE heat transfer module, Monte Carlo code OpenMC, and Cardinal to calculate the DOME shield temperature distribution during steady state

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

Reproducible benchmark for the SNAP 8 experimental reactor at dry conditions

Here, this work provides fully reproducible benchmark models of the Systems for Nuclear Auxiliary Power (SNAP) 8 Experimental Reactor. Validation benchmarks of the criticality configuration experiments under dry conditions with no coolant are presented. In addition, relevant reactivity worth experiments, and measurement of power distributions are validated and presented here. Discrepancies between modeled and experimental results are at most 110 pcm for fuel and poison worths, and critical configurations that do not manipulate control elements are within 50 pcm. Larger discrepancies found in reflector element worth experiments are due to experimental methodology which was noted as being simplified due to limited calculational capabilities at the time, while discrepancy in the control element manipulated critical configuration is due the absence of structural components for modeling simplification. Power distributions closely follow what was observed in experiment with expected peaking in reflecting elements. All models are well documented with cited references describing and justifying assumptions, simplifications, and adjustments to reproduce the models with any nuclear safety codes; model inputs and outputs are stored in the snapReactors GitHub repository.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Machine Learning Full NMR Chemical Shift Tensors of Silicon Oxides with Equivariant Graph Neural Networks

The nuclear magnetic resonance (NMR) chemical shift tensor is a highly sensitive probe of the electronic structure of an atom and furthermore its local structure. Recently, machine learning has been applied to NMR in the prediction of isotropic chemical shifts from a structure. Current machine learning models, however, often ignore the full chemical shift tensor for the easier-to-predict isotropic chemical shift, effectively ignoring a multitude of structural information available in the NMR chemical shift tensor. Here we use an equivariant graph neural network (GNN) to predict full 29 Si chemical shift tensors in silicate materials. The equivariant GNN model predicts full tensors to a mean absolute error of 1.05 ppm and is able to accurately determine the magnitude, anisotropy, and tensor orientation in a diverse set of silicon oxide local structures. When compared with other models, the equivariant GNN model outperforms the state-of-the-art machine learning models by 53%. The equivariant GNN model also outperforms historic analytical models by 57% for isotropic chemical shift and 91% for anisotropy. The software is available as a simple-to-use open-source repository, allowing similar models to be created and trained with ease.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Transformation of Ferrihydrite to Goethite and the Fate of Plutonium

Understanding the interactions between plutonium and iron (oxy)hydroxide minerals is necessary to gain a predictive understanding of plutonium environmental mobility and to evaluate long-term performance of nuclear waste repositories. We investigated the fate of plutonium during the formation of ferrihydrite and its subsequent transformation into goethite. Ferrihydrite was synthesized with varying quantities of Pu(IV) following either a sorption or coprecipitation process; the ferrihydrite was then aged hydrothermally to yield goethite. Additionally, the synthesized materials were characterized via extended X-ray absorption fine structure spectroscopy, transmission electron microscopy, and acid leaching to elucidate the nature of plutonium association with ferrihydrite and goethite. In samples prepared following the sorption method, plutonium was identified in two different forms: a PuO 2 precipitate and a surface-sorbed plutonium complex. For the samples prepared via coprecipitation, no PuO 2 formation occurs in the ferrihydrite precursor and in the goethite experiments where plutonium concentration is ≤1000 ppm (mg kg –1 ). In these coprecipitation products, plutonium is strongly bound to the minerals either via formation of an inner sphere complex, or via an incorporation process. In the coprecipitation experiments, PuO 2 formation only occurs at the highest plutonium concentration (3000 ppm), suggesting that during ferrihydrite transformation into goethite, part of the plutonium can be remobilized to form PuO 2 nanoparticles. Collectively, our results demonstrate that the nature of plutonium associated with the precursor ferrihydrite (adsorbed vs coprecipitated) will have a direct impact on the association of plutonium with its alteration product (goethite). Furthermore, the data illustrate that some properties of plutonium association with the precursor ferrihydrite are retained through the transformation into goethite. These findings show that plutonium strongly associates with iron (oxy)hydroxides formed through coprecipitation processes and in these materials, plutonium can be strongly retained by the iron minerals.

54 ENVIRONMENTAL SCIENCES↗

Data for "Plasmon-driven exciton formation in a non-equilibrium Fermi liquid"

This repository contains source data for key plots presented in the manuscript "Plasmon-driven exciton formation in a non-equilibrium Fermi liquid." Experimental data that was analyzed in Igor Pro 8 are presented as the .pxp files used to generate individual sub-plots. Electronic spectral function calculations are provided as .txt files, in which consecutive rows refer to the meshgrid x coordinate, y coordinate, spectral function (and, where relevant, axis-projected local angular momentum). We additionally include the Wannier model and DFT-obtained bulk band structure on which the Wannier model was based. Files are named as the number of the figure in the manuscript to which they correspond, with additional details included where necessary. Details of file names: 2a_DOS_Lxz_Ek_KGM_40layer_xnum_800kpt_tot.txt: Density of states, xz-axis projected local orbital angular momentum, for 800 points along the K-Gamma-M path, for a 40-layer model. 2c_composite_y.pxp: ARPES (angle-resolved photoemission spectroscopy) spectra along the ky axis, including both a scan near the Fermi level and a scan at high kinetic energies. 2d_LCP_RCP_diff_Sect_20K.pxp: difference between ARPES constant energy cuts at T=20 K at E0 + 0.23 eV taken with left- and right-circularly polarized photons. The polarization-integrated intensity at the constant energy cut is also included. 2e_DOS_L45_E11pt79_m0pt25to0pt25_xnum_800kpt_tot.txt: Density of states, xz-projected local orbital angular momentum, and corresponding k-points in two dimensions from ab-initio electronic structure calculations for a constant-energy cut. 3a_[x]_[y]ps: ARPES cut under excitation at a fluence of x uJ/cm2, measured y ps after photoexcitation. Measurements were performed at 9 K. 3b_[x]: Energy distribution curves under excitation at a fluence x uJ/cm2 at selected delay times after photoexcitation. 4a_ImSigma_vs_temperature.pxp: Imaginary self energy (extracted from ARPES linewidths) at different energies above E0 for selected lattice temperatures. 4b_EELS_lowE.pxp: Electron energy loss spectrum over a low energy range 5b_diff_55m15.pxp: Difference between momentum-integrated Tr-ARPES traces at 55 uJ/cm2 and 15 uJ/cm2 photoexcitation. Time-dependent intensity at each energy level has been normalized to a maximum of 1 for each individual fluence prior to subtraction. 5d_invtau_at_EX_vs_fluence.pxp: decay rate at a specified energy EX for different excitation fluences, from single exponential fits. NOTE: Analyses based on the Wannier model presented here should cite both the associated Article and this dataset. For all other files in the repository, citing the dataset alone is sufficient.

Acharya, Rishi [University of Illinois] (ORCID:000↗

Comparability of Liquid Chromatography Tandem Mass Spectrometry Analysis of Dissolved Organic Matter across Laboratories

Non-targeted liquid chromatography tandem highresolution mass spectrometry (LC−MS/MS) is increasingly applied for the structure-resolved chemical analysis of dissolved organic matter (DOM). With new developments in MS instrumentation and analysis software, the approach has gained substantial momentum over the past decade. However, achieving high-quality analytical data that is reproducible and comparable across laboratories can be a bottleneck in non-targeted metabolomics and organic matter chemical analysis, especially for data reuse in repository-scale analyses. Understanding the capabilities as well as challenges of comparing LC−MS/MS data from different laboratories is necessary for inferring global trends from public data sets. To illuminate instrumentation factors that drive differences and variability, we used a standardized data analysis pipeline, including classical (CMN) and featurebased molecular networking (FBMN), to analyze data from a ring trial by 24 laboratories on identical sample sets of algal and DOM extracts that were mixed in predefined concentrations and spiked with standards. Our results showed that data sets from similar mass spectrometer types with unified instrument parameters were qualitatively comparable, resolving the same general trends and shared mass spectral features. Interlaboratory comparability was best for high-intensity features, while low-intensity features showed greater detection variability. Our analysis also highlights challenges when comparing data from instruments with different acquisition rates or operating with less standardized methods. Lastly, we provide recommendations for data integration, public data sharing, standardization, and best practices for standardized LC−MS/MS data acquisition, which will be critical for long-term time series and intercomparability of DOM chemical analyses.

DOM↗

LLM Generation of Online Courses from a Curated Set of Documents in the Nuclear Safeguards Domain

A multidisciplinary team at Argonne National Laboratory explores the application of advanced technologies to enhance knowledge transfer and retention within the nuclear safeguards domain. Specifically, it examines the feasibility of leveraging secure large language models (LLMs) to streamline the creation of e-learning modules for the U.S. National Nuclear Security Administration (NNSA) Office of International Nuclear Safeguards (NA-241). The initiative addresses the critical need for preserving institutional memory and accelerating skill development amidst the imminent retirement of senior professionals in the field in addition to supporting good knowledge management practices. The project integrates instructional design theory with cutting-edge AI technologies to transform curated document sets from the Safeguards Knowledge Repository (SKR) into modular online courses. By automating the generation of learning objectives and instructional content, the effort aims to reduce manual effort while maintaining high-quality educational outcomes. A limited measure of human supervision, however, ensures accuracy, relevance, and alignment with NNSA’s strategic priorities. Key findings highlight the potential of AI-assisted course generation to support safeguards professionals by creating structured, interactive learning experiences. The report underscores the importance of SME validation to address limitations in AI-generated content, such as terminology errors and gaps in coverage. Recommendations include adopting a structured workflow combining LLM acceleration with expert oversight to ensure accuracy, usability, and alignment with learner needs. This work demonstrates Argonne’s commitment to advancing national security and scientific excellence through innovative knowledge management solutions.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Evaluation of Nuclear Spent Fuel Disposal in Clay-Bearing Rock - Process Model Development and Experimental Studies

This report represents the milestone deliverable M2SF-23SN010301072 “Evaluation of Nuclear Spent Fuel Disposal in Clay-Bearing Rock - Process Model Development and Experimental Studies” The report provides a status update of FY23 activities for the work package Argillite Disposal work packages for the DOE-NE Spent Fuel Waste Form Science and Technology (SFWST) Program. Clay-rich geological media (often referred as shale or argillite) are among the most abundant type of sedimentary rock near the Earth’s surface. Argillaceous rock formations have the following advantageous attributes for deep geological nuclear waste disposal: widespread geologic occurrence, found in stable geologic settings, low permeability, self-sealing properties, low effective diffusion coefficient, high sorption capacity, and have the appropriate depth and thickness to host nuclear waste repository concepts. The DOE R&D program under the Spent Fuel Waste Science Technology (SFWST) campaign has made key progress (through experiment, modeling, and testing) in the study of chemical and physical phenomena that could impact the long-term safety assessment of heat-generating nuclear waste disposition in clay/shale/argillaceous rock. International collaboration activities comprising field-scale heater tests, field data monitoring, and laboratory-scale experiments provide key information on changes to the engineered barrier system (EBS) material exposed high thermal loads. Moreover, consideration of direct disposal of large capacity dual-purpose canisters (DPCs) as part of the back-end SNF waste disposition strategy has generated interest in improving our understanding of the effects of elevated temperatures on the engineered barrier system (EBS) design concepts. Chemical and structural analyses of sampled bentonite material from laboratory tests at elevated temperatures are key to the characterization of thermal effects affecting bentonite clay barrier performance. The knowledge provided by these experiments is crucial to constrain the extent of sacrificial zones in the EBS design during the thermal period. Thermal, hydrologic, mechanical, and chemical (THMC) data collected from heater tests and laboratory experiments have been used in the development, validation, and calibration of THMC simulators to model near-field coupled processes. This information leads to the development of simulation approaches to assess issues on coupled processes involving porous media flow, transport, geomechanical phenomena, chemical interactions with barrier/geologic materials, and the development of EBS concepts. These lines of knowledge are central to the design of deep geological backfilled repository concepts where temperature plays a key role in the EBS behavior, potential interactions with host rock, and long-term performance in the safety assessment.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Human readiness levels and Human Views as tools for user-centered design

The Human Readiness Level (HRL) scale is a simple nine-level scale that brings structure and consistency to the real-world application of user-centered design. It enables multidisciplinary consideration of human-focused elements during the system development process. Use of the standardized set of questions comprising the HRL scale results in a single human readiness number that communicates system readiness for human use. The Human Views (HVs) are part of an architecture framework that provides a repository for human-focused system information that can be used during system development to support the evaluation of HRL levels. Here, this paper illustrates how HRLs and HVs can be used in combination to support user-centered design processes. A real-world example for a U.S. Army software modernization program is described to demonstrate application of HRLs and HVs in the context of user-centered design.

42 ENGINEERING↗

EXCHANGE Campaign 1: A Community-Driven Baseline Characterization of Soils, Sediments, and Water Across Coastal Gradients

The EXploration of Coastal Hydrobiogeochemistry Across a Network of Gradients and Experiments (EXCHANGE) program is a consortium of scientists working together to improve our understanding of how the two-way exchange of water between estuaries or large lake lacustuaries and the terrestrial landscape influence the state and function of ecosystems across the coastal interface. EXCHANGE Campaign 1 (EC1) focuses on the spatial variation in biogeochemical structure and function at the coastal terrestrial-aquatic interface (TAI). In the Fall of 2021, the EXCHANGE Consortium gathered samples from 52 TAIs. Samples collected from EC1 were analyzed for bulk geochemical parameters, bulk physicochemical parameters, organic matter characteristics, and redox-sensitive elements.Please download ec1_README.pdf for a complete list of available data in each .zip folder, package version history, and detailed information about the project. This README will serve as the central place for EC1 Data Package updates. Experimental setup and v1 methods are documented in Myers-Pigg and Pennington et al., 2023 (https://doi.org/10.1038/s41597-023-02548-7).EC1 Data Package Structure:ec1_README.pdfec1_methods.pdfec1_metadata_v3.zip...ec1_dd.csv...ec1_flmd.csv...ec1_sample_catalog.csv...ec1_metadata_kitlevel.csv...ec1_metadata_collectionlevel.csv...ec1_data_collectionlevel.csv...ec1_igsn_metadata.csvec1_soil_v3.zipec1_sediment_v3.zipec1_water_v3.zipec1_processingscripts_v3.zipThis data package is on v3 and was originally published May 2023 (v1). Subsequent updates will be published here with new version numbers. Please see the Change History section in ec1_README.pdf for detailed changes.---Acknowledging EXCHANGE: General Support and Data Product UseWe ask that users of EXCHANGE data add the following acknowledgement when publishing data in scholarly articles and data repositories:"This research is based on work supported by COMPASS-FME, a multi-institutional project supported by the U.S. Department of Energy, Office of Science, Biological and Environmental Research as part of the Environmental System Science Program."

54 ENVIRONMENTAL SCIENCES↗

Urban Parameters Maricopa County 100m Grid Spacing

132 urban parameters for Maricopa County are provided in WRF-readable binary form at 100m grid spacing with index. These parameters allow regional weather modelers to account for the contribution of built structures in modeling the urban heat island. This data is also provided in CSV format. Data are generated using 2023 Model America Version 1 data (https://www.osti.gov/biblio/1774134) and will be used to represent the urban morphology in Maricopa County to the WRF model for experiments conducted for the Southwest Urban Corridor Integrated Field Laboratory (SW-IFL). Three files associated with these parameters are included in this repository: index, binary file 00001-01549.00001-01796, Maricopa_Parameters_03072024.csv . To use the binary file with the Weather Research and Forecasting (WRF) model, the binary file and the index file must be placed in their own directory in WRF_GEOG and accessed in the same way the National Urban Database and Access Portal Tool data (NUDAPT44) would be accessed. The name of the binary file must be in the format: 00001-02715.00001-01803. If, upon download, the binary filename has additional or different characters, please change them to match this format.

54 ENVIRONMENTAL SCIENCES↗

Improving the Accessibility and Usability of Geothermal Information with Data Lakes and Data Pipelines on the Geothermal Data Repository: Preprint

The Geothermal Data Repository (GDR) provides universal access to data and information resulting from research and development activities funded by the Department of Energy (DOE). The GDR has extended this universal access to big data through integration with data lakes developed by the Open Energy Data Initiative (OEDI). Previously, large datasets such as seismic waveform or distributed acoustic sensing (DAS) data could only be accessed by institutions with high performance data storage and compute capabilities, effectively limiting the accessibility of big data to national labs, larger universities, and major corporations. Moreover, the time and resources needed to transport big data and configure them can produce additional barriers to use. Many of the standard formats used for structured data models (also known as content models) are incapable of handling big data and can introduce additional usability problems, often requiring data to be reformatted prior to use. This paper will explore how recent integrations between the GDR and the OEDI data lake have improved the accessibility and usability of geothermal data in a big way, making the data available to a broader audience, and enabling collaborative analysis and innovation across the greater geothermal industry.

access↗

Improving the Accessibility and Usability of Geothermal Information with Data Lakes and Data Pipelines on the Geothermal Data Repository

The Geothermal Data Repository (GDR) provides universal access to data and information resulting from research and development activities funded by the Department of Energy (DOE). The GDR has extended this universal access to big data through integration with data lakes developed by the Open Energy Data Initiative (OEDI). Previously, large datasets such as seismic waveform or distributed acoustic sensing (DAS) data could only be accessed by institutions with high performance data storage and compute capabilities, effectively limiting the accessibility of big data to national labs, larger universities, and major corporations. Moreover, the time and resources needed to transport big data and configure them can produce additional barriers to use. Many of the standard formats used for structured data models (also known as content models) are incapable of handling big data and can introduce additional usability problems, often requiring data to be reformatted prior to use. This paper will explore how recent integrations between the GDR and the OEDI data lake have improved the accessibility and usability of geothermal data in a big way, making the data available to a broader audience, and enabling collaborative analysis and innovation across the greater geothermal industry.

access↗

Network Analysis of Academic Medical Center Websites in the United States

Healthcare resources are published annually in repositories such as the AHA Annual Survey Database TM . However, these data repositories are created via manual surveying techniques which are cumbersome in collection and not updated as frequently as website information of the respective hospital systems represented. Also, this resource is not widely available to patients in an easy-to-use format. Network analysis techniques have the potential to create topological maps which serve to aid in pathfinding for patients in their search for healthcare services. This study explores the topological structure of forty United States academic health center websites. Network analysis is utilized to analyze and visualize 48,686 webpages. Several elements of network structure are examined including basic network properties, and centrality measures distributions. The Louvain community detection algorithm is used to examine the extent to which these techniques allow identification of healthcare resources within networks. The results indicate that websites with related healthcare services tend to form observable clusters useful in mapping key resources within a hospital system.

97 MATHEMATICS AND COMPUTING↗

Microbial Influence on the Mobility of +3 Actinides from a Salt-Based Nuclear Waste Repository

Biologically enhanced transport of radionuclides is one of several processes that can affect the performance of a nuclear waste repository. In this work, several microbial isolates from the Waste Isolation Pilot Plant (WIPP) were tested for their influence on the concentration of neodymium, as an analog for +3 actinides, in simple sodium chloride solutions and in anoxic WIPP brines. Batch sorption experiments were carried out over a period of 4–5 weeks. In many cases, the effect on neodymium in solution was immediate and extensive and assumed to be due to surface complexation. However, over time, the continued loss of Nd from the solution was more likely due to biologically induced precipitation and/or mineralization and possible entrapment in extracellular polymeric substances. The results showed no correlation between organism type and the extent of its influence on neodymium in solution. However, a correlation was observed between different test matrices (simple NaCl versus high-magnesium brine versus high-NaCl brine). Further experiments were conducted to test these matrix effects, and the results showed a significant effect of magnesium concentration on the ability of microorganisms to remove Nd from solution. Possible mechanisms include cation competition and the alteration of cell surface structures. This suggests that the aqueous chemistry of the WIPP environs could play a larger role in the final disposition of +3 actinides than the microbiology.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Open access repository-scale propagated nearest neighbor suspect spectral library for untargeted metabolomics

Despite the increasing availability of tandem mass spectrometry (MS/MS) community spectral libraries for untargeted metabolomics over the past decade, the majority of acquired MS/MS spectra remain uninterpreted. To further aid in interpreting unannotated spectra, we created a nearest neighbor suspect spectral library, consisting of 87,916 annotated MS/MS spectra derived from hundreds of millions of MS/MS spectra originating from published untargeted metabolomics experiments. Entries in this library, or “suspects,” were derived from unannotated spectra that could be linked in a molecular network to an annotated spectrum. Annotations were propagated to unknowns based on structural relationships to reference molecules using MS/MS-based spectrum alignment. We demonstrate the broad relevance of the nearest neighbor suspect spectral library through representative examples of propagation-based annotation of acylcarnitines, bacterial and plant natural products, and drug metabolism. Our results also highlight how the library can help to better understand an Alzheimer’s brain phenotype. The nearest neighbor suspect spectral library is openly available for download or for data analysis through the GNPS platform to help investigators hypothesize candidate structures for unknown MS/MS spectra in untargeted metabolomics data.

59 BASIC BIOLOGICAL SCIENCES↗

Challenges and Vision for Standardization of Biopolymer Data Sets for Machine Learning

Machine learning (ML) is transforming materials research, yet potential for biopolymer discovery remains constrained by fragmented data and nonstandardized reporting. Biopolymers differ significantly from synthetic polymers, requiring specialized approaches to represent their biosynthetic origins, hierarchical structures, and application-specific metrics. In this Perspective, we identify three core challenges limiting biopolymer representation: information encoding, data quality, and data sharing. We describe the most pressing issues and propose commensurate approaches to address each key challenge. Recommendations include the design and adoption of biopolymer-specific fingerprinting and representation frameworks, development of hybrid human-large language model (LLM) data extraction strategies, and expanding Findable, Accessible, Interoperable, Reusable (FAIR)-compliant repositories. We propose a robust foundation to define interoperable, high-quality data sets that capture the full context of biopolymer materials. Standardized metadata, shared ontologies, and community-driven infrastructure would enable scalable, reproducible workflows and accelerate the ML-driven development of biopolymers.

36 MATERIALS SCIENCE↗