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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Electrochemical Proton Insertion Modulates the Hydrogen Evolution Reaction on Tungsten Oxides

Development of new electrocatalysts for the hydrogen evolution reaction (HER) could reduce dependence on Pt and other rare metals and enable large-scale production of hydrogen with near-zero carbon emissions. Mechanistic insight into the electrocatalytic activity of a material helps to accelerate the development of new electrocatalysts. Alternative electrocatalyst materials such as transition metal oxides and sulfides can undergo insertion reactions that change their properties. Recent reports indicate that the presence of inserted ions can influence electrocatalytic activity. In this work, we utilized a materials chemistry approach to understand the role of proton insertion on the HER activity of layered tungsten oxide hydrates (WO 3 ∙xH 2 O, x = 1, 2). We synthesized a series of tungsten oxide hydrates along with an octylamine-pillared tungsten oxide (OA-WO 3 ). We used cyclic voltammetry to study the electrochemical reactivity of each material and performed ex situ X-ray diffraction and Raman spectroscopy to understand bulk and surface structural changes during electrochemical cycling. We show an inverse relationship between the degree of proton insertion and HER overpotential in tungsten oxides: the lack of proton insertion leads to a high overpotential for the HER. We discuss three hypotheses for how proton insertion leads to HER activity in WO 3 ∙xH 2 O: 1) proton insertion changes the electronic band structure of WO 3 ∙xH 2 O, 2) the presence of bulk protons can influence ΔG H,ads at the surface sites, and 3) inserted protons may participate in the HER mechanism on WO 3 ∙xH 2 O. Overall, this work shows the critical role of proton insertion in enabling high HER activity in tungsten oxides.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2013

High-Pressure Lightweight Thrusters

Returning samples of Martian soil and rock to Earth is of great interest to scientists. There were numerous studies to evaluate Mars Sample Return (MSR) mission architectures, technology needs, development plans, and requirements. The largest propulsion risk element of the MSR mission is the Mars Ascent Vehicle (MAV). Along with the baseline solid-propellant vehicle, liquid propellants have been considered. Similar requirements apply to other lander ascent engines and reaction control systems. The performance of current state-ofthe- art liquid propellant engines can be significantly improved by increasing both combustion temperature and pressure. Pump-fed propulsion is suggested for a single-stage bipropellant MAV. Achieving a 90-percent stage propellant fraction is thought to be possible on a 100-kg scale, including sufficient thrust for lifting off Mars. To increase the performance of storable bipropellant rocket engines, a high-pressure, lightweight combustion chamber was designed. Iridium liner electrodeposition was investigated on complex-shaped thrust chamber mandrels. Dense, uniform iridium liners were produced on chamber and cylindrical mandrels. Carbon/carbon composite (C/C) structures were braided over iridium-lined mandrels and densified by chemical vapor infiltration. Niobium deposition was evaluated for forming a metallic attachment flange on the carbon/ carbon structure. The new thrust chamber was designed to exceed state-of-the-art performance, and was manufactured with an 83-percent weight savings. High-performance C/Cs possess a unique set of properties that make them desirable materials for high-temperature structures used in rocket propulsion components, hypersonic vehicles, and aircraft brakes. In particular, more attention is focused on 3D braided C/Cs due to their mesh-work structure. Research on the properties of C/Cs has shown that the strength of composites is strongly affected by the fiber-matrix interfacial bonding, and that weakening interface realizes pseudo-plastic behavior with significant increase in the tensile strength. The investigation of high-temperature strength of C/Cs under high-rate heating (critical for thrust chambers) shows that tensile and compression strength increases from 70 MPa at room temperature to 110 MPa at 1,773 K, and up to 125 MPa at 2,473 K. Despite these unique properties, the use of C/Cs is limited by its high oxidation rate at elevated temperatures. Lining carbon/carbon chambers with a thin layer of iridium or iridium and rhenium is an innovative way to use proven refractory metals and provide the oxidation barrier necessary to enable the use of carbon/ carbon composites. Due to the lower density of C/Cs as compared to SiC/SiC composites, an iridium liner can be added to the C/C structure and still be below the overall thruster weight. Weight calculations show that C/C, C/C with 50 microns of Ir, and C/C with 100 microns of Ir are of less weight than alternative materials for the same construction.

Holmes, Richard↗
DOE OSTI2025

ZnTiN 2 as an Electron-Selective, Protective Layer on Si Photocathodes

Photoelectrochemical production of fuels requires photoelectrodes that efficiently convert sunlight to electrochemical energy by producing photovoltage and photocurrent and maintain this ability over time under a variety of pH, illumination, and applied bias conditions. Work in the photovoltaic community has demonstrated that interfaces with high charge carrier selectivity provide high photovoltages. This offers a co-design opportunity to create semiconductor photoelectrodes with contact layers that are both carrier-selective and offer protection from degradation in aqueous solutions. In this work, we explored the ternary nitride ZnTiN 2 as an electronselective, protective layer for Si-based photocathodes. We demonstrated that ZnTiN 2 formed a heterojunction with p-type Si that facilitated electron movement toward the ZnTiN 2 surface for light-driven reduction reactions. Across a variety of electrolyte conditions, ZnTiN 2 /Si produced an open circuit voltage of ca. 400 mV vs the solution potential, while bare Si produced 220−480 mV vs the solution potential depending on conditions. ZnTiN 2 was also shown to protect Si over 72 h at open circuit in the dark in 0.1 M KHCO 3 aqueous solution at pH 10.5, with a 2.4% loss in open circuit voltage compared to a 17% loss for unprotected Si. A protective effect was also observed under illumination during methyl viologen reduction at pH 3.5 for 21 h, with a 2.5% loss in open circuit voltage observed for ZnTiN 2 /Si compared to a 25% loss in open circuit voltage for unprotected Si under the same conditions. Elemental characterization revealed the presence of oxides on the surface of ZnTiN 2 that are consistent with the Pourbaix diagram after photoelectrochemical operation; these oxides appeared to support durability without hindering charge carrier extraction to drive electrochemical work. This work highlights the promise of ZnTiN 2 for durable photoelectrochemical applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Reduced order modeling for flow and transport problems with Barlow Twins self-supervised learning

Abstract We propose a unified data-driven reduced order model (ROM) that bridges the performance gap between linear and nonlinear manifold approaches. Deep learning ROM (DL-ROM) using deep-convolutional autoencoders (DC–AE) has been shown to capture nonlinear solution manifolds but fails to perform adequately when linear subspace approaches such as proper orthogonal decomposition (POD) would be optimal. Besides, most DL-ROM models rely on convolutional layers, which might limit its application to only a structured mesh. The proposed framework in this study relies on the combination of an autoencoder (AE) and Barlow Twins (BT) self-supervised learning, where BT maximizes the information content of the embedding with the latent space through a joint embedding architecture. Through a series of benchmark problems of natural convection in porous media, BT–AE performs better than the previous DL-ROM framework by providing comparable results to POD-based approaches for problems where the solution lies within a linear subspace as well as DL-ROM autoencoder-based techniques where the solution lies on a nonlinear manifold; consequently, bridges the gap between linear and nonlinear reduced manifolds. We illustrate that a proficient construction of the latent space is key to achieving these results, enabling us to map these latent spaces using regression models. The proposed framework achieves a relative error of 2% on average and 12% in the worst-case scenario (i.e., the training data is small, but the parameter space is large.). We also show that our framework provides a speed-up of $$7 \times 10^{6}$$ 7 × 10 6 times, in the best case, and $$7 \times 10^{3}$$ 7 × 10 3 times on average compared to a finite element solver. Furthermore, this BT–AE framework can operate on unstructured meshes, which provides flexibility in its application to standard numerical solvers, on-site measurements, experimental data, or a combination of these sources.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2009

Micro-Horn Arrays for Ultrasonic Impedance Matching

Thin-layered structures containing arrays of micromachined horns, denoted solid micro-horn arrays (SMIHAs), have been conceived as improved means of matching acoustic impedances between ultrasonic transducers and the media with which the transducers are required to exchange acoustic energy. Typically, ultrasonic transducers (e.g., those used in medical imaging) are piezoelectric or similar devices, which produce small displacements at large stresses. However, larger displacements at smaller stresses are required in the target media (e.g., human tissues) with which acoustic energy is to be exchanged. Heretofore, efficiencies in transmission of acoustic energy between ultrasonic transducers and target media have been severely limited because substantial mismatches of acoustic impedances have remained, even when coupling material layers have been interposed between the transducers and the target media. In contrast, SMIHAs can, in principle, be designed to effect more nearly complete acoustic impedance matching, leading to power transmission efficiencies of 90 percent or even greater. The SMIHA concept is based on extension, into the higher-frequency/ lower-wavelength ultrasonic range, of the use of horns to match acoustic impedances in the audible and lower-frequency ultrasonic ranges. In matching acoustic impedance in transmission from a higher-impedance acoustic source (e.g., a piezoelectric transducer) and a lowerimpedance target medium (e.g., air or human tissue), a horn acts as a mechanical amplifier. The shape and size of the horn can be optimized for matching acoustic impedance in a specified frequency range. A typical SMIHA would consist of a base plate, a face plate, and an array of horns that would constitute pillars that connect the two plates (see figure). In use, the base plate would be connected to an ultrasonic transducer and the face plate would be placed in contact with the target medium. As at lower frequencies, the sizes and shapes of the pillars could be tailored for impedance matching in a specified ultrasonic frequency range. In a design that would be simplest to implement by micromachining, the horns would have constant cross-sectional areas as shown in the upper part of the figure. In this case, the dimensions of the horns could be chosen on the basis of a Mason equivalent-circuit model (a simplified model, well-known in the piezoelectric-transducer art, in which the electrical and mechanical dynamics, including electromechanical couplings, are expressed as electrical circuit elements that can include inductors, capacitors, and lumped-parameter complex impedances.) In a more complex, more nearly optimum design, the cross-sectional area of each horn would be either stepped or made to vary as a continuous function of through-the thickness position, as shown in the lower part of the figure.

Rao, Shanti↗
NASA NTRS2018

Relative Sputtering Rates of FeS, MgS, and Mg Silicates: Implications for ISM Gas Phase Depletions of Rock-Forming Elements

Astronomical measurements of S abundances in the diffuse interstellar medium (ISM) indicate ionized S is a dominant species with little (< 5%) S residing in grains (e.g. Jenkins 2009). This is an enigmatic result, given that abundant Fe-sulfide grains are observed in dust around pre- and post-main sequence stars and are also observed as major components of primitive meteoritic and cometary samples. These disparate observations suggest that the lifetime of sulfide grains in the ISM is short because of destruction processes. Our previous work has shown that FeS and MgS retain their crystallinity and do not amorphize during radiation processing, whereas enstatite and forsterite are readily amorphized. We have extended this study to measure the relative sputtering rates of FeS and MgS compared to enstatite and forsterite. Irradiation of FeS with 4 keV He+ results in preferential sputtering of S and the formation of a thin 2-3 nm, compact Fe metal layer that armors the surface. The zone of S loss extends to a depth of ~8-10 nm below the exposed surface. Despite this S loss, the FeS retains its crystallinity and shows no sign of incipient amorphization. Irradiation of FeS with 5kV Ga+ in a focused ion beam (FIB) instrument resulted in preferential sputtering of S and the formation of a 5-8-nm thick surface layer of nanophase Fe metal. X-ray mapping shows that the zone of S sputtering extends to a depth of nearly 20 nm, but there is no evidence for FeS amorphization, consistent with our previous work. The irradiation experiments show that the relative sputtering rate of FeS and MgS are much higher than olivine or enstatite. Sputtering experiments utilizing 30 kV and 5 kV Ga ions in the FIB produced volume loss in troilite that was ~4X greater than in enstatite or forsterite. The sputter yield under these conditions is such that for every Si atom sputtered from enstatite, ~14 S atoms are sputtered from FeS. We have performed similar sputtering experiments on Fe-bearing niningerite (MgS) and co-existing enstatite from the ALH 84170 EH3 chondrite. MgS also sputters much more rapidly than enstatite with a relative Si:S sputter yield of 1:8. For MgS, sulfur is highly depleted at the surface and the S-depletion zone extends to a depth of ~15 nm (using 5 kV Ga+). There is a corresponding zone of Mg and especially Fe enrichment that extends from 5 to ~10 nm below the surface, respectively. The dominant grain destruction mechanism in the ISM is sputtering from passage of supernova-generated shock waves. This process also results in the amorphization of crystalline silicates in the ISM. Our results indicate that FeS and MgS grains produced in evolved stars and injected into the ISM will be destroyed more rapidly than crystalline silicates. This process may account for the lack of significant depletion of S from the gas phase in the ISM. However, rare nanophase FeS grains occur as inclusions in circumstellar amorphous silicate grains found in comet dust particles analyzed in the laboratory. These results show that a finite amount of S in the ISM is sequestered in solid grains.

SPUTTERING RATES↗
DOE OSTI2023

Oxide– and Silicate–Water Interfaces and Their Roles in Technology and the Environment

Interfacial reactions drive all elemental cycling on Earth and play pivotal roles in human activities such as agriculture, water purification, energy production and storage, environmental contaminant remediation, and nuclear waste repository management. The onset of the 21st century marked the beginning of a more detailed understanding of mineral aqueous interfaces enabled by advances in techniques that use tunable high-flux focused ultrafast laser and X-ray sources to provide near-atomic measurement resolution, as well as by nanofabrication approaches that enable transmission electron microscopy in a liquid cell. This leap into atomic- and nanometer-scale measurements has uncovered scale-dependent phenomena whose reaction thermodynamics, kinetics, and pathways deviate from previous observations made on larger systems. A second key advance is new experimental evidence for what scientists hypothesized but could not test previously, namely, interfacial chemical reactions are frequently driven by “anomalies” or “non-idealities” such as defects, nanoconfinement, and other nontypical chemical structures. Third, progress in computational chemistry has yielded new insights that allow a move beyond simple schematics, leading to a molecular model of these complex interfaces. In combination with surface-sensitive measurements, we have gained knowledge of the interfacial structure and dynamics, including the underlying solid surface and the immediately adjacent water and aqueous ions, enabling a better definition of what constitutes the oxide– and silicate–water interfaces. This critical review discusses how science progresses from understanding ideal solid–water interfaces to more realistic systems, focusing on accomplishments in the last 20 years and identifying challenges and future opportunities for the community to address. Further, we anticipate that the next 20 years will focus on understanding and predicting dynamic transient and reactive structures over greater spatial and temporal ranges as well as systems of greater structural and chemical complexity. Closer collaborations of theoretical and experimental experts across disciplines will continue to be critical to achieving this great aspiration.

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

Stationary Oxygen Vacancy Construction toward a Superior-Performance Ultrahigh Nickel Single-Crystal Cathode

Oxygen vacancies exert a complex and profound influence on the layered cathodes, especially those with ultrahigh nickel content. They can facilitate lithium-ion transport and enhance electronic conductivity, while aggressive oxygen vacancy formation causes structural degradation and electrolyte decomposition. Herein, taking ultrahigh nickel single-crystal LiNi 0.92 Co 0.06 Mn 0.02 O 2 (SC-Ni92) as a model material, we propose a pinning strategy to harness the benefits of oxygen vacancies while mitigating their detrimental effects. Through a carefully controlled thermal process, both oxygen vacancies and pinning atoms are successfully introduced into the surface region. The resulting anchored oxygen vacancies, capitalizing on their inherent advantages, improve conductivity and lithium-ion diffusion. Simultaneously, the neighboring pinning atoms effectively increase the migration barrier and suppress the adverse effects of these vacancies, including electrolyte decomposition and structural degradation during long-term electrochemical cycling. Consequently, oxygen vacancy-anchored single-crystal LiNi 0.92 Co 0.06 Mn 0.02 O 2 (SC-Ni92-OV) demonstrates significantly improved high-voltage electrochemical performance, with 86.16% capacity retention after 200 cycles at 4.6 V and 1 C in a half-cell and 90.71% after 300 cycles at 4.5 V and 1 C in a full cell. Furthermore, this study not only provides valuable insights into the chemistry of oxygen vacancy but also introduces a viable strategy for leveraging oxygen vacancies to achieve stable high-voltage performance in ultrahigh nickel single-crystal cathodes.

defects in solids↗
NASA NTRSDate not supplied

Mineralogical Analysis of Calcium-Aluminum-Rich Inclusions Provides Insight Into Post-Formation Processes

Introduction: Calcium-aluminum inclusions (CAIs) are cm- to mm-sized intergrowths of refractory phases found in chondritic meteorites [1]. Their mineral compositions closely match the compositions of the solids thought to condense from an extremely hot (>1500K) gas with a bulk solar composition [2-4], suggesting that CAIs were the earliest solids within the Solar System [2-4]. These inclusions provide invaluable insights into the conditions and dynamics of the early Solar System. CAIs must be transported from their formation region near the protosun to the chondrite parent-body accretion region. The nature of their journey could affect how, when, and where the secondary processes recorded in these CAIs occurred [4]. Did these secondary processes occur in the solar nebula or during accretion with the parent body, or both? How were the CAIs affected by varying thermochemical processes? To better answer these questions, we have undertaken an in-depth, textural study of the secondary alteration of select CAI samples. Methods: We chose three CAIs that experienced a range of post-formation processing to gain better understanding of secondary alteration based on previous preliminary examination [5]. Representative CAIs were chosen from NWA 5508 (CV3), NWA 12772 (CV3), and Coolidge (CL4) carbonaceous chondrites. We used scanning electron microscopy (SEM) and electron backscatter diffraction (EBSD) techniques for detailed chemical, mineralogical, and textural analysis of the CAIs. Backscattered electron (BSE) images and X-ray elemental maps were taken of Coolidge and NWA 5508 using the Lunar and Planetary Institute (LPI) Phenom SEM. The JEOL 7900F SEM at NASA Johnson Space Center (JSC) was used to obtain energy dispersive spectroscopy (EDS) chemical maps of all samples. High resolution EBSD analysis identified the mineral phases and textures, providing key information on their nature. Based on the SEM and EBSD data, minerals of interest were selected for quantitative chemical electron probe micro-analysis (EPMA) using the JEOL JXA-8530F at NASA JSC. Results and Discussion: The EDS maps show that the NWA 5508 and NWA 12772 CAIs designated “Saguaro” and “Hoopoe” respectively [5] are enriched in calcium while the Coolidge CAI designated “Cottonwood” is aluminum and magnesium rich. Saguaro. A ~1.5cm diameter igneous Type B CAI with a rounded shape. The dominant phases are melilite, spinel, and Al-Ti pyroxene with minor anorthite. Spinel is subhedral and occurs in clusters. Some of these clusters have a circular geometry which encloses other minerals, known as a palisade structure [6] (Fig. 1). Some palisades form near perfect circles while others are more irregular in shape. Melilite in Saguaro ranges in size from coarse (>250m) to fine-grained (5-7m) and forms intergrown laths. A third of the melilite grains exhibit simple twinning about their <001> axis. The spinel palisades and twinned melilite in Saguaro suggest an igneous history, and the lack of secondary minerals suggests minimal aqueous alteration. At some point in time after the initial condensation of the minerals and formation of the inclusion, the sample was remelted and quickly solidified. The formation of the palisades is still heavily debated. One hypothesis is that the palisades are the rims of smaller CAIs that accreted early on, essentially acting as xenoliths within the larger CAIs [7]. Another hypothesis suggests an igneous origin for palisade structures [6-8] wherein the melt traps gas bubbles, and the spinel nucleates on the surface of this bubble. Based on the WDS spot analyses of 41 melilite grains using EPMA, the data suggest that the composition inside and outside the palisades is nearly identical. This finding indicates that these palisades are likely not exogenous but rather formed from melt-vapor reactions. Our results are consistent with studies by Simon and Grossman,1997 [6] and Zhang et al. (2019) [8]. Hoopoe. A ~0.5cm compact Type A CAI with an irregular shape. The dominant mineral phases are melilite, spinel, and hibonite with minor amounts of anorthite, augite, and perovskite. The melilite ranges in size from ~500 to 50µm. The larger melilite grains have simple twinning along the <001> axis like melilite in Saguaro. Melilite in Hoopoe exhibits crystal-plastic strain with misorientation dominantly about the <010> and <110> axes. Spinel shows subhedral to euhedral morphology and appears in clusters. Hibonite grains are similar to spinel in habit and size but show more plastic strain. The two minerals are often found together with one appearing to replace the other. Perovskite appears in fine grained recrystallized regions alongside fine augite and spinel. The abundant strain and deformation features in the melilite and hibonite suggest that Hoopoe experienced shock. This shock could have occurred in the nebula [9] or from an impact of another body on the parent body asteroid. The appearance of fine-grained (<10m) areas of augite, perovskite, and spinel in the dominantly coarse-grained inclusion suggest recrystallization, possibly due to the sudden increase in pressure and temperature. Cottonwood. This ~0.5cm CAI exhibits distinct mineralogy and textures suggesting a high degree of alteration. It is irregular in shape. The dominant mineral phases are spinel and anorthite with minor amounts of augite and rutile. The two main texture types can be seen in Fig. 2. The first type consists of coarse euhedral to subhedral spinel and anorthite. The second includes fine grained spinel, anorthite, rutile, and iron sulfides. Within these fine-grained regions, the anorthite grains are clustered into domains exhibiting the same crystallographic orientation. Rutile exclusively occurs with fine anorthite indicating a potential relationship between the two. Cottonwood has a clear and unbroken Wark-Lovering [10] rim (Fig. 2) on one side that consists of a sequence of spinel followed by anorthite and an outer layer of augite. The abundance of the fine-grained regions containing iron oxides and iron sulfides, secondary phases such as rutile, and oriented anorthite grains is evidence for recrystallization associated with a high degree of thermal metamorphism. The EPMA analyses on both coarse- and fine-grained spinel show that the fine spinel grains are more enriched in Cr (1-2 wt. %) than their coarse counterparts (0.1-0.5 wt. %). The data suggest thermal metamorphism drove chemical exchange of the previously refractory inclusion, introducing chromium and iron as well as sulfur, which is moderately volatile. Conclusions: The three CAIs analyzed record distinct secondary nebular and parent body processes. Saguaro melted in the nebula as seen by the twinned melilite and spinel palisades. Hoopoe experienced intense shock which deformed its melilite and recrystallized perovskite, augite, and spinel in fine-grained regions. Cottonwood shows evidence of recrystallization and chemical changes consistent with thermal metamorphism occurring after accretion into the parent-body.

V E Burnette↗
DOE OSTI2026

HydraGNN_Predictive_GFM_2026 - Ensemble of predictive graph foundation models for atomistic materials modeling

This release contains data and parameters of HydraGNN-based graph foundation models trained as a result of the work published in the pre-print "Exascale Multi-Task Graph Foundation Models for Imbalanced, Multi-Fidelity Atomistic Data" by M. Lupo Pasini et al. (https://arxiv.org/abs/2604.15380). We jointly train on 16 open first-principles datasets (544+ million structures covering 85+ elements) using a multi-task architecture with per-dataset heads and a scalable ADIOS2/DDStore data pipeline. On Frontier, we execute six large-scale DeepHyper hyperparameter optimization campaigns in FP64 and promote the top-performing message-passing models to sustained 2,048-node training, yielding a PaiNN-based lead model. The version of HydraGNN used to generate the outputs provided in this release is HydraGNN v5.0 (https://github.com/ORNL/HydraGNN/releases/tag/v5.0) The list of datasets used for the training of the graph foundation model is the following: 1) Alexandria [1] 2) ANI1x [2] 3) MPTrj [3] 4) Open Catalyst 2020 (OC20) [4] 5) Open Catalyst 2022 (OC22) [5] 6) Open Catalyst 2025 (OC25) [6] 7) Open Direct ir Capture 2023 (ODAC23) [7] 8) Open Materials 2024 (OMat24) [8] 9) Open Molecules 2025 (OMol25) [9] 10) OMol25-neutral (subset of OMol25 that contains only molecules with zero total charge) 11) OMol25-non-neutral (subset of OMol25 that contains only molecules with non-zero total charge) 12) Open Polymers 2026 (OPoly2026) [10] 13) Nabla2DFT [11] 14) QCML [12] 15) QM7X [reference 13] 16) transition1x [14] Dataset references: [1] J. Schmidt et al., “A dataset of 175k stable and metastable materials calculated with the PBEsol and SCAN functionals,” Scientific Data, vol. 9, p. 64, 2022. [2] J. S. Smith et al., “The ANI-1ccx and ANI-1x data sets, coupled-cluster and density functional theory properties for molecules,” Scientific Data, vol. 7, p. 134, 2020. [Online]. Available: https: //www.nature.com/articles/s41597-020-0473-z [3] A. Jain et al., “Commentary: The Materials Project: A materials genome approach to accelerating materials innovation,” APL Materials, vol. 1, no. 1, p. 011002, 07 2013. [Online]. Available: https://doi.org/10.1063/1.4812323 [4] L. Chanussot et al., “Open catalyst 2020 (oc20) dataset and community challenges,” ACS Catalysis, vol. 11, no. 10, pp. 6059–6072, 2021. [Online]. Available: https://doi.org/10.1021/acscatal.0c04525 [5] K. Tran et al., “Open catalyst 2022 (oc22) dataset and challenges for oxidation electrocatalysts,” ACS Catalysis, vol. 13, no. 5, pp. 3066–3084, 2023. [Online]. Available: https://doi.org/10.1021/acscatal.2c05426 [6] S. J. Sahoo et al., “The open catalyst 2025 (oc25) dataset and models for solid-liquid interfaces,” arXiv preprint arXiv:2509.17862, 2025. [Online]. Available: https://arxiv.org/abs/2509.17862 [7] A. Sriram et al., “The open DAC 2023 dataset and challenges for sorbent discovery in direct air capture,” ACS Central Science, vol. 10, no. 5, pp. 923–941, 2024. [8] L. Barroso-Luque et al., “Open materials 2024 (omat24) inorganic materials dataset and models,” 2024. [Online]. Available: https://arxiv.org/abs/2410.12771 [9] D. S. Levine et al., “The open molecules 2025 (OMol25) dataset, evaluations, and models,” 2025. [Online]. Available: https://arxiv.org/abs/2505.08762 [10] D. S. Levine et al., The open polymers 2026 (OPoly26) dataset and evaluations,” arXiv preprint arXiv:2512.23117, 2025. [Online]. Available: https://arxiv.org/abs/2512.23117 [11] K. Khrabrov et al., “Nabla2dft: A universal quantum chemistry dataset of drug-like molecules and a benchmark for neural network potentials,” in NeurIPS 2024 Datasets and Benchmarks Track, 2024. [Online]. Available: https://openreview.net/forum?id=ElUrNM9U8c [12] S. Ganscha et al., “The QCML dataset, quantum chemistry reference data from 33.5M DFT and 14.7B semi-empirical calculations,” Scientific Data, vol. 12, p. 406, 2025. [13] J. Hoja et al., “QM7-X, a comprehensive dataset of quantum-mechanical properties spanning the chemical space of small organic molecules,” Scientific Data, vol. 8, p. 43, 2021. [Online]. Available: https://www.nature.com/articles/s41597-021-00812-2 [14] M. Schreiner et al., “Transition1x - a dataset for building generalizable reactive machine learning potentials,” Scientific Data, vol. 9, p. 779, 2022. The folder "datasets_ADIOS2_format" contains the set of pre-processed datasets in Adaptable I/O System (ADIOS) format (https://www.exascaleproject.org/research-project/adios/) that have been used for the development and training of GFMs in this work. The "datasets_ADIOS2_format" directory contains 2 sub-directories, one for the version "v1" of the datasets and one for the version "v2" of the datasets. The version "v1" of the datasets provides values of the total energy as they are extracted from the original data as it was released by the respective institutions. The version "v2" of the datasets provides values of the energy that have been realigned. The realignment was performed by training a linear regression model that predicts the total energy as a function of the chemical composition of the atomistic structure, and then subtract such prediction from the original value of the total energy. Both folders "v1" and "v2" contain 16 sub-directories, each corresponding to an ADIOS2-formatted dataset The folder "DeepHyper-results" contains the configurational files and model's parameters for all the 186 HPO trials that were successfully completed by the scalable hyperparameter optimization (HPO) runs on Frontier. The content of the folder "DeepHyper-results" I structured as follows: 1) task-list.txt: list of mpnn name, jobid, and deephyper task id 2) gfm_${MPNN}_${JOBID}_0.${TASKID}: run directory with checkpoint files 3) gfm_${MPNN}: deephyper summary directory (*.csv) for each specific MPNN type 4) deephyper-experiment-${JOBID}: output and error logs for each job The file "deephyper-sorted.csv" contains the details of each HydraGNN model built and tested by HPO, obtained by merging the (*.csv) filed from each HPO run executed. Out of all the HPO trials, we selected 10 to continue the training of the respective HydraGNN models. Due to limited computational budget available in the LRN070 allocation we could not complete the training till convergence for all these 10 selected models. The folder "models" contains multiple sub-folders, one per each HydraGNN model trained. Each model sub-folder contains the parameters of each HydraGNN model, with multiple checkpoint-restarts. The list of sub-folders are as follows: 1) multidataset_hpo-BEST1-fp64 2) multidataset_hpo-BEST2-fp64 3) multidataset_hpo-BEST3-fp64 4) multidataset_hpo-BEST4-fp64 5) multidataset_hpo-BEST5-fp64 6) multidataset_hpo-BEST6-fp64 7) multidataset_hpo-BEST7-fp64 8) multidataset_hpo-BEST8-fp64 9) multidataset_hpo-BEST9-fp64 10) multidataset_hpo-BEST10-fp64 Within each one of these folders, additional auxiliary log files are provided with descriptions about how the training proceeded. The lead PaiNN-model is contained inside "multidataset_hpo-BEST6-fp64". The file "mlp_branch_weights" contains the parameters of the multi-layer perceptron (MLP) used to reconcile the predictions of the 16 output decoding heads of the HydragNN architectures. The MLP takes in input the chemical composition of the atomistic structure and predicts averaging weights to linearly mix the predictions of each output decoding head toward consolidating them into a single one. The folder "1.1billion-structure-inference" contains 1.1 billion atomistic structures randomly generated. Each structures is associated with energy and forces predicted with the lead-PaiNN model combined with the MLP model for reconciliation of the multi-branch predictions generated by the 16 output decoding heads. The folder "1.1billion-structure-inference" contains 9,300 (*.tar.gz) subdirectories, one per Frontier compute node used to execute the inference at exascale. Once uncompressed, each (*.tar.gz) subdirectory contains an ADIOS2 (*.bp) file container, where each atomistic structure is stored as a PyTorch-Geometric Data object. The file "export_dataset_environment_variables.sh" contains the environment variables that need to be set before running the HydraGNN code to reproduce the results provided in this dataset release. The code that can be used to load the ADIOS2 files, load HydraGNN models, and run inference is available at: https://github.com/ORNL/HydraGNN/releases/tag/v5.0

36 MATERIALS SCIENCE↗