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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

HydraGNN_Predictive_GFM_2024 - Ensemble of predictive graph foundation models for ground state atomistic materials modeling

We provide the ensemble of fifteen pre-trained graph foundation models (GFMs) for atomistic materials modeling applications. Each one of the fifteen GFMs has been trained on five open-source datasets that (once aggregated) amount to over 154 million atomistic structures, which cover over two-thirds of the natural elements of the periodic table and that comprises a broad set of organic and inorganic compounds. This vast set of atomistic structures comprises ground state configurations that are dynamically stable (i.e., equilibrated structures with atomic forces approximately close to zero values) as well as dynamically unstable structures (i.e., non-equilibrium structures with non-negligible non-zero values of atomic forces). The ensemble of datasets aggregated does NOT include excited states. The datasets have been curated to remove atomistic structures with spectral norm of the force tensor above 100 eV/angstrom. Moreover, a linear term of the energy was computed for each dataset using a linear regression model that uses the chemical concentration of each natural element as regressor. The linear term predicted by the linear regression model has been subtracted from each original energy value to perform a re-alignment of the energy values across different electronic structures approximation theories performed to generate the diverse multi-source, multi-fidelity datasets. The folder "ADIOS_files" 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 "ADIOS_files" directory contains 6 sub-directories named as follows: - ANI1x-v3.bp - MPTrj-v3.bp - OC2020-20M-v3.bp - OC2020-v3.bp - OC2022-v3.bp - qm7x-v3.bp Each sub-directory contains the pre-processed datasets converted in Adaptable I/O System (ADIOS) format (https://www.exascaleproject.org/research-project/adios/) that have been used to the development, training, and performance testing of the ensemble go predictive graph foundation models. Each GFM was developed using HydraGNN (https://github.com/ORNL/HydraGNN) as underlying graph neural network (GNN) architecture. The multi-task learning (MTL) capability of HydraGNN was used to simultaneously train the GFMs on labeled values for direct predictions of energy (a total system property of an atomistic structure that measures the chemical stability) and atomic forces (an atomic level property of an atomistic structure that measures the dynamical stability). The hyper parameters of the GFM have been tuned using scalable hyperparameter optimization (HPO) algorithms implemented in the software DeepHyper (https://github.com/deephyper/deephyper). The pre-training of each HPO trial was performed using distributed data parallelism (DDP) to scale the training across 128 compute nodes of the exascale OLCF supercomputer Frontier. Each HPO trial was trained only for 10 epochs and an early stopping was performed to avoid wasting significant computational resources on GNN architectures that were clearly underperforming. For each HPO trial, the 'omnistat' tool developed by (AMD Research - Advanced Micro Device) was used to measure the total energy consumption in kWh. The ensemble of GFMs was obtained by selecting the fifteen best performing HPO trials. Four models have been selected for their clear advantage in accuracy, and these are the GFMs with IDs 229, 156, 147, 260. Additional eleven models have been selected based on judicious balance between accuracy and energy consumption needed for training, and these are the GFMs with IDs 165, 78, 137, 1, 175, 171, 181, 67, 179, 167, 351. Each selected GFM of the ensemble was continued to cumulate a total of at most 30 epochs. In some cases, the total number of epochs actually performed was les than 30 due to two combined factors: (1) the size of the GFM (i.e., the number of model parameters to train) and (2) the total wall-clock time for which the computational resources could be allocated on OLCF-Frontier. The "Ensemble_of_models" directory contains 15 sub-directories named as follows: - gfm_0.229 - gfm_0.156 - gfm_0.147 - gfm_0.260 - gfm_0.165 - gfm_0.78 - gfm_0.137 - gfm_0.1 - gfm_0.175 - gfm_0.171 - gfm_0.181 - gfm_0.67 - gfm_0.179 - gfm_0.167 - gfm_0.351 Each one of these sub-directories refers to one of the fifteen HPO trials that have been selected to continue the pre-training with at most 30 epochs. With each sub-directory associated with a specific HPO trial, the following files can be found: - config.json: file for argument parsing to develop and train an HydraGNN architecture - gfm_0.ID_epoch_N.pk: file with model parameters for HPO ID trial after N epochs of training The ensemble of fifteen GFM architectures was used for (1) ensemble averaging to stabilize the predictions of energy and atomic forces after pre-training for post-processing analysis and (2) ensemble uncertainty quantification (UQ). The code used to develop, pre-train, and load the pre-trained models for post-processing analysis is available on the ORNL-GitHub at the following link: https://github.com/ORNL/HydraGNN/tree/Predictive_GFM_2024

36 MATERIALS SCIENCE↗
DOE OSTI2025

A Flat Analyzer Polycapillary Spectrometer for X-ray Absorption Spectroscopy of Dilute Transition Metals at X-ray-Free Electron Lasers

X-ray absorption spectroscopy (XAS) coupled with highly intense pulses from an X-ray-free electron laser (XFEL) can be used to track ultrafast chemical dynamics. Nonetheless, measurements for dilute samples (≤1 mM) have been exceptionally challenging, as scattering background signals dominate over the sample’s X-ray fluorescence. We show that femtosecond time-resolved XAS measurements of sub-millimolar transition metal solutions are now possible at the Linac Coherent Light Source (LCLS) using a high-throughput polycapillary XAS spectrometer, designed, developed, and commissioned at LCLS and the Stanford Synchrotron Radiation Lightsource (SSRL). The instrument integrates three polycapillary optics that collect and collimate X-ray fluorescence emitted from the interaction point with a high solid angle. X-ray collimated fluorescence is then selectively diffracted by coupled graphite analyzer crystals. As a result, the contribution of scattered photons is suppressed. Experiments at the Pt L 3 -edge on 0.1 mM aqueous K 2 PtCl 6 (delivered via a 100 μm liquid jet) were successfully performed in the laser pump X-ray probe configuration at the LCLS XCS and XPP instruments. We report the transient spectra of hexachloroplatinate within the first 10 ps after a 266 nm photoexcitation. We observed a short-lived reduced intermediate (≈2 ps). The polycapillary X-ray spectrometer at LCLS now enables the efficient study of the dynamics of ultradilute transition metals in solution. This capability opens the door to investigating plasmonic systems, photocatalysts, enzymes, and other scarce and dilute samples.

LCLS↗
DOE OSTI2020

Nature of Magnetic Excitations in the High-Field Phase of α–RuCl 3

We present comprehensive electron spin resonance (ESR) studies of in-plane oriented single crystals of α–RuCl 3 , a quasi-two-dimensional material with honeycomb structure, focusing on its high-field spin dynamics. The measurements were performed in magnetic fields up to 16 T, applied along the [110] and [100] directions. Several ESR modes were detected. Combining our findings with recent inelastic neutron- and Raman-scattering data, we identified most of the observed excitations. Most importantly, we show that the low-temperature ESR response beyond the boundary of the magnetically ordered region is dominated by single- and two-particle processes with magnons as elementary excitations. In conclusion, the peculiarities of the excitation spectrum in the vicinity of the critical field are discussed.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Neural network for 3D inertial confinement fusion shell reconstruction from single radiographs

In inertial confinement fusion (ICF), x-ray radiography is a critical diagnostic for measuring implosion dynamics, which contain rich three-dimensional (3D) information. Traditional methods for reconstructing 3D volumes from 2D radiographs, such as filtered backprojection, require radiographs from at least two different angles or lines of sight (LOS). In ICF experiments, the space for diagnostics is limited, and cameras that can operate on fast timescales are expensive to implement, limiting the number of projections that can be acquired. To improve the imaging quality as a result of this limitation, convolutional neural networks (CNNs) have recently been shown to be capable of producing 3D models from visible light images or medical x-ray images rendered by volumetric computed tomography. Here, we propose a CNN to reconstruct 3D ICF spherical shells from single radiographs. We also examine the sensitivity of the 3D reconstruction to different illumination models using preprocessing techniques such as pseudo-flatfielding. To resolve the issue of the lack of 3D supervision, we show that training the CNN utilizing synthetic radiographs produced by known simulation methods allows for reconstruction of experimental data as long as the experimental data are similar to the synthetic data. We also show that the CNN allows for 3D reconstruction of shells that possess low mode asymmetries. Further comparisons of the 3D reconstructions with direct multiple LOS measurements are justified.

3D Reconstruction↗
DOE OSTI2024

Bipartite mutual information in classical many-body dynamics

Information theoretic measures have helped to sharpen our understanding of many-body quantum states. As perhaps the most well-known example, the entanglement entropy (or more generally, the bipartite mutual information) has become a powerful tool for characterizing the dynamical growth of quantum correlations. By contrast, although computable, the bipartite mutual information (MI) is almost never explored in classical many particle systems; this owes in part to the fact that computing the MI requires keeping track of the evolution of the full probability distribution, a feat which is rarely done (or thought to be needed) in classical many-body simulations. Here, we utilize the MI to analyze the spreading of information in 1D elementary cellular automata (CA). Broadly speaking, we find that the behavior of the MI in these dynamical systems exhibits a few different types of scaling that roughly correspond to known CA universality classes. Of particular note is that we observe a set of automata for which the MI converges parametrically slowly to its thermodynamic value. We develop a microscopic understanding of this behavior by analyzing a two-species model of annihilating particles moving in opposite directions. Furthermore, our work suggests the possibility that information theoretic tools such as the MI might enable a more fine-grained characterization of classical many-body states and dynamics.

Cellular automata↗
DOE OSTI2022

High‐Capacity Splitting of Mono‐ and Dibranched Hexane Isomers by a Robust Zinc‐Based Metal–Organic Framework

Abstract High‐efficiency separation of C 6 alkanes, particularly the mono‐ and dibranched isomers by using porous solids, is of paramount significance in the petrochemical industry and, remains a daunting challenge. In this work, we report the complete separation of linear/monobranched hexanes from their dibranched isomers through selective size‐exclusion by a microporous MOF, Zn‐tcpt (H 3 tcpt=2,4,6‐tris(4‐carboxyphenoxy)‐1,3,5‐triazine), with a two‐fold interpenetrated structure of hms nets. Importantly, its adsorption capacity and selectivity are notably higher than those of the previously reported adsorbents that can split mono‐ and dibranched alkane isomers. Dynamic breakthrough measurements verify the excellent separation of C 6 alkane isomers by Zn‐tcpt, and the size‐exclusion based separation mechanism has been confirmed by ab initio materials modeling. The high‐efficiency separation of alkane isomers by Zn‐tcpt can be attributed to its optimal pore dimensions as well as high porosity.

Yu, Liang↗
DOE OSTI2022

High–Capacity Splitting of Mono– and Dibranched Hexane Isomers by a Robust Zinc–Based Metal–Organic Framework

High-efficiency separation of C 6 alkanes, particularly the mono- and dibranched isomers by using porous solids, is of paramount significance in the petrochemical industry and, remains a daunting challenge. In this work, we report the complete separation of linear/monobranched hexanes from their dibranched isomers through selective size-exclusion by a microporous MOF, Zn-tcpt (H3tcpt=2,4,6-tris(4-carboxyphenoxy)-1,3,5-triazine), with a two-fold interpenetrated structure of hms nets. Importantly, its adsorption capacity and selectivity are notably higher than those of the previously reported adsorbents that can split mono- and dibranched alkane isomers. Dynamic breakthrough measurements verify the excellent separation of C 6 alkane isomers by Zn-tcpt, and the size-exclusion based separation mechanism has been confirmed by ab initio materials modeling. Furthermore, the high-efficiency separation of alkane isomers by Zn-tcpt can be attributed to its optimal pore dimensions as well as high porosity.

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

Two-dimensional glass transition–like behavior of Janus particle–laden interface

Abstract Understanding the interactive behavior of Janus particles (JPs) is a growing field of research. The enhancement in binding energy, in comparison to homogenous particles, and the dual characteristic of JPs open up new possibilities for novel applications. In many such applications, interfacial materials become subjected to flows that produce dilational and shear stresses. Therefore, it is important to understand the impact that the Janus character brings to interfaces. In this work, we study the microstructure of two-dimensional (2D) JP monolayers formed at the air–water interface and examine the shear viscoelasticity with an interface rheometer that was adapted for in situ surface pressure control via a Langmuir trough. We extend concepts from bulk rheology to data obtained from interfacial rheology as a tool to understand and predict the monolayer’s viscoelastic behavior. Finally, by calculating the time relaxation spectrum from the measured 2D dynamic moduli, we conclude that a phenomenon similar to glass transition is taking place by analogy.

42 ENGINEERING↗
DOE OSTI2021

Digital Image Correlation as an Experimental Modal Analysis Capability

Digital image correlation (DIC) is an established test technique in several fields including quasi-static displacement measurements. Recently there has been growing interest in using DIC to measure structural dynamic response and even extract modal parameters from that information. Although high-speed cameras have become more ubiquitous, there are no commercial end-to-end packages for modal analysis based on image data, particularly when combined with traditional data acquisition systems. As such, the practitioner is left to develop several key data processing capabilities, hardware interface equipment, and testing practices themselves. This work highlights several practical aspects that have been encountered while establishing DIC as a viable modal testing capability in a laboratory environment.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Modelling a compressible packed bed flow-through washing and deacetylation reactor for corn stover pretreatment

The deacetylation process is a key step in the lignocellulosic biomass pretreatment process that currently is done in batch reactors. A flow-through diffuser type reactor is a promising approach to make the process more efficient and economically favorable. A washing step before deacetylation can further reduce chemical usage and increase the process efficiency. However, the highly compacted biomass particles can cause significant pressure-drop for fluid flow through the bed, which in the worst case can cause self-enhancing pressure-drop leading to reactor blocking. Detailed understanding of the fundamentals of flow through a compressible packed bed is necessary to scale up the washing and deacetylation process. This work closely examines the classical Kozeny Carman equation and proposes modifications to accurately predict the pressure-drop at different compaction states. Here, a compressible packed bed model is further developed based on the interaction between solid mechanics and fluid dynamics. Experimental measurements of water flow through a packed bed of corn stover show good agreement with the developed model. Corn stover washing process scale up simulations show that smaller reactor diameter, higher friction lining material, lower process throughput, and higher process temperature is favorable in stabilizing the bed from extensive compression when the bed height is fixed.

09 BIOMASS FUELS↗
DOE OSTI2020

Cutting force and stability for inserted cutters using structured light metrology

This paper describes force and stability prediction for inserted end and face mills using a reverse engineering approach. Structured light scanning is used to identify the spatial coordinates of the points that define the multiple insert cutting edges. These points are used to extract the cutting edge radius and angle and are then incorporated in a time domain simulation that predicts cutting force and tool/workpiece deflection for user-selected operating parameters. Good agreement between predicted and measured cutting forces is demonstrated. The process stability is then predicted using the validated force model and measured structural dynamics.

Machining↗
DOE OSTI2020

Cutting force and stability prediction for inserted cutters

Here, this paper presents an approach for inserted end/face mill force and stability predictions using a reverse engineering approach. Structured light scanning is implemented to identify the spatial coordinates of the points that define the multiple insert cutting edges. These points are analyzed to extract the cutting edge radius and angle values, which are then incorporated in a time domain simulation that predicts cutting force and tool/workpiece deflection for user-selected operating parameters. Good agreement between predicted and measured cutting forces is first demonstrated. The process stability is then predicted using the validated force model and measured structural dynamics. Observations about the stability dependence on insert geometry are finally presented for a selected end mill.

Machining↗
DOE OSTI2025

Lattice Structure and Dynamics of Sparse Molecular Crystals: OsO 4 and RuO 4

OsO 4 and RuO 4 are molecular oxides with unique tetrameric structures and rare +8 oxidation states. Accurately modeling their properties remains challenging for density functional theory (DFT) due to weak intertetramer interactions, which standard functionals fail to capture. Here, in this work, we show that the van der Waals (vdW)-corrected density functional (vdW-DF-optB86b) provides structural parameters that are much closer to experimental values than the standard generalized gradient approximation, with volume predictions that fall within the experimentally observed range. Phonon band structure analysis shows that the inclusion of vdW interactions stabilizes soft phonon modes, highlighting the importance of dispersion corrections for accurate predictions of lattice dynamics. Experimental measurements of the phonon density of states for OsO 4 , obtained via inelastic neutron scattering, demonstrate good agreement with our vdW-DF-optB86b calculations. These results validate OsO 4 and RuO 4 as valuable benchmarks for structural and vibrational calculations via vdW-corrected DFT methods and offer insights for studying the broader class of sparse molecular materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Kinetics of Magnetic Skyrmion Crystal Formation from the Conical Phase

The particle-like magnetic skyrmion or skyrmion lattice (SkX) formation has promoted strong application and fundamental science interests. Despite extensive research, the kinetic of the SkX development is much less understood because of the ultrafast spin rotation and high sensitivity to external perturbations. In this work, using in situ Lorentz transmission electron microscopy, we successfully measured the dynamics of SkX formation from the conical phase with precise control of both the temperature and the magnetic field. We discovered that the Avrami equation can accurately describe the transition process with an initial Avrami constant around 1, suggesting that the rate-limiting step for the quasiparticle lattice formation is one-dimensional heterogeneous nucleation of individual skyrmions. A modified Arrhenius rate law is established, with an energy barrier that has a square-root dependence on temperature and a quadratic dependence on the magnetic field. This study paves the way toward precise and predictable manipulation of topological spin structures.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Spatio-Kinetic Electronic Heterogeneity in MoS 2 Revealed by Ultrafast Electron Microscopy: Implications for Optoelectronics

There is broad interest in layered, two-dimensional (2D) semiconductors owing to their high optical absorption and ability to heterogeneously integrate with various substrates. In such layered semiconductors, mesoscopic imperfections, such as surface step edges, may affect charge carrier kinetics and device performance, but studying their effects on carrier transport with sufficient spatial and temporal resolution is a challenge. Using scanning ultrafast electron microscopy, we image the near-surface charge carrier kinetics with μm/ps spatiotemporal resolution in single-crystal MoS 2 samples with surface steps tens of nanometers in height. We find an approximately 3-fold increase in surface trap density near such surface steps compared to the uniform, flat surface regions. Despite the difference in trap state density, filling of the traps occurs over the same time scale (∼100 ps), but carrier recovery is much slower near the step compared to the uniform regions of the material. Furthermore, these results provide an approach to measure ultrafast dynamics and determine the required uniformity of layered materials depending on the speed limit constraints for specific applications.

SEM↗
DOE OSTI2024

Importance of Site Diversity and Connectivity in Electrochemical CO Reduction on Cu

Electrochemical CO 2 reduction on Cu is a promising approach to produce value-added chemicals using renewable feedstocks, yet various Cu preparations have led to differences in activity and selectivity toward single and multicarbon products. Here, we find, surprisingly, that the effective catalytic activity toward ethylene improves when there is a larger fraction of less active sites acting as reservoirs of *CO on the surface of Cu nanoparticle electrocatalysts. In an adaptation of chemical transient kinetics to electrocatalysis, we measure the dynamic response of a gas diffusion electrode (GDE) cell when the feed gas is abruptly switched between Ar (inert) and CO. When switching from Ar to CO, CO reduction (COR) begins promptly, but when switching from CO to Ar, COR can be maintained for several seconds (delay time) despite the absence of the CO reactant in the gas phase. A three-site microkinetic model captures the observed dynamic behavior and shows that Cu catalysts exhibiting delay times have a less active *CO reservoir that exhibits fast diffusion to active sites. The observed delay times and the estimated *CO reservoir sizes are affected by catalyst preparation, applied potential, and microenvironment (electrolyte cation identity, electrolyte pH, and CO partial pressure). Notably, we estimate that the *CO reservoir surface coverage can be as high as 88 ± 7% on oxide-derived Cu (OD-Cu) at high overpotentials (–1.52 V vs SHE) and this increases in reservoir coverage coincide with increased turnover frequencies to ethylene. We also estimate that *CO can travel substantial distances (up to 10s of nm) prior to desorption or reaction. It appears that active C–C coupling sites by themselves do not control selectivity to C 2+ products in electrochemical COR; the supply of CO to those sites is also a crucial factor. More generally, the overall activity of Cu electrocatalysts cannot be approximated from linear combinations of individual site activities. Future designs must consider the diversity of the catalyst network and account for intersite transportation pathways.

30 DIRECT ENERGY CONVERSION↗