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At least 451 records · Page 25

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DOE OSTI2024

A Causal Approach to Model Validation and Calibration

This poster presents a novel method for validation and verification that focuses on identifying causal relationships between data elements, moving beyond traditional statistical and machine learning approaches. These methods employ causal discovery techniques to reveal the underlying mechanisms of data generation. The research utilizes structural causal models and directed acyclic graphs to depict causal relationships. This approach assists in achieving alignment between simulation models and reality.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Reward Driven Workflows for Unsupervised Explainable Analysis of Phases and Ferroic Variants From Atomically Resolved Imaging Data

Rapid progress in aberration corrected electron microscopy necessitates development of robust methods for the identification of phases, ferroic variants, and other pertinent aspects of materials structure from imaging data. While unsupervised methods for clustering and classification are widely used for these tasks, their performance can be sensitive to hyperparameter selection in the analysis workflow. In this study, the effects of descriptors and hyperparameters are explored on the capability of unsupervised ML methods to distill local structural information, exemplified by the discovery of polarization and lattice distortion in Sm − dopped BiFeO 3 (BFO) thin films. It is demonstrated that a reward-driven approach can be used to optimize these key hyperparameters across the full workflow, where rewards are designed to reflect domain wall continuity and straightness, ensuring that the analysis aligns with the material's physical behavior. This approach allows the discovery of local descriptors that are best aligned with the specific physical behavior, providing insight into the fundamental physics of materials. The reward driven workflow is further extended to disentangle structural factors of variation via an optimized variational autoencoder (VAE). Lastly, the importance of well-defined rewards is explored as a quantifiable measure of the success of the workflow.

Barakati, Kamyar [University of Tennessee, Knoxvil↗

DOE OSTI2025

Vibration-Damping Properties of 3D-Printed Auxetic Structures

Two-photon polymerization is a recently developed technique that is used to print millimeter-size cellular structures with micrometer resolution. The two-photon polymerization process discussed in this paper is used to build structures to stabilize direct-drive targets that are imploded at cryogenic temperatures. These targets are supported by a very thin stalk (10 to 18 µm diameter) that can be broken (or dislodged) by vibrations that occur when the target is transported or when the cryogenic shroud is removed. And any vibration at the moment of implosion affects how precisely the target is aligned to the focus of the laser beams. Finally, this study investigates the mechanical properties of different millimeter-sized cellular auxetic structures (~0.2 g/cm 3 ) at room and cryogenic temperatures (20°C and −140°C) and how well the most promising structure dampens vibrations at room temperature.

auxetic structures↗

DOE OSTI2025

PFSA-Ionomer Dispersions to Thin-Films: Interplay Between Sidechain Chemistry and Dispersion Solvent

In fuel-cell catalyst layers (CLs), ionomers exists as nanoscale thin-films binding catalyst particles, wherein ionic and gaseous species transport to catalyst sites. To improve film function, ionomers have been designed based on the prototypical perfluorosulfonic acid (PFSA). Since CLs are fabricated through solution-based processing of inks, understanding how ink/dispersion solvent impacts ionomer interactions and function is important to guide future ionomer design. Herein, PFSA and its chemical derivatives are characterized from dispersion (in solvent) to thin film (cast on support) to investigate the impact of solvent water content on ionomer dispersion (structure, acidity) and resulting film properties. Dispersion characterization reveals that secondary aggregate structure depends on the sidechain chemistry, but all PFSA-based ionomers evolve similarly as dispersion becomes water-rich. The differences in aggregation alter ionomer adsorption and thin film morphology. Further, hydrophilic domain spacing and orientation are affected primarily by sidechain chemistry, and modulated by solvent composition. Thin-film conductivity correlates with hydration and nanodomain alignment, signifying the role of morphology in properties. Overall, this work provides insights into how chemistry can be used to coarse-tune structure–property relationships, while processing solvent is for fine-tuning of dispersion-film interplay for controlling CL-ionomer function, which can be translated to other chemistries and ink formulations.

25 ENERGY STORAGE↗

DOE OSTI2026

Toward a standardization of cryostructure and cryogenic soil structure terminology for the field description of permafrost‐affected soils

This paper establishes standardized terminology and field documentation protocols for cryostructures and cryogenic soil structures in permafrost‐affected soils and provides brief guidance on descriptions of ground ice morphology and ice volume estimates. We consolidate permafrost terminology from Russian and North American literature, clarify long‐standing ambiguities, and provide explicit guidelines that align with US Department of Agriculture‐Natural Resources Conservation Service soil description standards. Our scheme makes critical distinctions between cryostructure, the distribution of ice within soil, and cryogenic soil structure, the morphological structure of soil resulting from ice formation. The scheme organizes cryostructures into three main categories: non‐segregated ice, visible segregated ice, and ice matrices. We introduce standardized codes and parameters for field descriptions of ice and soil that enable machine‐readable data collection compatible with existing soil information systems. This standardization will significantly enhance the integration of field observations into landscape‐scale assessments of permafrost stability, infrastructure vulnerability, and ecosystem response to permafrost thaw, addressing an urgent need for quantitative data to inform modeling and decision‐making in rapidly changing Arctic and subarctic environments.

Andersen, Megan L. [University of Minnesota, Saint↗

DOE OSTI2025

Self-Assembled Magnetic Nanoparticle Layers: Structural Control for Reconfigurable Magnetism and Functional Applications

We advance soft X-ray vector ptychographic tomography to map the 3D magnetization field in self-assembled superparamagnetic nanoparticles at a liquid–liquid interface, revealing how layered structures influence magnetic ordering. We observe that monolayers with low coordination numbers exhibit weak magnetic order, with magnetic vortices disrupting spin alignment. In contrast, bilayers and trilayers with higher coordination numbers display long-range magnetic order with strong spin correlations across larger distances and a suppression of magnetic vortices. We further quantify the average distance for vortex–antivortex pairs as 26.0 ± 2.0 nm, while vortex–vortex and antivortex–antivortex pairs exhibit larger separations, averaging 44.9 ± 5.2 and 54.1 ± 7.4 nm, respectively. These experimental results are supported by micromagnetic Monte Carlo simulations. Our findings illustrate how layered structures enhance magnetic order and spin correlation in superparamagnetic nanoparticle assemblies, providing a promising approach for tuning magnetic properties in applications such as data storage, microrobotics, and biomedicine.

Lu, Xingyuan↗

DOE OSTI2025

Orthorhombic Structures as Inorganic Halide Perovskite Models for High-Throughput DFT Investigations

Although high-symmetry Pm-3m space group cubic models are computationally efficient for high-throughput density functional theory (DFT) calculations of inorganic ternary (ABX 3 ) halide perovskites (HPs), they frequently predict band gaps (E g ) that disagree with experiment. Conversely, while low-symmetry cubic polymorphous networks (PN) comprised of 160 to 320 atoms incur significantly greater computational cost, they predict E g ’s that are more closely aligned with experiment. Here, in this study, we compare the DFT total energies and E g ’s predicted by four high-symmetry structure models (Pnma orthorhombic, R3m trigonal, P4/mbm tetragonal, and Pm-3m cubic) to cubic PNs for 5 experimentally characterized ternary HPs and find that the orthorhombic model computes Eg’s with the smallest MAD of 0.23 eV relative to the PNs. Pair distribution functions and DFT-computed total energies show that octahedral tilting, which is present in the 20-atom orthorhombic and 160-atom cubic PN models but not in the 5-atom cubic models, stabilizes all 5 compositions in our benchmarking set. We also find that imposing PN constraints when generating and optimizing these orthorhombic structures by fixing the unit cell lattice vectors and displacing the atoms prior to ionic relaxation with DFT, which we call the orthorhombic surrogate model (OSM), lowers the MAD of E g predictions to 0.09 eV. Our OSM predicts the PN band gaps of an additional 95 theoretical inorganic ternary HPs with MAD of 0.08 eV, supporting its usage in high-throughput DFT investigations to closely estimate PN band gaps with much less computational expense.

14 SOLAR ENERGY↗

DOE OSTI2020

Anisotropic X-Ray Scattering of Transiently Oriented Water

We study the structural dynamics of liquid water by time-resolved anisotropic x-ray scattering under the optical Kerr effect condition. In this way, we can separate the anisotropic scattering decay of 160 fs from the delayed temperature increase of ~ 0.1 K occurring at 1 ps and quantify transient changes in the O-O pair distribution function. Polarizable molecular dynamics simulations reproduce well the experiment, indicating transient alignment of molecules along the electric field, which shortens the nearest-neighbor distances. In addition, analysis of the simulated water local structure provides evidence that two hypothesized fluctuating water configurations exhibit different polarizability.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2022

Gradient Architecture Design in Scalable Porous Battery Electrodes

Because it has been demonstrated to be effective toward faster ion diffusion inside the pore space, low-tortuosity porous architecture has become the focus in thick electrode designs, and other possibilities are rarely investigated. Here, to advance current understanding in the structure-affected electrochemistry and to broaden horizons for thick electrode designs, we present a gradient electrode design, where porous channels are vertically aligned with smaller openings on one end and larger openings on the other. With its 3D morphology carefully visualized by Raman mapping, the electrochemical properties between opposite orientations of the gradient electrodes are compared, and faster energy storage kinetics is found in larger openings and more concentrated active material near the separator. As further verified by simulation, this study on gradient electrode design deepens the knowledge of structure-related electrochemistry and brings perspectives in high-energy battery electrode designs.

25 ENERGY STORAGE↗

DOE OSTI2023

Chemical and Electronic Structure at the Interface between a Sputter-Deposited Zn(O,S) Buffer and a Cu(In,Ga)(S,Se) 2 Solar Cell Absorber

The chemical and electronic structure of the interface between a sputter-deposited Zn(O,S) buffer layer and an industrial Cu(In,Ga)(S,Se) 2 (CIGSSe) absorber for thin-film solar cells is investigated with X-ray and UV photoelectron spectroscopy, inverse photoemission spectroscopy, and X-ray emission spectroscopy. We find a CIGSSe absorber surface band gap of 1.61 (±0.14) eV, which is significantly increased as compared to the minimal value derived with bulk-sensitive methods (≈1.1 eV). We find no indication for diffusion of absorber elements into the buffer layer. Surface- and bulk-sensitive measurements of the buffer layer suggest the presence of S-Zn and S-O bonds in the Zn(O,S) layer. We find that the naturally existing downward band bending toward the CIGSSe absorber surface is increased by the formation of the interface, likely enhancing carrier separation under illumination. We also derive a flat conduction band alignment, in line with the reported high conversion efficiencies of corresponding large-area solar cells.

14 SOLAR ENERGY↗

DOE OSTI2025

Driving rapid atomic order in MnAl via low-magnitude magnetic field annealing

Application of a mild (60 mT), uniform magnetic field during short-term thermal treatment of kinetically retained, atomically disordered (paramagnetic) ε-MnAl was found to deliver a significant ~50 % increase in the formation of L1 0 atomically ordered (ferromagnetic) τ-MnAl product phase, compared to that produced by conventional (i.e., zero-field) annealing under identical thermal conditions. The magnetic field, applied in a passive closed-circuit configuration during annealing, induced significant changes in the structural, magnetic, and phase evolution of the material. Computational results based on electronic structure calculations demonstrate that the effective magnetic susceptibility of τ-MnAl is sensitive to the orientation, rather than the magnitude, of an applied magnetic field in the vicinity of the Curie temperature. The uniaxial magnetocrystalline anisotropy of the L1 0 structure is proposed to act as a filter for selective propagation of the population of τ-MnAl variants that are favorably aligned with the applied field. In this manner, crystallographic “gridlock” is alleviated that would otherwise arise from the coexistence of multiple, energetically equivalent τ-phase variants within the parent ε-phase matrix. These results confirm that static, low-magnitude magnetic field annealing is able to accelerate L1 0 atomic ordering in the MnAl system and likely can exert similar influences in relevant magnetic systems, facilitating efficient tailoring of structure-sensitive magnetic properties for the manufacture of magnetic materials.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Post-Modification of Crystalline Peptoid Nanomembranes with Active Nanoparticles for Efficient Photooxidation of a Mustard Gas Simulant

Peptoids (or poly-N-substituted glycines) hold immense potential for assembling into hierarchically structured functional materials via controlled molecular interactions. To create self-assembled materials with tailored functionalities, peptoid sequences are often conjugated with reactive or recognition motifs to enable applications including specific binding, biomimetic catalysis, and fluorescence imaging. However, the direct integration of bulky functional motifs into peptoid sequences can disrupt assembly processes and structural outcomes. Herein, we present a post-modification strategy for functionalizing pre-formed 2D crystalline assemblies. Through introducing clickable active sites, such as azide, alkyne, or thiol groups into a peptoid sequence, site-specific conjugation is achieved post-assembly via efficient “click”-type reactions. This strategy enables the ordered alignment of functional groups and gold nanoparticles (Au NPs) on the surface of 2D peptoid nanomaterials with controlled density, while preserving their high crystallinity and structural integrity. Furthermore, we demonstrated that nanomembranes functionalized with both Au NPs and porphyrins enhance the efficiency and selectivity of the photooxidation of 2-chloroethyl ethyl sulfide, a simulant of sulfur mustard. This innovative strategy lays the groundwork for advancing peptoid-based functional materials across diverse applications, from catalysis to biomedicine.

Chemistry↗

DOE OSTI2026

Commutative Algebra Modeling in Materials Science – A Case Study on Metal–Organic Frameworks (MOFs)

Metal-organic frameworks (MOFs) are a class of important crystalline and highly porous materials whose hierarchical geometry and chemistry hinder interpretable predictions in materials properties. Commutative algebra is a branch of abstract algebra that has been rarely applied in data and material sciences. We introduce the first ever commutative algebra modeling and prediction in materials science. Specifically, category-specific commutative algebra (CSCA) is proposed as a new framework for MOF representation and learning. It integrates element-based categorization with multiscale algebraic invariants to encode both local coordination motifs and global network organization of MOFs. These algebraically consistent, chemically aware representations enable compact, interpretable, and data efficient modeling of MOF properties such as Henry’s constants and uptake capacities for common gases. Compared to traditional geometric and graph-based approaches, CSCA achieves comparable or superior predictive accuracy while substantially improving interpretability and stability across data sets. By aligning commutative algebra with the chemical hierarchy, the CSCA establishes a rigorous and generalizable paradigm for understanding structure and property relationships in porous materials and provides a nonlinear algebra-based framework for data-driven material discovery.

Khaemba, Caleb S.↗

DOE OSTI2025

Human protein synthesis requires aminoacyl-tRNA pivoting during proofreading

Abstract Rigorous studies have characterized the aa-tRNA selection mechanism in bacteria, which is essential for maintaining translational fidelity. Recent investigations have identified critical distinctions in humans, such as the requirement of subunit rolling and a tenfold slower proofreading step. Although these studies captured key intermediates involved in tRNA selection, they did not elucidate the transitions of aa-tRNA between intermediates. Through diverse structure-based simulations, we simulated 1856 aa-tRNA accommodation events into the human ribosomal A site. Here we show the requirement for a distinct ~30° pivoting of aa-tRNA about the anticodon stem within the accommodation corridor. This pivoting is crucial for navigating the crowded accommodation corridor, which becomes more constrained due to subunit rolling. Subunit rolling-dependent crowding increases the steric contributions of the accommodation corridor during aa-tRNA accommodation, consistent with the tenfold reduction in the rate of proofreading. Furthermore, we show that eEF1A interacts with the accommodating aa-tRNA through conserved basic residues, limiting premature aa-tRNA dissociation from the A site. These findings provide a structural description of the human aa-tRNA selection process and demonstrate that the aa-tRNA alignment relative to the ribosomal catalytic sites is a critical determinant of translational fidelity.

Science & Technology - Other Topics↗

DOE OSTI2026

A multimodal large language model for materials science

Understanding and predicting the properties of inorganic materials is crucial for accelerating advancements in materials science and driving applications in energy, electronics and beyond. Integrating material structure data with language-based information through multimodal large language models (LLMs) offers great potential to support these efforts by enhancing human–artificial intelligence interaction. However, a key challenge lies in integrating atomic structures at full resolution into LLMs. In this work, we introduce MatterChat, a versatile structure-aware multimodal LLM that unifies material structural data and textual inputs into a single cohesive model. MatterChat uses a bridging module to effectively align a pretrained universal machine learning interatomic potential with a pretrained LLM, reducing training costs and enhancing flexibility. Our results demonstrate that MatterChat greatly improves performance in material property prediction and human–artificial intelligence interaction, surpassing general-purpose LLMs such as GPT-4. We also demonstrate its usefulness in applications such as more advanced scientific reasoning and step-by-step material synthesis.

Tang, Yingheng [Lawrence Berkeley National Laborat↗

DOE OSTI2026

metagRoot: a comprehensive database of protein families associated with plant root microbiomes

The plant root microbiome is vital in plant health, nutrient uptake, and environmental resilience. To explore and harness this diversity, we present metagRoot, a specialized and enriched database focused on the protein families of the plant root microbiome. MetagRoot integrates metagenomic, metatranscriptomic, and reference genome-derived protein data to characterize 71 091 enriched protein families, each containing at least 100 sequences. These families are annotated with multiple sequence alignments, CRISPR elements, hidden Markov models, taxonomic and functional classifications, ecosystem and geolocation metadata, and predicted 3D structures using AlphaFold2. MetagRoot is a powerful tool for decoding the molecular landscape of root-associated microbial communities and advancing microbiome-informed agricultural practices by enriching protein family information with ecological and structural context. The database is available at https://pavlopoulos-lab.org/metagroot/ or https://www.metagroot.org.

Chasapi, Maria N↗

DOE OSTI2026

Low-temperature magnetic structure and lattice response in SmCuAs 2

We investigated the structural and magnetic properties of single-crystalline SmCuAs 2 using high-resolution synchrotron x-ray diffraction and x-ray resonant magnetic scattering (XRMS) at the Sm 𝐿 2 and 𝐿 3 edges. Temperature-dependent diffraction measurements confirm that SmCuAs2 maintains its tetragonal symmetry from room temperature down to 8 K, with lattice parameters showing anomalous behavior below the resistivity minimum (𝑇≈30K). Notably, the c-axis lattice parameter exhibits a plateau and subsequent increase near the Néel temperature, indicating magnetoelastic coupling. XRMS measurements reveal a commensurate antiferromagnetic structure with a propagation vector 𝒒=(0,0,0.5). Our measurement shows that the Sm moments are aligned within the 𝒂𝒃 plane and arranged in a ++−− stacking along the 𝒄 axis. Comparison with related 𝑅⁢𝐸⁢CuAs 2 compounds (RE = Pr, Nd, and Gd) suggests that in-plane moment orientation and associated magnetic frustration play a key role in the emergence of the resistivity minimum. Differences in spin-orbit and magnetoelastic coupling across the series highlight their importance in governing low-temperature transport behavior.

36 MATERIALS SCIENCE↗

DOE OSTI2021

FERMI (Q1 Project Report: May-June 2021): LLNL Contribution (short version)

This work delineates the work accomplished in the 2nd quarter of CY 2021, which consists of the first quarter of funding for LLNL in the FERMI project (Fusion Energy Reactors Modeling Initiative), a project of the GAMOW (Galvanizing Advances in Market-Aligned Fusion for an Overabundance of Watts) program under ARPA-E. LLNL is responsible for the structural mechanics component of FERMI, concentrating on fusion first wall and blankets.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗