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DOE OSTI2019

Optimized oxygen deprived low temperature sputtered WO3 thin films for crystalline structures

In this work, we report a detailed analysis on the effects of processing parameters for sputtered tungsten trioxide (WO 3 ) thin nanoscale films on their structural, vibrational and electrical properties. The research aims to understand the fundamental aspects of WO3 sputtering at relatively low temperatures and in an oxygen deprived environment targeting applications of temperature and oxygen sensitive substrates. Structural analysis indicates that films deposited at room temperature, or substrate temperatures at or below 400 degrees C with low oxygen partial pressure are amorphous. Furthermore, crystallization of the films was observed with distinct Raman peaks when the films were annealed at 300 degrees C or above using rapid thermal annealing for 10 min. Films revealed monoclinic phases of WO 3 with the presence of W-O-W stretching, bending and lattice vibrational modes in the Raman spectra. Interestingly, a change of transport behavior from insulating to semiconducting was observed for as deposited films on post annealing. Annealed films revealed stoichiometric WO 3 phases with no external defects detected. The present study adopts a route to intercalate WO 3 in a variety of applications from electrochromic coloration to a nanocrystalline thin film for electronic devices sensitive to higher temperatures and gas flow in the sputtering system.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2022

Analysis of Interpretable Data Representations for 4D-STEM Using Unsupervised Learning

Abstract Understanding the structure of materials is crucial for engineering devices and materials with enhanced performance. Four-dimensional scanning transmission electron microscopy (4D-STEM) is capable of mapping nanometer-scale local crystallographic structure over micron-scale field of views. However, 4D-STEM datasets can contain tens of thousands of images from a wide variety of material structures, making it difficult to automate detection and classification of structures. Traditional automated analysis pipelines for 4D-STEM focus on supervised approaches, which require prior knowledge of the material structure and cannot describe anomalous or deviant structures. In this article, a pipeline for engineering 4D-STEM feature representations for unsupervised clustering using non-negative matrix factorization (NMF) is introduced. Each feature is evaluated using NMF and results are presented for both simulated and experimental data. It is shown that some data representations more reliably identify overlapping grains. Additionally, real space refinement is applied to identify spatially distinct sample regions, allowing for size and shape analysis to be performed. This work lays the foundation for improved analysis of nanoscale structural features in materials that deviate from expected crystallographic arrangement using 4D-STEM.

Bruefach, Alexandra (ORCID:0000000209323477)↗

DOE OSTI2023

Causal interaction in high frequency turbulence at the biosphere–atmosphere interface: Structure–function coupling

At the biosphere–atmosphere interface, nonlinear interdependencies among components of an ecohydrological complex system can be inferred using multivariate high frequency time series observations. Information flow among these interacting variables allows us to represent the causal dependencies in the form of a directed acyclic graph (DAG). Here, we use high frequency multivariate data at 10 Hz from an eddy covariance instrument located at 25 m above agricultural land in the Midwestern US to quantify the evolutionary dynamics of this complex system using a sequence of DAGs by examining the structural dependency of information flow and the associated functional response. We investigate whether functional differences correspond to structural differences or if there are no functional variations despite the structural differences. We base our analysis on the hypothesis that causal dependencies are instigated through information flow, and the resulting interactions sustain the dynamics and its functionality. To test our hypothesis, we build upon causal structure analysis in the companion paper to characterize the information flow in similarly clustered DAGs from 3-min non-overlapping contiguous windows in the observational data. We characterize functionality as the nature of interactions as discerned through redundant, unique, and synergistic components of information flow. Through this analysis, we find that in turbulence at the biosphere–atmosphere interface, the variables that control the dynamic character of the atmosphere as well as the thermodynamics are driven by non-local conditions, while the scalar transport associated with CO and H 2 O is mainly driven by short-term local conditions.

58 GEOSCIENCES↗

DOE OSTI2026

Emerging hierarchical dislocation structures: Insights from scanning electron microscopy-electron backscatter diffraction in situ tensile testing and multifractal analysis

Understanding the evolution of dislocation structures during plastic deformation is critical for predicting the mechanical performance of metallic materials. In this work, we applied in situ scanning electron microscopy/electron backscatter diffraction tensile testing combined with multifractal (MF) analysis to assess deformation-induced dislocation structure evolution in solution-annealed 304 L stainless steel, both in its as-received and neutron-irradiated states (5.4 displacements per atom). The analysis of kernel average misorientation patterns revealed the formation of hierarchical dislocation arrangements that exhibit clear MF scaling behavior. Despite pronounced visual differences between nonirradiated and irradiated specimens—most notably, the appearance of dislocation channels after irradiation—the singularity spectra suggest that both conditions give rise to similar underlying hierarchical structures. MF analysis provides a quantitative measure of the spatial complexity and self-organization of dislocation patterns, highlighting the accelerated emergence and evolution of the dislocation structures in irradiated polycrystalline materials, as well as the limitation of their spatial extent. The findings indicate that irradiation not only modifies microstructure but also alters correlation-driven dislocation organization. More generally, they demonstrate that MF analysis is a powerful tool for probing mesoscale deformation mechanisms.

Dislocation structures↗

DOE OSTI2025

Comparative Study of Solvatomorphs of Stryker's Reagent Using MicroED and Quantum Mechanics

Abstract The atomic position of hydrogen atoms in metal hydrides has been a long‐standing structural question in inorganic chemistry given that hydride delivery is integral to diverse chemical reactions. Microcrystal electron diffraction (microED), with it's increased sensitivity toward hydrogen atoms relative to X‐ray diffraction, offers a potential path to addressing this challenge. Herein, the first microED study of Stryker's reagent is reported, resulting in the structure of a new benzene solvate. Improved accuracy for hydrogen atom positions was obtained via a quantum crystallography (QCr) approach, Hirshfeld atom refinement (HAR). Structural and topological analysis supports edge bridging hydrides in the microED structure of a THF solvate form, consistent with previous diffraction studies. Interestingly, analysis of a new benzene solvate, discovered in this study, is consistent with mixed edge‐ and face‐bridging hydrides.

Jha, Kunal K. [Division of Chemistry &amp, Chemica↗

DOE OSTI2024

Agrivoltaic Racking Design Optimization Based on Wind and Snow Loading Finite Element Analysis

The racking structure of photovoltaic (PV) systems plays a critical role in ensuring the PV panels generate power properly as it provides integral structural support and sometimes even solar tracking ability. Distinct applications of PV systems require variations of racking structure designs, which yield different mechanical performances under external loading conditions from the environment, such as heavy wind and snow. Past works, such as Reddy et al. [1], have analyzed the pressure effects of wind and snow loading on the racking structure of conventional rooftop and utility PV systems, but there is little knowledge of how various agrivoltaic racking systems perform, in terms of stress and strain, under the same loading conditions. There is also a knowledge gap in the industry on a set of optimized agrivoltaic racking design standards. This study investigates the mechanical performance of various existing racking systems and proposes novel designs that are optimized for agrivoltaics applications under wind and snow loading.

Liao, Quanhuan↗

DOE OSTI2022

Light-induced protein structural dynamics in bacteriophytochrome revealed by time-resolved x-ray solution scattering

Bacteriophytochromes (BphPs) are photoreceptors that regulate a wide range of biological mechanisms via red light–absorbing (Pr)–to–far-red light–absorbing (Pfr) reversible photoconversion. The structural dynamics underlying Pfr-to-Pr photoconversion in a liquid solution phase are not well understood. We used time-resolved x-ray solution scattering (TRXSS) to capture light-induced structural transitions in the bathy BphP photosensory module of Pseudomonas aeruginosa. Kinetic analysis of the TRXSS data identifies three distinct structural species, which are attributed to lumi-F, meta-F, and Pr, connected by time constants of 95 μs and 21 ms. Structural analysis based on molecular dynamics simulations shows that the light activation of PaBphP accompanies quaternary structural rearrangements from an “II”-framed close form of the Pfr state to an “O”-framed open form of the Pr state in terms of the helical backbones. This study provides mechanistic insights into how modular signaling proteins such as BphPs transmit structural signals over long distances and regulate their downstream biological responses.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Synchrotron X-ray microtomography and multifractal analysis for the characterization of pore structure and distribution in softwood pellet biochar

Biochar pores in the micrometer range (1–100 µm) derive from cellular structures of the plant biomass subjected to pyrolysis or can be the result of mechanical processing, such as pelleting. In this study, synchrotron X-ray microtomography was used to investigate the internal pore structure of softwood pellet biochar produced by slow pyrolysis at 550 and 700 °C. The microtomographic data sets consisted of 2025 images of 2560 × 2560 voxels with a voxel side length of 0.87 µm. The three-dimensional reconstructions revealed that pelleting and pyrolysis significantly altered the pore structures of the wood feedstock, creating a network of connected pores between fragments that resembled the wood morphology. While higher pyrolysis temperature increased the specific surface area (as determined by BET nitrogen adsorption), it did not affect the total observed porosity. Multifractal analysis was applied to assess the characteristics of the frequency distribution of pores along each of the three dimensions of reconstructed images of five softwood pellet biochar samples. The resulting singularity and Rényi spectra (generalized dimensions) indicated that the distribution of porosity had monofractal scaling behavior, was homogeneous within the analyzed volumes and consistent between replicate samples. Moreover, the pore distributions were isotropic (direction-independent), which is in strong contrast with the anisotropic pore structure of wood. As pores at the scale analyzed in this study are relevant, for example, for the supply of plant accessible water and habitable space for microorganisms, our findings combined with the ability to reproduce biochar with such pore distribution offer substantial advantages in various biochar applications.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

From Machine Learning to Machine Reasoning: A Model-based Approach to Analyze Equipment Reliability Data

In current nuclear power plants (NPPs) a large amount of condition-based data which can be used to assess and monitor component health and performance. Assessing component health from such data can be performed with a large variety of methods. While the analysis of numeric data can be performed with several methods, the extraction of information from textual data remains a challenge. Currently employed natural language processing (NLP) methods do not really provide quantitative information that might be contained in IRs. In addition, the integration of numeric and textual data to identify possible causal relationships between data elements is still an unresolved challenge. This paper presents an approach to extract information from textual (e.g., incident or maintenance reports) and numeric data that relies on model based system engineer (MBSE) models. MBSE are diagrams designed to represent system and component dependencies (from both a form and functional point of view). In our approach, MBSE models emulate system engineer knowledge about component/system architecture. NLP methods are employed to perform syntactic and semantic analyses. Syntactic analysis analyzes the grammatical structure of a sentence while semantic analysis is designed to analyze the logic structure of a sentence. An innovative element of our approach is that semantic analysis uses MBSE models to identify links between textual elements. Similarly, numeric data is directly linked to elements of the MBSE models in order to map which functions are being monitored.

97 - MATHEMATICS AND COMPUTING↗

DOE OSTI2024

High-Resolution Tandem Mass Spectrometry-Based Analysis of Model Lignin–Iron Complexes: Novel Pipeline and Complex Structures

Understanding the chemical nature of soil organic carbon (SOC) with great potential to bind iron (Fe) minerals is critical for predicting the stability of SOC. Organic ligands of Fe are among the top candidates for SOCs able to strongly sorb on Fe minerals, but most of them are still molecularly uncharacterized. To shed insights into the chemical nature of organic ligands in soil and their fate, this study developed a protocol for identifying organic ligands using ultrahigh-performance liquid chromatography-high-resolution tandem mass spectrometry (UHPLC-HRMS/MS) and metabolomic tools. The protocol was used for investigating the Fe complexes formed by model compounds of lignin-derived organic ligands, namely, caffeic acid (CA), p-coumaric acid (CMA), vanillin (VNL), and cinnamic acid (CNA). Isotopologue analysis of 54/56 Fe was used to screen out the potential UHPLC-HRMS (m/z) features for complexes formed between organic ligands and Fe, with multiple features captured for CA, CMA, VNL, and CNA when 35/37 Cl isotopologue analysis was used as supplementary evidence for the complexes with Cl. MS/MS spectra, fragment analysis, and structure prediction with SIRIUS were used to annotate the structures of mono/bidentate mono/biligand complexes. The analysis determined the structures of monodentate and bidentate complexes of FeL x Cl y (L: organic ligand, x = 1–4, y = 0–3) formed by model compounds. The protocol developed in this study can be used to identify unknown organic ligands occurring in complex environmental samples and shed light on the molecular-level processes governing the stability of the SOC.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Exploring the Genetic Basis of Wild Boar ( Sus scrofa ) and Its Connection to Classical Swine Fever Spread

Classical swine fever (CSF) is the one of the most devastating contagious diseases in domestic swine and wild boar/pigs (Sus scrofa). Population genetics is often used to estimate animal dispersal and can also help evaluate host population connectivity, which is crucial for understanding pathogen dispersal. We surveyed genetic population structure of boars using MIG-seq analysis to clarify the geographic barriers that influence boar dispersal in north-central Japan and to demonstrate the relationship between the spread of CSF infection among boars and their population structure. We obtained 382 single-nucleotide polymorphisms from 348 wild boar samples, and the results of STRUCTURE analysis indicated that the highest ΔK value was at K = 2, followed by K = 4. Based on these results, it is evident that the Abukuma river, a major river within north-central Japan, does not act as a barrier to the gene flow of boars, but rather that human infrastructure hinders their dispersal. Further, according to the time series change in the capture site of CSF-infected wild boar and the sum of the probability of belonging to each of the four clades in individual CSF-infected wild boar, our results indicated that the genetic structure of boar populations was correlated with the outbreak pathway of CSF across our study region. Our study suggests that predictions of disease spread, especially for widely distributed host species, is challenging because of the risk of cryptic breaks and changes in wide range connectivity; however, understanding the genetic population structure of wild boar can be a useful tool for predicting the spread of CSF. We concluded that genetic analysis of host population structure may have the possibility to improve predictions of the future dynamics of disease spread.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2024

Co 3 Ga 2 Ge 5 : Probing site mixing of the Ru 3 Sn 7 structure type with elements difficult to distinguish by diffraction

Co 3 Ga 2 Ge 5 was synthesized through arc-melting stoichiometric ratios of the elements, and a Ru 3 Sn 7 -type structure was confirmed by X-ray diffraction. Because Co 3 Ga 2 Ge 5 contains Ga and Ge, which have very similar X-ray and neutron scattering factors, any Ga/Ge crystallographic site preference cannot be determined with diffraction alone. The purpose of this study is to highlight the importance of using multiple techniques to characterize otherwise structurally ambiguous intermetallic compounds. Here, we utilize 71 Ga nuclear magnetic resonance spectroscopy and an analysis of the X-ray absorption fine structure to clarify the amount of Ga/Ge site mixing. Our combined use of X-ray diffraction and spectroscopy provides a comprehensive structural analysis of Ga site mixing across the Ge crystallographic sites, enhancing the understanding of the structure and properties of Co 3 Ga 2 Ge 5 .

36 MATERIALS SCIENCE↗

DOE OSTI2020

Structure of phospholipase Cε reveals an integrated RA1 domain and previously unidentified regulatory elements

Phospholipase Cε (PLCε) generates lipid-derived second messengers at the plasma and perinuclear membranes in the cardiovascular system. It is activated in response to a wide variety of signals, such as those conveyed by Rap1A and Ras, through a mechanism that involves its C-terminal Ras association (RA) domains (RA1 and RA2). However, the complexity and size of PLCε has hindered its structural and functional analysis. Herein, we report the 2.7 Å crystal structure of the minimal fragment of PLCε that retains basal activity. This structure includes the RA1 domain, which forms extensive interactions with other core domains. A conserved amphipathic helix in the autoregulatory X–Y linker of PLCε is also revealed, which we show modulates activity in vitro and in cells. The studies provide the structural framework for the core of this critical cardiovascular enzyme that will allow for a better understanding of its regulation and roles in disease.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Fingerprinting Interactions between Proteins and Ligands for Facilitating Machine Learning in Drug Discovery

Molecular recognition is fundamental in biology, underpinning intricate processes through specific protein–ligand interactions. This understanding is pivotal in drug discovery, yet traditional experimental methods face limitations in exploring the vast chemical space. Computational approaches, notably quantitative structure–activity/property relationship analysis, have gained prominence. Molecular fingerprints encode molecular structures and serve as property profiles, which are essential in drug discovery. While two-dimensional (2D) fingerprints are commonly used, three-dimensional (3D) structural interaction fingerprints offer enhanced structural features specific to target proteins. Machine learning models trained on interaction fingerprints enable precise binding prediction. Recent focus has shifted to structure-based predictive modeling, with machine-learning scoring functions excelling due to feature engineering guided by key interactions. Notably, 3D interaction fingerprints are gaining ground due to their robustness. Various structural interaction fingerprints have been developed and used in drug discovery, each with unique capabilities. This review recapitulates the developed structural interaction fingerprints and provides two case studies to illustrate the power of interaction fingerprint-driven machine learning. The first elucidates structure–activity relationships in β2 adrenoceptor ligands, demonstrating the ability to differentiate agonists and antagonists. The second employs a retrosynthesis-based pre-trained molecular representation to predict protein–ligand dissociation rates, offering insights into binding kinetics. Despite remarkable progress, challenges persist in interpreting complex machine learning models built on 3D fingerprints, emphasizing the need for strategies to make predictions interpretable. Binding site plasticity and induced fit effects pose additional complexities. Interaction fingerprints are promising but require continued research to harness their full potential.

3D structural interaction fingerprints↗

DOE OSTI2026

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↗

DOE OSTI2024

Impacts of Irradiation Structural Behavior on Thermal Hydraulics Safety Analysis to Support MURR LEU Conversion

The University of Missouri Research Reactor (MURR) located in Columbia, Missouri is one of six U.S. High Performance Research Reactors (USHPRR), including one critical facility, that is actively collaborating with U. S. Department of Energy (DOE) National Nuclear Security Administration (NNSA) Material Management and Minimization (M3) Office of Reactor Conversion and Uranium Supply to convert from the use of highly enriched uranium (HEU; ≥20 wt% U-235) to low-enriched uranium (LEU; <20 wt% U-235) fuel. A new type of very high-density LEU fuel based on an alloy of uranium and 10 wt% molybdenum (U-10Mo) is expected to allow the conversion to LEU of MURR, as well as four other USHPRR. MURR has been working with the Reactor Conversion Pillar at Argonne to perform fuel element design and fuel cycle performance analyses, steady-state thermal hydraulics safety analysis, and accident safety analyses in preparation for the conversion of MURR and to support a preliminary safety analysis report for conversion to LEU fuels. Subsequent analyses have also been performed, including transition cycles where all-fresh LEU fuel elements are introduced upon conversion and progressing through reactor operations the core is brought to equilibrium. Thermal hydraulics safety analyses performed as part of the above have employed an assumption on channel gap reduction due to burnup-related phenomena including fuel swelling, irradiation creep, and oxide layer buildup. Recently, a series of structural analyses have been performed on the MURR LEU fuel plates and an element due to significant differences between the plate and element designs of the MURR HEU and LEU fuels. In addition, NUREG-1537 indicates that structural phenomena are to be evaluated. Two separate types of structural analyses were performed for the MURR LEU fuel element: fluid-structure interaction (FSI) and irradiation thermo-mechanical. The FSI analysis evaluated the effects of hydraulic forces on the MURR LEU fuel element to quantify the flow-induced plate deflection, and a minimal impact to the channel gap thickness was predicted under prototypic and bounding conditions. The irradiation thermo-mechanical analysis evaluated the effects of fuel swelling, irradiation creep, and thermal expansion for the MURR LEU plates and the element for prototypic thermal and irradiation conditions based on a high-fidelity approach multiphysics approach. Overall, this thermo-mechanical analysis predicts smaller gap thickness changes in previously limiting regions. Larger changes are predicted in the middle of channels, and for end channels where power density is not typically a maximum. An additional thermo-mechanical analysis was performed for the outermost HEU fuel plate, which showed a similar magnitude of deflection as the outermost LEU plate. Due to substantial differences between the channel gap reductions assumed for the previous safety analyses and those predicted by the irradiation thermo-mechanical analysis, a need to evaluate their impact on the thermal hydraulics safety analyses arose. This report presents the results from the steady-state safety analyses for normal operation as well as the accident analyses for the two most limiting accident scenarios.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2022

Disentangling Coexisting Structural Order Through Phase Lock-In Analysis of Atomic-Resolution STEM Data

As a real-space technique, atomic-resolution STEM imaging contains both amplitude and geometric phase information about structural order in materials, with the latter encoding important information about local variations and heterogeneities present in crystalline lattices. Such phase information can be extracted using geometric phase analysis (GPA), a method which has generally focused on spatially mapping elastic strain. Here we demonstrate an alternative phase demodulation technique and its application to reveal complex structural phenomena in correlated quantum materials. As with other methods of image phase analysis, the phase lock-in approach can be implemented to extract detailed information about structural order and disorder, including dislocations and compound defects in crystals. Extending the application of this phase analysis to Fourier components that encode periodic modulations of the crystalline lattice, such as superlattice or secondary frequency peaks, we extract the behavior of multiple distinct order parameters within the same image, yielding insights into not only the crystalline heterogeneity but also subtle emergent order parameters such as antipolar displacements. When applied to atomic-resolution images spanning large (~0.5 × 0.5 μm 2 ) fields of view, this approach enables vivid visualizations of the spatial interplay between various structural orders in novel materials.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2026

Noncanonical folding of peptoid oligomers: Formation of a closed conformation in nonpolar solvent

Peptoids provide a versatile platform for foldamer design, yet their conformational behavior in low-dielectric media remains poorly understood. The structural characteristics of N-1-phenylethylglycine (Nspe) homo-oligomers were inves-tigated in chloroform, a solvent that mimics the interior of lipid bilayers, using nuclear magnetic resonance (NMR) spec-troscopy and molecular dynamics (MD) simulations. Nspe7 populated two distinct compact conformations, while Nspe10 adopted a single homogeneous conformation related to the previously reported Nspe9 threaded-loop structure. Integrated experimental and computational analysis reveals that these structures are stabilized by cooperative end-to-end intramo-lecular hydrogen bonding, cis-trans backbone isomerism, and hydrophobic side-chain shielding. The resulting structures minimize exposed polar surface area, demonstrating a closed conformation in the low-dielectric environment. These find-ings establish specific chain-length requirements for achieving well-defined closed conformations. This work provides insights into peptoid folding in nonpolar media, enabling rational design strategies for solvent-directed conformational switching systems.

Oh, Jinyoung↗