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DOE OSTI2025

Diffusion and phase formation in the γ-uranium-technetium system

Phase formation in the U-Tc binary system at 800 °C was investigated using a diffusion couple experiment. Scanning electron microscopy (SEM) and energy dispersive X-ray spectroscopy (EDS) identified four novel potential intermetallic phases - U 7 Tc 3 , U 13 Tc 12 , U 3 Tc 5 , and UTc 4 . Diffusion coefficients were calculated for the intermetallic phases using the Boltzmann-Matano method and were respectively found to be – 120, 38.2, 15.6, and 1.51 × 10 −18 m 2 /s. Tc also exhibits a solid-solution phase with high penetration into the U with a diffusion coefficient of ∼ 10 −14 m 2 /s. Furthermore, these findings expand the number of known U-Tc phases and provide the first diffusion coefficients for the U-Tc system, and contribute valuable data to the broader field of actinide metallurgy.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2025

X-ray Diffraction Studies of Single-Crystal Materials for Broad Battery Applications

Single-crystal materials have attracted growing interest in battery research due to their well-defined crystallographic orientation, absence of grain boundaries, and enhanced mechanical and electrochemical stability. This Review provides a comprehensive overview of recent advances in the synthesis, structural evolution, and performance optimization of single-crystal electrodes and solid electrolytes. Particular focus is placed on the application of advanced X-ray diffraction (XRD) techniques, including operando synchrotron diffraction, reciprocal space mapping, and Bragg coherent diffraction imaging, which have enabled in-depth investigations of lattice strain, cation disorder, phase transitions, and defect formation. Representative case studies across Ni-rich layered oxides, spinel-type cathodes, and garnet-based electrolytes are examined to highlight the structural features unique to single crystals. Additionally, the synergistic integration of XRD with machine learning, tomography, and spectroscopy is discussed as a powerful direction for real-time analysis and predictive modeling. Furthermore, these insights provide critical guidance for the rational design of high-performance single-crystal materials in lithium, sodium, and solid-state battery systems.

25 ENERGY STORAGE↗

DOE OSTI2023

Evolving efforts to maintain and improve XPS analysis quality in an era of increasingly diverse uses and users

Based on literature analysis, X-ray photoelectron spectroscopy (XPS) use continues to increase exponentially. This increased use is accompanied by anecdotal reports and systematic analyses indicating a growing presence of significantly flawed data analyses. Recognition of this problem within the surface analysis community has increased with an understanding that both inexperienced users and increased use of XPS outside the surface analysis community contribute to the problem. The XPS community has initiated several efforts to help address the problem, which is not unique to XPS. This paper describes some of the specific problems identified and some of the community efforts intended to address them. Here, we describe activities focused on three specific issues: (i) requests for detailed guides and protocols and bite-sized versions of information for non-experts, (ii) incomplete data and analysis reporting, and (iii) the high rate of peak fitting problems. A 2019 survey identified the need for guides, protocols, and standards to assist XPS users. One set of such guides has been published, and another is being assembled. Providing incremental bites of useful information is the goal of a series of papers on specific challenges to surface analysis with example solutions has been initiated as Notes and Insights papers in Surface and Interface Analysis. Examination of XPS-containing papers finds that information to establish the credibility and reproducibility of XPS results is often very incomplete. Unfortunately, ISO and ASTM standards require an amount of parameter reporting that seems excessive and unrealistic for many research publications. Initial approaches to develop and distribute a graded approach to parameter reporting are briefly described. Multiple efforts are underway to address the high rate of problems associated with photoelectron peak fitting. These include guides to peak fitting, guides to peak identification and fitting for specific elements, and the development of a peak fitting social network. The fitting social network is designed to facilitate interactions between new and experienced XPS users; analysts trying to fit XPS data (for publication or other reasons) can ask questions and establish dynamic conversations. Encouraging and enabling high-quality XPS analysis and reporting requires several different types of effort from all members of the surface and interface analysis community.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2021

Particle emission with identification from an atmospheric pressure plasma liquid interface

A conspicuous emission phenomenon of luminous particles from the liquid anode surface of an atmospheric pressure DC glow discharge is reported. The emission has been shown to occur when the plasma forms a pattern on the surface of the liquid electrolyte. Here, the spatial-temporal evolutions of the trajectories of emitted particles were studied using a high-speed imaging system. Particles were sampled in flight using a witness plate for analysis. Critical particle characteristics were examined using electron microscope technologies. The morphology of the resulting splats and compositions suggest that they are molten droplets with a great deal of structure, including evidence of nanoprecipitation. A theoretical model was employed to estimate the particle size from the measured splats, which provides a radius range within a hundred micrometers. This experiment leads to the postulation of a mechanism in which particle emission at the plasma liquid interface is likely driven by the Taylor cone effect.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

Scaling and merging time-resolved pink-beam diffraction with variational inference

Time-resolved x-ray crystallography (TR-X) at synchrotrons and free electron lasers is a promising technique for recording dynamics of molecules at atomic resolution. While experimental methods for TR-X have proliferated and matured, data analysis is often difficult. Extracting small, time-dependent changes in signal is frequently a bottleneck for practitioners. Recent work demonstrated this challenge can be addressed when merging redundant observations by a statistical technique known as variational inference (VI). However, the variational approach to time-resolved data analysis requires identification of successful hyperparameters in order to optimally extract signal. In this case study, we present a successful application of VI to time-resolved changes in an enzyme, DJ-1, upon mixing with a substrate molecule, methylglyoxal. We present a strategy to extract high signal-to-noise changes in electron density from these data. Furthermore, we conduct an ablation study, in which we systematically remove one hyperparameter at a time to demonstrate the impact of each hyperparameter choice on the success of our model. We expect this case study will serve as a practical example for how others may deploy VI in order to analyze their time-resolved diffraction data.

47 OTHER INSTRUMENTATION↗

DOE OSTI2024

Identification and characterization of small molecule inhibitors of the LINE-1 retrotransposon endonuclease

The long interspersed nuclear element-1 (LINE-1 or L1) retrotransposon is the only active autonomously replicating retrotransposon in the human genome. L1 harms the cell by inserting new copies, generating DNA damage, and triggering inflammation. Therefore, L1 inhibition could be used to treat many diseases associated with these processes. Previous research has focused on inhibition of the L1 reverse transcriptase due to the prevalence of well-characterized inhibitors of related viral enzymes. Here we present the L1 endonuclease as another target for reducing L1 activity. We characterize structurally diverse small molecule endonuclease inhibitors using computational, biochemical, and biophysical methods. We also show that these inhibitors reduce L1 retrotransposition, L1-induced DNA damage, and inflammation reinforced by L1 in senescent cells. These inhibitors could be used for further pharmacological development and as tools to better understand the life cycle of this element and its impact on disease processes.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2022

Structural definition of a pan-sarbecovirus neutralizing epitope on the spike S2 subunit

Three betacoronaviruses have crossed the species barrier and established human-to-human transmission causing significant morbidity and mortality in the past 20 years. The most current and widespread of these is SARS-CoV-2. The identification of CoVs with zoonotic potential in animal reservoirs suggests that additional outbreaks could occur. Monoclonal antibodies targeting conserved neutralizing epitopes on diverse CoVs can form the basis for prophylaxis and therapeutic treatments and enable the design of vaccines aimed at providing pan-CoV protection. We previously identified a neutralizing monoclonal antibody, CV3-25 that binds to the SARS-CoV-2 spike, neutralizes the SARS-CoV-2 Beta variant comparably to the ancestral Wuhan Hu-1 strain, cross neutralizes SARS-CoV-1 and binds to recombinant proteins derived from the spike-ectodomains of HCoV-OC43 and HCoV-HKU1. Here, we show that the neutralizing activity of CV3-25 is maintained against the Alpha, Delta, Gamma and Omicron variants of concern as well as a SARS-CoV-like bat coronavirus with zoonotic potential by binding to a conserved linear peptide in the stem-helix region. Negative stain electron microscopy and a 1.74 Å crystal structure of a CV3-25/peptide complex demonstrates that CV3-25 binds to the base of the stem helix at the HR2 boundary to an epitope that is distinct from other stem-helix directed neutralizing mAbs.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Identification of $\mathrm{IOMA}$-class neutralizing antibodies targeting the $\mathrm{CD4}$-binding site on the $\mathrm{HIV}$-1 envelope glycoprotein

A major goal of current HIV-1 vaccine design efforts is to induce broadly neutralizing antibodies (bNAbs). The VH1-2-derived bNAb IOMA directed to the CD4-binding site of the HIV-1 envelope glycoprotein is of interest because, unlike the better-known VH1-2-derived VRC01-class bNAbs, it does not require a rare short light chain complementarity-determining region 3 (CDRL3). Here, we describe three IOMA-class NAbs, ACS101-103, with up to 37% breadth, that share many characteristics with IOMA, including an average-length CDRL3. Cryo-electron microscopy revealed that ACS101 shares interactions with those observed with other VH1-2 and VH1-46-class bNAbs, but exhibits a unique binding mode to residues in loop D. Analysis of longitudinal sequences from the patient suggests that a transmitter/founder-virus lacking the N276 glycan might have initiated the development of these NAbs. Together these data strengthen the rationale for germline-targeting vaccination strategies to induce IOMA-class bNAbs and provide a wealth of sequence and structural information to support such strategies.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Identification of a broadly conserved family of enzymes that hydrolyze (p)ppApp

Bacteria produce a variety of nucleotide second messengers to adapt to their surroundings. Although chemically similar, the nucleotides guanosine penta- and tetraphosphate [(p)ppGpp] and adenosine penta- and tetraphosphate [(p)ppApp] have distinct functions in bacteria. (p)ppGpp mediates survival under nutrient-limiting conditions and its intracellular levels are regulated by synthetases and hydrolases belonging to the RelA-SpoT homolog (RSH) family of enzymes. By contrast, (p)ppApp is not known to be involved in nutrient stress responses and is synthesized by RSH-resembling toxins that inhibit the growth of bacterial cells. However, it remains unclear whether there exists a family of hydrolases that specifically act on (p)ppApp to reverse its toxic effects. Here, we present the structure and biochemical characterization of adenosine 3'-pyrophosphohydrolase 1 (Aph1), the founding member of a monofunctional (p)ppApp hydrolase family of enzymes. Our work reveals that Aph1 adopts a histidine-aspartate (HD)-domain fold characteristic of phosphohydrolase metalloenzymes and its activity mitigates the growth inhibitory effects of (p)ppApp-synthesizing toxins. Using an informatic approach, we identify over 2,000 putative (p)ppApp hydrolases that are widely distributed across bacterial phyla and found in diverse genomic contexts, and we demonstrate that 12 representative members hydrolyze ppApp. In addition, our in silico analyses reveal a unique molecular signature that is specific to (p)ppApp hydrolases, and we show that mutation of two residues within this signature broadens the specificity of Aph1 to promiscuously hydrolyze (p)ppGpp in vitro. Overall, our findings indicate that like (p)ppGpp hydrolases, (p)ppApp hydrolases are widespread in bacteria and may play important and underappreciated role(s) in bacterial physiology.

(p)ppApp↗

DOE OSTI2024

Accurate and Data‐Efficient Micro X‐ray Diffraction Phase Identification Using Multitask Learning: Application to Hydrothermal Fluids

Traditional analysis of highly distorted micro X‐ray diffraction (μ‐XRD) patterns from hydrothermal fluid environments is a time‐consuming process, often requiring substantial data preprocessing and labeled experimental data. Herein, the potential of deep learning with a multitask learning (MTL) architecture to overcome these limitations is demonstrated. MTL models are trained to identify phase information in μ‐XRD patterns, minimizing the need for labeled experimental data and masking preprocessing steps. Notably, MTL models show superior accuracy compared to binary classification convolutional neural networks. Additionally, introducing a tailored cross‐entropy loss function improves MTL model performance. Most significantly, MTL models tuned to analyze raw and unmasked XRD patterns achieve close performance to models analyzing preprocessed data, with minimal accuracy differences. This work indicates that advanced deep learning architectures like MTL can automate arduous data handling tasks, streamline the analysis of distorted XRD patterns, and reduce the reliance on labor‐intensive experimental datasets.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2026

Decoding α-MoC 1− x Nanoparticle Formation in Continuous Flow via Machine Learning

Molybdenum carbide nanoparticles (α-MoC 1−x NPs) are promising catalysts that offer noble-metal-like performance at lower cost. We report a mild continuous-flow synthesis of α-MoC 1−x NPs from Mo(CO) 6 , coupled with in-line spectroscopic monitoring and machine learning (ML)-based analysis to quantify precursor conversion and product formation in real time. A multilayer perceptron ML model was found to accurately deconvolute complex, nonlinear spectral patterns, enabling identification of a two-step reaction pathway, involving precursor conversion to an amorphous intermediate followed by intraparticle crystallization to α-MoC 1−x NPs, with the first step being rate limiting. Ex situ small angle X-ray scattering (SAXS) and X-ray diffraction (XRD) validation confirm the predicted concentration profiles and crystallization behavior. This integrated approach showcases how ML can empower insights into NP nucleation and growth, paving the way for self-driving, flow-based platforms for NP synthesis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Fast-neutron/gamma-ray radiography using a broad-energy neutron source

Transmission radiography is a well-established nondestructive examination technique with widespread application to fields ranging from medicine to security. Traditionally, inspection is performed using a single particle type (such as x-rays). However, the information available using a single probe for traditional radiography is limited. The present work evaluates material discrimination via transmission radiography using the attenuation ratio of monoenergetic gamma rays to a broad spectrum of fast neutrons. Here, the method was assessed using an 241 Am/Be radioisotope source that provides both 4.4 MeV gamma rays and a spectrum of fast neutrons up to 12 MeV. A total of 14 object configurations were measured: seven different materials each with two thicknesses (2.5 cm and 5 cm). The ability to distinguish materials was evaluated and shows more significant variation among atomic numbers than for high-energy x-rays alone, making it easier to distinguish between classes such as low-, mid-, and high-Z materials. These results suggest that superior material discrimination is also possible using a combination of monoenergetic gamma rays and broad-spectrum fast neutrons from a variety of nuclear reactions, such as 11 B(d,nγ) 12 C, that could be implemented in future inspection systems.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2026

Machine-Learning-Driven Discovery of Water Splitting BaFe 2 O 4 and Human-in-the-Loop Improvement via Al-Substitution for Increased Thermal Stability

Thermochemical hydrogen (TCH) production offers a promising method for converting thermal energy into hydrogen fuel through heat-driven redox cycles of metal oxides. Here, in this work a defect graph neural network (dGNN) was used to predict oxygen vacancy formation energies ΔH V O combined with Materials Project predictions of oxygen chemical potential stability to screen candidate oxides via high-throughput database analysis. BaFe 2 O 4 was identified as a promising material for experimental validation based on its predicted ΔH V O , oxygen chemical potential stability range, and potential for tunable substitutions to improve thermal properties. Experimental validation using thermogravimetric analysis (TGA), stagnation flow reactor (SFR), X-ray diffraction (XRD), and electron microscopy confirmed positive water-splitting behavior but also revealed limitations in thermal stability under aggressive reduction conditions. To address this, a human-in-the-loop modification strategy was employed introducing Al substitution in BaFe 2–x Al x O 4 ; this modification improves thermal stability, alters the crystal structure and enhances overall performance. These results demonstrate a combined computational and experimental workflow in which machine learning accelerates identification of promising candidates, while targeted experimental design enables optimization of functional performance. This approach advances the development of robust, cost-effective TCH materials and highlights the importance of integrating data-driven discovery with human-guided materials design in paving the way for scalable hydrogen production technologies.

organic↗

DOE OSTI2022

Resolving atomistic structure and oxygen evolution activity in nickel antimonates

The oxygen evolution reaction (OER) requires electrodes that are not only catalytically active, but also stable under harsh electrochemical environments to enable efficient, durable technologies. Our recent report of a stable amorphous Ni 0.5 Sb 0.5 O z OER photoanode established Ni–Sb–O as an important system for computational understanding of both the structural and catalytic behavior of these complex oxides. In the present work we show that Ni x Sb 1-x O z with x > 0.33 crystallizes into a previously unknown phase. Guided by experimental X-ray diffraction, here, we use density functional theory calculations to perform a prototype phase search to identify a broad family of stable and metastable mixed rutile and hexagonal-like phases for x = 0.33, 0.50, and 0.66 compositions. For the identified phases, we predict favorable oxygen vacancy formation energies for Ni-rich compositions under the reducing synthesis conditions which match measured Ni K-edge X-ray absorption spectra. The calculated overpotential for the most active site decreases with increasing Ni content, from 0.91 V (x = 0.33) to 0.49 V (x = 0.66), which captures the experimentally observed trend. We find the active site changes from the Ni–O–Sb bridge to a Ni–O–Ni bridge at increasing Ni concentrations, rather than the commonly studied singly under-coordinated sites. Finally, detailed Pourbaix analysis of the identified phases show excellent electrochemical stability, consistent with experimentally measured low metal ion concentrations in the electrolyte of photoelectrochemical cells. Collectively, our consideration of an ensemble of structures enables identification of the most catalytically prolific structural motifs, aiding the understanding of crystalline and amorphous catalysts and elucidating the co-optimization of activity and durability in nickel antimonates.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

CODEX: Role of velocity substructure in the scaling relations of galaxy clusters

The use of galaxy clusters as cosmological probes relies on a detailed understanding of their properties. They define cluster selection and ranking linked to a cosmologically significant cluster mass function. Previous studies have employed small samples of clusters, concentrating on achieving the first calibrations of cluster properties with mass, while the diversity of cluster properties has been revealed via detailed studies. The large spectroscopic follow-up on the CODEX cluster sample with SDSS and NOT enables a detailed study of hundreds of clusters, lifting the limitations of previous samples. We aim to update the spectroscopic cluster identification of CODEX by running the spectroscopic group finder on the follow-up spectroscopy results and connecting the dynamical state of clusters to their scaling relations. We implemented a reproducible spectroscopic membership determination and cleaning procedures, based on the redMaPPer membership, running the spectroscopic group finder on the follow-up spectroscopy results and cleaning the membership for spectroscopic outliers. We applied the Anderson-Darling test for velocity substructure and analysed its influence on the scaling relations. We also tested the effect of the X-ray-to-optical centre offset on the scaling relations. We report on the scaling relations between richness, X-ray luminosity, and velocity dispersion for a complete sample of clusters with at least 15 members. Clusters with velocity substructure exhibit enhanced velocity dispersion for a given richness and are characterized by 2.5 times larger scatter. Clusters that have a strong offset in X-ray-to-optical centres have comparable scaling relations as clusters with substructure. We demonstrate that there is a consistency in the parameters of the scaling relations for the low- and high-richness galaxy clusters. Splitting the clusters by redshift, we note a decrease in scatter with redshift in all scaling relations. We localize the redshift range where a high scatter is observed to z < 0.15, which is in agreement with the literature results on the scatter. We note that the increase in scatter for both high- and low-luminosity clusters is z < 0.15, suggesting that both cooling and the resulting active galactic nucleus feedback are at the root of this scatter.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2023

3D track reconstruction of low-energy electrons in the MIGDAL low pressure optical time projection chamber

Here, we demonstrate three-dimensional track reconstruction of electrons in a low pressure (50 Torr) optical TPC consisting of two glass GEMs with an ITO strip readout in CF 4 and CF 4 /Ar mixtures. The reconstructed tracks show a variety of event topologies, including short tracks from photoelectrons induced by 55 Fe 5.9 keV X-rays and long tracks from gamma ray interactions and beta decays. Algorithms for event identification and track ridge detection are discussed as well as multiple methods for integrating information from the camera image and ITO waveforms with the goal of full 3D reconstruction of the track.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2023

Effect of Pt vacancies on magnetotransport of Weyl semimetal candidate GdPtSb epitaxial films

Here, we examine the effects of Pt vacancies on the magnetotransport properties of Weyl semimetal candidate GdPtSb films, grown by molecular beam epitaxy on c-plane sapphire. Rutherford backscattering spectrometry and x-ray diffraction measurements suggest that phase-pure GdPt x ⁢Sb films can accommodate up to 15% of Pt vacancies (x = 0.85), which act as acceptors, as measured by the Hall effect. Two classes of electrical transport behavior are observed. Pt-deficient films display metallic temperature-dependent resistivity (dρ/dT > 0). The longitudinal magnetoresistance (LMR, magnetic field B parallel to electric field E) is more negative than transverse magnetoresistance (TMR, B⁢⊥⁢E), consistent with the expected chiral anomaly for a Weyl semimetal. The combination of Pt-vacancy disorder and doping away from the expected Weyl nodes, however, suggests that conductivity fluctuations may explain the negative LMR rather than chiral anomaly. Samples closer to stoichiometry display the opposite behavior: semiconductorlike resistivity (dρ/dT > 0) and more negative TMR than LMR. Hysteresis and other nonlinearities in the low-field Hall effect and magnetoresistance suggest that spin-disorder scattering and possible topological Hall effect may dominate the near-stoichiometric samples. Our findings highlight the complications of transport-based identification of Weyl nodes but point to possible topological spin textures in GdPtSb.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2021

Infrared reflection absorption spectroscopy and temperature-programmed desorption studies of CO adsorption on Ni/CeO 2 (111) thin films: The role of the ceria support

Ceria-supported Ni has shown unique catalytic activity due to unique properties of small Ni particles and strong metal-support interaction. Identification of adsorption sites and understanding the chemical interaction over Ni-ceria at the fundamental level provide crucial insights into the reaction pathways of complex catalytic processes. In this study, to probe the surface sites, the adsorption of CO was carried out with model Ni/ceria systems consisting of Ni nanoparticles vapor-deposited on well-ordered CeO x (111) (1.5 < x < 2) thin films using infrared reflection absorption spectroscopy (IRRAS) and temperature-programmed desorption (TPD) under ultrahigh vacuum (UHV) conditions. Fully oxidized CeO 2 (111) (Ce 4+ ) and partially reduced CeO 1.75 (111) (Ce 4+ /Ce 3+ ) thin films were grown on Ru(0001) to examine the role of the ceria support. Additionally, Ni with low coverages (e.g., 0.2 ML) grows forming small two-dimensional particles on ceria at 300 K, which develop into three-dimensional clusters after heating to 700 K. In the absence of Ni, CO adsorption at 1 mTorr at 100 K shows distinct IR bands at 2158 cm -1 on CeO 2 and 2165 cm -1 on CeO 1.75 . Bridging and atop IR bands associated with CO adsorption over metallic Ni were observed on the Ni-CeO 1.75 surface at 300 K under UHV conditions. CO adsorption over Ni 0 was also observed over as-deposited Ni on CeO 2 . However, a new IR band at 2146 cm -1 due to CO adsorption over Ni 2+ species was detected at 100 K over the annealed Ni particles on CeO 2 . CO IRRAS data suggest the oxidation of Ni to Ni 2+ on CeO 2 and the formation of predominant Ni 2+ species with heating, which is further confirmed with CO TPD data and previous x-ray photoelectron spectroscopy results.

36 MATERIALS SCIENCE↗