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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Synthesis of Lanthanide-Based Intermetallic Silicides

Lanthanide-containing materials are of interest because of their useful magnetic and electronic behavior. To study this intrinsic behavior, researchers need high-quality single crystals to avoid interference from grain boundaries or defects commonly found in polycrystalline samples. One method for growing single crystals is metal-flux synthesis, an approach that promotes crystal growth at lower reaction temperatures thus providing access to complex intermetallic phases. My project focuses on synthesizing novel lanthanide-containing intermetallic silicides related to previously reported f-element compounds with the Gd1??Fe4Si10?? structure type. I investigated reactions targeting lanthanum, praseodymium, neodymium, samarium, europium, and gadolinium-containing products, and used scanning electron microscopy with energy-dispersive X-ray spectroscopy (SEM-EDS) to identify promising lanthanide-containing phases. I prepared reactions by loading lanthanide oxides, Co, Si, Al, and Ga into alumina crucibles in a 0.2:1:1:10:10 Ln2O3/Co/Si/Al/Ga mmol ratio, where Ln = La, Nd, Pr, Sm, Eu, or Gd. The reactions were sealed in quartz tubes, heated in a furnace, and centrifuged to separate crystals from excess flux. Afterwards, I mechanically isolated single crystals and prepared them for characterization. Pr-, Nd-, and Sm-containing reactions were confirmed through SEM-EDS to have formed the targeted quaternary phase. Single crystal X-ray diffraction (SC-XRD) data showed the Nd-containing crystals exhibited a hexagonal unit cell associated with the Gd1??Fe4Si10?? structure type. La- and Eu-containing reactions instead formed competing Co(Al/Ga/Si)3 phase crystals. Single-crystal XRD, powder XRD, and magnetic susceptibility and heat-capacity measurements will be collected for the remaining lanthanide-containing crystals. This data will help determine the complete crystal structure of the lanthanide analogues, their phase purity and whether they exhibit localized magnetic behavior, magnetic ordering, or other electronic signatures that can be compared with the previously reported actinide analogues. The disordered structure of this intermetallic family is associated with unusual magnetic and electronic behavior meaning lanthanide analogues may show potential as thermoelectric materials. Developing new thermoelectric candidate materials is relevant to energy efficiency and waste-heat recovery, which supports DOE’s broader goal of advancing science and technology solutions for America’s energy needs.

37 - INORGANIC, ORGANIC, PHYSICAL AND ANALYTICAL C↗
DOE OSTI2026

EDXplorer: A Utility for APA Analysis

The automated particle analysis (APA) method of scanning electron microscopy (SEM) energy dispersive X-ray spectroscopy (EDS/EDX) is a useful tool for analyzing the elemental and morphological data of particulate samples. Often, such datasets have many thousands of particles, and it can be difficult to sift through the data to find meaningful trends. EDXplorer is a software utility for processing APA data. They enable the user to easily load data and determine the important components and aspects of the datasets using a powerful and versatile library of data plotting functions, mainly centered around scatter plots and histograms. These programs are intended to fill a void in the data processing of data from certain instruments, where often the user must rely on their own code or other software that is not user-friendly. EDXplorer is intended as a general plotting utility for browsing through data and discovering data trends.

Moseley, Duncan [ORNL] (ORCID:0000000343518347)↗
DOE OSTI2023

Coso Geothermal Spectral Library for Rocks and Minerals

An integrated open mineral spectral library designed to enhance the utility and precision of mineral spectral data for geothermal exploration, developed from a reliable and comprehensive digital dataset for seamless sharing by integrating field data, the USGS spectral library, and pertinent information obtained from Coso geothermal field (Coso) in California. The ASD FieldSpec portable spectrometer was utilized for collecting spectral data, which was subsequently analyzed using the THOR Material Identification tool in ENVI, The Spectral Geologist (TSG) software by CSIRO, and the Fully Constrained Linear Spectral Unmixing algorithm (FCLSU) in MATLAB. Scanning Electron Microscopy (SEM) with a mineralogy-analyzing function was employed to assess the mineral composition of samples, ensuring precise mineralogical analysis. A portable X-ray fluorescence (pXRF) spectrometer was also utilized to gather information on elemental enrichment. A framework for developing spectra data and establishing spectral libraries for various geological cases was proposed within this study. The characteristic spectra of six alteration minerals - alunite, chalcedony, epidote, hematite, kaolinite, and opal - were acquired from Coso samples. The spectral library for the Coso alteration minerals was introduced for further application in academic study or industrial exploration. To browse the Coso Geothermal Spectral data and related figures from spreadsheets: #1 Unzip and store the following items in the same folder. 'Contact Probe Data.zip', 'Sample Photos.zip', and 'Coso spectra of higher-certainity minerals.xlsx'. #2 Open 'Coso spectra of higher-certainity minerals.xlsx'. The hyperlinks in the spreadsheet lead to the folders or figures of: spectra .asd file, spectra ASC II file, spectra plots, and sample photos. The spectra data is raw data without splice correction. Spectra .asd files require particular software to open. (These cannot be opened in GIS software such as ArcGIS.) Spectra ASC II files can be opened in a text editor or spread sheet program.

15 GEOTHERMAL ENERGY↗
DOE OSTI2026

Geology of the One Earth Energy Site

The One Earth Energy site is one of two sites in the Illinois Storage Corridor (ISC) project. The objectives of the ISC project is to accelerate commercial deployment of carbon capture utilization and storage at two individual sites and receive approvals for Underground Injection Control (UIC) Class VI permits for construction at each site. At the One Earth Energy site, an extensive data collection program was undertaken, which included the drilling of a test well (One Earth Energy #1 [OEE #1]), four 2D seismic lines, and a small 3D seismic survey. The OEE #1 well was drilled in 2022 and acquired extensive core, log, and testing data to characterize the subsurface geology of the site. Coring was focused on the storage interval, the Mt. Simon Sandstone, and the confining interval, the Eau Claire Formation. The core and log data were used to evaluate the sedimentology and sequence stratigraphy, as well as to develop the conceptual geologic model. This report includes the geological summaries of the Mt. Simon Sandstone and the Eau Claire Formation. The extensive analysis of the log data is included in the petrophysical section, showing ranges of porosity, estimated pore size, and the mineral content of selected zones in the well. The separate petrographic technical report entitled “Petrographic and Advanced Geologic Characterization Report on One Earth Energy #1 (API# 1211325373)”, report number DOE-UIUC-0031892-04, details thin section point-counting analysis that includes mineralogical and pore space analysis, including grain size analysis, annotated thin section photomicrographs, scanning electron microscopy (SEM) with energy dispersive X-ray spectroscopy (EDS), and statistics of grain size analysis on Mt. Simon thin sections from OEE #1. The final OEE #1 well data to be included in this geology report is the routine core analysis of both whole core plugs and rotary sidewall core plugs. In addition to the OEE #1 well, four 2D seismic lines and a small 3D survey were acquired as part of the overall subsurface geological characterization. This geology report references the seismic interpretation report, entitled “One Earth Energy Site Seismic Interpretation Task 5.0”, report number DOE-UIUC-0031892-07. This report details the stratigraphic and structural interpretation of the 2D and 3D seismic data acquired at the One Earth Energy site. The 2D seismic data was acquired in 2019 and 2021, and the 3D survey was acquired in 2022. The objectives of the seismic programs were to contribute to the subsurface characterization of the Mt. Simon-Eau Claire Storage Complex by evaluating the continuity of potential storage reservoirs and containment intervals across the project area, and to determine if any geologic features are present that would increase containment risk to the proposed carbon storage project.

09 BIOMASS FUELS↗
DOE OSTI2025

An integrated approach to examine fuel-cladding chemical interaction in HT9/U-10Zr metallic fast reactor fuels: Coupling machine learning with electron microscopy and local mechanical properties analysis

The metallic U-Zr nuclear fuel alloy has garnered renewed interest as a promising candidate for next-generation sodium-cooled fast reactors. Recent studies and technology assessments have identified several areas requiring improvements, enhanced knowledge, and reliable data to strengthen the U-Zr fuel design basis for qualification and commercial applications. One of the most challenging phenomena impacting this fuel system’s performance is fuel-cladding chemical interaction (FCCI). This work aimed to harvest FCCI data by examining selected HT9/U-10Zr (wt. %) fuel samples of prototypic full-length fuel pins through an integrated approach. This approach integrated scanning electron microscopy (SEM) microstructure characterization with localized mechanical properties examination to deepen understanding of FCCI phenomenon in HT9/U-10Zr fuel system. Particularly, this study focused on MFF fuel pins irradiated at Fast Flux Test Facility (FFTF), which aimed to qualify metallic fuel as a driver fuel for FFTF and to assess its viability for larger-scale fast reactors. Electron microscopy provided high confidence in detecting and distinguishing the different FCCI layers, while small-scale mechanical testing (SSMT) probed the mechanical properties of these layers. SEM examination of a MFF-2 pin 192167, with a time averaged inner cladding temperature (TICT) slightly over 500°C, revealed minimal cladding-side FCCI (cladding wastage). In contrast, significantly thicker cladding wastage comprising two distinct sublayers was observed in samples from the thermally hot MFF-3 pin 193045 and MFF-5 pin 195011 where the TICT ranged from 610-635°C. SSMT indicated complete embrittlement in the sublayer adjacent to the fuel and a tendency toward embrittlement in the other sublayer. Additionally, a new machine learning method was developed, validated, and used to quantify cladding wastage thickness. The machine learning method reliably predicted the wastage thickness across various fuel pins and sample cross-sections. Furthermore, the available cladding wastage data from HT9/U-10Zr fuel system demonstrated a strong temperature dependency. However, the dataset remains small, and ongoing research activities are essential to further understand the FCCI phenomenon and develop a reliable FCCI model for enhanced fuel performance simulation under various conditions.

36 - MATERIALS SCIENCE↗
DOE OSTI2023

Large Eddy Simulation of Gasoline Sprays in a Lagrangian–Eulerian Framework Using the High-Order Spectral Element Method

Predicting the spray evolution using simulations requires accurate modeling of the turbulent gas-phase flow field. Here, in this study, the high-order spectral-element method (SEM), implemented in the code Nek5000, was used to provide highly resolved solutions to the turbulent flow field. Spray modeling capabilities were implemented into the Nek5000 code. The spray is modeled in a Lagrangian–Eulerian (LE) framework, where the liquid is represented by discrete parcels of droplets. The method for coupling liquid and gas in the context of SEM is described, which allows for very fine meshes to be used without affecting the stability of the solution. Large-eddy simulations (LES) of the eight-hole ECN Spray G gasoline injector were conducted. Numerical results are compared against experimental data for liquid penetration, droplet size and gas velocity. The morphology of the multiplume spray is compared against experimental data. The effect of different spray injection inputs is analyzed. It was found that using a plume direction of 33 deg and an injection cone angle of 30 deg produced the best results overall. This work shows the applicability of SEM for spray modeling applications, where use of a high-order flow solver can help us understand the multiplume spray aerodynamics and how it leads to plume collapse under certain conditions. Results also highlight the need for tuning spray input parameters in the LE framework, even when high-fidelity gas flow solutions are possible.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

Advances in imaging, scattering, spectroscopy, and machine learning-aided approaches for multiscale characterization of cementitious systems

Recent progress in methods used in the multiscale characterization of cementitious systems is reviewed, focusing on advances in imaging, scattering, and spectroscopy. The review includes relevant applications and developments in machine learning and other data analytics approaches to enhance characterization. Developments in imaging using light and electron microscopy as well as x-ray (i.e., from synchrotron) methods are summarized. Updates include scanning electron microscopy (SEM), transmission electron microscopy (TEM), tomography, and holography. A critical overview of spectroscopy (e.g., MAS NMR, Raman) and scattering (e.g., neutron, x-ray, synchrotron x-ray) methods is provided, and the intersection of these with imaging is developed (e.g., Raman imaging). Additionally, the paper summarizes recent developments in and implementations of state-of-the-art machine-learning algorithms and data analytics methods for automated, systematic, and/or quantitative analyses of image data sets. The review considers but is not limited to the application of these methods for investigating the hydration and microstructure development of cement phases, low-carbon-footprint cements (e.g., limestone calcined clay cements, LC3), environmental interactions (e.g., ASR) and model systems. Finally, the present work provides a critical presentation of advances in characterization methods that link together the composition and multiscale structure of cementitious materials.

42 ENGINEERING↗
DOE OSTI2026

Raw electron microscopy images for "The Importance of Nano-edges in Atomic Stencilling and Chiroptically Active Assembly of Patchy Gold Tetrahedra"

This dataset contains the raw transmission electron microscopy (TEM) and scanning electron microscopy (SEM) images used in the main figures of the paper “The Importance of Nano-edges in Atomic Stencilling and Chiroptically Active Assembly of Patchy Gold Tetrahedra (2026).” All the images were acquired at the Materials Research Laboratory, University of Illinois at Urbana-Champaign, by Qian Chen group. 1. We provide five subfolders, each named according to the corresponding figure numbers in the paper. 2. All files in the subfolders for Figures 1–3 and 5 are named as "Panel [letter]_*", where [letter] (e.g., a, b, c) represents the raw images used for the corresponding panels. 3. All files in the subfolder for Figure 4 correspond to panel f and show the configurations of patchy tetrahedra synthesized at varying concentrations of iodide and 2-naphthalenethiol. They are named "Experiment_[number]", where [number] represents the corresponding data points in the phase diagram. 4. In TEM images, the bright and dark regions indicate the polymer patches and nanoparticle cores, respectively. 5. In SEM images, the bright and dark regions indicate the nanoparticle cores and polymer patches, respectively. 6. Abbreviations in file names: HAADF-STEM (high-angle annular dark-field scanning transmission electron microscopy), PINEM (photon-induced near-field electron microscopy), and RCP/LCP (left-/right-handed circularly polarized).

chirality↗
DOE OSTI2021

Tunable structural, morphological and optical properties of undoped, Mn, Ni and Ag-doped CuInS 2 thin films prepared by AACVD

The preparation of high-quality copper indium sulphide, CuInS 2 photo-absorber material with tunable properties for efficient, low-cost, thin film solar cells using scalable methods remains a challenge. In order to address this, high quality off-stoichiometric undoped and Mn, Ni and Ag-doped CuInS 2 (CIS) thin films have been deposited onto glass substrates by aerosol-assisted chemical vapour deposition (AACVD) using metal diethyldithiocarbamate precursors at temperatures of 350, 400 and 450 °C. Data from powder X-ray diffraction (p-XRD), Raman spectroscopy and scanning electron microscopy-energy dispersive X-ray spectroscopy (SEM-EDS) suggest a correlation of morphology and composition of tetragonal phase (chalcopyrite and copper-gold-type) sulphur-deficient microcrystalline CIS thin films. For undoped thin films, near-infrared optical absorption and emission with tunable band gap between 1.32 and 1.42 eV are likely associated with donor-acceptor pairs involving deep or shallow electronic states such as sulphur vacancies (V S •• ), indium-copper anti-sites (In Cu •• ) and indium interstitials (In i ••• ) as donors and copper vacancies (V Cu ') as acceptors. Whilst Mn-doped thin films exhibit minimal tunable properties, Ni and Ag-doped films exhibit tunable morphology, composition and near-infrared absorption for small dopant content. Here, though further studies are required to explore the defect chemistry, these results show the utility of AACVD in tuning structural, morphological and optical properties of undoped, Mn, Ni and Ag-doped CIS thin films.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Voltage and temperature effects on low cobalt lithium-ion battery cathode degradation

Degradation of low cobalt lithium-ion cathodes was tested using a full factorial combination of upper cut-off voltage (4.0 V and 4.3 V vs. Li/Li + ) and operating temperature (25 °C and 60 °C). Half-cell batteries were analyzed with electrochemical and microstructural characterization methods. Electrochemical performance was assessed with galvanostatic cycling, cyclic voltammetry (CV), and electrochemical impedance spectroscopy (EIS) supported by distribution of relaxation times (DRT) analysis. Electrode microstructure was characterized with scanning electron microscopy (SEM), X-ray diffraction (XRD), and X-ray absorption near edge structure (XANES) imaging. Higher cut-off voltage cycling shows presence of NiO x formation, a low diffusivity rock-salt phase, in both CV and XRD data. XRD patterns confirmed that the rock-salt phase was beginning to form at the low cut-off voltage at high temperature, but in much lower intensity than at the high cut-off voltage. Higher temperature accelerates degradation processes at both voltages. Degradation factors at high temperature include NiO x formation, cathode material dissolution, and electrolyte decomposition. SEM analysis suggests that supporting phases may isolate and disconnect active material particles reducing capacity retention and battery life cycle. DRT analysis and XANES imaging show that both high temperature samples revealed a NiO x phase based on an increased diffusive impedance and a visible shift in the XANES spectra. The low cut-off voltage, high temperature sample showed a split peak and shift to lower energies indicating early formation of the NiO x phase. The diffusive impedance, which hinders intercalation and deintercalation, is driven by the formation of the NiO x phase. While primarily driven by cut-off voltage, elevated temperature also contributes to this degradation mechanism.

electrochemical impedance spectroscopy↗
DOE OSTI2026

Understanding the structural and morphological effects of synthesis route on NpO 2

The availability of actinide standard materials for use in nuclear safeguard applications is critical, as is thorough characterization thereof. Although accurate trace element compositions and isotopic considerations are paramount for deployment of reference standards, structural characterization is also essential towards accurately describing the chemical form and potential matrix effects in candidate materials. Here, to this end, samples of NpO 2 were synthesized via a direct denitration (DD) method and probed with powder X-ray diffraction (PXRD), Raman spectroscopy, and scanning electron microscopy (SEM) for structural and morphological characterization and comparison with NpO 2 materials produced via modified direct denitration (MDD). PXRD confirmed the bulk identity of NpO 2 , and no additional phases were identified using this method. Analysis of Raman data collected using a 532 nm excitation wavelength indicates that samples are mostly phase pure; however, some variability in spectral features is observed. Analysis of additional spectroscopic data collected with a 785 nm excitation wavelength revealed variability in the relative intensity of spectral features. Raman spectroscopy indicates that the sample is primarily NpO 2 ; however, additional signals indicate possible structural disorder, oxidized species, or potential contributions from other Np phases. To further investigate the possibility of additional phase contributions within the sample of NpO 2 , Raman spectroscopic mapping was employed to examine the homogeneity of the sample produced via DD. From this analysis, we determined that despite variability in the intensity of Raman-active vibrational modes, consistent spectra are obtained throughout the area of the sample investigated. SEM images show aggregates with variable sizes and shapes, with rounded, primary particles possessing an average diameter of approximately 100 nm. Comparison of the results of these multimodal analyses to the literature indicates that the crystal chemical, spectroscopic, and microstructural properties of NpO 2 vary based on synthesis method, even if X-ray diffraction data indicate that the bulk phase is NpO 2 .

Direct denitration↗
DOE OSTI2022

Is the Adoption of Electric Vehicles (EVs) and Solar Photovoltaics (PVs) Interdependent or Independent? An Integrated EVs-PVs Modeling Framework

Transportation and residential energy consumption account for more than one-half of the overall energy consumption in the United States. Adoption of electric vehicles (EVs) can play a key role in decarbonizing the transportation sector, while the adoption of renewable energy sources (e.g., solar photovoltaics or PVs) could bring similar benefits to the residential energy sector and in turn support transport electrification. Although the market share for both EVs and PVs continue to grow, both these emerging technologies are deployed rather disjoint without considering the existence of potential similarities among users who own (or aspire to own) EVs and PVs. This might be due to lack of understanding of the behavioral interdependence in consumer preferences towards these technologies. To fill this gap in knowledge, this study utilizes data from the 2018 WholeTraveler Transportation Behavior Study to develop an integrated model system that explores EV and PV adoption behaviors. A structural equations model (SEM) is employed that incorporates direct effects as well as error correlations among the adoption behaviors for EVs and PVs. Model results indicate that the adoption behavior for both these technologies is indeed interconnected and significantly influenced by attitudes, values and personality traits. Findings from this research suggest that incentives (e.g., subsidies) that drive 'bundled' adoption of EVs and PVs could accelerate the adoption of both these sustainable technologies. The results highlights the need to consider transport and building energy efficient technology adoption behavior in a single integrated structure.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗
DOE OSTI2021

A study of real-world micrograph data quality and machine learning model robustness

Abstract Machine-learning (ML) techniques hold the potential of enabling efficient quantitative micrograph analysis, but the robustness of ML models with respect to real-world micrograph quality variations has not been carefully evaluated. We collected thousands of scanning electron microscopy (SEM) micrographs for molecular solid materials, in which image pixel intensities vary due to both the microstructure content and microscope instrument conditions. We then built ML models to predict the ultimate compressive strength (UCS) of consolidated molecular solids, by encoding micrographs with different image feature descriptors and training a random forest regressor, and by training an end-to-end deep-learning (DL) model. Results show that instrument-induced pixel intensity signals can affect ML model predictions in a consistently negative way. As a remedy, we explored intensity normalization techniques. It is seen that intensity normalization helps to improve micrograph data quality and ML model robustness, but microscope-induced intensity variations can be difficult to eliminate.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Foundation Models for Zero-Shot Segmentation of Scientific Images without AI-Ready Data

Zero-shot and prompt-based models have excelled at visual reasoning tasks by leveraging large-scale natural image corpora, but they often fail on sparse and domain-specific scientific image data. We introduce Zenesis, a no-code interactive computer vision platform designed to reduce data readiness bottlenecks in scientific imaging workflows. Zenesis integrates lightweight multimodal adaptation for zero-shot inference on raw scientific data, human-in-the-loop refinement, and heuristic-based temporal enhancement. We validate our approach on Focused Ion Beam Scanning Electron Microscopy (FIB-SEM) datasets of catalyst-loaded membranes. Zenesis outperforms baselines, achieving an average accuracy of 0.947, Intersection over Union (IoU) of 0.858, and Dice score of 0.923 on amorphous catalyst samples; and 0.987 accuracy, 0.857 IoU, and 0.923 Dice on crystalline samples. These results represent a significant performance gain over conventional methods such as Otsu thresholding and standalone models like the Segment Anything Model (SAM). Zenesis enables effective image segmentation in domains where annotated datasets are limited, offering a scalable solution for scientific discovery.

Mukherjee, Shubhabrata↗
DOE OSTI2022

SAXS-guided unbiased coarse-grained Monte Carlo simulation for identification of self-assembly nanostructures and dimensions

Recent studies have shown that solvated amphiphiles can form nanostructured self-assemblies called dynamic binary complexes (DBCs) in the presence of ions. Since the nanostructures of DBCs are directly related to their viscoelastic properties, it is important to understand how the nanostructures change under different solution conditions. However, it is challenging to obtain a three-dimensional molecular description of these nanostructures by utilizing conventional experimental characterization techniques or thermodynamic models. To this end, we combined the structural data from small angle X-ray scattering (SAXS) experiments and thermodynamic knowledge from coarse-grained Monte Carlo (CGMC) simulations to identify the detailed three-dimensional nanostructure of DBCs. Specifically, unbiased CGMC simulations are performed with SAXS-guided initial conditions, which aids us to sample accurate nanostructures in a computationally efficient fashion. As a result, an elliptical bilayer nanostructure is obtained as the most probable nanostructure of DBCs whose dimensions are validated by scanning electron microscope (SEM) images. Then, utilizing the obtained molecular model of DBCs, here we could also explain the pH tunability of the system. Overall, our results from SAXS-guided unbiased CGMC simulations highlight that using potential energy combined with SAXS data, we can distinguish otherwise degenerate nanostructures resulting from the inherent ambiguity of SAXS patterns.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Correlative Surface Imaging Reveals Chemical Signatures for Bacterial Hotspots on Plant Roots

The rhizosphere is arguably the most complex microbial habitat on earth, comprising an integrated network of plant roots, soil and a highly diverse microbial community (the rhizosphere microbiome)1. Understanding, predicting and controlling plant-microbe interactions in the rhizosphere will allow us to harness the plant microbiome as a means to increase or restore plant ecosystem productivity, improve plant responses to a wide range of environmental perturbations, and mitigate effects of climate change by designing ecosystems for long-term soil carbon storage1. To this end, it is imperative to develop new molecular approaches with high spatial resolution to capture interactions at the plant-microbe, microbe-microbe, and plant-plant interfaces. In this work, we designed an imaging sample holder that allows integrated surface imaging tools to map the same locations of a plant root-microbe interface with submicron lateral resolutions, providing novel in vivo analysis of root-microbe interactions. Specifically, confocal fluorescence microscopy, time-of-flight secondary ion mass spectrometry (ToF-SIMS), X-ray photoelectron spectroscopy (XPS), and scanning electron microscope (SEM) were used for the first time for correlative imaging of the Brachypodium distachyon root and its interaction with Pseudomonas SW25, a typical plant growth-promoting soil bacterium. Imaging data suggest that the root surface is inhomogeneous and that the interaction between Pseudomonas and Brachypodium roots was confined to only few spots along the sampled root segments and that the bacterial attachment spots were enriched in Na- and S-related and high-mass organic species. We conclude that attachment of the Pseudomonas cells to the root surface is outcompeted by strong root-soil mineral interactions but facilitated by formation of extracellular polymeric substances (EPS).

Plant root, Plant growth-promoting bacteria, soil,↗
DOE OSTI2026

Predicting U 3 O 8 powder processing conditions: An AI/ML approach analyzing deep learning embeddings of SEM micrographs

High-resolution SEM images of uranium-oxide powders encode micro- and nanoscale clues to their synthesis route and calcination temperature. We trained a ResNet-50 model on 11 commercial-scale U₃O₈ classes, ammonium diuranate (ADU) or uranyl peroxide (H₂O₂) precursors calcined at temperatures ranging from 400 to 750 °C and added a 256-D projection head before the classifier to analyze the learned representation. The best of eight seeds reached 92.4 % accuracy on reserved testing data, but our focus is the structure of the embedding space rather than the accuracy and labels. We quantify class relatedness in the original 256-D space using centroid similarity and distributional distances, and we use Uniform Manifold Approximation Projection (UMAP) for visualization. ‘Unknown’ images from different preparation methods, SEM operators, and from the literature localized near the expected classes under a nearest-centroid analysis without retraining, as well as clustered in similar UMAP space. In conclusion, this embedding-centered workflow complements black-box classification by providing quantitative, similarity-based comparisons of U₃O₈ morphologies and reduces storage space by up to 98 % for image data used in millisecond vector search comparisons.

36 MATERIALS SCIENCE↗