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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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10 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Patch-Based Convolutional Neural Networks for Multiple Microstructural Features Detection in FIB-SEM Micrographs of Irradiated Nuclear Fuel

Focused ion beam scanning electron microscopy (FIB-SEM) tomography has increasingly been utilized for acquiring three-dimensional (3D) microstructure features at the sub-micron scale in irradiated nuclear materials. This technique involves sequential ion beam slicing followed by electron beam imaging and compositional mapping using energy dispersive spectroscopy (EDS). Despite its growing use, several challenges persist. These include the time-intensive nature of data collection of EDS data, difficulties in distinguishing between various microstructures, and issues with image alignment. These challenges currently limit the broader application of FIB-SEM tomography in the field. To overcome these limitations, we propose using convolutional neural networks (CNNs) to automate microstructure identification in SEM images. Our study introduces a new framework for identifying microstructures in irradiated U-10Zr (wt. %) metallic fuel with limited annotated data. The framework includes the creation of a reliable annotated dataset with paired SEM and ground truth data from EDS maps, the applications of CNNs for microstructure identification, and the validation of model performance. Specifically, we employed the Segment Anything Model (SAM) to align SEM images with corresponding EDS maps and focused ion beam (FIB) tomography SEM data. We evaluate several models, including Patch-based U-Net, Attention U-Net, and Residual U-Net, finding that patch-based U-Net exhibits superior segmentation performance and consistency. This approach reduces reliance on EDS detectors and aids in accelerating nuclear material analysis process, highlighting the potential of advanced deep learning techniques to improve microstructural understanding in nuclear material. This is the first framework to integrate SAM and Patch-based CNN models for semantic segmentation of irradiated nuclear materials, with potential applicability to other tomography datasets.

36 - MATERIALS SCIENCE↗
DOE OSTI2024

Towards a quantitative understanding of bonding in supersonic single particle impacts: A three-dimensional FIB-SEM exploration

Particle bonding is crucial to coating quality in cold spray, but it has been a challenge to accurately quantify bonding even in single particle impacts. This paper uses FIB-SEM to explicitly map the particle-substrate interface for Cu-on-Cu single microparticle impacts in a full 3D rendering that spans a wide range of impact velocities. This approach permits a detailed quantification of the total bonding area and all of its associated components. In addition to revealing why prior 2D characterization efforts have missed important details about impact bonding, these data quantitatively reveal the evolution of bonding from its onset at the “critical velocity” V cr (where bonding is generally poor, ∼6 %) to its peak at around 1.3‧V cr (where almost 90 % of the particle bonds). Further increase in the velocity to 1.5‧V cr and beyond finds the onset of hydrodynamic penetration and a decrease in bonding. These data then support the development of a simple analytical model based on oxide rarefication and extrusion of bare metal through gaps in the oxide layer as driving the development of bonding. As a result, the model reproduces the experiments and provides guidance on optimization of bonding as a function of material and process parameters.

Analytical methods↗
DOE OSTI2025

Site-specific plan-view (S)TEM sample preparation from thin films using a dual-beam FIB-SEM

To fully evaluate the atomic structure, and associated properties of materials using transmission electron microscopy, examination of samples from three non-collinear orientations is needed. This is particularly challenging for thin films and nanoscale devices built on substrates due to limitations with plan-view sample preparation. In this work, a new method for preparation of high-quality, site-specific, plan-view TEM samples from thin-films grown on substrates, is presented and discussed. Here, it is based on using a dual-beam focused ion beam scanning electron microscope (FIB-SEM) system. To demonstrate the method, the samples were prepared from thin films of perovskite oxide BaSnO 3 grown on a SrTiO 3 substrate and metal oxide IrO 2 on a TiO 2 substrate, ranging from 20–80 nm in thicknesses using molecular beam epitaxy. While the method is optimized for the thin films, it can be extended to other site-specific plan-view samples and devices build on wafers. Aberration-corrected STEM was used to evaluate the quality of the samples and their applicability for atomic-resolution imaging and analysis.

BaSnO3↗
DOE OSTI2026

Comprehensive structural characterization of charged polymers involved in moisture-driven direct air capture

This study provides a comprehensive structural characterization of commercially available alkaline anion-exchange polymers (Fumasep FAA-3 and IRA 900) used in moisture-driven direct air capture (DAC) of carbon dioxide. Using X-ray diffraction, SAXS/WAXS, atomic force microscopy, FIB-SEM, and transmission electron microscopy, the authors identify nanoscale clustering, porosity, swelling behavior, and humidity-dependent structural changes that influence CO₂ adsorption and release. These findings establish structure–function relationships critical for designing more durable and energy-efficient DAC polymer materials.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Pore-Scale Transport Effects in Electrochemical CO 2 Reduction on Gold via Coupled Microkinetic-Transport Modeling

A pore-resolved modeling framework is developed to quantify how pore-scale transport affects the intrinsic microkinetics of CO 2 -to-CO on Au. A DFT-informed microkinetic model is coupled self-consistently to a Generalized-Modified Poisson–Nernst–Planck (GMPNP) transport description in a single, electrolyte-filled cylindrical pore, allowing local concentrations and potential to feed back into site-specific reaction rates. FIB-SEM is used to determine pore sizes within realistic electrode materials. Across pore diameters, d p = 10–6000 nm, the surface-averaged CO 2 reduction rate is systematically reduced relative to the ideal microkinetic baseline where mass transport is not accounted for; the effectiveness factor 𝜂 𝑠,CO 2 , which quantifies this ratio, decreases rapidly at more negative potentials and is about 1% near −1.0 V vs SHE due to reactant depletion. Spatial maps reveal pore-bulk alkalization that emerges at higher cathodic bias, with a small, near-wall pH dip due to electrostatic repulsion of hydroxide at the cathode interface. For a fixed aspect ratio L p /d p , narrower pores exhibit larger 𝜂 𝑠,CO 2 by shortening diffusion paths, whereas variations in the aspect ratio L p /d p play a secondary role. A dimensionless analysis (surface/bulk Damköhler numbers) delineates operating regimes. In conclusion, this work offers a concept for incorporating microkinetic models into homogenized porous-electrode models through effectiveness factors and pore-size distribution.

Au-catalyst↗
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 OSTI2025

Development of mesopores in superfine grain graphite neutron-irradiated at high fluence

Microstructural changes induced by neutron irradiation of superfine grain graphite G347A (Tokai Carbon, Japan) were examined by nitrogen adsorption at 77K and by three microscopy techniques (SEM, TEM and FIB-SEM tomography). The specimens were irradiated at doses of up to 30 dpa, covering stages before and after the turnaround fluence at three temperatures (300, 450, 750 °C) of their irradiation envelope. The initial graphite densification at low fluences did not produce any detectable effect in the pore size range (<350 nm) measured by gas adsorption. However, graphite irradiated at high fluences, after turnaround, showed severe structural changes. At all three temperatures and high irradiation fluences, gas adsorption revealed significant increase of the volume of narrow mesopores (<5–20nm) and up to five times increase of BET surface area, both in linear relationship with the relative volume expansion. Analysis of microscopy images showed multiplication of fine macropores (>50 nm) at high irradiation fluences and more structural changes on multiple scales, from nanometers to microns. This work demonstrates the unique ability of gas adsorption techniques to analyze open pores with sizes between sub-nanometer and sub-micron in bulk nuclear graphite, with supporting microscopy results.

I. Contescu, Cristian↗
DOE OSTI2025

Assessment of metadynamic recrystallization in single copper particle impacts by focused ion beam tomography

We study single Cu-on-Cu impacts relevant to cold spray deposition and quantitatively analyze the metadynamic recrystallization (mDRX) that takes place after the impact by virtue of lingering impact adiabatic heat. Unlike prior studies, the current full 3D tomographic analysis of the mDRX volume shows that mDRX is extremely common in such impacts, although it is often missed when examining 2D sections. We also report an unexpected trend: there is a “sour spot” for mDRX at velocities about 20–40 % above the velocity for particle adhesion. This non-monotonic trend is contrary to the expectations based on increasing adiabatic heating with velocity. With a schematic model, we show that the trend can be explained on the basis of heat transfer: cooling of the heat-affected region is limited by transport through the bonded regions at the particle-substrate interface. Thus, bonding has a prominent role in the heat dissipation process and the best bonded particles most rapidly bulk quench, avoiding mDRX. Here, the developed semi-empirical model aligns with the experimental findings and may help inform microstructural evolution during cold spray and post-spray processing.

FIB-SEM tomography↗
DOE OSTI2025

Tomographic assessment of peening for metallurgical bonding in cold spray

It is widely asserted that peening densifies cold spray coatings and improves particle–particle and particle–substrate bonding, yet systematic studies analyzing the evolution of bonding due to peening particle strikes are scarce. We explore peening at the level of individual particle impacts, by creating two-particle Cu-on-Cu stacks using laser-induced particle impact testing. Exploring impact velocities that range from the onset of bonding at the “critical velocity”, V cr , to its peak near 1.4⋅V cr , we perform full 3D tomography of the particle stacks to characterize the bonding state at the particle-substrate interface. Direct labeling of non-bonded patches and the total particle-substrate interface permits quantification and comparison of bonding in single impacts with bonding after subsequent impacts to reveal the origins of the peening effect. The data reveal a surprising finding: although a second impact directly atop the first particle increases the area of the particle-substrate interface (~40% area increase), there is no improvement in metallurgical bonding. Analysis of these data suggest that not only area expansion (and associated oxide rarefication), but also stress-induced extrusion of metal at that interface needs to occur to achieve metal-on-metal contact to see an enhancement in bonding. Furthermore, our analysis suggests that the subsequent impacting particle needs to have ~70% more kinetic energy to produce additional bonding; this implies that particle and velocity distributions within a spray may be helpful, and that peening may rely on unaligned impacts.

Bonding↗
DOE OSTI2024

Electro-Chemo-Mechanical Evolution at the Garnet Solid Electrolyte–Cathode Interface

Solid-state batteries promise higher energy density and improved safety compared with lithium-ion batteries. However, electro-chemomechanical instabilities at the solid electrolyte interface with the cathode and the anode hinder their large scale implementation. Here, in this study, we focus on resolving electro-chemo-mechanical instability mechanisms and their onset conditions between a state-of-the-art cathode, LiNi 0.6 Mn 0.2 Co 0.2 O 2 (NMC622), and the garnet Li 7 La 3 Zr 2 O 12 (LLZO) solid electrolyte. We used thin-film NMC622 on LLZO pellets to place the interfacial region within the detection depth of the X-ray characterization techniques. The experimental probes of the near-interface region included in operando X-ray absorption spectroscopy and ex situ focused ion beam scanning electron microscopy. Electrochemical degradation was not observable during cycling at room temperature with 4.3 V versus Li/Li + charge voltage cutoff, or with stepwise potentiostatic hold up to 4.1 V versus Li/Li + . In contrast, secondary phases including reduced transition metal species (Ni 2+ , Co 2+ ) were found after cycling up to 4.3 V versus Li/Li + at 80 °C and during potentiostatic hold at 4.3 V versus Li/Li + (Ni 2+ ). Intergranular cracks between NMC622 grains and delamination at the NMC622|LLZO interface occurred readily after the first charge. These interface reaction products and mechanical failure lowered the capacity and cell efficiency due to partial loss of the NMC622 phase, partial loss of contact at the interface, and a higher polarization resistance. Electrochemical instability between delithiated NMC622 and LLZO could be mitigated by using a low charge voltage cutoff or cycling at lower temperature. Ways to engineer the mechanical properties to avoid crack deflection and delamination at the interface are also discussed for enhancing mechanical stability.

36 MATERIALS SCIENCE↗