Jean C. Bilheux

Advanced battery characterization using in situ/operando neutron imaging is essential for uncovering degradation modes in lithium-ion batteries (LIBs). However, current LIB designs hinder operando neutron radiography (NR) and in situ micro-computed tomography (N-µCT) for visualizing Li plating near the graphite-separator interface due to strong neutron attenuation by hydrogen-rich components such as trilayer polypropylene–polyethylene–polypropylene (PP-PE-PP) battery separators, electrolyte, and Fe-containing spacers. Here, we present the design, electrochemical testing, and neutron imaging of a neutron-friendly LIB (NFB) optimized for in situ Li detection during extreme fast charging (XFC). Guided by total neutron attenuation cross-sections, path lengths, and material transmission, the NFB enables clear visualization at the graphite–separator interface, where standard LIBs are opaque. Electrochemical testing reveals that both standard and NFB cells exhibit similar voltage and current responses during formation and XFC for up to 50 cycles. However, the NFB shows lower reversibility and specific capacity, likely due to degradation of the Cu-coated Al spacer on the graphite side caused by corrosion or delamination during cycling. Despite these limitations, the NFB achieves stable coulombic efficiency and small cell-to-cell variability. To mitigate spacer degradation, we recommend titanium as a replacement material, owing to its significantly lower solubility in Li, although custom fabrication may be required. Neutron radiography confirms significantly improved transmission at the graphite–separator interface unlike the fully opaque images from standard LIBs. Additionally, our custom cell design enabled simultaneous neutron tomography of multiple coin cells, allowing in situ 3D detection of dead Li following XFC, characterized by spatially heterogeneous accumulation near the graphite edges. Disconnected clusters form, with nodules of varying density concentrated at electrode edges—indicating non-uniform plating behavior likely driven by localized current density hotspots.

Over the past decade, Oak Ridge National Laboratory developed neutron capabilities at both the High Flux Isotope Reactor and the Spallation Neutron Source. A broad scientific portfolio has flourished at both facilities such that a new facility named VENUS is currently under construction at the Spallation Neutron Source. With a large range of applications, comes a broad range of user expertise regarding data processing, analysis, and visualization. Our team has developed and implemented a suite of tools to respond to all user needs. These tools span from data reduction, normalization, general tools such as organization of data folders, pre-processing of data, etc., to strain mapping, neutron grating interferometry, and advanced reconstruction algorithms for computed tomography. This manuscript provides an overview of some of the aforementioned tools.

The pyRS (Python residual stress) analysis software was designed to address the data reduction and analysis needs of the High Intensity Diffractometer for Residual Stress Analysis (HIDRA) user community. pyRS implements frameworks for the calibration and reduction of measured 2D data into intensity versus scattering vector magnitude and subsequent single-peak-fitting analysis to facilitate texture and residual strain/stress analysis. pyRS components are accessible as standalone user interfaces for peak-fitting and stress/strain analysis or as Python scripts. The scripting interface facilitates automated data reduction and peak-fitting analysis using an autoreduction protocol. Details of the implemented functionality are discussed.

Neutron radiography and computed tomography encompass a vibrant range of scientific applications, requiring advanced technique development and cutting-edge data processing and analysis software. We have developed an extensive portfolio of Python-based Jupyter notebooks that are custom-made for a specific experiment and sample geometry. These notebooks do not require any programming skills, although the code is accessible to programming experts if they wish to modify it. The notebooks are available on our analysis servers where the imaging data is also stored, preventing unnecessary and lengthy data transfer. This manuscript gives an overview of our efforts to empower the research community, that uses both the Spallation Neutron Source and High Flux Isotope Reactor imaging capabilities, to process and analyze their data in collaboration with our imaging team.

Over the past decade, wavelength-dependent neutron radiography, also known as Bragg-edge imaging, has been employed as a non-destructive bulk characterization method due to its sensitivity to coherent elastic neutron scattering that is associated with crystalline structures. Several analysis approaches have been developed to quantitatively determine crystalline orientation, lattice strain, and phase distribution. In this study, we report a systematic investigation of the crystal structures of metallic materials (such as selected textureless powder samples and additively manufactured (AM) Inconel 718 samples), using Bragg-edge imaging at the Oak Ridge National Laboratory (ORNL) Spallation Neutron Source (SNS). Firstly, we have implemented a phenomenological Gaussian-based fitting in a Python-based computer called iBeatles. Secondly, we have developed a model-based approach to analyze Bragg-edge transmission spectra, which allows quantitative determination of the crystallographic attributes. Moreover, neutron diffraction measurements were carried out to validate the Bragg-edge analytical methods. These results demonstrate that the microstructural complexity (in this case, texture) plays a key role in determining the crystallographic parameters (lattice constant or interplanar spacing), which implies that the Bragg-edge image analysis methods must be carefully selected based on the material structures.