Dataset Information

Resolving Li-Ion Battery Electrode Particles Using Rapid Lab-Based X-Ray Nano-Computed Tomography for High-Throughput Quantification.

ABSTRACT: Vast quantities of powder leave production lines each day, often with strict control measures. For quality checks to provide the most value, they must be capable of screening individual particles in 3D and at high throughput. Conceptually, X-ray computed tomography (CT) is capable of this; however, achieving lab-based reconstructions of individual particles has, until now, relied upon scan-times on the order of tens of hours, or even days, and although synchrotron facilities are potentially capable of faster scanning times, availability is limited, making in-line product analysis impractical. This work describes a preparation method and high-throughput scanning procedure for the 3D characterization of powder samples in minutes using nano-CT by full-filed transmission X-ray microscopy with zone-plate focusing optics. This is demonstrated on various particle morphologies from two next-generation lithium-ion battery cathodes: LiNi_0.8Mn_0.1Co_0.1O₂ and LiNi_0.6Mn_0.2Co_0.2O₂; namely, NMC811 and NMC622. Internal voids are detected which limit energy density and promote degradation, potentially impacting commercial application such as the drivable range of an electric vehicle.

SUBMITTER: Heenan TMM

PROVIDER: S-EPMC7312274 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

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Publications

Resolving Li-Ion Battery Electrode Particles Using Rapid Lab-Based X-Ray Nano-Computed Tomography for High-Throughput Quantification.

Heenan Thomas M M TMM Llewellyn Alice V AV Leach Andrew S AS Kok Matthew D R MDR Tan Chun C Jervis Rhodri R Brett Dan J L DJL Shearing Paul R PR

Advanced science (Weinheim, Baden-Wurttemberg, Germany) 20200430 12

Vast quantities of powder leave production lines each day, often with strict control measures. For quality checks to provide the most value, they must be capable of screening individual particles in 3D and at high throughput. Conceptually, X-ray computed tomography (CT) is capable of this; however, achieving lab-based reconstructions of individual particles has, until now, relied upon scan-times on the order of tens of hours, or even days, and although synchrotron facilities are potentially capa ...[more]

PMID: 32596123

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Project description:BackgroundLeaf cellular architecture plays an important role in setting limits for carbon assimilation and, thus, photosynthetic performance. However, the low density, fine structure, and sensitivity to desiccation of plant tissue has presented challenges to its quantification. Classical methods of tissue fixation and embedding prior to 2D microscopy of sections is both laborious and susceptible to artefacts that can skew the values obtained. Here we report an image analysis pipeline that provides quantitative descriptors of plant leaf intercellular airspace using lab-based X-ray computed tomography (microCT). We demonstrate successful visualisation and quantification of differences in leaf intercellular airspace in 3D for a range of species (including both dicots and monocots) and provide a comparison with a standard 2D analysis of leaf sections.ResultsWe used the microCT image pipeline to obtain estimates of leaf porosity and mesophyll exposed surface area (Smes) for three dicot species (Arabidopsis, tomato and pea) and three monocot grasses (barley, oat and rice). The imaging pipeline consisted of (1) a masking operation to remove the background airspace surrounding the leaf, (2) segmentation by an automated threshold in ImageJ and then (3) quantification of the extracted pores using the ImageJ 'Analyze Particles' tool. Arabidopsis had the highest porosity and lowest Smes for the dicot species whereas barley had the highest porosity and the highest Smes for the grass species. Comparison of porosity and Smes estimates from 3D microCT analysis and 2D analysis of sections indicates that both methods provide a comparable estimate of porosity but the 2D method may underestimate Smes by almost 50%. A deeper study of porosity revealed similarities and differences in the asymmetric distribution of airspace between the species analysed.ConclusionsOur results demonstrate the utility of high resolution imaging of leaf intercellular airspace networks by lab-based microCT and provide quantitative data on descriptors of leaf cellular architecture. They indicate there is a range of porosity and Smes values in different species and that there is not a simple relationship between these parameters, suggesting the importance of cell size, shape and packing in the determination of cellular parameters proposed to influence leaf photosynthetic performance.

Dataset Information

Resolving Li-Ion Battery Electrode Particles Using Rapid Lab-Based X-Ray Nano-Computed Tomography for High-Throughput Quantification.

Publications

Resolving Li-Ion Battery Electrode Particles Using Rapid Lab-Based X-Ray Nano-Computed Tomography for High-Throughput Quantification.

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