scholarly journals Resolving Li‐Ion Battery Electrode Particles Using Rapid Lab‐Based X‐Ray Nano‐Computed Tomography for High‐Throughput Quantification

2020 ◽  
Vol 7 (12) ◽  
pp. 2000362 ◽  
Author(s):  
Thomas M. M. Heenan ◽  
Alice V. Llewellyn ◽  
Andrew S. Leach ◽  
Matthew D. R. Kok ◽  
Chun Tan ◽  
...  
Keyword(s):  
Computed Tomography ◽  
High Throughput ◽  
Li Ion Battery ◽  
X Ray ◽  
Battery Electrode ◽  
Li Ion

scholarly journals Short-Range Ordering in Battery Electrode, the ‘Cation-Disordered’ Rocksalt Li1.25Nb0.25Mn0.5O2

2019 ◽  
Author(s):  
Michael Jones ◽  
Philip J. Reeves ◽  
Ieuan D. Seymour ◽  
Matthew J. Cliffe ◽  
Siân E. Dutton ◽  
...  
Keyword(s):  
Local Structure ◽  
Solid State Nmr ◽  
Cation Ordering ◽  
Li Ion Battery ◽  
X Ray Diffraction ◽  
X Ray ◽  
Short Range Ordering ◽  
Battery Electrode ◽  
Li Ion ◽  
Battery Material

We show the occurrence of local cation ordering in Li-ion battery material Li<sub>1.25</sub>Nb<sub>0.25</sub>Mn<sub>0.5</sub>O<sub>2</sub>, previously thought to be disordered. We deduce this ordering from X-ray diffraction, and test it against neutron diffraction & PDF, magnetic susceptibility and solid state NMR evidence. We identify the nature of the ordering as having a local structure related to that of gamma-LiFeO<sub>2</sub>, determine the correlation length of such ordering, and demonstrate its significant consequences for the material's electrochemistry.

scholarly journals Short-Range Ordering in Battery Electrode, the ‘Cation-Disordered’ Rocksalt Li1.25Nb0.25Mn0.5O2

2019 ◽  
Author(s):  
Michael Jones ◽  
Philip J. Reeves ◽  
Ieuan D. Seymour ◽  
Matthew J. Cliffe ◽  
Siân E. Dutton ◽  
...  
Keyword(s):  
Local Structure ◽  
Solid State Nmr ◽  
Cation Ordering ◽  
Li Ion Battery ◽  
X Ray Diffraction ◽  
X Ray ◽  
Short Range Ordering ◽  
Battery Electrode ◽  
Li Ion ◽  
Battery Material

We show the occurrence of local cation ordering in Li-ion battery material Li<sub>1.25</sub>Nb<sub>0.25</sub>Mn<sub>0.5</sub>O<sub>2</sub>, previously thought to be disordered. We deduce this ordering from X-ray diffraction, and test it against neutron diffraction & PDF, magnetic susceptibility and solid state NMR evidence. We identify the nature of the ordering as having a local structure related to that of gamma-LiFeO<sub>2</sub>, determine the correlation length of such ordering, and demonstrate its significant consequences for the material's electrochemistry.

scholarly journals In-line monitoring of Li-ion battery electrode porosity and areal loading using active thermal scanning - modeling and initial experiment

2018 ◽  
Vol 375 ◽  
pp. 138-148 ◽  
Author(s):  
Przemyslaw Rupnowski ◽  
Michael Ulsh ◽  
Bhushan Sopori ◽  
Brian G. Green ◽  
David L. Wood ◽  
...  
Keyword(s):  
Li Ion Battery ◽  
Initial Experiment ◽  
Battery Electrode ◽  
Li Ion

scholarly journals High throughput phenotyping of morpho-anatomical stem properties using X-ray computed tomography in sorghum

Plant Methods ◽  
2018 ◽  
Vol 14 (1) ◽  
Author(s):  
Francisco E. Gomez ◽  
Geraldo Carvalho ◽  
Fuhao Shi ◽  
Anastasia H. Muliana ◽  
William L. Rooney
Keyword(s):  
Computed Tomography ◽  
High Throughput ◽  
X Ray ◽  
High Throughput Phenotyping ◽  
X Ray Computed

scholarly journals ROOT PHENOTYPING FROM X-RAY COMPUTED TOMOGRAPHY: SKELETON EXTRACTION

2021 ◽  
Vol XLIII-B4-2021 ◽  
pp. 417-422
Author(s):  
M. Herrero-Huerta ◽  
V. Meline ◽  
A. S. Iyer-Pascuzzi ◽  
A. M. Souza ◽  
M. R. Tuinstra ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Root System ◽  
High Throughput ◽  
Skeletal Structure ◽  
Plant Phenotyping ◽  
Skeleton Extraction ◽  
X Ray ◽  
Digital Twin ◽  
Three Samples ◽  
Root Phenotyping

Abstract. Breakthrough imaging technologies are a potential solution to the plant phenotyping bottleneck in marker-assisted breeding and genetic mapping. X-Ray CT (computed tomography) technology is able to acquire the digital twin of root system architecture (RSA), however, advances in computational methods to digitally model spatial disposition of root system networks are urgently required.We extracted the root skeleton of the digital twin based on 3D data from X-ray CT, which is optimized for high-throughput and robust results. Significant root architectural traits such as number, length, growth angle, elongation rate and branching map can be easily extracted from the skeleton. The curve-skeleton extraction is computed based on a constrained Laplacian smoothing algorithm. This skeletal structure drives the registration procedure in temporal series. The experiment was carried out at the Ag Alumni Seed Phenotyping Facility (AAPF) at Purdue University in West Lafayette (IN, USA). Three samples of tomato root at 2 different times and three samples of corn root at 3 different times were scanned. The skeleton is able to accurately match the shape of the RSA based on a visual inspection.The results based on a visual inspection confirm the feasibility of the proposed methodology, providing scalability to a comprehensive analysis to high throughput root phenotyping.

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