Rebekka Klemmt, Amelia C. Y. Liu, Cheng Hu, Mark J. Biggs, Timothy C. Petersen, Espen D. Bøjesen
{"title":"Effect of thickness and noise on angular correlation analysis from scanning electron nanobeam diffraction of disordered carbon","authors":"Rebekka Klemmt, Amelia C. Y. Liu, Cheng Hu, Mark J. Biggs, Timothy C. Petersen, Espen D. Bøjesen","doi":"10.1107/S1600576724010586","DOIUrl":"https://doi.org/10.1107/S1600576724010586","url":null,"abstract":"<p>Disordered carbons are of significant scientific and industrial interest for modern applications. To understand the differences in the performance of disordered carbons, it is crucial to elucidate their structure, but this is challenging due to the variation and complexity of structures they can possess: for example, different hybridizations of the carbon atoms, and significant extended-range order composed of connected rings, curved sheets and stacks. This study establishes the useful information that can be obtained from angular correlation analysis of scanning electron nanobeam diffraction patterns for disordered carbons and other materials with extended-range order. The effects of sample thickness and experimental noise are investigated, showing that it is crucial to consider their impact when interpreting the results. Furthermore, opportunities for analyzing different ranges of scattering angles are explored, for example, to access structural information about the intralayer structure of disordered carbons. These approaches could be used to access novel quantitative measures to probe the structural differences of disordered carbons and understand their properties.</p>","PeriodicalId":48737,"journal":{"name":"Journal of Applied Crystallography","volume":"58 1","pages":"31-41"},"PeriodicalIF":5.2,"publicationDate":"2024-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143252862","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jeongdong Kim, Seongbin Ga, Sungho Suh, Joseph Sang-Il Kwon, Kiho Park, Junghwan Kim
{"title":"Optimal operation guidelines for direct recovery of high-purity precursor from spent lithium-ion batteries: hybrid operation model of population balance equation and data-driven classifier","authors":"Jeongdong Kim, Seongbin Ga, Sungho Suh, Joseph Sang-Il Kwon, Kiho Park, Junghwan Kim","doi":"10.1107/S1600576724010239","DOIUrl":"https://doi.org/10.1107/S1600576724010239","url":null,"abstract":"<p>The direct resynthesis of precursor from spent lithium-ion batteries (LIBs) via co-precipitation is a crucial step in closed-loop cathode recycling systems. However, design and operation strategies for producing high-purity precursors have not been comprehensively explored or optimized. Herein, we propose the optimization of co-precipitation during the recovery of spent LIBs to achieve impurity-free precursor resynthesis. By incorporating the thermodynamic equilibrium model of the leaching solution of spent LIBs into a population balance equation (PBE) model, we identified the operating ranges that prevented the formation of impurities. Bayesian optimization was employed within the screened operating ranges to determine the optimal operating conditions for minimizing both operation time and maximum particle size. This optimization was performed for both unseeded batch and semi-batch systems. The results demonstrate that the selection of an optimal semi-batch operation can reduce the operation time by 23.33% and increase the particle size by 54.75%, owing to the high nucleation and particle growth rate during the initial time step. By employing an optimization approach based on the PBE model, this study provides detailed operational guidelines for batch and semi-batch co-precipitation, enabling the production of high-purity precursor materials from spent LIBs, while minimizing both operating time and maximum particle size.</p>","PeriodicalId":48737,"journal":{"name":"Journal of Applied Crystallography","volume":"57 6","pages":"1924-1939"},"PeriodicalIF":5.2,"publicationDate":"2024-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142764429","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
P. S. Savchenkov, K. V. Nikolaev, V. I. Bodnarchuk, A. N. Pirogov, A. V. Belushkin, S. N. Yakunin
{"title":"Multimodal reconstruction of TbCo thin-film structure with Bayesian analysis of polarized neutron reflectivity","authors":"P. S. Savchenkov, K. V. Nikolaev, V. I. Bodnarchuk, A. N. Pirogov, A. V. Belushkin, S. N. Yakunin","doi":"10.1107/S1600576724010367","DOIUrl":"https://doi.org/10.1107/S1600576724010367","url":null,"abstract":"<p>Bayesian analysis has been applied to polarized neutron reflectivity data. Reflectivity data from a magnetic TbCo thin-film structure were studied using a combination of a Monte Carlo Markov-chain algorithm, likelihood estimation and error modeling. By utilizing Bayesian analysis, it was possible to investigate the uniqueness of the solution beyond reconstructing the magnetic and structure parameters. The expedience of this approach has been demonstrated, as several probable reconstructions were found (the multimodality case) concerning the isotopic composition of the surface cover layer. Such multimodal reconstruction emphasizes the importance of rigorous data analysis instead of the direct data fitting approach, especially in the case of poor statistically conditioned data typical for neutron reflectivity experiments. This article presents details of the analysis and a discussion of multimodality.</p>","PeriodicalId":48737,"journal":{"name":"Journal of Applied Crystallography","volume":"57 6","pages":"1940-1950"},"PeriodicalIF":5.2,"publicationDate":"2024-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142764430","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"PyFaults: a Python tool for stacking fault screening","authors":"Sinclair R. Combs, Annalise E. Maughan","doi":"10.1107/S1600576724009956","DOIUrl":"https://doi.org/10.1107/S1600576724009956","url":null,"abstract":"<p><i>PyFaults</i> is an open-source Python library designed to model stacking fault disorder in crystalline materials and qualitatively assess the characteristic selective broadening effects in powder X-ray diffraction (PXRD). Here, the main capabilities of <i>PyFaults</i> are presented, including unit cell and supercell model construction, PXRD pattern calculation, assessment against experimental PXRD, and methods for rapid screening of candidate models within a set of possible stacking vectors and fault occurrence probabilities. This program aims to serve as a computationally inexpensive tool for identifying and screening potential stacking fault models in materials with planar disorder. Three diverse case studies, involving GaN, Li<sub>2</sub>MnO<sub>3</sub> and Li<sub>3</sub>YCl<sub>6</sub>, are presented to illustrate the program functionality across a range of structure types and stacking fault modalities.</p>","PeriodicalId":48737,"journal":{"name":"Journal of Applied Crystallography","volume":"57 6","pages":"1996-2009"},"PeriodicalIF":5.2,"publicationDate":"2024-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142764459","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}