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Monte Carlo and Molecular Dynamics Studies of the Effects of Additives in Electrodeposition
Yutaka Kaneko,Shuichi Nishimura,Yasuaki Hiwatari,Katsuhiko Ohara,Fujio Asa 한국물리학회 2009 THE JOURNAL OF THE KOREAN PHYSICAL SOCIETY Vol.54 No.3
The microscopic effects of additives on the surface structure in electrodeposition have been studied by using the combined method of molecular dynamics and Monte Carlo simulations, which was recently proposed by our group as a new tool for the molecular simulation of electrodeposition. The basic system is a simple model of the solution-electrode interface and additives with inhibiting effects are included in the solution. The additives are assumed to have a spherical shape with an action range of preventing metal deposition on an electrode surface. The simulations are performed using the solutions with and without additives to compare the surface structures. The roughness of the surface is shown to be reduced in the presence of the additives. The relation between the physical properties of the additives and the leveling efficiency is discussed from a dynamical point of view.
Single-cell sequencing techniques from individual to multiomics analyses
Yukie Kashima,Yoshitaka Sakamoto,Keiya Kaneko,Masahide Seki,Yutaka Suzuki,Ayako Suzuki 생화학분자생물학회 2020 Experimental and molecular medicine Vol.52 No.-
Here, we review single-cell sequencing techniques for individual and multiomics profiling in single cells. We mainly describe single-cell genomic, epigenomic, and transcriptomic methods, and examples of their applications. For the integration of multilayered data sets, such as the transcriptome data derived from single-cell RNA sequencing and chromatin accessibility data derived from single-cell ATAC-seq, there are several computational integration methods. We also describe single-cell experimental methods for the simultaneous measurement of two or more omics layers. We can achieve a detailed understanding of the basic molecular profiles and those associated with disease in each cell by utilizing a large number of single-cell sequencing techniques and the accumulated data sets.