学术讲座
报告题目：Modeling of cyclic voltammetry
报告时间：2023-11-01 09:30
报告人： Associ.Prof.Alexander Oleinick
French National Centre for Scientific Research (CNRS)
报告地点：翔安校区能源材料大楼3号楼会议室5
转播地点：化学楼234会议室
报告摘要：
In this presentation we will provide a gentle introduction for modeling of cyclic voltammetry and related techniques. Modelling of mass transport and kinetics in electrochemical systems is a peculiar problem since one have to consider simultaneously, with adequate accuracy, multiple length and time scales. More precisely, concentration field(s) near the electrode surface, kinetic layers along with their evolution and overall development of the diffusion layer far from the electrode etc. are all interconnected and should be properly handled for precise evaluation of the electrochemical current. In this respect, we will consider approaches to treat these problems, emphasize some pitfalls and provide illustrative examples.
报告人简介：
Dr. Alexander Oleinick got his PhD in group of Prof. Irina Svir in 2005 in Kharkiv National University of Radioelectronics (Kharkiv, Ukraine) in mathematical modeling of electrochemical systems. He enriched his experience to improve his physicochemical expertise by a two years post-doc in Ecole Normale Superieure (Paris, France) followed by a one-year post-doc in Kharkiv, both under the supervision of Profs. Christian Amatore and Irina Svir. In 2010 he entered French National Centre for Scientific Research (CNRS) as a permanent researcher as CNRS Assistant Professor and was promoted to Associate Professor in 2014.
His current research activity is focused on modelling of complex electrochemical systems either for pure electroanalytical applications (regular or random arrays, ECL, bipolar electrochemistry, etc.) or for rationalizing the mechanisms of important biological processes related to oxidative stress and neurotransmission and extracting biochemical information from electrochemical detections at the level of single cells or their assemblies. Alexander is a co-author of 89 scientific publications with h-index of 23 (Web of Knowledge/Scopus).
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