Prof Demortière has had a distinguished career, with a PhD from the Sorbonne University in Paris and five years of postdoctoral research at Argonne National Laboratory in Chicago. Since 2015, he has been conducting research at the CNRS in France, focusing on understanding the dynamics of Li-ion battery materials. His work primarily involves multi-scale and multimodal techniques, including in situ/operando methods like TEM (transmission electron microscopy) and X-ray techniques. In addition to his research, Prof Demortière has been leading efforts to incorporate machine learning and deep learning into analysing experimental data, especially in image processing and computer vision. He also co-founded the startup PreDeeption, which focuses on predicting battery life, and he was awarded the CNRS Innovation RISE prize for this achievement.
期刊介绍
rsc.li/digitaldiscovery
Digital Discovery
2-年影响因子*
6.2分
5-年影响因子*
6.2分
JCR 分区*
Q1 计算机科学 - 跨学科应用 Q1化学-跨学科
CiteScore 分†
2.8分(
中位一审周期‡
55天
Digital Discovery 以数字化技术和自动化工具与基础科学的相互结合为重点，将囊括人工智能、实验自动化、机器人技术、数据库和先进 数据分析等领域的创新成果。本刊发表的研究工作范围广阔，但需有坚实的化学基础，具体包括：
