Webinar on Nov. 22 with the Royal Society of Chemistry: CO₂ storage, magic doors, and machine learning.
Live on November 22nd, 2023
GMT: 9:00 – 10:00
CET: 10:00 – 11:00
JST: 18:00 – 19:00
In collaboration with the Royal Society of Chemistry, Preferred Computational Chemistry will host a webinar titled “CO₂ storage, magic doors and machine learning“ on November 22nd.
This webinar will reveal how machine learning-based atomic scale simulations performed with Matlantis help rationalise experimental results, focusing on CO₂ storage.
Event title: CO₂ storage, magic doors, and machine learning
Event date: November 22nd, 2023 from 10 to 11 a.m. CET
※For those who will be attending from other time zones, kindly check the local time before registering
Venue: Virtual (GoToWebinar)
Participation fee: Free (preregistration required)
Organizer: Royal Society of Chemistry
- Discover how Cu-based coordination networks with isolated pores but no interconnecting channels selectively adsorb CO₂ under ambient conditions
- Learn how machine learning-based atomic scale simulations with Matlantis help rationalise experimental results
- Take your first step towards large-scale materials discovery, supported by state-of-the-art neural network potentials
Tokyo Institute of Technology
Professor in the Department of Chemistry, School of Science and Engineering, at the Tokyo Institute of Technology, since September 2015. He received his PhD in coordination chemistry from Waseda University in 1993. His research interests include coordination chemistry, supramolecular chemistry, in situ chemical crystallography, crystalline-state photochemistry, and ab initio powder X-ray crystallography.
Preferred Computational Chemistry, Inc.
Senior Manager at PFCC, he received his PhD in Chemistry from Cardiff University, UK in 2005 and his MBA from HEC Paris, France in 2013.