AI, Big Data, Machine Learning and Metal-Organic Framework synthesis, analysis and design. A proof of concept study (MOF-CADS)
Research Project , 2019

The goal is to build a chemical analysis, design and synthesis (CADS) software that uses Artificial Intelligence. Machine Learning and “Big Data” methods to compile and analyse original experimental data as well as third-party databases, patents and grey literature to speed up and improve the synthesis and commercial applications of the large subclass of new materials known as Metal-Organic Frameworks, MOFs.
This proof of concept study aims at using time restricted data on selected small problems to see if such a system can arrive at the preliminary solutions suggested by the latest experiments. 

Participants

Lars Öhrström (contact)

Professor vid Chalmers, Chemistry and Chemical Engineering, Chemistry and Biochemistry

Francoise Mystere Amombo Noa

Doktor vid Chalmers, Chemistry and Chemical Engineering, Chemistry and Biochemistry

Rongzhen Chen

Forskningsingenjör vid Chalmers, Computer Science and Engineering (Chalmers), CSE Verksamhetsstöd

Victor Eberstein

vid Chalmers, Computer Science and Engineering (Chalmers), CSE Verksamhetsstöd, Data Science Research Engineers

Funding

Chalmers

Funding Chalmers participation during 2019

Related Areas of Advance and Infrastructure

Information and Communication Technology

Areas of Advance

Sustainable development

Driving Forces

Basic sciences

Roots

Innovation and entrepreneurship

Driving Forces

Materials Science

Areas of Advance

More information

Latest update

2019-10-02