Accelerated Catalyst Development Platform
Yee-Fun Lim1,* Armando Borgna,2 Kedar Hippalgaonkar,1,3 Martin van Meurs,2 Michael Sullivan,4 Jia Zhang4
1Institute of Materials Research and Engineering, A*STAR, Singapore
2Institute of Chemical Engineering Sciences, A*STAR, Singapore
3Nanyang Technological University, Singapore
4Institute of High Performance Computing, A*STAR, Singapore
EXTENDED ABSTRACT: Catalyst development is a time consuming and laborious process. The large number of input variables, including catalyst alloying materials and co-dopants, promoters, support materials and morphologies, processing conditions and reactions conditions mean that development typically takes place via a slow trial-and-error process involving many iterations. As a case in point, the Fischer-Tropsch process was developed almost a hundred years ago, but chemists and chemical engineers are still optimizing and improving on this process today.[1] The Accelerated Catalyst Development Platform is a collaborative research program, set up by the A*STAR research institutes ICES, IMRE and IHPC, with the aim of accelerating the development and optimization of catalysts. It is based on similar principles for accelerating materials discovery,[2] by leveraging on high throughput experimentation and simulations with machine learning optimization in the loop to guide the next set of experiments. In this talk, I will share our efforts to build automated high throughput systems for catalyst synthesis, using robotic tools that are capable of autonomous liquid and solid handling and also performing chemical reactions. Further, we are acquiring capabilities to characterize these catalyst in a high throughput fashion, such as by means of a 16-channel parallel reactor. I will also discuss some of our recent progress on the use of machine learning algorithms for experimental optimization.
REFERENCES
[1] B. Liu et al., ACS Catal. 9, 7073 (2019).
[2] J.-P. Correa-Baena et al., Joule 2, 1410 (2018)
Yee-Fun Lim (limyf@imre.a-star.edu.sg) is a Scientist at the Institute
of Materials Research and Engineering (IMRE). He received his Ph.D. in Applied
Physics from Cornell University in 2011. He is currently leading a work package in the Accelerated Catalyst Development Platform, a collaborative research program between the Singapore A*STAR institutes ICES, IMRE and IHPC that aims to apply high throughput experimentation and machine learning tools to accelerate catalyst discovery and optimization. He is also the Deputy Head of the Electronic Materials Department at IMRE. His research interests include machine learning optimization and renewable fuels production via heterogeneous catalysis