Did you know that the Flowrence high-throughput reactor platform is not only a favorite for catalyst discovery, but also for adding Machine Learning and AI to catalyst performance design?
Avantium’s Flowrence® technology is the ultimate system for AI/Machine Learning implementation, utilizing patented microfluidic technology to split one flow into equal flows. This minimizes calibrated electronic components, resulting in more reliable and repeatable results, making it a perfect match for AI/Machine Learning integration.
So far, four separate research consortiums across the globe pioneered the implementation of Machine Learning and Artificial Intelligence algorithms for catalyst discovery in scientific publications featuring Flowrence high throughput technology:
ETH Zürich / Swiss Cat+
Accelerated exploration of heterogeneous CO2 hydrogenation catalysts by Bayesian-optimized high-throughput and automated experimentation
Chem Catalysis, Volume 4, Issue 2, 100888
Read here
Argonne National Laboratory
High-Throughput Experimentation, Theoretical Modeling, and Human Intuition: Lessons Learned in Metal–Organic-Framework-Supported Catalyst Design
ACS Cent. Sci. 2023, 9, 2, 266–276
Read here
University of Lille 1 Sciences and Technology / REALCAT
Platform Process-constrained batch Bayesian approaches for yield optimization in multi-reactor systems
Computers & Chemical Engineering 189:108779
Read here
JAIST
High-throughput screening and literature data-driven machine learning-assisted investigation of multi-component La2O3-based catalysts for the oxidative coupling of methane
Catal. Sci. Technol., 2022,12, 2766-2774
Read here
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