University of Liverpool
The design and discovery of porous materials have become a central theme in materials science, driven by their applications in gas storage, separation, carbon capture, and catalysis. Rapid advances in synthetic chemistry, particularly in metal–organic frameworks, porous organic cages, and conjugated microporous polymers, have enabled the generation of increasingly large and diverse material libraries. At the same time, the emergence of automation and data-driven workflows has created unprecedented opportunities for accelerating materials discovery. Despite these advances, the characterization of porosity remains a persistent bottleneck. Conventional gas adsorption methods, although highly reliable, are slow, labor-intensive, and require substantial sample quantities, making them poorly suited to high-throughput or automated environments. This imbalance between synthesis and characterization constrains the efficiency of discovery pipelines and limits the potential of self-driving laboratory concepts. In response to this challenge, this thesis develops two complementary high-throughput pre-screening methodologies for porosity assessment. Chapter 2 develops a multichannel colorimetric dye sorption array that uses dyes of varied size/polarity plus computer-vision analytics to classify porosity from simple images.
For details:
Accelerating Porosity Assessment in Solid Materials via SemiAutomated Platforms
By Yushu Han
Supervisor – Prof. Andrew I. Cooper
University of Liverpool
https://livrepository.liverpool.ac.uk/3195319/
