The Cronin Group

Research in the Cronin Group is motivated by the fascination for complex chemical systems, and the desire to construct complex functional molecular architectures that are not based on biologically derived building blocks.


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Assembly Theory Features in Scientific American

Assembly theory - a theory being developed by the Cronin group along with international collaborators - has been featured in the February 2023 edition of Scientific American. The article, “Life as We Don’t Know It”, explores how living systems on other worlds could work in very different ways from life on Earth. Assembly theory has been developed to distinguish living from non-living systems based on their complexity, and is agnostic to the specific molecules and structures involved, and so could be used to identify life in completely unfamiliar contexts.

The article can be viewed on the Scientific American website

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Prof. Leroy (Lee) Cronin

Prof Leroy (Lee) Cronin
Regius Chair of Chemistry
Advanced Research Centre (ARC)
Level 5, Digital Chemistry
University of Glasgow
11 Chapel Lane
Glasgow G11 6EW
Tel: +44 141 330 6650
Email: lee.cronin@glasgow.ac.uk

Latest Publications

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509. High-Nuclearity Polyoxometalate-Based Metal–Organic Frameworks for Photocatalytic Oxidative Cleavage of C−C Bond

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508. Operational considerations for approximating molecular assembly by Fourier transform mass spectrometry

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507. Reaction blueprints and logical control flow for parallelized chiral synthesis in the Chemputer

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506. Experimentally measured assemblyindices are required to determine the threshold for life

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505. Algorithm-driven robotic discovery of polyoxometalate-scaffolding metal–organic frameworks

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504. Reaction: Programmable chemputable click chemistry

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503. Rethinking pharma and biotech outsourcing: A call for data security and supply chain resilience

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502. Delocalized, asynchronous, closed-loop discovery of organic laser emitters

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501. Investigating and Quantifying Molecular Complexity Using Assembly Theory and Spectroscopy

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500. Electron density-based GPT for optimization and suggestion of host–guest binders


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