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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Cronin Group take robotic steps towards “Artificial Chemical Evolution”

In a breakthrough published in Nature Communications, Prof Cronin and his group have described the robotically-facilitated evolution of oil droplets. The group used a custom built robot based on a RepRap 3D printer which generates the droplets, measures their fitness against a fitness function, and then uses a genetic algorithm to generate a new population. By demonstrating that these could be viable “chemical protocell models” as they can be evolved yet are based upon simple chemical ingredients, Prof Cronin hopes that we can start to answer some important questions about the origin of life.

Open Access paper in Nature Communicatsions

News item on University of Glasgow website

Article in Wired

Article at Phys.org

Article in Nature Chemistry News and Views

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Prof. Leroy (Lee) Cronin

Prof Leroy (Lee) Cronin
Regius Chair of Chemistry
Cronin Laboratory
School of Chemistry
Joseph Black Building
University of Glasgow
Glasgow G12 8QQ
Tel: +44 141 330 6650
Email: lee.cronin@glasgow.ac.uk

Latest Publications

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442. A robotic prebiotic chemist probes long term reactions of complexifying mixtures

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441. Identifying molecules as biosignatures with assembly theory and mass spectrometry

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440. A molecular computing approach to solving optimization problems via programmable microdroplet arrays

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439. Influence of the Contact Geometry and Counterions on the Current Flow and Charge Transfer in Polyoxometalate Molecular Junctions: A Density Functional Theory Study

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438. Elucidating the Paramagnetic Interactions of an Inorganic-Organic Hybrid Radical-Functionalized Mn-Anderson Cluster

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437. Automatic Generation of 3D-Printed Reactionware for Chemical Synthesis Digitization using ChemSCAD

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436. Optimization of Formulations Using Robotic Experiments Driven by Machine Learning DoE

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435. Digitizing Chemistry Using the Chemical Processing Unit: From Synthesis to Discovery

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434. Convergence of multiple synthetic paradigms in a universally programmable chemical synthesis machine

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433. Peptide sequence mediated self-assembly of molybdenum blue nanowheel superstructures


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