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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New Polyoxometalate Flow Battery Explores Ultra-Reduced State

In joint work with the Symes group, the Cronin group have discovered that it is possible to reduce the {M18} Dawson cluster reversibly by up to 18 electrons. This ultra-reduced state is not only stable in water, but it is able to be used in a flow battery system demonstrating very high capacity and stability. This means the highly reduced cluster system might lead to new flexible energy systems both for stationary use and electric vehicles. The fact that the energy is carried in an aqueous liquid form might even mean that it would one day be possible to fill up electric cars, powered by such a battery, with the charged liquid.

The research was published in Nature Chemistry, and Prof Cronin has also written a “Behind the Paper” blog post about this work.

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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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