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Artificial Organic Chemistry Lab

Molecular catalysts and chemical reactions designed by artificial intelligence with the help of simulations, realized and tested utilizing automated lab protocols.

Our Team

The Pollice Research Group is committed to create an inclusive research environment where members feel safe and respected. We believe that diversity is an intrinsic and important part of the academic community and, therefore, we appreciate differences in backgrounds, experiences and perspectives, and facilitate them to help everyone in our team to reach their full potential in both scientific and non-scientific matters.

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Our Research

Our research interests rest on four main pillars. Our primary target is the design of molecular catalysts for organic reactions with the help of computers. To realize that, we combine the simulation of chemical reactions with lab automation for high-throughput experiments and artificial molecular design algorithms. This allows us to incorporate data-driven algorithms directly into our workflow enabling us to accelerate the discovery process.

Latest News

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May 1, 2024

Lab
Move to Feringa Building

On May 1, we moved to the Feringa building. It was a lot of work but we made it and we already enjoy the new offices and labs.

See pictures

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April 1, 2024

Members
Shiquan joins

On April 1, Shiquan joined the group as a Master student. Shiquan will work on inverse design of organocatalysts.

See bio

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April 1, 2024

Members
Serhii joins

On April 1, Serhii joined the group as a Postdoctoral researcher. Serhii will work on machine learning for chemistry.

See bio

Social Media

Recent Papers

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January 31, 2024

Reaction Simulation
Rational Design of Organic Molecules with Inverted Gaps between First Excited Singlet and Triplet

R. Pollice*, B. Ding, A. Aspuru-Guzik*

Matter 2024, 7, 1161.

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January 11, 2024

Artificial Design
Artificial Design of Organic Emitters via a Genetic Algorithm Enhanced by a Deep Neural Network

A. Nigam#, R. Pollice#,*, P. Friederich, A. Aspuru-Guzik*

Chem. Sci. 2024, 15, 2618.

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September 22, 2023

Artificial Design
Tartarus: A Benchmarking Platform for Realistic And Practical Inverse Molecular Design

A. Nigam, R. Pollice*, G. Tom, K. Jorner, J. Wiles, L. A. Thiede, A. Kundaje, A. Aspuru-Guzik

Advances in Neural Information Processing Systems 2023, 36, 3263.