Giovanni M. Pavan Research Group

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We explore new routes in physical chemistry, self-assembly & bioinspired materials
using
molecular modeling, computer simulations & machine learning


Our research group has a double affiliation with:

Politecnico di Torino (POLITO), Department of Applied Science and Technology (DISAT)

&

University of Applied Science and Arts of Southern Switzerland (SUPSI),
Department of Innovative Technologies (DTI), Institute for Mechanical Engineering and Materials Technologies (MEMTI)

Giovanni M. Pavan Lab Follow

We explore new routes in physical chemistry, self-assembly & bioinspired materials with molecular modeling, computer simulations & ML. @PoliTOnews @supsi_ch

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Avatar Alexander Menke @alexmenke62 ·
11 Aug

Pleased to announce my first collaborative authorship!

Well-Tempered Metadynamics Simulations Predict the Structural and Dynamic Properties of a Chiral 24-Atom Macrocycle in Solution https://pubs.acs.org/doi/10.1021/acsomega.2c03536#.YvRKK1PsPRo.twitter

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Avatar Chiara Lionello @lionellochiara ·
12 Aug

It's so difficult to say goodbye to these amazing people! Thanks @SaricLab for this great opportunity! Hope to see you again soon!❤️🍷

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Avatar Andela Saric @sariclab ·
12 Aug

Group hike in the vineyards of Vienna to say “see you again” to @LionelloChiara, a wonderful visiting Phd student from @LabPavan at @PoliTOnews. Thanks for sharing your science&fun with us! https://twitter.com/lionellochiara/status/1558134441024839680

Chiara Lionello @LionelloChiara

It's so difficult to say goodbye to these amazing people! Thanks @SaricLab for this great opportunity! Hope to see you again soon!❤️🍷

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Avatar Hybrid Materials Interfaces @hmi_group ·
12 Aug

Just learnt a lot about the behaviour of metal surfaces and lipid layers through data-driven analyses and representations - great talk by @MaxDellePiane from @LabPavan group!

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Avatar Pablo Piaggi @piaggipablo ·
8 Aug

Our paper on ice nucleation using first principles MD simulations driven by an ML model just appeared online in PNAS. 300,000 atoms with ab initio accuracy! Thanks @snsf_ch @doescience @CcscCsi @DeepModeling @plumed_org for making this possible. https://www.pnas.org/doi/full/10.1073/pnas.2207294119

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