Giovanni M. Pavan Lab

Into self-assembly, complex molecular systems & materials science w/ computer models, simulations & machine learning |
Managed by @LabPavan members @PoliTOnews

[PauloCTSouza @SouzaPauloCT]

Our collaborative work "The #Martini3 #Lipidome: Expanded and Refined Parameters Improve Lipid Phase Behavior" is now published in #ACSCentralScience! 🎉

📄 Read: https://t.co/86EQCoKrfp

💾 GitHub: https://t.co/Ody8z5zlzp

#MolecularDynamics #Biophysics #Simulations #Lipids

[Siewert-Jan Marrink @CG_Martini]

A true community effort ! The Martini 3 Lipidome: Expanded and Refined Parameters Improve Lipid Phase Behavior | ACS Central Science https://t.co/IubUxR8I6Q

[Giovanni M. Pavan Lab @LabPavan]

Great to see this finally out!! Congrats to all coauthors!🍾

[Siewert-Jan Marrink @CG_Martini]

A true community effort ! The Martini 3 Lipidome: Expanded and Refined Parameters Improve Lipid Phase Behavior | ACS Central Science https://t.co/IubUxR8I6Q

[Giovanni M. Pavan Lab @LabPavan]

Congratulations to all coauthors @mattiaperr
@MatteoCioniMC @MaxDellePiane @pamara54!!🙌🥳👏
Work supported by @ERC_Research & CINECA & DISAT & @PoliTOnews!🙏🙏

[Giovanni M. Pavan Lab @LabPavan]

Metals owe their properties to how local defects emerge & amplify in collective dislocations under stress.🛠️
👉We show how tracking local atomic fluctuations & their space&⏱️correlations allows tracking metals' behavior through the elastic&plastic phases🚀
https://t.co/XgdUosXWU0

[Giovanni M. Pavan Lab @LabPavan]

This provides a general data-driven approach for studying the internal physical behavior of metallic (but also other types of) systems just building on the abstract concepts of fluctuations & spatio-temporal fluctuations' correlations. 🤯🤩

[Giovanni M. Pavan Lab @LabPavan]

Congratulations to all coauthors!👏🙌🚀
🙏@ERC_Research CSCS @PoliTOnews DISAT SUPSI🙏

[Giovanni M. Pavan Lab @LabPavan]

How much complexity is needed in self-assembling molecular systems to observe non-trivial emergent behaviors typical of more complex, higher-scale systems?🤯
Not much!😲
See @NatureComms our work on the collective resilience of supramolecular polymers!🚀
https://t.co/iQGTgj0vQW

[Giovanni M. Pavan Lab @LabPavan]

In non-cooperative systems, all entities populating them suffer comparably from external perturbations.
In cooperative systems (with internal "interactions-avidity"), the stronger units survive at the expense of the weaker ones!🤯

[Giovanni M. Pavan Lab @LabPavan]

@MarioBarbatti Great paper! And thank you @MarioBarbatti for including our work on defects & dynamics of supramolecular polymers! https://t.co/luVJXQQG7c

[Mario Barbatti @MarioBarbatti]

Twenty case studies showing theoretical predictions in chemistry that were later confirmed experimentally. #CompChem

https://t.co/jIH50iFZMi

[ISMSC2025, Kyoto @ISMSC2025]

Sushi assembly with speakers!
#ISMSC2025

[supraGRC @SupraGRC]

Only a few days left before we kick of the GRS and GRC meeting in Les Diablerets! We hope you have safe travels!

[COSMO Lab 🇨🇭🇪🇺 @lab_COSMO]

🤫 you can get a better universal #machinelearning potential by training on fewer than 100k structures. too good to be true? head to arxiv:2503.14118, to the atomistic cookbook, or to the better science social if you want to find out more about PET-MAD. 🧑‍🚀 over and out 👋

[Giovanni M. Pavan Lab @LabPavan]

This work required the support of many people! Congratulations to @c__caruso for the massive effort!👏
Congrats also to all other coauthors -@martanit @asicardellini @MatteoCioniMC @mattiaperr Massimo Delle Piane @pamara54 - for the huge work!🙌
🙏 Supported by @ERC_Research 🙏

[Giovanni M. Pavan Lab @LabPavan]

#LEAP is out @PNASNexus!🚀
Building on abstract concepts of local fluctuations & their correlations in space & ⏱️, #LEAP provides info on the physics of complex dynamical systems from the atomic- to the macro-scale in agnostic & purely data-driven way!🤩
https://t.co/Rs7HtD5IRv

[Giovanni M. Pavan Lab @LabPavan]

Complete details & LEAP analysis code available at: https://t.co/JG0vKlVz8z
and at:
https://t.co/f3lt6v9ePP

[Giovanni M. Pavan Lab @LabPavan]

#LEAP analyses are agnostic & require just that a trajectory of the building blocks constituting the complex dynamical system is available.
Useful to explore complex dynamical systems whose physics is unknown a priori & to revisit well-known phenomena under a new perspective.🤯

[Giovanni M. Pavan Lab @LabPavan]

#LEAP allows to:
1) Detect relevant fluctuations in noisy trajectories
2) Classify fluctuations in classes based on their physics
3) Identify correlations in space & time between fluctuations
4) Unveil local & collective events, their correlations, causal relationships, etc.