Joined December 2019
- Tweets 478
- Following 870
- Followers 1,277
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52 Photos and videos
Giovanni M. Pavan Lab retweeted
1 Aug 2025
Our collaborative work "The #Martini3 #Lipidome: Expanded and Refined Parameters Improve Lipid Phase Behavior" is now published in #ACSCentralScience! ๐
๐ Read: pubs.acs.org/doi/10.1021/acsโฆ
๐พ GitHub: github.com/Martini-Force-Fieโฆ
#MolecularDynamics #Biophysics #Simulations #Lipids
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Giovanni M. Pavan Lab retweeted
1 Aug 2025
A true community effort ! The Martini 3 Lipidome: Expanded and Refined Parameters Improve Lipid Phase Behavior | ACS Central Science pubs.acs.org/doi/10.1021/acsโฆ
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1 Aug 2025
Great to see this finally out!! Congrats to all coauthors!๐พ
1 Aug 2025
A true community effort ! The Martini 3 Lipidome: Expanded and Refined Parameters Improve Lipid Phase Behavior | ACS Central Science pubs.acs.org/doi/10.1021/acsโฆ
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19 Jun 2025
Metals owe their properties to how local defects emerge & amplify in collective dislocations under stress.๐ ๏ธ
๐We show how tracking local atomic fluctuations & their space&โฑ๏ธcorrelations allows tracking metals' behavior through the elastic&plastic phases๐
pubs.aip.org/aip/jcp/articleโฆ
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19 Jun 2025
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. ๐คฏ๐คฉ
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19 Jun 2025
Congratulations to all coauthors @mattiaperr
@MatteoCioniMC @MaxDellePiane @pamara54!!๐๐ฅณ๐
Work supported by @ERC_Research & CINECA & DISAT & @PoliTOnews!๐๐
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18 Jun 2025
How much complexity is needed in self-assembling molecular systems to observe non-trivial emergent behaviors typical of more complex, higher-scale systems?๐คฏ
Not much!๐ฒ
See @NatureComms our work on the collective resilience of supramolecular polymers!๐
nature.com/articles/s41467-0โฆ
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18 Jun 2025
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!๐คฏ
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18 Jun 2025
Congratulations to all coauthors!๐๐๐
๐@ERC_Research CSCS @PoliTOnews DISAT SUPSI๐
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Giovanni M. Pavan Lab retweeted
31 May 2025
Twenty case studies showing theoretical predictions in chemistry that were later confirmed experimentally. #CompChem
doi.org/10.1515/pac-2025-045โฆ
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Giovanni M. Pavan Lab retweeted
19 Mar 2025
๐คซ 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. ๐งโ๐ over and out ๐
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19 Feb 2025
#LEAP is out @PNASNexus!๐
Building on abstract concepts of local fluctuations & their correlations in space & โฑ๏ธ, #LEAP provides info on the physics of complex dynamical systems from the atomic- to the macro-scale in agnostic & purely data-driven way!๐คฉ
academic.oup.com/pnasnexus/aโฆ
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19 Feb 2025
Complete details & LEAP analysis code available at: github.com/GMPavanLab/LEAP
and at:
doi.org/10.5281/zenodo.14851โฆ
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19 Feb 2025
This work required the support of many people! Congratulations to @c__caruso for the massive effort!๐
Congrats also to all other coauthors -@martanit @asicardellini @MatteoCioniMC @mattiaperr Massimo Delle Piane @pamara54 - for the huge work!๐
๐ Supported by @ERC_Research ๐
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19 Feb 2025
#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.
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19 Feb 2025
#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.๐คฏ
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Giovanni M. Pavan Lab retweeted
28 Jan 2025
Our latest work, led by @xu_youzhi, is dedicated to the memory of Fraser Stoddart! In May, I asked him about his favourite molecule ever made in his lab. After a while, he chose the iconic "Olympiadane" (ABCBA-type) [5]catenane. @LabPavan @Pingwu_Du
onlinelibrary.wiley.com/doi/โฆ
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