Giovanni M. Pavan
@pamara54
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Scientist. Full Professor at Politecnico di Torino (IT) @politonews, @ERC_research grantee, head of @LabPavan - https://t.co/GVzumEraiC
Italy
Joined December 2010
Extermely happy to have been appointed Full Professor at the Politecnico di Torino!! @PoliTOnews #PoliTo I am super-excited to start a new research group in Italy! News on multiple open positions at various levels in my group will follow very soon!!!
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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
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A true community effort ! The Martini 3 Lipidome: Expanded and Refined Parameters Improve Lipid Phase Behavior | ACS Central Science
pubs.acs.org
Lipid membranes are central to cellular life. Complementing experiments, computational modeling has been essential in unraveling complex lipid-biomolecule interactions, crucial in both academia and...
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Great to see this finally out!! Congrats to all coauthors!🍾
A true community effort ! The Martini 3 Lipidome: Expanded and Refined Parameters Improve Lipid Phase Behavior | ACS Central Science
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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
pubs.aip.org
Metals owe their unique mechanical properties to how defects emerge and propagate within their crystal structure under stress. However, the mechanisms leading f
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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
nature.com
Nature Communications - Supramolecular polymers possess features typical of complex systems, but the mechanisms that lead to the emergence of collective properties inside them are often difficult...
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#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
academic.oup.com
Abstract. The behaviors of many complex systems, from nanostructured materials to animal colonies, are governed by local events/rearrangements that, while
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When studying complex systems, common belief is that high-dimensional analyses are desirable to prevent losing important information... but to what extent this is really needed/beneficial remains often unclear.😵💫 Now @arxiv we challenge this assumption: https://t.co/NZEGnB8VU0 🚀
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Big congrats to @MatteoCioniMC on his PhD defense! 🎉✨ After years of hard work @PoliTOnews, Matteo's brilliant research in molecular dynamics & complex systems has pushed boundaries. 🌌💻 We're proud to celebrate this huge milestone with him! 🚀👨🎓 #PhDDefense #Science
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The choice of descriptors is key for extracting information from data.🧐 Look at @SimoneM118 work! https://t.co/PsSeIMMNe5 While advanced descriptors may rely on higher signal-to-noise, we show how even the simplest descriptor may become super efficient upon local denoising! 🚀
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Finally out in @PNASNews “Onion 🧅 Clustering” 🚀: an efficient & essentially parameter-free unsupervised clustering method that can classify statistically relevant fluctuations & microscopic dynamical domains in noisy timeseries data of any kind!!🤩🥳 https://t.co/fWH10JFATr
Tracking statistically-relevant fluctuations in noisy time-series data is key in many fields, from #MachineLearning, to the study of signals & complex systems! Use Onion #Clustering🧅: easy, unsupervised, physically-interpretable, statistically-robust!🚀🤯 https://t.co/2x5dBCkkUQ
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Recent simulations showed non-trivial dynamics in metals. But these often remain hard to prove experimentally. Here we combine for the 1st time experimentally-resolved Au-NP structures with MD simulations & #ML, proving their real-time atomic dynamics! https://t.co/FpN2OcCNMi
advanced.onlinelibrary.wiley.com
Experimental and computational techniques are bridged to unveil atomic dynamics in gold nanoparticles (NPs), using annular dark-field scanning transmission electron microscopy and molecular dynamics...
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😎: Onion Clustering does not attempt to fit all data in a time-series into clusters! Depending on the resolution, dt, it classifies all the information that can be classified in statistically robust way & store the "undetermined" information in the ENV0 cluster! 🚀🤯🔥
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Tracking statistically-relevant fluctuations in noisy time-series data is key in many fields, from #MachineLearning, to the study of signals & complex systems! Use Onion #Clustering🧅: easy, unsupervised, physically-interpretable, statistically-robust!🚀🤯 https://t.co/2x5dBCkkUQ
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Stereocontrolled Self-Assembly of a Helicate-Bridged CuI12L4 Cage That Emits Circularly Polarized Light | JACS @ChemCambridge @Cambridge_Uni @PoliTOnews
@supsi_ch @LabPavan #Stereocontrolled #Helicate #Cu #Cage #Light #Emission
pubs.acs.org
Control over the stereochemistry of metal–organic cages can give rise to useful functions that are entwined with chirality, such as stereoselective guest binding and chiroptical applications. Here,...
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Today at the cover of @ChemicalScience our collaboration with @LabPavan 🇮🇹🇪🇸 Moving supramolecular contacts around cyclic peptides 💍 allows control self-assembly in 2D 📄 Wonderful to work with @asicardellini @InsuaNacho @SandraDA95 @nanominions 🔖🎉👏 https://t.co/9HnBNLhnKH
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@LabPavan @martanit @asicardellini @MatteoCioniMC @Cambridge_Uni @pamara54 @ERC_Research @snsf_ch @PoliTOnews @supsi_ch Thank you again for publishing this great work with @MLSTjournal. We hope to have the opportunity to work with you again soon!
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Great new work by @martanit @asicardellini @MatteoCioniMC @pamara54 and Gabor Csanyi @LabPavan @PoliTOnews @supsi_ch @Cambridge_Eng - '#Machinelearning of microscopic structure-dynamics relationships in complex molecular systems' - https://t.co/ch7mZMHaSR
#compchem #materials #AI
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Fresh @ J. Chem. Eng. Data the new work of @mattiaperr! 🥳🤩 We tested SwarmCG to automatically optimize rigid 3-site water models onto multiple microscopic (exp. g(r))+macroscopic thermodynamic properties, hitting the physical limits of such models!🧐🤯
pubs.acs.org
The development of accurate water models is of primary importance for molecular simulations. Despite their intrinsic approximations, three-site rigid water models are still ubiquitously used to...
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