Giovanni M. Pavan

Delighted that our paper on gold(I)-based nano-onions has been named Paper of the Year 2025 by the RSC CNN Interest Group 🥳

Read now in Chem @cellpress.bsky.social how @eliebenchimol.bsky.social uses adjacent backbone interactions (ABI) to control self-sorting of chiral heteroleptic Pd3A2B4 isosceles triangles („star destroyers“) and Pd4A4C4 pseudo-tetrahedra:
doi.org/10.1016/j.ch...

@grk2376.bsky.social

Congratulations!

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 pubs.acs.org/doi/10.1021/...

Congratulations Grace! And best luck for the new adventure!

Congratulations to all coauthors @mattia-perrone.bsky.social Matteo Cioni & @massimodellepiane.bsky.social!!🙌🥳👏
Work supported by @erc.europa.eu @cineca.bsky.social & DISAT & Politecnico di Torino 🙏🙏

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

Our analyses demonstrate, in a completely unsupervised & abstract way, how metal lattices transition from the elastic to the plastic phase when new local defects/fluctuations cannot avoid emerging as correlated in space & simultaneous in time, leading to the early emergence of dislocations! 🤓

Unsupervised tracking of local and collective defects dynamics in metals under deformation Metals owe their unique mechanical properties to how defects emerge and propagate within their crystal structure under stress. However, the mechanisms leading f

Metals owe their 🛠️properties to how local defects emerge & propagate in collective dislocations in them under stress.📣
We show how tracking local atomic fluctuations & their space&time correlations allows tracking metals' behavior through the elastic & plastic phases.🚀🤯
pubs.aip.org/aip/jcp/arti...

Congratulations to all coauthors!👏🙌🚀
🙏 @erc.europa.eu, @cscsch.bsky.social, DISAT, Politecnico di Torino, SUPSI🙏

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!🤯

Non-trivial stimuli-responsive collective behaviours emerging from microscopic dynamic complexity in supramolecular polymer systems - 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 to ascertain. Here the autho...

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 @natcomms.nature.com our work on the collective resilience of dynamical supramolecular polymers!🚀
www.nature.com/articles/s41...

When Theory Came First: A Review of Theoretical Chemical Predictions Ahead of Experiments For decades, computational theoretical chemistry has provided critical insights into molecular behavior, often anticipating experimental discoveries. This review surveys twenty notable examples from t...

A free version of the paper is available:
doi.org/10.26434/che...

When theory came first: a review of theoretical chemical predictions ahead of experiments For decades, computational theoretical chemistry has provided critical insights into molecular behavior, often anticipating experimental discoveries. This review surveys twenty notable examples from t...

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

doi.org/10.1515/pac-...

Polar plot showing the errors of several machine-learning potential of different test sets. Smaller is better here!

Plots showing the evaluation time per atom for several machine-learning potentials as a function of the number of atoms in a simulation. Smaller is better

📢 PET-MAD has just landed! 📢 What if I told you that you can match & improve the accuracy of other "universal" #machinelearning potentials training on fewer than 100k atomic structures? And be *faster* with an unconstrained architecture that is conservative with tiny symmetry breaking? Sounds like 🧑‍🚀

When Theory Came First: A Review of Theoretical Chemical Predictions Ahead of Experiments For decades, computational theoretical chemistry has provided critical insights into molecular behavior, often anticipating experimental discoveries. This review surveys twenty notable examples from t...

It started as X discussion in Aug 2024. Now it's a preprint:

When Theory Came First: A Review of Theoretical Chemical Predictions Ahead of Experiments

🧪#compchem doi.org/10.26434/che...

Into the Dynamics of a Supramolecular Polymer at Submolecular Resolution - Nature Communications Accessing the dynamics of soft self-assembled materials at high resolution is very difficult. Here the authors show atomistic and coarse-grained modelling combined with enhanced sampling to characteri...

Nice work @mbarbatti.bsky.social!
Glad to see a section on our 2017 work www.nature.com/articles/s41... explaining via models/simulations how the dynamics of supramolecular polymers is controlled by defects, later observed by experiments @fluorenzo.bsky.social in 2024 (pubs.acs.org/doi/10.1021/...)!

Great initiative! Could you please add me! Many thanks!

#CompChemSky #CompChem #chemsky #data-analysis #machinelearning #AI

This work required the support of many people!
Congratulations to Cristina Caruso for the massive effort!👏
Congrats to all other coauthors - Martina Crippa, Annalisa Cardellini, Matteo Cioni, Mattia Perrone, @massimodellepiane.bsky.social l - for the huge work!
🙏 @erc.europa.eu for the support 🙏

Complete details & LEAP analysis code available at:
github.com/GMPavanLab/L...
and at:
doi.org/10.5281/zeno...

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

#LEAP analyses allow to:
1) Detect relevant fluctuations from noise in trajectories
2) Classify fluctuations in types based on their physics
3) Identifying correlations in space & time between fluctuations
4) Unveil local & collective events, their correlations, causal relationships, etc.

Classification and spatiotemporal correlation of dominant fluctuations in complex dynamical systems Abstract. The behaviors of many complex systems, from nanostructured materials to animal colonies, are governed by local events/rearrangements that, while

#LEAP is out @pnasnexus.org!🚀
Building on abstract concepts of local fluctuations & their correlations in space & ⏱️, #LEAP provides, in agnostic & purely data-driven way, info on the internal physics of complex dynamical systems from the atomic- to the macro-scale!🤩
academic.oup.com/pnasnexus/ad...

Happy ending (of the year): the release of our preprint, "The Martini 3 Lipidome: Expanded and Refined Parameters Improve Lipid Phase Behavior", now available on @ChemRxiv.

👉 Read the full preprint here: chemrxiv.org/engage/chemr...

and get the parameters here: github.com/Martini-Forc...

Excited to announce the release of our preprint, "The Martini 3 Lipidome: Expanded and Refined Parameters Improve Lipid Phase Behavior", now available on @chemrxiv.bsky.social

👉 Read the full preprint here: chemrxiv.org/engage/chemr...

with this approach the choice of the best cutoff distance or of the time intervals between the studied frames stop being parameters to be tuned in the analysis, but steps out as automatically encoded into the data: these are those allowing to maximise information extraction from the data itself!🚀🔥

GitHub - GMPavanLab/Optimal-Spatiotemporal-Resolutions: It contains all the code used for: "Optimal Spatiotemporal Resolutions" It contains all the code used for: "Optimal Spatiotemporal Resolutions" - GMPavanLab/Optimal-Spatiotemporal-Resolutions

Congrats all coauthors: Domiziano Doria @simonemartino.bsky.social Matteo Becchi! 🙌

Work supported by
#HorizonEU ERC @ec.europa.eu #NextGenerationEU
🙏

Data, code, and materials soon open-accessible at:
github.com/GMPavanLab/O...

The concept of “optimal spatiotemporal resolution” is general: a robust basis to characterize any type of system based on its data & to guide data analysis in general! 🤩