Giovanni M. Pavan
@giovannipavan.bsky.social
Scientist | Full Professor at Politecnico di Torino (IT) | ERC Consolidator grantee | Head of CPC Lab: http://www.gmpavanlab.polito.it | Self-assembly, chemical physics, materials science, soft matter, complex systems, emergent properties
Reposted by Giovanni M. Pavan
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
doi.org/10.1016/j.ch...
@grk2376.bsky.social
October 17, 2025 at 2:47 PM
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
doi.org/10.1016/j.ch...
@grk2376.bsky.social
Reposted by Giovanni M. Pavan
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/...
pubs.acs.org
August 1, 2025 at 11:32 AM
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/...
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...
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...
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
pubs.aip.org
June 19, 2025 at 4:11 PM
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...
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...
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...
Not much!😲
See @natcomms.nature.com our work on the collective resilience of dynamical supramolecular polymers!🚀
www.nature.com/articles/s41...
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...
www.nature.com
June 18, 2025 at 9:53 AM
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...
Not much!😲
See @natcomms.nature.com our work on the collective resilience of dynamical supramolecular polymers!🚀
www.nature.com/articles/s41...
Reposted by Giovanni M. Pavan
A free version of the paper is available:
doi.org/10.26434/che...
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...
doi.org
May 31, 2025 at 2:45 PM
A free version of the paper is available:
doi.org/10.26434/che...
doi.org/10.26434/che...
Reposted by Giovanni M. Pavan
Twenty case studies showing theoretical predictions in chemistry that were later confirmed experimentally. #CompChem 🧪
doi.org/10.1515/pac-...
doi.org/10.1515/pac-...
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...
doi.org
May 31, 2025 at 2:45 PM
Twenty case studies showing theoretical predictions in chemistry that were later confirmed experimentally. #CompChem 🧪
doi.org/10.1515/pac-...
doi.org/10.1515/pac-...
Reposted by Giovanni M. Pavan
📢 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 🧑🚀
March 19, 2025 at 7:23 AM
📢 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 🧑🚀
Reposted by Giovanni M. Pavan
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...
When Theory Came First: A Review of Theoretical Chemical Predictions Ahead of Experiments
🧪#compchem 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...
doi.org
March 1, 2025 at 5:13 AM
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...
When Theory Came First: A Review of Theoretical Chemical Predictions Ahead of Experiments
🧪#compchem doi.org/10.26434/che...
#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...
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...
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
academic.oup.com
February 19, 2025 at 10:03 AM
#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...
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...
Reposted by Giovanni M. Pavan
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...
👉 Read the full preprint here: chemrxiv.org/engage/chemr...
and get the parameters here: github.com/Martini-Forc...
December 27, 2024 at 10:16 AM
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...
👉 Read the full preprint here: chemrxiv.org/engage/chemr...
and get the parameters here: github.com/Martini-Forc...
Reposted by Giovanni M. Pavan
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...
👉 Read the full preprint here: chemrxiv.org/engage/chemr...
December 26, 2024 at 1:47 PM
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...
👉 Read the full preprint here: chemrxiv.org/engage/chemr...
#compchem #chemsky #data-analysis #machinelearning #AI folks 📣
In #ArXiv we propose the concept of “optimal spatiotemporal resolutions”!🤯
We demonstrate how any system/data has its own to be best studied/characterised & how to learn these directly from the system’s data!🚀
arxiv.org/abs/2412.13741
In #ArXiv we propose the concept of “optimal spatiotemporal resolutions”!🤯
We demonstrate how any system/data has its own to be best studied/characterised & how to learn these directly from the system’s data!🚀
arxiv.org/abs/2412.13741
Optimal Spatiotemporal Resolutions
In general, the comprehension of any type of complex system depends on the resolution used to look at the phenomena occurring within it. But identifying a priori, for example, the best time frequencie...
arxiv.org
December 20, 2024 at 8:25 AM
#compchem #chemsky #data-analysis #machinelearning #AI folks 📣
In #ArXiv we propose the concept of “optimal spatiotemporal resolutions”!🤯
We demonstrate how any system/data has its own to be best studied/characterised & how to learn these directly from the system’s data!🚀
arxiv.org/abs/2412.13741
In #ArXiv we propose the concept of “optimal spatiotemporal resolutions”!🤯
We demonstrate how any system/data has its own to be best studied/characterised & how to learn these directly from the system’s data!🚀
arxiv.org/abs/2412.13741
Reposted by Giovanni M. Pavan
Finally out my last work! If you are dealing with high dimensional data, you should definitely take a look! 😉
When studying complex systems, a 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.😵💫
In our last Arxiv preprint we challenge this assumption:
arxiv.org/abs/2412.094... 🚀🤩
In our last Arxiv preprint we challenge this assumption:
arxiv.org/abs/2412.094... 🚀🤩
Relevant, hidden, and frustrated information in high-dimensional analyses of complex dynamical systems with internal noise
Extracting from trajectory data meaningful information to understand complex systems might be non-trivial. High-dimensional analyses are typically assumed to be desirable, if not required, to prevent ...
arxiv.org
December 19, 2024 at 2:47 PM
Finally out my last work! If you are dealing with high dimensional data, you should definitely take a look! 😉
When studying complex systems, a 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.😵💫
In our last Arxiv preprint we challenge this assumption:
arxiv.org/abs/2412.094... 🚀🤩
In our last Arxiv preprint we challenge this assumption:
arxiv.org/abs/2412.094... 🚀🤩
Relevant, hidden, and frustrated information in high-dimensional analyses of complex dynamical systems with internal noise
Extracting from trajectory data meaningful information to understand complex systems might be non-trivial. High-dimensional analyses are typically assumed to be desirable, if not required, to prevent ...
arxiv.org
December 19, 2024 at 2:41 PM
When studying complex systems, a 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.😵💫
In our last Arxiv preprint we challenge this assumption:
arxiv.org/abs/2412.094... 🚀🤩
In our last Arxiv preprint we challenge this assumption:
arxiv.org/abs/2412.094... 🚀🤩
Reposted by Giovanni M. Pavan
Great interdisciplinary work in collaboration with Prof. @kay-severin.bsky.social's group at EPFL! Our computational work (with Luigi Leanza and Giovanni M. Pavan) provided key insights into the self-assembly mechanisms behind these fascinating structures! 🧅
💥RSC CNN Paper of the Week💥
Nano onions based on an amphiphilic Au3(pyrazolate)3 complex
Severin* (EPFL)
Solea et al, Nanoscale, 10.1039/D4NR03901G
#ChemSky #Science #NanoSky
Nano onions based on an amphiphilic Au3(pyrazolate)3 complex
Severin* (EPFL)
Solea et al, Nanoscale, 10.1039/D4NR03901G
#ChemSky #Science #NanoSky
Nano onions based on an amphiphilic Au3(pyrazolate)3 complex
Multilayer vesicles with an onion-like architecture can form by self-assembly of organic amphiphiles such as dendrimers, small-molecule surfactants, and block copolymers. Thus far, there are limited r...
doi.org
December 19, 2024 at 2:00 PM
Great interdisciplinary work in collaboration with Prof. @kay-severin.bsky.social's group at EPFL! Our computational work (with Luigi Leanza and Giovanni M. Pavan) provided key insights into the self-assembly mechanisms behind these fascinating structures! 🧅