Giovanni M. Pavan Research Group

  • Home
  • Research
  • People
  • Publications
  • ERC
  • Downloads
  • Life in the Group
  • Join the group
  • News
  • Collaborations
  • Contacts

ERC Consolidator Grant

DYNAPOL – Modeling approaches toward bioinspired dynamic materials

Abstract 

The DYNAPOL project will develop multiscale molecular models and use advanced computational simulation and machine learning techniques to discover the fundamental chemical-physical principles to learn how to design new classes of artificial materials with bio-inspired dynamic properties, or similar to those of living materials.



Description of the research project 

DYNAPOL will explore new routes to design new types of artificial materials for various technological applications. It will use innovative chemical-physical concepts, different from those on which technological materials are typically based, and exploit self-assembly properties. The idea is to take inspiration from nature and how it builds complex materials possessing fascinating properties, such as the ability to actively respond to different types of external stimuli: environmental (temperature, salt concentrations, pressure), biological (specific interactions with proteins or tissues), chemical and physical. Examples of similar natural supramolecular materials are microtubules or protein filaments, which can reconfigure in response to specific inputs.
In order to design bioinspired artificial polymeric materials it is necessary to understand in detail the molecular principles that control their dynamic behavior, and to learn the relationships existing between the chemical structure of the constitutive self-assembling building blocks and the dynamic properties of the assemblies that these form across various spatio-temporal scales. To this end, the DYNAPOL project will use multiscale molecular models, advanced molecular simulation techniques and machine learning. The models obtained will be validated through continuous comparison with experimental data from various international collaborations. This is a highly multidisciplinary research with a pioneering character, which will avail of the close collaboration between chemists, physicists, engineers and computer scientists.

Impact  

DYNAPOL is a fundamental research project that aims at exploring approaches and trace new routes toward innovative technological materials. The results of this project will impact various research fields and technological areas of high current interest, such as biomedical, pharmaceutical, energy, chemical. At the same time it will develop new knowledge allowing to explore applications not yet foreseen in the field of innovative materials and complex molecular systems.

Giovanni M. Pavan LabFollow

Avatar
Retweet on TwitterGiovanni M. Pavan Lab Retweeted
AvatarETH Zurich@ETH_en·
24 Feb

A digital twin of our #planet is to #simulate the Earth #system in future. It is intended to support policy-​makers in taking appropriate measures to better prepare for extreme events.
https://ethz.ch/en/news-and-events/eth-news/news/2021/02/a-highly-accurate-digital-twin-of-our-planet.html

Reply on Twitter 1364455018485710848Retweet on Twitter 136445501848571084821Like on Twitter 136445501848571084849Twitter 1364455018485710848
Retweet on TwitterGiovanni M. Pavan Lab Retweeted
AvatarNature@nature·
22 Feb

News & Views: A Nature paper reports an accessible machine-learning tool that can accelerate the optimization of a wide range of synthetic reactions — and reveals how cognitive bias might have undermined optimization by humans. https://go.nature.com/2O2Apco

Reply on Twitter 1363832916527247365Retweet on Twitter 136383291652724736545Like on Twitter 1363832916527247365112Twitter 1363832916527247365
AvatarGiovanni M. Pavan Lab@LabPavan·
17 Feb

Great work @ric_capelli!
A data-driven SOAP metrics to compare & classify lipid force fields based on the local environments surrounding the lipids along MD simulations. Versatile & not restricted to lipids! Useful to compare a variety of dynamic systems! https://chemrxiv.org/articles/preprint/A_Data-Driven_Dimensionality_Reduction_Approach_to_Compare_and_Classify_Lipid_Force_Fields/14039834

Riccardo Capelli@ric_capelli

The last @LabPavan preprint is out on @ChemRxiv! We employed a dimensionality reduction approach to compare lipid force fields, and we discovered that most of the relevant differences is not in the average, but in the local representation of the system!

https://chemrxiv.org/articles/preprint/A_Data-Driven_Dimensionality_Reduction_Approach_to_Compare_and_Classify_Lipid_Force_Fields/14039834/1

Reply on Twitter 1362045457682358273Retweet on Twitter 13620454576823582732Like on Twitter 136204545768235827314Twitter 1362045457682358273
Retweet on TwitterGiovanni M. Pavan Lab Retweeted
AvatarLarissa von Krbek@vkrbek·
15 Feb

(1/2) @aprahamian & I are organizing a #SystemsChemistry symposium on March 22-23 #ChemSystemsMeet, @nanoGe_Conf. Registration is now open and free for first 30 students, curtesy of @RoySocChem (+more depending on funding)
http://nanoge.org/ChemSystemsMeet/general-information
#realtimechem
#ChemTwitter ...

Reply on Twitter 1361330271908470789Retweet on Twitter 136133027190847078932Like on Twitter 136133027190847078972Twitter 1361330271908470789
AvatarGiovanni M. Pavan Lab@LabPavan·
29 Jan

Fascinated by molecular exchange in supramolecular polymers?
Your dream is to "encode" exchange pathways in supramolecular systems?
Better to start learning how to control defects & their statistical behavior!
All this in our last @ChemRxiv preprint: https://chemrxiv.org/articles/preprint/Controlling_Exchange_Pathways_in_Dynamic_Supramolecular_Polymers_by_Controlling_Defects/13655864

Reply on Twitter 1355249816842997764Retweet on Twitter 13552498168429977643Like on Twitter 135524981684299776430Twitter 1355249816842997764
Load More...

Cookie policy

CyberChimps ©2021
This website uses cookies to improve your experience. We'll assume you're ok with this, but you can opt-out if you wish. Cookie settingsACCEPTReject
Privacy & Cookies Policy

Privacy Overview

This website uses cookies to improve your experience while you navigate through the website. Out of these cookies, the cookies that are categorized as necessary are stored on your browser as they are essential for the working of basic functionalities of the website. We also use third-party cookies that help us analyze and understand how you use this website. These cookies will be stored in your browser only with your consent. You also have the option to opt-out of these cookies. But opting out of some of these cookies may have an effect on your browsing experience.
Necessary
Always Enabled

Necessary cookies are absolutely essential for the website to function properly. This category only includes cookies that ensures basic functionalities and security features of the website. These cookies do not store any personal information.

Non-necessary

Any cookies that may not be particularly necessary for the website to function and is used specifically to collect user personal data via analytics, ads, other embedded contents are termed as non-necessary cookies. It is mandatory to procure user consent prior to running these cookies on your website.

SAVE & ACCEPT