An interdisciplinary group of researchers has developed a strong mathematical modelling software that may enable researchers to foretell the properties of polymer networks earlier than they’re even created.
Polymers networks are made up of lengthy chains of molecules, like a string of pearls or spaghetti. This new mannequin predicts the connections between the spaghetti-like strands.
In the examine, revealed in Nature Materials, the researchers from Ghent University (UGent), QUT and Stanford University, developed the strategy for predicting polymer properties.
Professor Dagmar R. D’hooge, of UGent, Belgium, mentioned polymer networks had many functions together with rubbers, coatings, adhesives, and cosmetics.
“For the first time, this is a predictive tool for material properties of networks—from the smallest building block of the molecule up to how hard is the material, is it impact resistant or is it just a soft blob,” Professor D’hooge mentioned.
Dr. De Keer, of UGent, mentioned the software outlined within the analysis was an support within the design of recent supermolecular polymers in areas corresponding to drug supply, gene transfection and biomedical functions.
Along with Professor Dagmar R. D’hooge and Dr. De Keer, UGent researchers concerned within the examine embody Professor Paul Van Steenberge, Professor Marie-Françoise Reyniers, Professor Lode Daelemans and Professor Karen De Clerck.
Professor Christopher Barner-Kowollik, from QUT’s Centre for Materials Science, mentioned the researchers developed the mannequin utilizing superior arithmetic and molecular simulations, bringing collectively researchers from computational modelling, artificial chemistry and materials science.
“Recent chemistry developments have included unconventional properties such as self-healing, conductivity and stimuli-responsiveness in polymer networks, giving them a large potential in advanced applications such as recycling, drug delivery, tissue engineering scaffolds, gas storage, catalysis and electronic materials,” Professor Barner-Kowollik mentioned.
“It’s an enormous process to characterise polymer networks—it is actually tough.
“Here we are making a real step forward by fusing expertise from theoretical modelling to experimental chemists who provide examples by which the model can be tested.”
Professor Barner-Kowollik mentioned the final word dream for experimental chemists is to have a pc program that takes the unknown out of experiments.
“Imagine if you could have a supercomputer that, even before you hit the lab, would be able to say what the likely outcome would be,” he mentioned.
“This is a step in towards that.”
Along with Professor Barner-Kowollik, researchers concerned within the examine embody QUT’s Dr. Hendrick Frisch and Daniel Kodura.
Professor Reinhold Dauskardt at Stanford University mentioned he was “super excited” concerning the work.
“It represents a tour-de-force of fundamental materials chemistry and demonstrates what can be achieved from an international team with diverse backgrounds.”
Professor Dauskardt mentioned the work “shows how molecular building blocks can be assembled both temporally and spatially to create accurate materials structures including defects and resulting structure-property relationships”.
“This combination of both kinetics and molecular spatial assembly has not been achieved before,” Professor Dauskardt mentioned.
Lies De Keer et al, Computational prediction of the molecular configuration of three-dimensional community polymers, Nature Materials (2021). DOI: 10.1038/s41563-021-01040-0
Queensland University of Technology
New software to foretell polymer properties (2021, September 6)
retrieved 6 September 2021
This doc is topic to copyright. Apart from any truthful dealing for the aim of personal examine or analysis, no
half could also be reproduced with out the written permission. The content material is offered for info functions solely.