Talk: Polymer Informatics Tools for Sustainable Practices

Oral contribution presented at IUPAC Macro 2024 World Polymer Congress (https://www.macro2024.org/) which took place at the University of Warwick, UK on 1st-4th of July 2024. Abstract: In pursuance of making the polymer industry more sustainable, computational studies have been enriched with biodegradable polymers. However, owing to their complex structure resembling proteins, investigating the structure-properties-performance relationship of these polymers by simulations is still challenging.We present a systematic bottom-up approach starting from the atomistic description and involving multiple computational techniques. We focus on poly(lactic acid) due to its wide usage in additive manufacturing. We build a chemistry-specific coarse-grained (CG) model to extend the time and length scales to those relevant for experimental studies. To close the loop, we reinsert the atomistic details into CG models by applying a machine-learning based methodology.Since the computational techniques are considered to be a more sustainable alternative to the experimental characterization, the presented generic and open-access methodology aims to facilitate the digital polymer design.

Institutions

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-10-07
DOI
https://doi.org/10.5281/zenodo.17290363
Primary Topic
Telomeres, Telomerase, and Senescence
Type
article
Field-Weighted Citation Impact
0.00
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article

Talk: Polymer Informatics Tools for Sustainable Practices

Zenodo (CERN European Organization for Nuclear Research)
Telomeres, Telomerase, and Senescence
article

Talk: Polymer Informatics Tools for Sustainable Practices

article en

Abstract

Oral contribution presented at IUPAC Macro 2024 World Polymer Congress (https://www.macro2024.org/) which took place at the University of Warwick, UK on 1st-4th of July 2024. Abstract: In pursuance of making the polymer industry more sustainable, computational studies have been enriched with biodegradable polymers. However, owing to their complex structure resembling proteins, investigating the structure-properties-performance relationship of these polymers by simulations is still challenging.We present a systematic bottom-up approach starting from the atomistic description and involving multiple computational techniques. We focus on poly(lactic acid) due to its wide usage in additive manufacturing. We build a chemistry-specific coarse-grained (CG) model to extend the time and length scales to those relevant for experimental studies. To close the loop, we reinsert the atomistic details into CG models by applying a machine-learning based methodology.Since the computational techniques are considered to be a more sustainable alternative to the experimental characterization, the presented generic and open-access methodology aims to facilitate the digital polymer design.

Zenodo (CERN European Organization for Nuclear Research)
Universidad de Cádiz (ES)
Industry, innovation and infrastructure
Openalex Percentile: Top 41%
Telomeres, Telomerase, and Senescence
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Talk: Polymer Informatics Tools for Sustainable Practices · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS