# Elastic Properties of Defective 2D Polymers from Regression Driven Coarse-Graining

## TL;DR

Researchers developed a new method to predict the elastic properties of two-dimensional polymers with defects, enabling better material design.

## Contribution

A regression-driven coarse-graining approach called MikadoRR is introduced for modeling defective 2DPs.

## Key findings

- MikadoRR accurately calculates elastic properties of defective 2DPs at the microscale.
- Design principles for 2DPs with tailored elastic properties can be derived from the model.

## Abstract

Two-dimensional polymers (2DPs) are an interesting class
of polymers
due to their reticular synthetic assembly, which make them an ideal
platform for designing materials with specific target properties.
Predicting and understanding their elastic behavior is crucial for
their application. However, a realistic calculation of their properties
remains computationally challenging due to the ubiquitous presence
of defects in synthesized 2DPs. Here, we introduce a coarse-graining
(CG) approach based on elastic beams called MikadoRR with parameters extracted from a simple regression-based fitting.
This approach allows us to accurately calculate the elastic properties
of defective 2DPs up to the microscale. Furthermore, we show that
design principles of 2DPs for tailored elastic properties can be derived
from this CG model.