# MYTHOS: A Python Interface for Surface Crystal Structure Prediction of Organic Semiconductors

## TL;DR

This paper introduces a Python tool for predicting how organic semiconductors form crystals on surfaces, which is important for improving electronic devices.

## Contribution

The paper presents a new Python-based method for predicting surface-induced polymorphs in organic semiconductors.

## Key findings

- The method successfully identified surface-induced polymorphs in six test cases.
- Predicted crystalline structures matched experimental results well.
- The approach allows for layer-by-layer analysis of crystal formation.

## Abstract

We introduce a new computational approach for predicting
organic
crystalline structures on flat surfaces, an essential step in designing
and optimizing thin-film systems for electronic devices. Based on
molecular mechanics and molecular dynamics simulations, and implemented
in a user-friendly Python program, this method enables a sequential
layer-by-layer analysis of crystalline formation, thus allowing to
identify surface-induced polymorphs (SIPs) and to study the transition
between surface and bulk structures. A validation against six diverse
test cases demonstrated a good match with experimental crystalline
parameters and arrangements, underscoring the reliability of the method
in identifying the most relevant polymorphs for a given molecule.