High-throughput computational screening of small, eco-friendly, molecular crystals for sustainable piezoelectric materials

TL;DR

This study presents a database of small organic molecular crystals with DFT-predicted electromechanical properties, highlighting many with high longitudinal piezoelectric constants suitable for sensing and energy harvesting.

Contribution

The paper introduces CrystalDFT, a comprehensive database of molecular crystals with predicted electromechanical properties, aiding the discovery of eco-friendly piezoelectric materials.

Findings

Many crystals exhibit high longitudinal d33 constants.

The database reveals diverse electromechanical properties.

Natural occurrence of high d33 constants is common in the dataset.

Abstract

Organic molecular crystals are ideally placed to become next-generation piezoelectric materials due to their diverse chemistries that can be used to engineer tailor-made solid-state assemblies. Using crystal engineering principles, and techniques such as co-crystallisation, these materials can be engineered to have a wide range of electromechanical properties. For materials that have been structurally characterised by methods such as X-Ray Diffraction, computational chemistry is an effective tool to predict their electromechanical properties, allowing researchers to screen these molecular crystals and identify materials best suited to their chosen application. Here we present our database of small molecular crystals, and their Density Functional Theory (DFT) predicted electromechanical properties, CrystalDFT (https://actuatelab.ie/CrystalDFT). We highlight the broad range of electromechanical properties amongst this primary dataset, and in particular, the high number of crystals that have a naturally occurring longitudinal d33 constant. This longitudinal electromechanical coupling is a prerequisite for several conventional sensing and energy harvesting applications, the presence of which is notably rare amongst the literature on biomolecular crystal piezoelectricity to date.