Overview
Using a combination of automated characterization methods and computational chemistry methods the doctoral student will identify organic molecules for novel applications for electronic devices in displays, sensing, catalysis and energy applications.
About this opportunity
High-throughput virtual screening of conjugated molecules is a mature area with reliable computational datasets approaching millions of compounds and experimental validations for thousands of them. However, all applications in optoelectronic devices require molecular materials with optimal photophysical properties (lifetimes, fluorescence yields, rates of singlet-fission, up-conversion, oxidative and reductive quenching, etc.). These are currently not predictable by high-throughput computational methods. Furthermore, experimental data of photophysical properties are limited and inhomogeneous. The two key objectives of this combined theoretical/experimental problem are:
- To expand the capabilities of virtual screening for photophysical properties for datasets of the order of hundreds of thousands of entries.
- To exploit automated optical time-resolved characterization methods to construct reliable and homogeneous datasets of thousands of entries.
The two objectives are interdependent because reliable experimental datasets in (2) are required to fine tune many aspects of the methodology to be developed in (1). The challenge of the second objective is the development of automated interpretation of the optical spectra (absorption, excitation, fluorescence and fluorescence lifetime) which is now performed manually for just a few systems at a time.
This project will be supervised by Prof Alessandro Troisi (Theoretical Chemistry & Spectroscopy) and Dr John Ward (Organic Chemistry & Automation). The supervisory team combines experts in high throughput screening for organic electronics and automatic characterization of optical properties. Prof Troisi and his group have developed methodologies to perform high throughput screening for organic electronics [10.1021/jacs.3c05452], prediction of photophysical properties [10.1021/acs.jpclett.5c00176], automated interpretation of electronic spectra [10.1039/D4TC03511A] and explanation of novel observations [10.1039/D4SC04518A]. Dr Ward offers expertise in the automatic characterization of optical properties employer for example in the screening of organic photocatalysts [10.1021/acscatal.2c02743] which uses in large part the same facilities at the Materials Innovation Factory (MIF) used in this project. He actively contributes to robotics and chemistry automation [10.1038/s41586‑024‑08173‑7; 10.26434/chemrxiv‑2025‑bsfvz], ensuring the automated optical-characterisation component is developed with direct relevance to high-impact, industrially-relevant synthetic targets.
This project is expected to start in October 2026 and is offered under the EPSRC Centre for Doctoral Training in Digital and Automated Materials Chemistry based in the Materials Innovation Factory at the University of Liverpool, the largest industry-academia colocation in UK physical science. The successful candidate will benefit from training in robotic, digital, chemical and physical thinking, which they will apply in their domain-specific research in materials design, discovery and processing. PhD training has been developed with 35 industrial partners and is designed to generate flexible, employable, enterprising researchers who can communicate across domains.