Discovery of Pb-free solders for use in the glass industry

About the project

About the Project The project, in collaboration with a major industrial partner, will develop state of the art machine learning models to help predict the melting point of Pb-free solder compositions that will then be synthesised for validation and other physical property testing. The legal requirement to remove Pb and other toxic elements from all products is essential for future sustainable chemistry. Although Pb-free solders do exist there is a need for new compositions with properties suitable for specific applications, especially in the glass-using industry. This project, in collaboration with a major industrial partner, will collate databases of alloy melting points to allow the development of state-of-the-art machine learning (ML) models to predict the melting point of new alloy compositions. The predicted melting points will then be validated by synthesising the compositions for measurement and testing. The ML model will then be expanded to include other important physical properties such as Young’s modulus and coefficient of thermal expansion. Dr Dyer is a computational chemist with expertise in modelling and predicting materials for sustainable and renewable energy applications using DFT and machine learning. Prof Rosseinsky leads a research group in the design, discovery, synthesis, and characterisation of solid-state materials that fuses digital tools with scientific insight to accelerate the design of new materials for applications spanning energy and information storage to catalysis. Dr Manning is a Senior Research Fellow with expertise in inorganic materials synthesis and characterisation. 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. If you have a disability you may be entitled to a Disabled Students’ Allowance on top of your studentship to help cover the costs of any additional support that a person studying for a doctorate might need as a result.

Research areas