A data-centric approach to materials science requires access to large, high-quality datasets that are findable but also explorable, and whose connections to other datasets are identified. 

With this aim and in the spirit of the open science movement, Prof. Joao Quinta da Fonseca and Dr Christopher Daniel have been awarded funding under the competitive Royce Materials 4.0 Feasibility & Pilot Scheme, to develop a framework for organising large materials science databases. Having secured funding, they are now in the process of “pump-priming” a Royce database of high-quality microstructure data on hot formed Ti64, using microstructural data obtained in the TIFUN project, as part of LightForm. 

The TIFUN Ti64 data-set is made up of optical microscopy and electron backscatter diffraction (EBSD) data of samples produced in a recent, well-controlled hot-rolling study. This material is a Ti64 billet provided by TIMET for the TIFUN project, with agreements with TIMET and our other industrial partners to allow open sharing of this invaluable processing data. The rolling matrix is a rich data-set, at small temperature increments, covering the typical temperature range used in hot working of Ti alloys.

LightForm aims to demonstrate best practice in data management and sharing, which is vital in supporting future, scientifically reproducible, materials research. The data produced is being uploaded to the repository Zenodo, with full traceability to the physical samples and the original billet. We are creating an easy-to-use searchable database, using Ampletracks (a custom software for data organisation), and we are developing standardised metadata templates for optical microscopy, EBSD, and other forms of data.

Christopher Daniel, co-investigator on the proposal, and research associate with LightForm, said “this study is really going to lay the groundwork for open materials science data sharing, providing an easy-to-use platform for researchers in LightForm, and across the whole of the Royce network of UK universities. This will allow researchers to share their invaluable data with scientists in academia and industry, and we expect to see this database begin to grow exponentially from this point on.”

This data is only one of the initial outputs of the TIFUN project, which is due to finish in 2025. Over the next 3 years, it will be complemented by a variety of other rich, related datasets all using the same billet material, which will also be indexed using this Royce Materials 4.0 database. This includes further characterisation data such as mechanical flow data, data from in-situ synchrotron studies, spatially resolved acoustic spectroscopy (SRAS) texture measurements, and data from further processing studies. 

The database will also be supported by microstructural fingerprinting of Ti alloys, which is being developed by a PhD student at Manchester, Michael White, to enable data-intensive exploration of processing-microstructure-property relationships. This will enable our academic and industrial partners to index any Ti64 microstructure data-set, using unsupervised machine learning algorithms and data-based modelling.