Developing a new material currently takes up to 20 years—a pace far too slow for challenges like net-zero goals and fully recyclable products. This Centre for Doctoral Training aims to slash that timeline by training at least 70 PhD students in "Materials 4.0," which combines computer simulation, robotics, machine learning, and high-throughput testing to design and test materials faster. The problem is that most science and engineering graduates lack the digital skills—data informatics, advanced simulation, machine learning—needed for this approach. The CDT will fill that gap by producing a cohort of leaders who can bridge materials science and data science, working across universities in Cambridge, Oxford, Imperial, Manchester, Sheffield, Leeds, and Strathclyde. If successful, this could transform how quickly new materials reach industry—from lighter aircraft components to more efficient battery materials and fully recyclable packaging. The training programme will also be disseminated to existing researchers in universities and companies, accelerating a cultural shift in how the UK develops the physical substances that underpin everything from electronics to infrastructure.
View original technical description
The job of materials science is to develop the materials that we need to make all of the things that we rely on in our daily lives. These range from the materials used to make large scale objects, such as aeroplanes and buildings, right down to the smallest scales like the processors in the electronic devices we use every day. These materials are often complicated and need to be carefully designed with just the right properties needed to do their jobs for many decades and often in incredibly harsh conditions. There are many current challenges that require us to develop new, improved materials. We need to meet our net-zero climate goals and get better at designing products that can be fully recycled, for example. And there are some resources that we currently use in important materials for which we would like to find alternatives. These are difficult challenges and we need to overcome them quickly. But the way that materials scientists have worked to develop a new material in the past is too slow: it can take up to 20 years to develop a new material and we cannot wait that long. Fortunately, recent developments in the computer simulation of materials, in robotics and sensor technology, in our ability to exploit large volumes of data through machine learning and in techniques for quickly making and testing large numbers of different materials can help to speed things up. This idea, bringing digital technologies together to help us make better materials more quickly, is called "Materials 4.0". If we are going to take advantage of Materials 4.0 then we need to make sure that materials scientists have the necessary digital skills. These skills, things like data informatics, machine learning and advanced computer simulation, are not usually covered in depth in undergraduate university courses in science and engineering. So, the Henry Royce Institute, the UK's national institute for advanced materials, in partnership with the National Physical Laboratory, is proposing to set up a Centre for Doctoral Training (CDT) that will take at least 70 science and engineering graduates and train them in the techniques of Materials 4.0. These students will work towards PhDs and become leaders in the field of Materials 4.0. They will undertake research projects in universities across the UK (Cambridge, Oxford, Imperial College, Manchester, Sheffield, Leeds and Strathclyde), tackling a broad range of materials science challenges and developing new approaches in Materials 4.0. The need for these new approaches is widespread, throughout academia and in industry. In recognition of this, the training programme that we develop for the CDT will be made available more widely, in different forms, so that we can disseminate skills in Materials 4.0 to existing researchers in universities and industrial companies as quickly as possible. The training approach of the CDT will be to take our students from "Learners to Leaders" over the course of four years. Our students will be working across boundaries between materials science and computer / data science and between academia and industry. They will build new interfaces and help to develop a common language for communication. To strengthen our students' own learning and to disseminate their skills more widely, we will train our students as trainers so that the students are actively involved in designing and delivering training for fellow researchers and take the role of ambassadors for a cultural shift in materials science to modern ways of working.
Plain English summaries and category classifications on this site are generated by AI and may not perfectly reflect the original research.
Is something wrong? Let us know