EPSRC and SFI Centre for Doctoral Training in the Advanced Characterisation of Materials (CDT-ACM)

材料表征对于理解在多个工业部门应用的一系列功能和结构材料的关键过程至关重要。这些部门包括战略重点，如功能材料的发现，能源储存和转换以及材料制造和医疗保健。材料表征的复杂性越来越高，这是由于需要了解材料属性在操作中如何演变，在其整个生命周期和其层次结构的所有级别上，以预测其最终性能。新一代的材料表征技术将需要：1。更高的空间和化学分辨率; 2.连接纳米和厘米长度尺度的相关信息，将感兴趣的纳米级化学和结构与其固有的多尺度环境联系起来，以及3。关于极端环境中材料行为动力学的时间信息。CDT将培训学生一系列的补充技术，确保他们有知识的广度和深度，在考虑关键的表征挑战时做出明智的选择。我们的CDT将采用综合培训方法，以确保技术内容与每个学生的研究目标保持一致。这种特定研究需求的培训将由我们的行业合作伙伴告知，并将反映学生将承担的研究项目套件。我们的研究项目组合将提供创新和雄心勃勃的研究和培训经验，这将提高英国在高价值工业领域的长期能力。此外，我们的学生将接受一系列主题的培训，以支持他们的研究进展，包括科学传播，研究伦理，职业发展规划和数据科学。这些额外的课程将分布在整个4年的博士课程，并将确保在队列导师的支持下，为每个学生制定一个有凝聚力的培训计划。从CDT-ACM毕业的每个学生都将通过材料表征问题所带来的关键挑战的理解，并拥有为这些问题提供创造性解决方案的工具。他们将拥有与行业合作伙伴合作的第一手经验，并将很好地满足英国工业战略的战略需求。我们的培训将与领先的合作伙伴组织合作开发，包括与AMBER中心，科学基金会爱尔兰中心以及国家设施如钻石光源的国际合作。创新的在线和远程仪器访问将开发，这将使英国和爱尔兰的队列无缝互动。行业合作伙伴将密切参与设计和提供培训活动，包括暑期学校，并将包括创业活动。在CDT的整个生命周期中，将有70名学生接受培训，他们将在两个世界领先的机构接受出色的学费和研究培训，具有独特的特色能力。

Materials characterisation is critical to the understanding of key processes in a range of functional and structural materials that have applications across several industrial sectors. These sectors include strategic priorities such as discovery of functional materials, energy storage and conversion and materials manufacturing, and healthcare. Materials characterisation is increasing in complexity, driven by a need to understand how materials properties evolve in operando, over their full lifetimes and over all levels of their hierarchy to predict their ultimate performance. The new generation of materials characterisation techniques will require: 1. Greater spatial and chemical resolution; 2. Correlated information that bridges nano- and centimeter -length scales, to relate the nanoscale chemistry and structure of interest to their intrinsically multi-scale surroundings, and 3. Temporal information about the kinetics of materials behaviour in extreme environments. The CDT will train students in a range of complementary techniques, ensuring that they have the breadth and depth of knowledge to make informed choices when considering key characterisation challenges. Our CDT will use an integrated training approach, to ensure that the technical content is well aligned with the research objectives of each student. This training in specific research needs will be informed by our industry partners and will reflect the suite of research projects that the students will undertake. Our portfolio of research projects will provide an innovative and ambitious research and training experience that will enhance the UK's long-term capabilities across high value industrial sectors.Additionally, our students will receive training in a range of topics that will support their research progress including in science communication, research ethics, career development planning and data science. These additional courses will be distributed throughout the 4-year PhD programme and will ensure that a cohesive training plan is in place for each student, supported by cohort mentors. Each student graduating from the CDT-ACM will leave will a through understanding of the key challenges presented by materials characterisation problems, and have the tools to provide creative solutions to these. They will have first hand experience of collaborating with industry partners and will be well placed to address the strategic needs of the UK Industrial Strategy.Our training will be developed in collaboration with leading partner organisations, and include international collaboration with the AMBER centre, a Science Foundation Ireland centre, as well as national facilities such as Diamond Light Source. Innovative on-line and remote instrument access will be developed that will enable both UK and Irish cohorts to interact seamlessly. Industry partners will be closely involved in designing and delivering training activities including at summer schools, and will include entrepreneurship activities.Overall the 70 students that will be trained over the lifetime of the CDT will receive excellent tuition and research training at two world leading institutions with unique characterisation abilities.