{"links":{"self":"http://dataportal.arc.gov.au/NCGP/API/grants/DE260100623"},"data":{"type":"grant-details","id":"DE260100623","attributes":{"code":"DE260100623","administering-organisation":"The University of Queensland","announcement-administering-organisation":"The University of Queensland","scheme-name":"Discovery Early Career Researcher Award","grant-status":"Active","funding-commencement-year":2026,"years-funded":3,"project-start-date":"2026-02-01","anticipated-end-date":"2029-01-31","grant-summary":"Enabling local property measurement out of equilibrium. Molecular dynamics simulations are widely used to understand and predict properties of systems that shape the modern world. However, in many cases, obtaining accurate results for real-world conditions is not computationally feasible with existing theory and methods due to limitations in how space and time locality is treated by nonequilibrium statistical mechanics. This project aims to address these shortcomings by using a novel approach to develop new theory and methods which improve our understanding of nonequilibrium systems and enable new, more efficient and more capable simulations. This is expected to provide benefits in the development of advanced functional materials, and more generally in characterisation of nonequilibrium systems.","funding-current":518000.00,"funding-at-announcement":514043,"investigators-current":[{"title":"Dr","firstName":"Stephen","familyName":"Sanderson","roleName":"Discovery Early Career Researcher Award","roleCode":"DECRA","isFellowship":true,"orcidIdentifier":"0000-0002-4097-0496 "}],"investigators-at-announcement":[{"title":"Dr","firstName":"Stephen","familyName":"Sanderson","roleName":"Discovery Early Career Researcher Award","roleCode":"DECRA","isFellowship":true,"orcidIdentifier":"0000-0002-4097-0496 "}],"organisations-current":[{"organisationName":"The University of Queensland","roleName":"Administering Organisation","state":"QLD"}],"organisations-at-announcement":[{"organisationName":"The University of Queensland","roleName":"Administering Organisation","state":"QLD"}],"field-of-research":[{"isPrimary":true,"code":"3407","name":"Theoretical and Computational Chemistry","type":"FOR20"},{"isPrimary":false,"code":"340703","name":"Statistical Mechanics In Chemistry","type":"FOR20"},{"isPrimary":false,"code":"490206","name":"Statistical Mechanics, Physical Combinatorics and Mathematical Aspects of Condensed Matter","type":"FOR20"},{"isPrimary":false,"code":"510304","name":"Thermodynamics and Statistical Physics","type":"FOR20"}],"socio-economic-objective":[{"code":"280118","name":"Expanding Knowledge In the Mathematical Sciences","type":"SEO20"},{"code":"280120","name":"Expanding Knowledge In the Physical Sciences","type":"SEO20"}],"international-collaboration":["Italy"],"lief-register":[],"achievement-summary":null,"national-interest-test-statement":"Advanced materials are ubiquitous in the modern world, from solar cells and batteries for renewable energy capture and storage to filtration devices for water purification. Computer simulations at scales on the order of 10 nanometres play a key role in developing these materials, enabling manufacturers to understand important operating mechanisms and predict the performance of new devices. With nano-scale features now common in modern devices, these materials exhibit complex behaviour when driven out of equilibrium, which can be difficult or impossible to study using existing theories and methods. By using an innovative combination of machine learning, a subset of AI for learning mathematical relations, and nonequilibrium statistical mechanics, used to model how systems respond when acted upon, this project aims to provide new and more efficient ways to characterise advanced materials, which will be made widely available through open-source software. In the future, the outcomes of this project could lead to breakthroughs in device capabilities by enabling cheaper and more efficient development of materials for applications such as green energy production and storage and advanced manufacturing. Such materials form the core of Australia’s green energy transition, hence this project has the potential to deliver significant environmental benefits, helping Australia achieve its net-zero target while also providing economic benefits through improved material development processes."}}}