Unlocking self-healing bio-concrete through multiscale modelling. Self-healing bio-concrete, which uses bacteria as means to repair cracks, has the potential to revolutionise the construction industry and reduce the infrastructure repair and maintenance cost by billions of dollars annually. To unlock this, we need to understand the bacterial self-healing mechanisms for effective control of the performance. This project will develop a multiscale framework to describe the competing mechanisms betw ....Unlocking self-healing bio-concrete through multiscale modelling. Self-healing bio-concrete, which uses bacteria as means to repair cracks, has the potential to revolutionise the construction industry and reduce the infrastructure repair and maintenance cost by billions of dollars annually. To unlock this, we need to understand the bacterial self-healing mechanisms for effective control of the performance. This project will develop a multiscale framework to describe the competing mechanisms between crack widening and healing at the macro-scale, incorporated with key information of substances diffusion and bio-cementation at the meso- and micro-scales. This will enable to optimise the self-healing of bio-concrete via design–test–learn approach and enhance the durability of structures under sustained loads.Read moreRead less
Modelling network innovation performance capability: a multidisciplinary approach. Innovation is created in complex network interactions.
By combining agent-based and fuzzy logic modelling, this project will identify combinations of resources to generate new ideas/technologies. This will enable managers and policy makers to understand the mechanisms behind innovation and implement policies aimed at enhancing innovation processes.
Exploiting natural variation to discover tools to increase crop plant yield. This project aims to identify the specific biochemical and underlying molecular modifications that contributed to the evolution of the C4 pathway by studying C3, C4 and C3-C4 intermediate Flaveria species. Most land plants use C3 or C4 photosynthesis to assimilate CO2. Plants using the C4 pathway evolved from C3 ancestors in multiple plant lineages, and show higher rates of photosynthesis and conversion of solar radiati ....Exploiting natural variation to discover tools to increase crop plant yield. This project aims to identify the specific biochemical and underlying molecular modifications that contributed to the evolution of the C4 pathway by studying C3, C4 and C3-C4 intermediate Flaveria species. Most land plants use C3 or C4 photosynthesis to assimilate CO2. Plants using the C4 pathway evolved from C3 ancestors in multiple plant lineages, and show higher rates of photosynthesis and conversion of solar radiation to biomass in arid, high-light and saline environments, which are expanding due to global climate change. The outcomes of this project could define what is required to engineer plant varieties with increased yield and the ability to withstand effects of climate shift, and contribute to our understanding of convergent evolutionary processes.Read moreRead less
Building insights of our largest terrestrial carbon sink: rangelands soils. Rangelands soils represent Australia’s largest carbon sink. Yet, little is known about their potential for carbon sequestration or their vulnerability to climate and environmental change. This project leverages investments in national terrestrial observation platforms and integrates previous research outputs to develop new methods to measure and build understanding of soil carbon composition and dynamics in rangeland eco ....Building insights of our largest terrestrial carbon sink: rangelands soils. Rangelands soils represent Australia’s largest carbon sink. Yet, little is known about their potential for carbon sequestration or their vulnerability to climate and environmental change. This project leverages investments in national terrestrial observation platforms and integrates previous research outputs to develop new methods to measure and build understanding of soil carbon composition and dynamics in rangeland ecosystems. Under a framework that connects detailed measurements and small-scale processes, with machine-learning, data-model assimilation and large-scale next-generation biogeochemical modelling, it’ll allow more accurate predictions of soil carbon change and better decision-making to guide sustainable rangelands management.Read moreRead less
Frequency standards with breakthrough performance: engineering immunity to local oscillator instabilities using dynamical error suppression. This project aims to dramatically advance state-of-the-art performance of one of the most important technological systems in modern electronics - precision frequency standards. Our work will provide orders of magnitude gains in performance by translating new knowledge from quantum information to the precision metrology research community.