Industrial Transformation Research Hubs - Grant ID: IH170100009
Funder
Australian Research Council
Funding Amount
$4,000,000.00
Summary
ARC Research Hub for Energy-efficient Separation. The ARC Research Hub for Energy-efficient Separation aims to develop advanced separation materials, innovative products and smart processes to reduce the energy consumption of separation processes. The Research Hub will create a multi-disciplinary training platform, supplying a highly-trained workforce for the advanced manufacturing sector, particularly in separation technology–a growth area in which Australia can lead the world. The advancement ....ARC Research Hub for Energy-efficient Separation. The ARC Research Hub for Energy-efficient Separation aims to develop advanced separation materials, innovative products and smart processes to reduce the energy consumption of separation processes. The Research Hub will create a multi-disciplinary training platform, supplying a highly-trained workforce for the advanced manufacturing sector, particularly in separation technology–a growth area in which Australia can lead the world. The advancement of Australia’s capability as a world-leading technology provider in manufacturing advanced separation materials and equipment will enable Australian industry to become more energy-efficient and cost-competitive in a global economy.Read moreRead less
Supercritical-microfluidics technology for targeted delivery to the colon. This research will develop nanosystems to target delivery of drugs to the colon. Our nanosystems will permit the combination of clinically used chemotherapy drugs within a single dosage form. This will improve the efficiency of delivery to the colon while reducing unwanted side-effects. A novel supercritical microfluidics system will be developed to produce therapeutic nano-carriers in a continuous mode with lower labour ....Supercritical-microfluidics technology for targeted delivery to the colon. This research will develop nanosystems to target delivery of drugs to the colon. Our nanosystems will permit the combination of clinically used chemotherapy drugs within a single dosage form. This will improve the efficiency of delivery to the colon while reducing unwanted side-effects. A novel supercritical microfluidics system will be developed to produce therapeutic nano-carriers in a continuous mode with lower labour requirement, higher production rate and better quality control than conventional production methods. The new process will combine benefits from both supercritical fluid technology (green process) and microfluidics (high mass & heat transfer).Read moreRead less
A System Behavioral Approach to Big Data-driven Nonlinear Process Control. This project aims to develop a novel process control approach that utilises big process data to improve the cost-effectiveness of industrial processes. Existing monitoring systems in the industry have been collecting a tremendous amount of process operation data but little effort has been made to use the big process data to enhance process operations. Based on the system behavioural approach and dissipativity theory, inte ....A System Behavioral Approach to Big Data-driven Nonlinear Process Control. This project aims to develop a novel process control approach that utilises big process data to improve the cost-effectiveness of industrial processes. Existing monitoring systems in the industry have been collecting a tremendous amount of process operation data but little effort has been made to use the big process data to enhance process operations. Based on the system behavioural approach and dissipativity theory, integrated with machine learning techniques, this project expects to develop a novel framework for data-driven control using big process data. The outcomes are expected to benefit the Australian process industry, where many processes are controlled by inadequate logic controllers, by improving their operational efficiency.Read moreRead less
Covalently immobilised molecular catalysts for carbon dioxide reduction. This project aims to develop innovative catalytic systems on semiconductor surfaces, to use sunlight for conversion of carbon dioxide (CO2) into high energy-content products. Sustainable chemical transformation of CO2 into valuable products, especially fuels, is one of the most important chemical processing challenges. This project will use innovative molecular engineering to covalently fix light-harvester to semiconductors ....Covalently immobilised molecular catalysts for carbon dioxide reduction. This project aims to develop innovative catalytic systems on semiconductor surfaces, to use sunlight for conversion of carbon dioxide (CO2) into high energy-content products. Sustainable chemical transformation of CO2 into valuable products, especially fuels, is one of the most important chemical processing challenges. This project will use innovative molecular engineering to covalently fix light-harvester to semiconductors. The expected outcome will be an efficient system to enhance CO2 conversion, which will not only reduce the environmental impact but also generate a cheap source of energy by closing the carbon loop. Using this approach, existing high carbon-emitting processes will be able to be replaced by new carbon-neutral or even carbon-negative ones for much-reduced environmental impact on our society.Read moreRead less
Data-based Control of Process Feature Dynamics through Latent Behaviours. This project aims to develop a novel data-based approach to control the feature dynamics of complex industrial processes. The dynamic features of desired process operations (leading to high energy and material efficiencies and good product quality) are often not directly measured but can be distilled from high-dimensional big process data. However, little effort has been made to develop process control approaches to achiev ....Data-based Control of Process Feature Dynamics through Latent Behaviours. This project aims to develop a novel data-based approach to control the feature dynamics of complex industrial processes. The dynamic features of desired process operations (leading to high energy and material efficiencies and good product quality) are often not directly measured but can be distilled from high-dimensional big process data. However, little effort has been made to develop process control approaches to achieve desired dynamic features. This project aims to develop such a data-based approach by controlling latent variable dynamics, using the behavioural systems framework integrated with big data analytics and artificial neural networks. The outcomes are expected to help build a cornerstone for future smart manufacturing.Read moreRead less