Industrial Transformation Research Hubs - Grant ID: IH230100005
Funder
Australian Research Council
Funding Amount
$5,000,000.00
Summary
ARC Research Hub in Zero-emission Power Generation for Carbon Neutrality. This Hub aims to develop sustainable zero-emission power generation technologies to transform gaseous waste (mainly CO2) from our energy and manufacturing sectors into valuable products and create scalable pathways to market for driving industry transformation. This Hub expects to harvest renewable energy from the environment by using zero-emission power generators and then store it in green and safer batteries for convert ....ARC Research Hub in Zero-emission Power Generation for Carbon Neutrality. This Hub aims to develop sustainable zero-emission power generation technologies to transform gaseous waste (mainly CO2) from our energy and manufacturing sectors into valuable products and create scalable pathways to market for driving industry transformation. This Hub expects to harvest renewable energy from the environment by using zero-emission power generators and then store it in green and safer batteries for converting gaseous waste from sectors that cannot easily avoid emission into useful chemicals, which in turn realize carbon neutrality and negativity. The outcomes of this Hub are likely to be transformative for industry, the economy, and society in new-type renewable energy resources through decreasing environmental pollutants. Read moreRead less
Industrial Transformation Research Hubs - Grant ID: IH200100035
Funder
Australian Research Council
Funding Amount
$5,000,000.00
Summary
ARC Research Hub in New Safe and Reliable Energy Storage and Conversion Technologies. This Research Hub addresses safety and reliability issues, and environmental impact of current energy storage and conversion technologies. The research will deliver a new generation of technologies for storage from small scale portable devices to large scale industrial applications, using recycled and natural materials, and eliminating the serious fire risk in current technologies. Outcomes include innovative ....ARC Research Hub in New Safe and Reliable Energy Storage and Conversion Technologies. This Research Hub addresses safety and reliability issues, and environmental impact of current energy storage and conversion technologies. The research will deliver a new generation of technologies for storage from small scale portable devices to large scale industrial applications, using recycled and natural materials, and eliminating the serious fire risk in current technologies. Outcomes include innovative integrated energy conversion and storage technologies and new energy materials and devices designed for different scale applications, leading to creation of start up companies and commercialisation opportunities for existing partners, benefiting both the Australian economy and potentially transforming the energy industry landscape.Read moreRead less
Solar-thermal desalination system for parallel water-electricity generation. This project aims to develop a multi-functional solar-thermal desalination device to simultaneously produce clean water and electricity. Interfacial solar evaporation-based desalination technology has the unique advantage of using solar light as the sole energy source for affordable clean water production. However, its absolute evaporation rate is still too low for practical application and all of the latent heat releas ....Solar-thermal desalination system for parallel water-electricity generation. This project aims to develop a multi-functional solar-thermal desalination device to simultaneously produce clean water and electricity. Interfacial solar evaporation-based desalination technology has the unique advantage of using solar light as the sole energy source for affordable clean water production. However, its absolute evaporation rate is still too low for practical application and all of the latent heat released from vapor condensation during desalination is wasted. Solving these two critical issues by the study of energy nexus, design and fabrication of advanced photothermal materials and desalination devices could accelerate practical adoption of this technology and benefit millions of people who desperately need clean water. Read moreRead less
Legal and social dynamics of eBook lending in Australia’s public libraries. Legal and social dynamics of eBook lending in Australia’s public libraries. This project aims to develop an evidence base of quantitative and qualitative data about how eBooks are used in libraries. EBooks have tremendous beneficial potential, particularly for Australians in remote areas and those with impaired mobility or vision. However, libraries’ rights to acquire and lend them are more restricted than for physical b ....Legal and social dynamics of eBook lending in Australia’s public libraries. Legal and social dynamics of eBook lending in Australia’s public libraries. This project aims to develop an evidence base of quantitative and qualitative data about how eBooks are used in libraries. EBooks have tremendous beneficial potential, particularly for Australians in remote areas and those with impaired mobility or vision. However, libraries’ rights to acquire and lend them are more restricted than for physical books. Libraries and legal, social and data science researchers will investigate eBook lending practices and understand their social impacts. The project will identify ways of reforming policy, law, and practice to help libraries fulfil their public interest missions. This project is expected to enable libraries to extract more value from existing public investments.Read moreRead less
Blue energy harvesting and storage technology for wearable electronics. This project aims to develop new self-charging power devices that can harvest and store body energy generated during body motions, and power smart and implantable medical electronics. The project will develop new Piezo-supercapacitors by designing new electrode materials and cell designs. The charge storage and transport kinetics will be uncovered using advanced in-situ characterisation techniques and modern simulation metho ....Blue energy harvesting and storage technology for wearable electronics. This project aims to develop new self-charging power devices that can harvest and store body energy generated during body motions, and power smart and implantable medical electronics. The project will develop new Piezo-supercapacitors by designing new electrode materials and cell designs. The charge storage and transport kinetics will be uncovered using advanced in-situ characterisation techniques and modern simulation methods. The project expects to generate new knowledge in blue energy harvesting and storage systems, training for young scientists, and generate intellectual property with potential commercialised products to be used in implantable devices, placing Australia at the forefront of new technology.Read moreRead less
Linkage Infrastructure, Equipment And Facilities - Grant ID: LE210100153
Funder
Australian Research Council
Funding Amount
$497,264.00
Summary
Integrated In situ Characterisation Facilities for Energy Studies. This project aims to establish a new capability to reveal catalytic behaviour of materials under practical working conditions at multi-scale levels. Through in situ monitoring of surface, interface and structural properties of catalysts, this unique integrated facility will overcome current limitations due to a lack of understanding of reaction mechanism, by ex situ and/or individual in situ characterisations. This world-class fa ....Integrated In situ Characterisation Facilities for Energy Studies. This project aims to establish a new capability to reveal catalytic behaviour of materials under practical working conditions at multi-scale levels. Through in situ monitoring of surface, interface and structural properties of catalysts, this unique integrated facility will overcome current limitations due to a lack of understanding of reaction mechanism, by ex situ and/or individual in situ characterisations. This world-class facility will significantly advance a range of electrocatalysis, photocatalysis and battery applications for renewable energy-storage and clean-fuel generation. This will be Australia’s only platform; it will benefit a number of innovative research projects in energy, catalysis and environmental and materials science.Read moreRead less
Learning human activities through low cost, unobtrusive RFID technology. A rapidly growing aged population presents many challenges to Australia's health and aged care services. The outcomes of this project will help aging Australians live in their own homes longer, with greater independence and safety by providing an automated, unobtrusive means for health professionals to monitor activity and intervene as required.
Linkage Infrastructure, Equipment And Facilities - Grant ID: LE160100090
Funder
Australian Research Council
Funding Amount
$250,000.00
Summary
Computational infrastructure for developing deep machine learning models. Computational infrastructure for developing deep machine learning models:
The computational infrastructure for developing deep machine learning models aims to enable new developments in machine learning of deep neural network models by providing the specialised computing necessary to train and evaluate the networks. In the last three years, deep networks have smashed previous performance ceilings for tasks such as object ....Computational infrastructure for developing deep machine learning models. Computational infrastructure for developing deep machine learning models:
The computational infrastructure for developing deep machine learning models aims to enable new developments in machine learning of deep neural network models by providing the specialised computing necessary to train and evaluate the networks. In the last three years, deep networks have smashed previous performance ceilings for tasks such as object recognition in images, speech recognition and automatic translation, bringing the prospect of machine intelligence closer than ever. Modern machine learning techniques have had huge impact in the last decade in fields such as robotics, computer vision and data analytics. The facility would enable Australian researchers to develop, learn and apply deep networks to problems of national importance in robotic vision and big data analytics. Read moreRead less
Sewer Monitoring and Management in the Digital Era. Overflow, flooding, corrosion, and odorous emissions are persistent issues for utilities managing sewers. Current sewer maintenance is reactive, and focuses on solving problems in local networks, despite that optimal solutions require a system-wide approach. Capitalising on recent development in IoT sensors, wireless transmission, and machine learning, this multidisciplinary project aims to develop digital-twin supported data analytics for proa ....Sewer Monitoring and Management in the Digital Era. Overflow, flooding, corrosion, and odorous emissions are persistent issues for utilities managing sewers. Current sewer maintenance is reactive, and focuses on solving problems in local networks, despite that optimal solutions require a system-wide approach. Capitalising on recent development in IoT sensors, wireless transmission, and machine learning, this multidisciplinary project aims to develop digital-twin supported data analytics for proactive sewer management including network-wide real-time control. The project aims to generate significant social, environmental and economic benefits by enabling utilities to better protect public and environmental health, reduce sewer odour and greenhouse gas emissions, and extend sewer asset life.Read moreRead less
Automated analysis of multi-modal medical data using deep belief networks. This project will develop an improved breast cancer computer-aided diagnosis (CAD) system that incorporates mammography, ultrasound and magnetic resonance imaging. This system will be based on recently developed deep learning techniques, which have the capacity to process multi-modal data in a unified and optimal manner. The advantage of this technique is that it is able to automatically learn both the relevant features t ....Automated analysis of multi-modal medical data using deep belief networks. This project will develop an improved breast cancer computer-aided diagnosis (CAD) system that incorporates mammography, ultrasound and magnetic resonance imaging. This system will be based on recently developed deep learning techniques, which have the capacity to process multi-modal data in a unified and optimal manner. The advantage of this technique is that it is able to automatically learn both the relevant features to analyse in each modality and the hidden relationships between them. The use of deep belief networks has produced promising results in several fields, such as speech recognition, and so this project believes that our approach has the potential to improve both the sensitivity and specificity of breast cancer detection.Read moreRead less