Industrial Transformation Research Hubs - Grant ID: IH230100006
Funder
Australian Research Council
Funding Amount
$4,933,330.00
Summary
ARC Research Hub for Engineering Plants to Replace Fossil Carbon . This Hub aims to develop new plant varieties that enable sustainable production of sugars from crop ‘waste’ (plant biomass) as a base for renewable carbon products. Only now possible through emerging technologies, the Hub expects to translate extensive foundational research and world-leading expertise into cost-effective sustainable aviation fuel. Anticipated outcomes include diversified cropping opportunities for agricultural pr ....ARC Research Hub for Engineering Plants to Replace Fossil Carbon . This Hub aims to develop new plant varieties that enable sustainable production of sugars from crop ‘waste’ (plant biomass) as a base for renewable carbon products. Only now possible through emerging technologies, the Hub expects to translate extensive foundational research and world-leading expertise into cost-effective sustainable aviation fuel. Anticipated outcomes include diversified cropping opportunities for agricultural producers and new industries to convert the biomass to high-volume renewable products. The expected benefits include a decarbonised pathway for Australia’s critical flight, freight and defence connections to world and the substantial economic returns and job creation from new manufacturing capacity in Australia.Read moreRead less
A unifying model for ion exchange membranes – towards a low carbon future. Polymeric ion exchange membranes are key to emerging renewable energy systems and bioprocessing applications. Advances in this field are currently impeded by a focus on their performance in idealised pure solutions and siloed research. This project aims to draw together fundamental and applied research to develop an innovative, unifying model for the transport of both charged ions and uncharged molecules through these mem ....A unifying model for ion exchange membranes – towards a low carbon future. Polymeric ion exchange membranes are key to emerging renewable energy systems and bioprocessing applications. Advances in this field are currently impeded by a focus on their performance in idealised pure solutions and siloed research. This project aims to draw together fundamental and applied research to develop an innovative, unifying model for the transport of both charged ions and uncharged molecules through these membranes within complex, multicomponent mixtures. The team will build on strong collaborations to drive uptake of the new model within the clean energy and CO2 reduction sectors to advance the abatement of Australian emissions; and will prepare young researchers for a role within these emerging fields.Read moreRead less
Nanoengineered, Encapsulated Catalysts from Fly Ash Waste. This project aims to deliver advanced catalysts and novel catalyst synthesis methods from the use of iron-rich fly ash, an otherwise abundant valueless waste with projected steady growth across Australia and globally. The as-synthesised catalysts are expected to be applicable to and exhibit excellent activity in the production of green hydrogen and renewable bio-fuels from lignocellulosic waste. These efforts are significant and benefici ....Nanoengineered, Encapsulated Catalysts from Fly Ash Waste. This project aims to deliver advanced catalysts and novel catalyst synthesis methods from the use of iron-rich fly ash, an otherwise abundant valueless waste with projected steady growth across Australia and globally. The as-synthesised catalysts are expected to be applicable to and exhibit excellent activity in the production of green hydrogen and renewable bio-fuels from lignocellulosic waste. These efforts are significant and beneficial in restoring the manufacturing capability of Australian industry, driving Australian industry towards the development of a circular economy for the appropriate management of solid waste, as well as for a seamless introduction of renewable and clean energy sources to address the pressing climate change.Read moreRead less
Industrial Transformation Training Centres - Grant ID: IC210100023
Funder
Australian Research Council
Funding Amount
$4,943,949.00
Summary
ARC Training Centre in Bioplastics and Biocomposites. There is unprecedented growth in demand for bioderived and biodegradable materials. This Training Centre in Bioplastics and Biocomposites will capitalise on Australia’s abundance of the requisite natural bioresources to drive advances in technology for the development of bioplastic and biocomposite products for the new bioeconomy. The aim is to deliver leading edge research with a holistic focus on technical, social, policy and end of life so ....ARC Training Centre in Bioplastics and Biocomposites. There is unprecedented growth in demand for bioderived and biodegradable materials. This Training Centre in Bioplastics and Biocomposites will capitalise on Australia’s abundance of the requisite natural bioresources to drive advances in technology for the development of bioplastic and biocomposite products for the new bioeconomy. The aim is to deliver leading edge research with a holistic focus on technical, social, policy and end of life solutions, training a cohort of industry ready research specialists to underpin Australia’s transition to a globally significant bioplastics and biocomposites industry, while at the same time laying the foundations for accelerated growth in this space.Read moreRead less
Fairness in Natural Language Processing. Natural language processing (NLP) has achieved spectacular commercial successes in recent years, and has been deployed across an ever-increasing breadth of devices and application areas. At the same time, there has been stark evidence to indicate that naively-trained models amplify biases in training data, and perform inconsistently across text relating to different demographic groupings of individuals. This project aims to systematically quantify the ext ....Fairness in Natural Language Processing. Natural language processing (NLP) has achieved spectacular commercial successes in recent years, and has been deployed across an ever-increasing breadth of devices and application areas. At the same time, there has been stark evidence to indicate that naively-trained models amplify biases in training data, and perform inconsistently across text relating to different demographic groupings of individuals. This project aims to systematically quantify the extent of such biases, and develop models that are both more socially equitable, as well as less prone to expose private data in the learned representations. In doing so, it will make NLP more accessible to new populations of users, and remove socio-technological barriers to NLP uptake.Read moreRead less
In-situ catalytic upgrading of bio-oil using scrap tyre char. This project aims to develop advanced, cost-competitive catalysts based on scrap tyre char, an otherwise low-value by-product. These catalysts will be optimised for use in upgrading bio-oil derived from the pyrolysis of woody eucalyptus, an abundant biomass resource across Australia. The project is expected to promote the commercialisation of bio-oil production and enhance the valorisation of scrap tyre char. This is expected to reduc ....In-situ catalytic upgrading of bio-oil using scrap tyre char. This project aims to develop advanced, cost-competitive catalysts based on scrap tyre char, an otherwise low-value by-product. These catalysts will be optimised for use in upgrading bio-oil derived from the pyrolysis of woody eucalyptus, an abundant biomass resource across Australia. The project is expected to promote the commercialisation of bio-oil production and enhance the valorisation of scrap tyre char. This is expected to reduce the carbon footprint from Australian industry, and promote the recycling and reuse of waste scrap tyres.Read moreRead less
Multi-Modal Dictionary Learning for Smart City Operation and Management. This Project aims to provide new digital asset management tools for city councils to improve city services by utilising new sensing and automated learning technologies for recognising, tracking and auditing of assets. Currently, there are no digital tools available to handle these services. This project proposes new multi-modal sensing and mapping of city asset techniques by building new multi-modal dictionary learning proc ....Multi-Modal Dictionary Learning for Smart City Operation and Management. This Project aims to provide new digital asset management tools for city councils to improve city services by utilising new sensing and automated learning technologies for recognising, tracking and auditing of assets. Currently, there are no digital tools available to handle these services. This project proposes new multi-modal sensing and mapping of city asset techniques by building new multi-modal dictionary learning procedures. The new framework will recognise different conditions of city assets in real-time to make decisions. Expected outcomes of this Project include integration and easy access of assets with unique digital identities to help city councils, governments, and navigation services for real-time asset monitoring.Read moreRead less
Robust, valid and interpretable deep learning for quantitative imaging. One of the biggest challenges in employing artificial intelligence is the “black-box” nature of the models used. This project aims to improve the effectiveness and trustworthiness of deep learning within quantitative magnetic resonance imaging. Deep learning has great promise in speeding-up complex image processing tasks, but currently suffers from variable data inputs, predictions are not guaranteed to be plausible and it i ....Robust, valid and interpretable deep learning for quantitative imaging. One of the biggest challenges in employing artificial intelligence is the “black-box” nature of the models used. This project aims to improve the effectiveness and trustworthiness of deep learning within quantitative magnetic resonance imaging. Deep learning has great promise in speeding-up complex image processing tasks, but currently suffers from variable data inputs, predictions are not guaranteed to be plausible and it is not clear to the end user how reliable the results are. The outcomes intend to deliver advanced knowledge and capability in artificial intelligence and machine learning that Australia urgently needs to capitalise on bringing deep learning into practical applications delivering economic, commercial and social impact.Read moreRead less
Automated assessment of data quality in biological knowledge resources. This project aims to develop methods for identifying poor quality data in biological databases. Research in biomedicine is underpinned by massive databases of biological data. Data quality is largely managed through manual curation, but automated methods to assess quality are critically needed. This project expects to develop a suite of computational tools for assessing biological data quality, utilising an innovative approa ....Automated assessment of data quality in biological knowledge resources. This project aims to develop methods for identifying poor quality data in biological databases. Research in biomedicine is underpinned by massive databases of biological data. Data quality is largely managed through manual curation, but automated methods to assess quality are critically needed. This project expects to develop a suite of computational tools for assessing biological data quality, utilising an innovative approach based on network analysis of database record connectivity. These tools will enable quantifying data quality at scale. Researchers, evidence-based decision-makers in biomedicine, and the analytical or predictive tools that use this data will make more reliable inferences and decisions.Read moreRead less
Constraint-based Reasoning for Multi-agent Pathfinding. Automation is a transformative technology for logistics -- using robots to manipulate inventory allows warehouses to be more efficient, and larger-scale, than ever before. But doing this in practice requires efficient, reliable methods for coordinating ever-larger fleets of robots. These problems are extremely difficult, and current approaches either scale poorly or give weak or no guarantees on solution quality. The project will develop t ....Constraint-based Reasoning for Multi-agent Pathfinding. Automation is a transformative technology for logistics -- using robots to manipulate inventory allows warehouses to be more efficient, and larger-scale, than ever before. But doing this in practice requires efficient, reliable methods for coordinating ever-larger fleets of robots. These problems are extremely difficult, and current approaches either scale poorly or give weak or no guarantees on solution quality. The project will develop transformative approaches to multi-agent pathfinding which can handle industrial size problems, and handle all of the complications that arise in practical applications. This will deliver improved cost-effectiveness and productivity to automated warehouse logistics and other agent coordination problems.Read moreRead less