Precision-engineered hybrid core-shell materials . This project aims to develop new platform technologies for making nanostructured hybrid core-shell materials with exceptionally high drug loading and programmed release. Building on this research team's recent breakthrough in the precision engineering of core-shell materials, this research will revolutionise current approaches for making drug-loaded polymer and inorganic particles. Significant outcomes will include a novel sequential nanoprecipi ....Precision-engineered hybrid core-shell materials . This project aims to develop new platform technologies for making nanostructured hybrid core-shell materials with exceptionally high drug loading and programmed release. Building on this research team's recent breakthrough in the precision engineering of core-shell materials, this research will revolutionise current approaches for making drug-loaded polymer and inorganic particles. Significant outcomes will include a novel sequential nanoprecipitation platform technology for making drug-core polymer-shell nanoparticles, and a new bio-inspired approach for making hybrid drug-core silica-shell nanocomposites, and new materials for applications in programmed release and delivery systems.Read moreRead less
Innovative Data Driven Techniques for Structural Condition Monitoring . Safe and sustainable infrastructure involves the development and application of structural monitoring and assessment techniques for condition evaluation. This project develops an innovative structure condition monitoring approach based on the emerging digital technologies on image processing, data analytics and machine learning techniques, for better infrastructure asset management under operational environment. Expected out ....Innovative Data Driven Techniques for Structural Condition Monitoring . Safe and sustainable infrastructure involves the development and application of structural monitoring and assessment techniques for condition evaluation. This project develops an innovative structure condition monitoring approach based on the emerging digital technologies on image processing, data analytics and machine learning techniques, for better infrastructure asset management under operational environment. Expected outcomes of this project enhance the capacity to conduct the operational monitoring and data interpretation to deliver the best life cycle performance of infrastructure. This project should provide significant benefits to Australia in infrastructure asset management by reducing the interruption of infrastructure operations.Read moreRead less
Australian Laureate Fellowships - Grant ID: FL190100014
Funder
Australian Research Council
Funding Amount
$2,871,982.00
Summary
New Technologies for Delivering Sustainable Free-form Architecture. This project aims to harness the full potential of digital technologies to significantly enhance the performance and reduce the environmental impact of free-form architecture of the future. The research expects to establish a fundamentally new computational platform capable of producing diverse and competitive designs, and an environmentally friendly manufacturing process for realising such designs. Expected outcomes include an ....New Technologies for Delivering Sustainable Free-form Architecture. This project aims to harness the full potential of digital technologies to significantly enhance the performance and reduce the environmental impact of free-form architecture of the future. The research expects to establish a fundamentally new computational platform capable of producing diverse and competitive designs, and an environmentally friendly manufacturing process for realising such designs. Expected outcomes include an unprecedented cloud-based interactive design tool, and a novel minimum-waste manufacturing technology for fabricating mass-customised building components. This project will transform the architecture, engineering and construction (AEC) sector and make the Australian manufacturing industry more competitive globally.Read moreRead less
AI Assisted Probabilistic Structural Health Monitoring with Uncertain Data. This project aims to develop an advanced Artificial Intelligence (AI) assisted probabilistic structural health monitoring approach for civil engineering structures. The developed approach applies novel deep learning techniques with a large amount of data measured from uncertain and complex environment, for reliable structural condition monitoring and performance prediction. This project expects to make a step change in d ....AI Assisted Probabilistic Structural Health Monitoring with Uncertain Data. This project aims to develop an advanced Artificial Intelligence (AI) assisted probabilistic structural health monitoring approach for civil engineering structures. The developed approach applies novel deep learning techniques with a large amount of data measured from uncertain and complex environment, for reliable structural condition monitoring and performance prediction. This project expects to make a step change in data mining and interpretation. Expected outcomes of the project include novel AI assisted approaches to conduct probabilistic structural condition monitoring with sensitive features and future structural performance prediction. This will provide significant benefits to infrastructure asset owners to reduce maintenance costs.Read moreRead less
Damage Detection and Quantification using Infrastructure Digital Twins. Structural health monitoring is vital for infrastructure assets management as early detection of structural conditions is key to both safety and ongoing maintenance. This project combines computer vision, vibration tests, finite element modelling and deep learning technologies to develop an efficient structural health monitoring system. Digital twins created from images taken by cameras or UAVs will be correlated through dee ....Damage Detection and Quantification using Infrastructure Digital Twins. Structural health monitoring is vital for infrastructure assets management as early detection of structural conditions is key to both safety and ongoing maintenance. This project combines computer vision, vibration tests, finite element modelling and deep learning technologies to develop an efficient structural health monitoring system. Digital twins created from images taken by cameras or UAVs will be correlated through deep learning with structural conditions and load-carrying capacities obtained from vibration tests and finite element model analysis for efficient structural damage detection and quantification. The project will lead to effective structural health monitoring and enhance structural safety and reduce maintenance costs. Read moreRead less
Next generation nondestructive inspection using guided-wave mixing. This project aims to develop a novel approach for early damage detection. It relies on a systematic experimental investigation of nonlinear ultrasonic interaction between different input wave modes in the presence of damage, so as to identify optimal mode selections and operating parameters that will maximise the sensitivity to particular forms of structural damage. The effects of in-service loading on wave-mixing response, and ....Next generation nondestructive inspection using guided-wave mixing. This project aims to develop a novel approach for early damage detection. It relies on a systematic experimental investigation of nonlinear ultrasonic interaction between different input wave modes in the presence of damage, so as to identify optimal mode selections and operating parameters that will maximise the sensitivity to particular forms of structural damage. The effects of in-service loading on wave-mixing response, and non-contact detection suitable for hard-to-inspect surface conditions, will also be investigated. The new developments will help transform existing schedule-based maintenance practice to a condition-based maintenance paradigm, to achieve significant cost savings in maintenance.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE200100119
Funder
Australian Research Council
Funding Amount
$424,607.00
Summary
Manipulation of non-wetting droplets for cell culture. We have recently discovered an innovative and interdisciplinary approach for manipulating non-wetting droplets called “liquid marbles” as a platform for three-dimensional cell culture. This project aims to elucidate the fundamental physics underpinning the electrostatic handling concept of this platform technology. The project is expected to deliver an inexpensive but sophisticated cell culture platform that is well-suited for high-throughpu ....Manipulation of non-wetting droplets for cell culture. We have recently discovered an innovative and interdisciplinary approach for manipulating non-wetting droplets called “liquid marbles” as a platform for three-dimensional cell culture. This project aims to elucidate the fundamental physics underpinning the electrostatic handling concept of this platform technology. The project is expected to deliver an inexpensive but sophisticated cell culture platform that is well-suited for high-throughput drug screening and preparing cells for implantation therapy. Significant benefits for end users in pharmaceutical industry, life sciences research and hospitals are expected from the project and the application of the developed technology.Read moreRead less
Mechanical modulation of particle-cell interactions. Mechanical forces play critical roles in many biological processes, but how particle mechanical properties modulate particle-cell interactions remains elusive. This project aims to develop new design principles for engineering nano/micromaterials with tunable mechanical properties for improved cell activation and expansion, and to advance knowledge of the role of particle stiffness in modulating receptor-mediated particle-cell interactions. Ex ....Mechanical modulation of particle-cell interactions. Mechanical forces play critical roles in many biological processes, but how particle mechanical properties modulate particle-cell interactions remains elusive. This project aims to develop new design principles for engineering nano/micromaterials with tunable mechanical properties for improved cell activation and expansion, and to advance knowledge of the role of particle stiffness in modulating receptor-mediated particle-cell interactions. Expected outcomes and benefits include new fundamental understanding of the effect of particle mechanical properties on cell function, new insights into T cell activation and expansion, and new classes of stiffness-tunable fit-for-purpose materials for various applications in cell manufacturing.Read moreRead less
Multi-hazard resilient hybrid modular structures. This project aims to develop the next generation of multi-hazard resilient modular construction methods for efficient, affordable and sustainable buildings. New demountable modular connections will be developed and the response of hybrid modular buildings to multiple hazards such as wind, earthquake, blast and impact will be investigated through a combination of experimental, numerical, and analytical studies. The project will develop knowledge o ....Multi-hazard resilient hybrid modular structures. This project aims to develop the next generation of multi-hazard resilient modular construction methods for efficient, affordable and sustainable buildings. New demountable modular connections will be developed and the response of hybrid modular buildings to multiple hazards such as wind, earthquake, blast and impact will be investigated through a combination of experimental, numerical, and analytical studies. The project will develop knowledge of the structural behaviour of hybrid modular buildings, and expects to deliver design methods and robust simplified models for building design purposes. This project will advance construction techniques and practices for resilient hybrid modular buildings.Read moreRead less
Non-invasive and safe human-machine interface (HMI) systems . This project aims to establish novel non-invasive human-machine interface systems based on multi-modal sensing and machine learning to intuitively command and control robotic and autonomous systems safely interacting and cooperating with humans. This will be achieved by harnessing the synergies across design optimisation, multi-modal sensing, additive manufacturing, machine learning, and assistive and cooperative robotic devices. Expe ....Non-invasive and safe human-machine interface (HMI) systems . This project aims to establish novel non-invasive human-machine interface systems based on multi-modal sensing and machine learning to intuitively command and control robotic and autonomous systems safely interacting and cooperating with humans. This will be achieved by harnessing the synergies across design optimisation, multi-modal sensing, additive manufacturing, machine learning, and assistive and cooperative robotic devices. Expected outcomes are a novel human-machine interface methodology, a new multi-purpose wearable data glove, and function and application-specific machine learning methods for cutting-edge applications in assistive robotic devices such as a prosthetic hand, advanced manufacturing, construction and agriculture.Read moreRead less