35MECHANICAL ENGINEERING
Thermal Management of Microelectronics Systems to Improve Energy Efficiency and Lifespan
Dr Hung , Yew Mun Professor PhD
Research expertise : Electronics Cooling , Microscale Heat Transfer , Interfacial Phenomena , Graphene Nanostructures , Ultrafast Water Permeation .
E : hung . yew . mun @ monash . edu T : + 603 5514 6251
This study aims to investigate the effective phase-change heat transfer achieved via surface functionalization using graphene coatings such as graphene nanoplatelets and carbon nanotubes . The fast water transport confined in the nanocapillaries formed between graphene sheets is attributed to the frictionless interaction between the atomically smooth , hydrophobic carbon wall and the well-ordered hydrogen bonds of water molecules . For the sake of achieving high evaporation rate , high surface temperature , large surface area , and low intermolecular strength of molecules are favourable conditions . The graphene coatings on the heated surface provide nanocapillaries that distribute the liquid water over the coated surface by promoting filmwise evaporation , giving rise to a larger surface area for evaporation and facilitating a higher evaporation rate . With the application of graphene coatings , the hightemperature region is eliminated while maintaining the LED surface temperature for optimal operation . The development of graphene-assisted two-phase cooling devices manifests impact on efficiency and lifespan of microelectronics components and thus the nation ’ s economy .
Significant temperature reduction of LED due to graphene coatings
Enhancement of phase-change heat transfer attributed to the ultrafast water permeation property of carbon nanostructures
High Resolution Single Pixel Imaging based on Compressive Sensing and Deep Learning
Single-pixel imaging ( SPI ) is an advanced imaging approach that is applicable to acquiring spatial information in low light , high absorption , and backscattering conditions , such as in medical and remote 3D imaging . The combination of SPI and compressive sensing ( CS ) has enabled image reconstruction with fewer measurements . This is an important consideration in light detection and ranging ( LIDAR ) applications . In this study , a novel single-pixel imaging reconstruction model based on deep learning and compressive sensing will be developed . This will be useful in the development of low cost LIDAR systems , which is a key technology used for guidance and navigation in autonomous robots . This
research is in conjunction with the principle of bringing Industry 4.0 technologies related to automation and robotics to the manufacturing sector .
35MECHANICAL ENGINEERING
Dr Wang , Xin Associate Professor PhD
Research expertise : Optical Metrology , Range Sensing , Non-destructive Testing , Machine Vision and Deep Learning
E : wang . xin @ monash . edu
T : + 603 5514 4627 Schematic diagram of our single-pixel imaging setup
Overview of the proposed method
RESEARCHER PROFILE 2025 / 2026