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PhD Programs in Laboratory for Energy & Environmental Conservation (LEEC) at Monash University
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Principal Investigator: Dr. Baiqian Dai

www.monash.edu/engineering/leec        

Email: bai-qian.dai@monash.edu


1.Research on the application for the advanced catalysts synthesized from solid waste (2 PhD + 2 Masters)
This project aims to obtain advanced catalysts from variety of sold waste, such as coal fly ash, slag, which were landfill waste with environment issues. Through the directional extraction of specific metals from the solid waste to cations, with the impregnation of catalytic cations (Ni, Pd), selected chemistry synthesis, and structure modification, the crystallised nanosized catalysts will be obtained. The performance on the catalytic combustion for VOCs will be investigated for the obtained catalysts. Potential electrocatalysis for the obtained catalysts will be studied. Modelling approaches including the DTF to indicate the growth of the catalysts will be involved. The successful of the project will provide innovative approach from solid waste to high-valued catalyst in an environment friendly manner.
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2.Innovative approaches for sludge high temperature conversion (2 PhDs + 2 Masters)
This project aims to establish an efficient integrated process to produce building materials from sludge. The process simulation and energy analysis will be investigated for the integrated process, including the pretreatment, high-temperature conversion, the synergistic reactions for the ash-forming metals and inorganic compounds. The completion of this project aims to establish an economic process to minimize the sludge and transfer the waste to treasure.
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3.Research on the slag fluidity for low-rank fuels (1 PhDs +1 Masters)

The fluidity of the slag from low-rank fuels, including biomass, sludge and lignite determine the technologies to deal with these resources. This project aims clarify the fluidity, melting, sintering mechanisms to establish a proper method to quantify the slag fluidity. Data base for low-rank fuel slags will be established based on the experiment and image identification. Reliable model will be created for accurate prediction for slag viscosity.
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