STAFF PROFILE
Dr Tu Le
Position:
Senior Lecturer, Mechatronics
College / Portfolio:
STEM College
School / Department:
STEM|School of Engineering
Phone:
+61399252216
Email:
tu.le@rmit.edu.au
Campus:
City Campus
Contact me about:
Research supervision
- Huynh, H.,Kelly, T.,Vu, L.,Hoang, T.,Nguyen, P.,Le, T.,Jarvis, E.,Phan, H. (2023). Quantum Chemistry-Machine Learning Approach for Predicting Properties of Lewis Acid-Lewis Base Adducts In: ACS Omega, 8, 19119 - 19127
- Zhao, Y.,Houshyar, S.,Le, T. (2023). A review on the application of molecular descriptors and machine learning in polymer design In: Polymer Chemistry, 14, 3325 - 3346
- Mai, H.,Li, X.,Lu, J.,Wen, x.,Le, T.,Russo, S.,Chen, D.,Caruso, R. (2023). Synthesis of Layered Lead-Free Perovskite Nanocrystals with Precise Size and Shape Control and Their Photocatalytic Activity In: Journal of the American Chemical Society, 145, 17337 - 17350
- Irfan, M.,Zuraqi, K.,Nguyen, K.,Le, T.,Jabbar, F.,Ameen, M.,Parker, C.,Chiang, K.,Jones, L.,Elbourne, A.,McConville, C.,Yang, D.,Daeneke, T. (2023). Liquid metal-based catalysts for the electroreduction of carbon dioxide into solid carbon In: Journal of Materials Chemistry A, 11, 14990 - 14996
- Rahman, M.,Dip, T.,Haase, T.,Truong, Y.,Le, T.,Houshyar, S. (2023). Fabrication of Zein-Based Fibrous Scaffolds for Biomedical Applications—A Review In: Macromolecular Materials and Engineering, , 1 - 23
- Orhan, I.,Daglar, H.,Keskin, S.,Le, T.,Babarao, R. (2022). Prediction of O2/N2Selectivity in Metal-Organic Frameworks via High-Throughput Computational Screening and Machine Learning In: ACS Applied Materials and Interfaces, 14, 736 - 749
- Duong, D.,Tran, H.,Kadaoluwa Pathirannahalage, S.,Brown, S.,Hassett, M.,Yalcin, D.,Meftahi, N.,Christofferson, A.,Greaves, T.,Le, T. (2022). Machine Learning Investigation of Viscosity and Ionic Conductivity of Protic Ionic Liquids in Water Mixtures In: The Journal of Chemical Physics, 156, 1 - 17
- Mai, H.,Le, T.,Chen, D.,Winkler, D.,Caruso, R. (2022). Machine Learning for Electrocatalyst and Photocatalyst Design and Discovery In: Chemical Reviews, 122, 13478 - 13515
- Brown, S.,Yalcin, D.,Pandiancherri, S.,Le, T.,Orhan, I.,Hearn, K.,Han, Q.,Drummond, C.,Greaves, T. (2022). Characterising a protic ionic liquid library with applied machine learning algorithms In: Journal of Molecular Liquids, 367, 1 - 17
- Nele, V.,Holme, M.,Rashid, M.,Barriga, H.,Le, T.,Thomas, M.,Doutch, J.,Yarovsky, I.,Stevens, M. (2021). Design of Lipid-Based Nanocarriers via Cation Modulation of Ethanol-Interdigitated Lipid Membranes In: Langmuir, 37, 11909 - 11921
Materials science, machine learning, artificial neural networks, computational chemistry,
5 PhD Current Supervisions and 1 Masters by Research Current Supervisions
- Data-driven development of photocatalytic and optoelectronic perovskites. Funded by: ARC Discovery Projects commencing in 2022 from (2022 to 2025)
- Autonomous platform for remote aerosol-based threat neutralisation and soldier countermeasure therapeutics. Funded by: Defence Science Institute (DSI) Grant for Scholarships from (2018 to 2022)