Appointment: Associate Professor, School of Material Science & Engineering

Assistant Chair, Graduate Studies and Lifelong Learning

Research topics:

• developing high sensitive substrates for surface-enhanced Raman scattering and fluorescence

• optical properties of metal-semiconductor nanostructures

• assembly of metallic nanostructures

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11 to 20 of 21 Results
Project: Catalyst design principle in low temperature methane activation and conversion through machine learning(Nanyang Technological University)
Oct 10, 2023
data for project "Catalyst design principle in low temperature methane activation and conversion through machine learning"
Data for: Memristors as synapses for neuromorphic computing
Data for: Memristors as synapses for neuromorphic computing
May 13, 2022 - 2018-T1-002-092
Wang, Junling, 2021, "Data for: Memristors as synapses for neuromorphic computing", https://doi.org/10.21979/N9/TK1GDN, DR-NTU (Data), V2, UNF:6:izFLoS3mzigVzaqMjYYFCw== [fileUNF]
Research data from project "Memristors as synapses for neuromorphic computing"
Data for Single Site Biatomic Metal Catalysts for Electrochemical Oxygen Reduction
Mar 8, 2022 - Single Site Biatomic Metal Catalysts for Electrochemical Oxygen Reduction
Li, Shuzhou, 2021, "Data for Single Site Biatomic Metal Catalysts for Electrochemical Oxygen Reduction", https://doi.org/10.21979/N9/VU36DZ, DR-NTU (Data), V2
Unconventional Oxygen Reduction Reaction Mechanism and Scaling Relation on Single-Atom Catalysts
2018-T1-002-092 (Nanyang Technological University)
May 17, 2021
Single Site Biatomic Metal Catalysts for Electrochemical Oxygen Reduction(Nanyang Technological University)
Apr 15, 2021
Quantify Polyhedral Nanoparticle Orientation at Fluid/Fluid Interfaces(Nanyang Technological University)
Mar 23, 2021
Dataset from Quantify Polyhedral Nanoparticle Orientation at Fluid/Fluid Interfaces through Artificial Intelligence Project
Mar 22, 2021 - Quantify Polyhedral Nanoparticle Orientation at Fluid/Fluid Interfaces
Li, Shuzhou, 2021, "Dataset from Quantify Polyhedral Nanoparticle Orientation at Fluid/Fluid Interfaces through Artificial Intelligence Project", https://doi.org/10.21979/N9/9WIQMA, DR-NTU (Data), V1
Data from Quantify Polyhedral Nanoparticle Orientation at Fluid/Fluid Interfaces through Artificial Intelligence Project. Mainly Gromacs raw data.
Related Data for: Polymer/Graphene Composite With Ultrahigh Carrier Mobility
Jun 28, 2019 - charge carrier mobility
Hao, Wei, 2019, "Related Data for: Polymer/Graphene Composite With Ultrahigh Carrier Mobility", https://doi.org/10.21979/N9/H5EF7T, DR-NTU (Data), V1
This dataset contains the atomic models of Polymer/Graphene Composite and the related simulation results of the charge carrier mobility.
charge carrier mobility(Nanyang Technological University)
Jun 28, 2019Hao Wei
Screening Semiconductive Polymer/Graphene Composite With Ultrahigh Carrier Mobility
Replication Data for: Quantitative Prediction of Position and Orientation for Platonic Nanoparticles at Liquid/Liquid Interfaces
Jun 28, 2019 - nanoparticles superlattice
Shi Wenxiong, 2019, "Replication Data for: Quantitative Prediction of Position and Orientation for Platonic Nanoparticles at Liquid/Liquid Interfaces", https://doi.org/10.21979/N9/4OC5RI, DR-NTU (Data), V1
Because of their intrinsic geometric structure of vertices, edges, and facets, Platonic nanoparticles are promising materials in plasmonics and biosensing. Their position and orientation often play a crucial role in determining the resultant assembly structures at a liquid/liquid...
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