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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31 to 40 of 1,794 Results
md.log
Oct 31, 2023 - Replication Data for: Designing degradable polyethene with desirable physical properties via molecular dynamics simulation and machine learning
Plain Text - 26.4 KB - MD5: af96e80efcbb799fe1af6d7637107c21
md.mdp
Oct 31, 2023 - Replication Data for: Designing degradable polyethene with desirable physical properties via molecular dynamics simulation and machine learning
Unknown - 556 B - MD5: 2fb719c4b6b659267b6ed701b0fd013a
mdout.mdp
Oct 31, 2023 - Replication Data for: Designing degradable polyethene with desirable physical properties via molecular dynamics simulation and machine learning
Unknown - 11.9 KB - MD5: 9d36aac059957d69ab6ea88ac6f3175d
mdout.mdp
Oct 31, 2023 - Replication Data for: Designing degradable polyethene with desirable physical properties via molecular dynamics simulation and machine learning
Unknown - 11.9 KB - MD5: 60249784cd23b08f4e4b72ebb8a8a002
md.tpr
Oct 31, 2023 - Replication Data for: Designing degradable polyethene with desirable physical properties via molecular dynamics simulation and machine learning
Unknown - 9.7 MB - MD5: 96f42b615527d21fddb62e13a090cdec
md.xtc
Oct 31, 2023 - Replication Data for: Designing degradable polyethene with desirable physical properties via molecular dynamics simulation and machine learning
Unknown - 1.5 MB - MD5: 4361cfe192e8fdf17691c770cc411ffe
mix2.gro
Oct 31, 2023 - Replication Data for: Designing degradable polyethene with desirable physical properties via molecular dynamics simulation and machine learning
Unknown - 8.3 MB - MD5: aeef9b34a861b49db2e2b104750c2cde
mix_all.gro
Oct 31, 2023 - Replication Data for: Designing degradable polyethene with desirable physical properties via molecular dynamics simulation and machine learning
Unknown - 17.9 MB - MD5: f083981ad2d48bd21e3708c1ac0ee64c
mix.gro
Oct 31, 2023 - Replication Data for: Designing degradable polyethene with desirable physical properties via molecular dynamics simulation and machine learning
Unknown - 18.0 MB - MD5: 5b2946e865a1f7cfe0e2f0fab76c02a5
mix.gro
Oct 31, 2023 - Replication Data for: Designing degradable polyethene with desirable physical properties via molecular dynamics simulation and machine learning
Unknown - 6.7 MB - MD5: 64274028b7e0a0ec5a7820cd65b761a1
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