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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81 to 90 of 1,773 Results
pr_all.xtc
Oct 31, 2023 - Replication Data for: Designing degradable polyethene with desirable physical properties via molecular dynamics simulation and machine learning
Unknown - 1.4 GB - MD5: 13fd6b3dd379b02fe9e9b4b1c3c05809
pr_all.xtc
Oct 31, 2023 - Replication Data for: Designing degradable polyethene with desirable physical properties via molecular dynamics simulation and machine learning
Unknown - 304.5 MB - MD5: f675842cee3337b53e08da2b541df9d5
pr.cpt
Oct 31, 2023 - Replication Data for: Designing degradable polyethene with desirable physical properties via molecular dynamics simulation and machine learning
application/mac-compactpro - 15.7 KB - MD5: 26d483e8a711197fcc1e889dc74026b9
pr.cpt
Oct 31, 2023 - Replication Data for: Designing degradable polyethene with desirable physical properties via molecular dynamics simulation and machine learning
application/mac-compactpro - 15.7 KB - MD5: 80ac06558f5b34ee218b9578e77853bc
pr.edr
Oct 31, 2023 - Replication Data for: Designing degradable polyethene with desirable physical properties via molecular dynamics simulation and machine learning
Unknown - 212.1 KB - MD5: b73a6cd95b680d5899c9e4d827659860
pr.edr
Oct 31, 2023 - Replication Data for: Designing degradable polyethene with desirable physical properties via molecular dynamics simulation and machine learning
Unknown - 207.4 KB - MD5: 43a765fd67164dc79ce318a71f74e7d3
pr.gro
Oct 31, 2023 - Replication Data for: Designing degradable polyethene with desirable physical properties via molecular dynamics simulation and machine learning
Unknown - 41.1 KB - MD5: c14cf0f01bcea442bb20f5acca8e1402
pr.gro
Oct 31, 2023 - Replication Data for: Designing degradable polyethene with desirable physical properties via molecular dynamics simulation and machine learning
Unknown - 41.2 KB - MD5: cec41368348a7f8e1c52aadd1caf6806
pr.log
Oct 31, 2023 - Replication Data for: Designing degradable polyethene with desirable physical properties via molecular dynamics simulation and machine learning
Plain Text - 275.3 KB - MD5: 6b1fd09d952a1bf1cf4aee4fc5fb1cf7
pr.log
Oct 31, 2023 - Replication Data for: Designing degradable polyethene with desirable physical properties via molecular dynamics simulation and machine learning
Plain Text - 263.2 KB - MD5: 0d7d180912ae945f7e81f9e7980b8fdf
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