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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21 to 30 of 1,794 Results
em.log
Oct 31, 2023 - Replication Data for: Designing degradable polyethene with desirable physical properties via molecular dynamics simulation and machine learning
Plain Text - 325.8 KB - MD5: a57182f66d56cbfd4cc0b84d7480979c
em.log
Oct 31, 2023 - Replication Data for: Designing degradable polyethene with desirable physical properties via molecular dynamics simulation and machine learning
Plain Text - 6.3 MB - MD5: eef7cd5a880ba83169b31c96f7c49ea6
em.mdp
Oct 31, 2023 - Replication Data for: Designing degradable polyethene with desirable physical properties via molecular dynamics simulation and machine learning
Unknown - 1.0 KB - MD5: b237d1717d6b370c14eb51149740629a
em.mdp
Oct 31, 2023 - Replication Data for: Designing degradable polyethene with desirable physical properties via molecular dynamics simulation and machine learning
Unknown - 1.0 KB - MD5: b237d1717d6b370c14eb51149740629a
em.tpr
Oct 31, 2023 - Replication Data for: Designing degradable polyethene with desirable physical properties via molecular dynamics simulation and machine learning
Unknown - 169.3 KB - MD5: ac5da554c3e76482f1489ff748e600ed
em.tpr
Oct 31, 2023 - Replication Data for: Designing degradable polyethene with desirable physical properties via molecular dynamics simulation and machine learning
Unknown - 169.4 KB - MD5: be58b04119d7303ae01ab0fdc794acef
em.trr
Oct 31, 2023 - Replication Data for: Designing degradable polyethene with desirable physical properties via molecular dynamics simulation and machine learning
Unknown - 7.2 KB - MD5: a33cf881e51a52be81566c42180412fc
em.trr
Oct 31, 2023 - Replication Data for: Designing degradable polyethene with desirable physical properties via molecular dynamics simulation and machine learning
Unknown - 7.2 KB - MD5: c4a29be4b2581b0d687f4ece67943dbe
md.cpt
Oct 31, 2023 - Replication Data for: Designing degradable polyethene with desirable physical properties via molecular dynamics simulation and machine learning
application/mac-compactpro - 9.4 MB - MD5: fd6e96c6486f596f3ade7787cd9814a4
md.edr
Oct 31, 2023 - Replication Data for: Designing degradable polyethene with desirable physical properties via molecular dynamics simulation and machine learning
Unknown - 1.7 KB - MD5: 606991f5c671dac3e0a8b0dbaa1b5f03
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