School of Materials Science and Engineering (MSE)

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2,081 to 2,090 of 8,076 Results

Figure 1. Scheme.png Nov 14, 2023 - Dual-Conductive and Stiffness-Morphing Microneedle Patch Enables Continuous in Planta Monitoring of Electrophysiological Signal and Ion Fluctuation PNG Image - 12.3 MB - MD5: 9809f9167ffdc9834582ce222d7f5e38
Figure 2. Characterization.png Nov 14, 2023 - Dual-Conductive and Stiffness-Morphing Microneedle Patch Enables Continuous in Planta Monitoring of Electrophysiological Signal and Ion Fluctuation PNG Image - 10.2 MB - MD5: e1f2626eb642971fc874411057f4d670
Figure 3. In Planta Biopotential Monitoring.png Nov 14, 2023 - Dual-Conductive and Stiffness-Morphing Microneedle Patch Enables Continuous in Planta Monitoring of Electrophysiological Signal and Ion Fluctuation PNG Image - 9.6 MB - MD5: bd1d9f357edfd8c880c1b0c68b13208c
Figure 4. Cation Fluctuation Monitoring.png Nov 14, 2023 - Dual-Conductive and Stiffness-Morphing Microneedle Patch Enables Continuous in Planta Monitoring of Electrophysiological Signal and Ion Fluctuation PNG Image - 391.5 KB - MD5: 82541471f40264dde726aaa038661f8c
Replication Data for: Designing degradable polyethene with desirable physical properties via molecular dynamics simulation and machine learning Oct 31, 2023 - Designing degradable polyethene with desirable physical properties via molecular dynamics simulation and machine learning Goh, Jueyu Chester, 2023, "Replication Data for: Designing degradable polyethene with desirable physical properties via molecular dynamics simulation and machine learning", https://doi.org/10.21979/N9/QR3JP5, DR-NTU (Data), V1 Data generated during project: Designing degradable polyethene with desirable physical properties via molecular dynamics simulation and machine learning
em2.edr Oct 31, 2023 - Replication Data for: Designing degradable polyethene with desirable physical properties via molecular dynamics simulation and machine learning Unknown - 1.2 MB - MD5: 95ed69d696ce8934a2aa1fc47c02aae9
em2.gro Oct 31, 2023 - Replication Data for: Designing degradable polyethene with desirable physical properties via molecular dynamics simulation and machine learning Unknown - 27.0 KB - MD5: 61c83b6c12a9c573a907b98bba3316b2
em2.log Oct 31, 2023 - Replication Data for: Designing degradable polyethene with desirable physical properties via molecular dynamics simulation and machine learning Plain Text - 2.8 MB - MD5: c0f21e91e88439fdf6e80b8453868559
em2.tpr Oct 31, 2023 - Replication Data for: Designing degradable polyethene with desirable physical properties via molecular dynamics simulation and machine learning Unknown - 168.7 KB - MD5: ffe53624072ecc494143c789b4d06574
em2.trr Oct 31, 2023 - Replication Data for: Designing degradable polyethene with desirable physical properties via molecular dynamics simulation and machine learning Unknown - 7.1 KB - MD5: 09cc6782523584857d3794e3219cee23

Figure 1. Scheme.png

Nov 14, 2023 - Dual-Conductive and Stiffness-Morphing Microneedle Patch Enables Continuous in Planta Monitoring of Electrophysiological Signal and Ion Fluctuation

PNG Image - 12.3 MB -

Figure 2. Characterization.png

Nov 14, 2023 - Dual-Conductive and Stiffness-Morphing Microneedle Patch Enables Continuous in Planta Monitoring of Electrophysiological Signal and Ion Fluctuation

PNG Image - 10.2 MB -

Figure 3. In Planta Biopotential Monitoring.png

Nov 14, 2023 - Dual-Conductive and Stiffness-Morphing Microneedle Patch Enables Continuous in Planta Monitoring of Electrophysiological Signal and Ion Fluctuation

PNG Image - 9.6 MB -

Figure 4. Cation Fluctuation Monitoring.png

Nov 14, 2023 - Dual-Conductive and Stiffness-Morphing Microneedle Patch Enables Continuous in Planta Monitoring of Electrophysiological Signal and Ion Fluctuation

PNG Image - 391.5 KB -

Replication Data for: Designing degradable polyethene with desirable physical properties via molecular dynamics simulation and machine learning

Oct 31, 2023 - Designing degradable polyethene with desirable physical properties via molecular dynamics simulation and machine learning

Goh, Jueyu Chester, 2023, "Replication Data for: Designing degradable polyethene with desirable physical properties via molecular dynamics simulation and machine learning", https://doi.org/10.21979/N9/QR3JP5, DR-NTU (Data), V1

Data generated during project: Designing degradable polyethene with desirable physical properties via molecular dynamics simulation and machine learning

em2.edr

Oct 31, 2023 - Replication Data for: Designing degradable polyethene with desirable physical properties via molecular dynamics simulation and machine learning

Unknown - 1.2 MB -

em2.gro

Oct 31, 2023 - Replication Data for: Designing degradable polyethene with desirable physical properties via molecular dynamics simulation and machine learning

Unknown - 27.0 KB -

em2.log

Oct 31, 2023 - Replication Data for: Designing degradable polyethene with desirable physical properties via molecular dynamics simulation and machine learning

Plain Text - 2.8 MB -

em2.tpr

Oct 31, 2023 - Replication Data for: Designing degradable polyethene with desirable physical properties via molecular dynamics simulation and machine learning

Unknown - 168.7 KB -