School of Materials Science and Engineering (MSE)

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2,081 to 2,090 of 8,079 Results

Zeta Potenial.tab Nov 15, 2023 - Data for: Harnessing Gradients for Self-Assembly of Peptide-Based Nanocapsules: A Pathway to Advanced Drug Delivery Systems Tabular Data - 117 B - 4 Variables, 6 Observations - UNF:6:cPweXLOJSBbXkhCwOCk84g==
Li Haopeng(Nanyang Technological University) Nov 14, 2023
Dual-Conductive and Stiffness-Morphing Microneedle Patch Enables Continuous in Planta Monitoring of Electrophysiological Signal and Ion Fluctuation Nov 14, 2023 - KONG Lingxuan Kong, Lingxuan; Wen, Hanqi; Luo, Yifei; Chen, Xiaodong; Sheng, Xing; Liu, Yuxin; Chen, Peng, 2023, "Dual-Conductive and Stiffness-Morphing Microneedle Patch Enables Continuous in Planta Monitoring of Electrophysiological Signal and Ion Fluctuation", https://doi.org/10.21979/N9/4D5WR2, DR-NTU (Data), V1 The use of conductive microneedles presents a promising solution for achieving high-fidelity electrophysiological recordings with minimal impact on interfaced tissue. However, conventional metal-based microneedle suffers from high electrochemical impedance and mechanical mismatch...
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

Zeta Potenial.tab

Nov 15, 2023 - Data for: Harnessing Gradients for Self-Assembly of Peptide-Based Nanocapsules: A Pathway to Advanced Drug Delivery Systems

Tabular Data - 117 B - 4 Variables, 6 Observations -

Li Haopeng(Nanyang Technological University)

Nov 14, 2023

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

Nov 14, 2023 - KONG Lingxuan

Kong, Lingxuan; Wen, Hanqi; Luo, Yifei; Chen, Xiaodong; Sheng, Xing; Liu, Yuxin; Chen, Peng, 2023, "Dual-Conductive and Stiffness-Morphing Microneedle Patch Enables Continuous in Planta Monitoring of Electrophysiological Signal and Ion Fluctuation", https://doi.org/10.21979/N9/4D5WR2, DR-NTU (Data), V1

The use of conductive microneedles presents a promising solution for achieving high-fidelity electrophysiological recordings with minimal impact on interfaced tissue. However, conventional metal-based microneedle suffers from high electrochemical impedance and mechanical mismatch...

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 -

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