In niobium oxide-based capacitors non-linear switching characteristics can be observed if the oxide properties are adjusted accordingly. Such non-linear threshold switching characteristics can be utilized in various non-linear circuit applications, which have the potential to pave the way for the application of new computing paradigms. Furthermore, the non-linearity also makes them an interesting candidate for the application as selector devices e.g. for non-volatile memory devices. To satisfy the requirements for those two areas of application, the threshold switching characteristics need to be adjusted to either obtain a maximized voltage extension of the negative differential resistance region in the quasi-static I-V characteristics, which enhances the non-linearity of the devices and results in improved robustness to device-to-device variability or to adapt the threshold voltage to a specific non-volatile memory cell. Those adaptations of the threshold switching characteristics were successfully achieved by deliberate modifications of the niobium oxide stack. Furthermore, the impact of the material stack on the dynamic behavior of the threshold switches in non-linear circuits as well as the impact of the electroforming routine on the threshold switching characteristics were analyzed. The optimized device stack was transferred from the micrometer-sized test structures to submicrometer-sized devices, which were packaged to enable easy integration in complex circuits. Based on those packaged threshold switching devices the behavior of single as well as of coupled relaxation oscillators was analyzed. Subsequently, the obtained results in combination with the measurement results for the statistic device-to-device variability were used as a basis to simulate the pattern formation in coupled relaxation oscillator networks as well as their performance in solving graph coloring problems. Furthermore, strategies to adapt the threshold voltage to the switching characteristics of a tantalum oxide-based non-volatile resistive switch and a non-volatile phase change cell, to enable their application as selector devices for the respective cells, were discussed.:Abstract I
Zusammenfassung II
List of Abbrevations VI
List of Symbols VII
1 Motivation 1
2 Basics 5
2.1 Negative differential resistance and local activity in memristor devices 5
2.2 Threshold switches as selector devices 8
2.3 Switching effects observed in NbOx 13
2.3.1 Threshold switching caused by metal-insulator transition 13
2.3.2 Threshold switching caused by Frenkel-Poole conduction 18
2.3.3 Non-volatile resistive switching 32
3 Sample preparation 35
3.1 Deposition techniques 35
3.1.1 Evaporation 35
3.1.2 Sputtering 36
3.2 Micrometer-sized devices 36
3.3 Submicrometer-sized devices 37
3.3.1 Process flow 37
3.3.2 Reduction of the electrode resistance 39
3.3.3 Transfer from structuring via electron beam lithography to structuring via
laser lithography 48
3.3.4 Packaging procedure 50
4 Investigation and optimization of the electrical device characteristic 51
4.1 Introduction 51
4.2 Measurement setup 52
4.3 Electroforming 53
4.3.1 Optimization of the electroforming process 53
4.3.2 Characterization of the formed filament 62
4.4 Dynamic device characteristics 67
4.4.1 Emergence and measurement of dynamic behavior 67
4.4.2 Impact of the dynamic device characteristics on quasi-static I-V
characteristics 70
5 Optimization of the material stack 81
5.1 Introduction 81
5.2 Adjustment of the oxygen content in the bottom layer 82
5.3 Influence of the thickness of the oxygen-rich niobium oxide layer 92
5.4 Multilayer stacks 96
5.5 Device-to-device and Sample-to-sample variability 110
6 Applications of NbOx-based threshold switching devices 117
6.1 Introduction 117
6.2 Non-linear circuits 117
6.2.1 Coupled relaxation oscillators 117
6.2.2 Memristor Cellular Neural Network 121
6.2.3 Graph Coloring 127
6.3 Selector devices 132
7 Summary and Outlook 138
8 References 141
9 List of publications 154
10 Appendix 155
10.1 Parameter used for the LT Spice simulation of I-V curves for threshold
switches with varying oxide thicknesses 155
10.2 Dependence of the oscillation frequency of the relaxation oscillator circuit
on the capacitance and the applied source voltage 156
10.3 Calculation of the oscillation frequency of the relaxation oscillator circuit 157
10.4 Characteristics of the memristors and the cells utilized in the simulation of
the memristor cellular neural network 164
10.5 Calculation of the impedance of the cell in the memristor cellular network 166
10.6 Example graphs from the 2nd DIMACS series 179
11 List of Figures 182
12 List of Tables 194
| Identifer | oai:union.ndltd.org:DRESDEN/oai:qucosa:de:qucosa:88560 |
| Date | 11 December 2023 |
| Creators | Herzig, Melanie |
| Contributors | Mikolajick, Thomas, Ziegler, Martin, Marschner, Uwe, Technische Universität Dresden |
| Source Sets | Hochschulschriftenserver (HSSS) der SLUB Dresden |
| Language | English |
| Detected Language | English |
| Type | info:eu-repo/semantics/publishedVersion, doc-type:doctoralThesis, info:eu-repo/semantics/doctoralThesis, doc-type:Text |
| Rights | info:eu-repo/semantics/openAccess |
| Relation | 10.1088/1361-6641/ab1da3, 10.1088/1361-6463/ab217a, 10.1109/TCSI.2021.3061973, 10.1109/TCSI.2019.2894218, 10.1109/NVMTS.2016.7781515 |
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