| AVS 66th International Symposium & Exhibition | |
| Nanometer-scale Science and Technology Division | Thursday Sessions |
| Session NS-ThA |
| Session: | SPM for Functional Characterization |
| Presenter: | Adnan Mehonic, University College London, UK |
| Authors: | A. Mehonic, University College London, UK M. Buckwell, University College London, UK W.H. Ng, University College London, UK A.J. Kenyon, University College London, UK |
| Correspondent: | Click to Email |
Resistive Random Access Memory (RRAM) has established itself as a promising technology for the next generation of non-volatile memories due to the simple design, high scalability, fast and low-power operation. Additionally, RRAM devices are considered for the implementation of power efficient hardware in applications of artificial intelligence (AI) and machine learning (ML) implemented in non-von Neumann architectures. Redox-based RRAM (ReRAM), based on the formation of conductive filaments in thin metal oxides are particularly popular due to excellent CMOS compatibility. However, significant challenges still exist for the full utilisation of the technology; such as device variability and yield. To better design and optimise the devices it is crucial to understand the physics that underlies the resistance switching processes. Here we present how SPM techniques can be used to characterise silicon oxide-based ReRAM devices. We find these techniques to be invaluable for developing a better sense of the oxide microstructure and the link with resistance switching processes. We also use the method of conductance tomography to directly visualise the shapes and sizes of conductive filaments in three dimensions - this is typically extremely challenging to obtain using conventional microscopy techniques.