MEMRISTIVE DEVICE

The development of technologies such as computer vision, artificial hearing and artificial intelligence has created a growing demand for systems capable of processing and storing large volumes of data quickly and efficiently. However, current devices separate data processing and storage into independent components. This separation not only implies a high energy cost but also makes it difficult to quickly and efficiently handle large amounts of data. Memristive devices combine information processing and memory storage into a single component, similar to how biological neurons work. However, memristors developed to date offer long-term memory but only allow access to a limited number of electronic states, which restricts their use in neuromorphic computing. Furthermore, they are unstable and poorly reproducible, so there is a great variability of properties between devices. Memristive devices based on ion migration currently present two major limitations that make their commercial use difficult. First, they need high voltages to operate, which makes the system energy-intensive, unstable, and makes electronic states difficult to control. Second, these systems are memoryless, as information is erased immediately after being written, severely limiting their practical usefulness. Therefore, it is essential to develop advanced materials that allow data to be pre-processed efficiently directly in the sensor or capture device with a low energy cost, and have an information storage capacity adequate for current technologies.