Artificial sensory system based on memristive devices.

In the biological nervous system, the integration and cooperation of parallel system of receptors, neurons, and synapses allow efficient detection and processing of intricate and disordered external information. Such systems acquire and process environmental data in real-time, efficiently handling complex tasks with minimal energy consumption. Memristors can mimic typical biological receptors, neurons, and synapses by implementing key features of neuronal signal-processing functions such as selective adaption in receptors, leaky integrate-and-fire in neurons, and synaptic plasticity in synapses. External stimuli are sensitively detected and filtered by "artificial receptors," encoded into spike signals via "artificial neurons," and integrated and stored through "artificial synapses." The high operational speed, low power consumption, and superior scalability of memristive devices make their integration with high-performance sensors a promising approach for creating integrated artificial sensory systems. These integrated systems can extract useful data from a large volume of raw data, facilitating real-time detection and processing of environmental information. This review explores the recent advances in memristor-based artificial sensory systems. The authors begin with the requirements of artificial sensory elements and then present an in-depth review of such elements demonstrated by memristive devices. Finally, the major challenges and opportunities in the development of memristor-based artificial sensory systems are discussed.

An Artificial Olfactory System Based on a Chemi-Memristive Device.

Technologies based on the fusion of gas sensors and neuromorphic computing to mimic the olfactory system have immense potential. However, the implementation of neuromorphic olfactory systems remains in a state of infancy because conventional gas sensors lack the necessary functions. Therefore, this study proposes a hysteretic "chemi-memristive gas sensor" based on oxygen vacancy chemi-memristive dynamics that differ from that of conventional gas sensors. After the memristive switching operation, the redox reaction with the external gas molecules is enhanced, resulting in the generation and elimination of oxygen vacancies that induce rapid current changes. In addition, the pre-generated oxygen vacancies enhance the post-sensing properties. Therefore, fast responses, short recovery times, and hysteretic gas response are achieved by the proposed sensor at room temperature. Based on the advantageous functionality of the sensor, device-level olfactory systems that can monitor the history of input gas stimuli are experimentally demonstrated as a potential application. Moreover, analog conductance modulation induced by oxidizing and reducing gases enables the conversion of external gas stimuli into synaptic weights and hence the realization of typical synaptic functionalities without an additional device or circuit. The proposed chemi-memristive device represents an advance in the bioinspired technology adopted in creating artificial intelligence systems.

Highly Reliable Threshold Switching Characteristics of Surface-Modulated Diffusive Memristors Immune to Atmospheric Changes.

Active cation-based diffusive memristors featuring essentially volatile threshold switching have been proposed for novel applications, such as a selector in a one-selector-and-one-resistor structure and signal generators in neuromorphic computing. However, the high variability of the switching behavior, which results from the high electroforming voltage, external environmental conditions, and transition to the non-volatile switching mode in a high-current range, is considered a major impediment to such applications. Herein, for the first time, we developed a highly reliable threshold switching device immune to atmospheric changes based on an ultraviolet-ozone (UVO)-treated diffusive memristor consisting of Ag and SiO2 nanorods (NRs). UVO treatment forms a stable water reservoir on the surface of SiO2 NRs, facilitating the redox reaction and ion migration of Ag. Consequently, diffusive memristors possess reliable switching characteristics, including electroforming-free, repeatable, and consistent switching with resistance to changes in ambient conditions and compliance levels during operation. We demonstrated that our approach is suitable for various metal oxides and can be used in numerous applications.