Litcius/Paper detail

Memristors with Biomaterials for Biorealistic Neuromorphic Applications

Jiaqi Xu, Xiaoning Zhao, Xiaoning Zhao, Xiaoli Zhao, Xiaoli Zhao, Zhongqiang Wang, Qingxin Tang, Haiyang Xu, Yichun Liu

2022Small Science42 citationsDOIOpen Access PDF

Abstract

Electronic devices with biomaterials have paved a way toward "green electronics" to create a sustainable future. Memristors are drawing growing attention with integrated sensing, memory, and computing for future artificial intelligence applications. Biomaterial is an emerging class of memristive materials (the device is called as biomemristor) for transient and/or biodegradable purpose. Importantly, several unique features such as faithful synaptic behaviors, bimodal switching, and biovoltage operations are observed in biomemristors. Moreover, the biomemristors are suitable for human-related applications due to the inherent biocompatibility of biomaterials and flexibility of the device with ultrathin thickness. These features make the biomemristors promising for biorealistic neuromorphic applications. Herein, the state of the art of biomemristors are comprehensively summarized and systematically discussed with particular attention on their unique biorealistic features. Challenges and prospects toward the further development of biomemristors are also provided and discussed.

Topics & Concepts

Neuromorphic engineeringMemristorFlexibility (engineering)NanotechnologyComputer scienceElectronicsBioelectronicsMaterials scienceComputer architectureEngineeringArtificial intelligenceArtificial neural networkElectronic engineeringElectrical engineeringBiosensorMathematicsStatisticsAdvanced Memory and Neural ComputingNeuroscience and Neural EngineeringPhotoreceptor and optogenetics research