Four levels of in-sensor computing in bionic olfaction: from discrete components to multi-modal integrations

Lin, Liwu; Zhang, Yuchun; Yan, Yonghong

doi:10.1039/d3nh00115f

Nanoscale Horiz.

2023

DOI: 10.1039/d3nh00115f

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Four levels of in-sensor computing in bionic olfaction: from discrete components to multi-modal integrations

Liwu Lin¹,

Yuchun Zhang²,

Yonghong Yan³

Abstract: Sensing and computing are important parts that human attempts to perceive and understand the analog world through digital devices. The analog-to-digital converters (ADCs) discretize the analog signals while the data...

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Cited by 5 publications

(1 citation statement)

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“…In addition, this analogue device is set-step free (vs the digital one), highly efficient in terms of energy consumption, and tolerant of constant mechanical deformation and has tunable conductance modulation capabilities in terms of the degree of deprotonation of ligand molecules. Importantly, these gold nanoparticles can transduce various physical, chemical, and biochemical stimuli into electrical signals, which suggests a very promising computing paradigm in which sensing and processing are implemented in a single device. − The metal nanoparticle diffusive memristor is subsequently used to emulate several basic synaptic functions and build memristive operators for edge extraction.…”

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confidence: 99%

A Diffusive Artificial Synapse Based on Charged Metal Nanoparticles

Guo,

Liu,

Wang

et al. 2024

Nano Lett.

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We show that a diffusive memristor with analogue switching characteristics can be achieved in a layer of gold nanoparticles (AuNPs) functionalized with charged self-assembled monolayers (deprotonated 11-mercaptoundecanoic acid). The nanoparticle core and the anchored stationary charges are jammed within the layer while the mobile counterions [N(CH 3 ) 4 + ] can respond to the electric field and spontaneously diffuse back to the initial positions upon removal of the field. This metal nanoparticle device is set-step free, energy consumption efficient, mechanically flexible, and analogous to bio-Ca 2+ dynamics and has tunable conductance modulation capabilities at the counterion concentrations. The gradual resistive switching behavior enables us to implement several important synaptic functions such as potentiation/depression, spike voltage-dependent plasticity, spike durationdependent plasticity, spike frequency-dependent plasticity, and paired-pulse facilitation. Finally, on the basis of the paired-pulse facilitation characteristics, the metal nanoparticle diffusive artificial synapse is used for edge extraction with exhibits excellent performance.

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confidence: 99%

A Diffusive Artificial Synapse Based on Charged Metal Nanoparticles

Guo,

Liu,

Wang

et al. 2024

Nano Lett.

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Device‐Level in‐Sensor Olfactory Perception System Based on Array of PCBM‐MAPbI₃ Heterostructure Transistors

Zhai,

Duan,

et al. 2024

Adv Funct Materials

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Although there are significant advancements in device‐level artificial tactile and visual perception systems based on in‐sensor computing paradigms, the development of hardware‐implemented neuromorphic olfactory system is still in its early stages. One of the primary challenges in this field is that most of the gas sensors lack the capability to fuse the sensing and computing functions in a single sensor. Through surface passivation and interface engineering, this work introduces a device‐level artificial olfactory system utilizing array of PCBM‐MAPbI3 heterostructure transistors. Noteworthly, the formation of metastable intermediate phase NH3PbI3•MA can occur at room temperature and can be used to store gas sensory information. Both gas pulse and electrical pulse can dynamically modulate the amount of this intermediate phase, and then change the channel conductance (weight), realizing the fusion of the sensing and synaptic functions in single device. Based on these excellent properties, the spatiotemporal information of gas diffusion can be encoded and processed simultaneously. As a result, an in‐sensor olfactory perception system is successfully demonstrated based on 5 × 5 PCBM‐MAPbI3 heterostructure transistor array, which can be used for detecting the distance and direction of the hazardous gas. This work paves the way for future application of real‐time and data‐intensive machine‐olfactory system.

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In‐Sensor Computing‐Based Smart Sensing Architecture Implemented Using a Dual‐Gate Metal‐Oxide Thin‐Film Transistor Technology

Lei,

Hu,

Xie

et al. 2024

Adv Elect Materials

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An array of sensors generating a collection of correlated signals can benefit from integration with a “smart” system for autonomous inferencing. Mimicking their biological counterparts, smart sensor systems shall possess the capabilities of sensing, memory, and neuromorphic computation. However, state‐of‐the‐art biomimetic systems either do not employ a full set of devices to cover the complete range of capabilities or incorporate devices that are capable of all but appropriate only for a limited range of sensing applications. Presently proposed is a smart sensor architecture that combines an array of sensing elements with an overlapping array of computing and memory elements, thus emulating an innervated peripheral sensing system (IPSS) capable of local and autonomous neuromorphic in‐sensor data pre‐processing. Compatibility of the proposed architecture with functionally distinct elements for sensing, memory, and computing removes the restrictive demand for a single element simultaneously capable of all, thus making this architecture more generally applicable to a wider range of sensors and usage scenarios. An artificial synapse as a computing element is implemented using dual‐gate (DG) thin‐film transistors (TFTs) and the low‐leakage current of transistors based on metal‐oxide semiconductors allows the deployment of capacitors as memory elements. The outputs of the IPSS are passed on to an adjacent artificial neural network (ANN) for near‐sensor inferencing. Monolithic integration of the IPSS and the ANN is made possible by the deployment of the same memory and computing elements in their construction. A smart tactile sensing system based on the proposed architecture is constructed and characterized. The functionality of the system is demonstrated by its application to the classification of a set of tactile images of 3‐dimensionally printed alphabet stamps.

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Four levels of in-sensor computing in bionic olfaction: from discrete components to multi-modal integrations

Abstract: Sensing and computing are important parts that human attempts to perceive and understand the analog world through digital devices. The analog-to-digital converters (ADCs) discretize the analog signals while the data...

Cited by 5 publications

References 61 publications

A Diffusive Artificial Synapse Based on Charged Metal Nanoparticles

A Diffusive Artificial Synapse Based on Charged Metal Nanoparticles

Device‐Level in‐Sensor Olfactory Perception System Based on Array of PCBM‐MAPbI₃ Heterostructure Transistors

In‐Sensor Computing‐Based Smart Sensing Architecture Implemented Using a Dual‐Gate Metal‐Oxide Thin‐Film Transistor Technology

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Four levels of in-sensor computing in bionic olfaction: from discrete components to multi-modal integrations

Abstract: Sensing and computing are important parts that human attempts to perceive and understand the analog world through digital devices. The analog-to-digital converters (ADCs) discretize the analog signals while the data...

Cited by 5 publications

References 61 publications

A Diffusive Artificial Synapse Based on Charged Metal Nanoparticles

A Diffusive Artificial Synapse Based on Charged Metal Nanoparticles

Device‐Level in‐Sensor Olfactory Perception System Based on Array of PCBM‐MAPbI3 Heterostructure Transistors

In‐Sensor Computing‐Based Smart Sensing Architecture Implemented Using a Dual‐Gate Metal‐Oxide Thin‐Film Transistor Technology

Contact Info

Product

Resources

About

Device‐Level in‐Sensor Olfactory Perception System Based on Array of PCBM‐MAPbI₃ Heterostructure Transistors