Hongwei Tan | 檀洪伟

Optoelectronic Synapses for Artificial Neural Networks (OSANN)

The Optoelectronic Synapses for Artificial Neural Network (OSANN) project is funded by the Academy of Finland and Aalto University, Finland. The funding period is 01.09.2018 - 31.08.2021.

Bioinspired optoelectronic spiking afferent nerve

The emulation of sensory neurons and synapses is vital for neuromorphic sensing and computing. In this project, with the goal of optoelectronic neuromorphic devices and systems, optoelectronic synapses are developed to detect and process optical information by interfacial optoelectronic effects in semiconductor devices. Compared with electronic synapses, the optoelectronic synapses offer the added merits of integrating sensing-processing-memory, and allowing high-speed optical communications. Furthermore, artificial optoelectronic spiking afferent nerves that integrate pressure sensors, spike encoders, and the optoelectronic synapses are demonstrated with capabilities of pressure sensing, neural coding, perceptual learning, memorizing and recognizing, well resembling human tactile sensing and processing. The project results provide a promising approach towards e-skin, neurorobotics, and human-machine interactions.

Bioinspired multisensory neural networks

The integration and interaction of vision, touch, hearing, smell, and taste in the human multisensory neural network facilitate high-level cognitive functionalities, such as crossmodal integration, recognition, and imagination for accurate evaluation and comprehensive understanding of the multimodal world. Here, we report a bioinspired multisensory neural network that integrates artificial optic, afferent, auditory, and simulated olfactory and gustatory sensory nerves. With distributed multiple sensors and biomimetic hierarchical architectures, our system can not only sense, process, and memorize multimodal information, but also fuse multisensory data at the hardware and software levels. Using crossmodal learning, the system is capable of crossmodally recognizing and imagining multimodal information, such as visualizing alphabet letters upon handwritten input, recognizing multimodal visual/smell/taste information, or imagining a never-seen picture when hearing its description. Our multisensory neural network provides a promising approach towards robotic sensing and perception.

Members

Dr. Hongwei Tan (principal investigator)

Mr. Ishan Pande (graduate student)

Mr. Atte Tupala (undergraduate student)

Ms. Ella Paasio (undergraduate student)

Mr. Syed Ashraf (undergraduate student)

Collaborations

Materials Design Group (Prof. Johanna Rosen), Linköping University, Sweden

Molecular Materials Group (Prof. Olli Ikkala and Dr. Bo Peng), Aalto University, Finland

Dr. Sayani Majumdar, VTT, Finland

Publications of the project

1. Ziyue Miao, Hongwei Tan, Lotta Gustavsson, Yang Zhou, Quan Xu, Olli Ikkala,* and Bo Peng*. Gustation-inspired design of hydrogels for taste sensing enabled by machine learning. Small 2023, 2305195.

2. Hongwei Tan*, Sebastiaan van Dijken*. Dynamic machine vision with retinomorphic photomemristor-reservoir computing. Nature Communications 2023, 14, 2169. (Photomemristor as dynamic machine vision sensor)

3. Xianhu Liu, Hongwei Tan, Carlo Rigoni, Teemu Hartikainen, Nazish Asghar, Sebastiaan van Dijken, Jaakko V. I. Timonen, Bo Peng*, Olli Ikkala*. Magnetic field-driven particle assembly and jamming for bistable memory and response plasticity. Science Advances 2022, 8, eadc9394.

4. Hongwei Tan*, Yifan Zhou, Quanzheng Tao, Johanna Rosen, Sebastiaan van Dijken*. Bioinspired multisensory neural network with crossmodal integration and recognition. Nature Communications 2021, 12, 1120.

5. Hongwei Tan*, Quanzheng Tao, Ishan Pande, Sayani Majumdar, Fu Liu, Yifan Zhou, Per O. Å. Persson, Johanna Rosen, Sebastiaan van Dijken*. Tactile sensory coding and learning with bio-inspired optoelectronic spiking afferent nerves. Nature Communications 2020, 11, 1369.

6. Hongwei Tan*, Sayani Majumdar, Qihang Qin, Jouko Lahtinen, Sebastiaan van Dijken*. Mimicking Neurotransmitter Release and Long-Term Plasticity by Oxygen Vacancy Migration in a Tunnel Junction Memristor. Advanced Intelligent Systems 2019, 1, 1900036.

7. Sayani Majumdar*, Hongwei Tan, Ishan Pande, Sebastiaan Van Dijken*. Crossover from synaptic to neuronal functionalities through carrier concentration control in Nb-doped SrTiO3-based organic ferroelectric tunnel junctions. APL Materials 2019, 7, 091114.

Acknowledgments

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