Tag Archives: Guozhen Shen

A nontraditional artificial synaptic device and roadmap for Chinese research into neuromorphic devices

A November 9, 2022 Science China Press press release on EurekAlert announces a new approach to developing neuromorphic (brainlike) devices,

Neuromorphic computing is an information processing model that simulates the efficiency of the human brain with multifunctionality and flexibility. Currently, artificial synaptic devices represented by memristors have been extensively used in neural morphological computing, and different types of neural networks have been developed. However, it is time-consuming and laborious to perform fixing and redeploying of weights stored by traditional artificial synaptic devices. Moreover, synaptic strength is primarily reconstructed via software programming and changing the pulse time, which can result in low efficiency and high energy consumption in neural morphology computing applications.

In a novel research article published in the Beijing-based National Science Review, Prof. Lili Wang from the Chinese Academy of Sciences and her colleagues present a novel hardware neural network based on a tunable flexible MXene energy storage (FMES) system. The system comprises flexible postsynaptic electrodes and MXene nanosheets, which are connected with the presynaptic electrodes using electrolytes. The potential changes in the ion migration process and adsorption in the supercapacitor can simulate information transmission in the synaptic gap. Additionally, the voltage of the FMES system represents the synaptic weight of the connection between two neurons.

Researchers explored the changes of paired-pulse facilitation under different resistance levels to investigate the effect of resistance on the advanced learning and memory behavior of the artificial synaptic system of FMES. The results revealed that the larger the standard deviation, the stronger the memory capacity of the system. In other words, with the continuous improvement of electrical resistance and stimulation time, the memory capacity of the artificial synaptic system of FMES is gradually improved. Therefore, the system can effectively control the accumulation and dissipation of ions by regulating the resistance value in the system without changing the external stimulus, which is expected to realize the coupling of sensing signals and storage weight.

The FMES system can be used to develop neural networks and realize various neural morphological computing tasks, making the recognition accuracy of handwritten digit sets reach 95%. Additionally, the FMES system can simulate the adaptivity of the human brain to achieve adaptive recognition of similar target data sets. Following the training process, the adaptive recognition accuracy can reach approximately 80%, and avoid the time and energy loss caused by recalculation.

“In the future, based on this research, different types of sensors can be integrated on the chip to further realize multimodal sensing computing integrated architecture.” Prof. Lili Wang stated, “The device can perform low-energy calculations, and is expected to solve the problems of high write noise, nonlinear difference, and diffusion under zero bias voltage in certain neural morphological systems.”

Here’s a link to and a citation for the paper,

Neuromorphic-computing-based adaptive learning using ion dynamics in flexible energy storage devices by Shufang Zhao, Wenhao Ran, Zheng Lou, Linlin Li, Swapnadeep Poddar, Lili Wang, Zhiyong Fan, Guozhen Shen. National Science Review, Volume 9, Issue 11, November 2022, nwac158, EOI: https://doi.org/10.1093/nsr/nwac158 Published: 13 August 2022

This paper is open access.

The future (or roadmap for) of Chinese research on neuromorphic engineering

While I was trying (unsuccessfully) to find a copy of the press release on the issuing agency’s website, I found this paper,

2022 roadmap on neuromorphic devices & applications research in China by Qing Wan, Changjin Wan, Huaqiang Wu, Yuchao Yang, Xiaohe Huang, Peng Zhou, LinChen, Tian-Yu Wang, Yi Li, Kanhao Xue, Yuhui He, Xiangshui Miao, Xi Li, Chenchen Xie, Houpeng Chen, Z. T. Song, Hong Wang, Yue Hao, Junyao Zhang, Jia Huang, Zheng Yu Ren, Li Qiang Zhu, Jianyu Du, Chen Ge, Yang Liu, Guanglong Ding, Ye Zhou, Su-Ting Han, Guosheng Wang, Xiao Yu, Bing Chen, Zhufei Chu, Lunyao Wang, Yinshui Xia, Chen Mu, Feng Lin, Chixiao Chen, Bojun Cheng, Yannan Xing, Weitao Zeng, Hong Chen, Lei Yu, Giacomo Indiveri and Ning Qiao. Neuromorphic Computing and Engineering DOI: 10.1088/2634-4386/ac7a5a *Accepted Manuscript online 20 June 2022 • © 2022 The Author(s). Published by IOP Publishing Ltd

The paper is open access.

*From the IOP’s Definitions of article versions: Accepted Manuscript is ‘the version of the article accepted for publication including all changes made as a result of the peer review process, and which may also include the addition to the article by IOP of a header, an article ID, a cover sheet and/or an ‘Accepted Manuscript’ watermark, but excluding any other editing, typesetting or other changes made by IOP and/or its licensors’.*

This is neither the published version nor the version of record.

Glucose-sensing contact lens invented by US and Korean researchers

Blood tests for glucose levels may one day be a feature of the past according to an Oct. 3, 2016 news item on ScienceDaily,

Blood testing is the standard option for checking glucose levels, but a new technology could allow non-invasive testing via a contact lens that samples glucose levels in tears.

“There’s no noninvasive method to do this,” said Wei-Chuan Shih, a researcher with the University of Houston [UH] who worked with colleagues at UH and in Korea to develop the project, described in the high-impact journal Advanced Materials. “It always requires a blood draw. This is unfortunately the state of the art.”

A Sept. 27, 2016 UH news release (also on EurekAlert) by Jeannie Kever, which originated the news item, describes the proposed technology,

… glucose is a good target for optical sensing, and especially for what is known as surface-enhanced Raman scattering spectroscopy [also known as surface-enhanced Raman scattering or surface-enhanced Raman spectroscopy, and SERS], said Shih, an associate professor of electrical and computer engineering whose lab, the NanoBioPhotonics Group, works on optical biosensing enabled by nanoplasmonics.

This is an alternative approach, in contrast to a Raman spectroscopy-based noninvasive glucose sensor Shih developed as a Ph.D. student at the Massachusetts Institute of Technology. He holds two patents for technologies related to directly probing skin tissue using laser light to extract information about glucose concentrations.

The paper describes the development of a tiny device, built from multiple layers of gold nanowires stacked on top of a gold film and produced using solvent-assisted nanotransfer printing, which optimized the use of surface-enhanced Raman scattering to take advantage of the technique’s ability to detect small molecular samples.

Surface-enhanced Raman scattering – named for Indian physicist C.V. Raman [Raman scattering; SERS history begins in 1973 according to its Wikipedia entry], who discovered the effect in 1928 – uses information about how light interacts with a material to determine properties of the molecules that make up the material.

The device enhances the sensing properties of the technique by creating “hot spots,” or narrow gaps within the nanostructure which intensified the Raman signal, the researchers said.

Researchers created the glucose sensing contact lens to demonstrate the versatility of the technology. The contact lens concept isn’t unheard of – Google has submitted a patent for a multi-sensor contact lens, which the company says can also detect glucose levels in tears – but the researchers say this technology would also have a number of other applications.

“It should be noted that glucose is present not only in the blood but also in tears, and thus accurate monitoring of the glucose level in human tears by employing a contact-lens-type sensor can be an alternative approach for noninvasive glucose monitoring,” the researchers wrote.

“Everyone knows tears have a lot to mine,” Shih said. “The question is, whether you have a detector that is capable of mining it, and how significant is it for real diagnostics.”

In addition to Shih, authors on the paper include Yeon Sik Jung, Jae Won Jeong and Kwang-Min Baek, all with the Korea Advanced Institute of Science and Technology; Seung Yong Lee of the Korea Institute of Science and Technology, and Md Masud Parvez Arnob of UH.

Although non-invasive glucose sensing is just one potential application of the technology, Shih said it provided a good way to prove the technology. “It’s one of the grand challenges to be solved,” he said. “It’s a needle in a haystack challenge.”

Scientists know that glucose is present in tears, but Shih said how tear glucose levels correlate with blood glucose levels hasn’t been established. The more important finding, he said, is that the structure is an effective mechanism for using surface-enhanced Raman scattering spectroscopy.

Although traditional nanofabrication techniques rely on a hard substrate – usually glass or a silicon wafer – Shih said researchers wanted a flexible nanostructure, which would be more suited to wearable electronics. The layered nanoarray was produced on a hard substrate but lifted off and printed onto a soft contact, he said.

Here’s a link to and a citation for the paper,

Wafer Scale Phase-Engineered 1T- and 2H-MoSe2/Mo Core–Shell 3D-Hierarchical Nanostructures toward Efficient Electrocatalytic Hydrogen Evolution Reaction by Yindong Qu, Henry Medina, Sheng-Wen Wang, Yi-Chung Wang, Chia-Wei Chen, Teng-Yu Su, Arumugam Manikandan, Kuangye Wang, Yu-Chuan Shih, Je-Wei Chang, Hao-Chung Kuo, Chi-Yung Lee, Shih-Yuan Lu, Guozhen Shen, Zhiming M. Wang, and Yu-Lun Chueh. Advanced Materials DOI: 10.1002/adma.201602697 Version of Record online: 26 SEP 2016

© 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim

This paper is behind a paywall.