Emergence of In‐Materio Intelligence from an Incidental Structure of a Single‐Walled Carbon Nanotube–Porphyrin Polyoxometalate Random Network-Reference-Cited by-同舟云学术

Emergence of In‐Materio Intelligence from an Incidental Structure of a Single‐Walled Carbon Nanotube–Porphyrin Polyoxometalate Random Network

Published:2022-01-04 Issue:4 Volume:4 Page:2100145
ISSN:2640-4567
Container-title:Advanced Intelligent Systems
language:en
Short-container-title:Advanced Intelligent Systems

Author:

Banerjee Deep¹,Kotooka Takumi¹,Azhari Saman¹²^ORCID,Usami Yuki¹²^ORCID,Ogawa Takuji³^ORCID,Gimzewski James K.²⁴⁵^ORCID,Tamukoh Hakaru¹²^ORCID,Tanaka Hirofumi¹²^ORCID

Affiliation:

1. Department of Human Intelligence System Graduate School of Life Science and Systems Engineering Kyushu Institute of Technology (Kyutech) 2-4 Hibikino Wakamatsu Kitakyushu 808-0196 Japan

2. Research Center for Neuromorphic AI Hardware Kyushu Institute of Technology (Kyutech) 2-4 Hibikino Wakamatsu Kitakyushu 808-0196 Japan

3. Department of Chemistry Graduate School of Science Osaka University Osaka 560-0043 Japan

4. California NanoSystems Institute University of California at Los Angeles Los Angeles CA 90095 USA

5. Department of Chemistry University of California at Los Angeles Los Angeles CA 90095 USA

Funder

Japan Society for the Promotion of Science

Ministry of Education, Culture, Sports, Science and Technology

Publisher

Wiley

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/aisy.202100145

Reference51 articles.

1. Organization, development and function of complex brain networks

2. Emerging neuromorphic devices

3. Neuromorphic nanoelectronic materials

Cited by 30 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Physical Reservoir Computing Devices Utilizing Nanomaterial Random Network and Its Sensing Application;Vacuum and Surface Science;2024-09-10

2. Short‐Term and Long‐Term Memory Functionality of a Brain‐Like Device Built from Nanoparticle Atomic Switch Networks;Advanced Electronic Materials;2024-09-07

3. Physical reservoir application of random network of gold nanoparticles fabricated by multi-step immersion in gold colloidal solution;Japanese Journal of Applied Physics;2024-06-03

4. Enhancing Memory Capacity of Reservoir Computing with Delayed Input and Efficient Hardware Implementation with Shift Registers;2024 IEEE International Symposium on Circuits and Systems (ISCAS);2024-05-19

5. An organized view of reservoir computing: a perspective on theory and technology development;Japanese Journal of Applied Physics;2024-05-01