TY - JOUR
T1 - Two-dimensional materials for bio-realistic neuronal computing networks
AU - Sangwan, Vinod K.
AU - Liu, Stephanie E.
AU - Trivedi, Amit R.
AU - Hersam, Mark C.
N1 - Funding Information:
The authors acknowledge support from the National Science Foundation Materials Research Science and Engineering Center at Northwestern University under contract no. DMR-1720139 and by the National Science Foundation Neuroplane Program under contract no. CCF-2106964 . The authors also acknowledge the Laboratory Directed Research and Development Program at Sandia National Laboratories (SNL). SNL is a multi-mission laboratory managed and operated by National Technology and Engineering Solutions of Sandia LLC, a wholly owned subsidiary of Honeywell International Inc. for the US DOE National Nuclear Security Administration under contract DE-NA0003525. This work describes objective technical results and analysis. Any subjective views or opinions that might be expressed in the paper do not necessarily represent the views of the United States Government.
Funding Information:
The authors acknowledge support from the National Science Foundation Materials Research Science and Engineering Center at Northwestern University under contract no. DMR-1720139 and by the National Science Foundation Neuroplane Program under contract no. CCF-2106964. The authors also acknowledge the Laboratory Directed Research and Development Program at Sandia National Laboratories (SNL). SNL is a multi-mission laboratory managed and operated by National Technology and Engineering Solutions of Sandia LLC, a wholly owned subsidiary of Honeywell International Inc. for the US DOE National Nuclear Security Administration under contract DE-NA0003525. This work describes objective technical results and analysis. Any subjective views or opinions that might be expressed in the paper do not necessarily represent the views of the United States Government. The authors declare no competing interests.
Publisher Copyright:
© 2022 Elsevier Inc.
PY - 2022/12/7
Y1 - 2022/12/7
N2 - Two-dimensional (2D) van der Waals materials have found broad utility in a diverse range of applications including electronics, optoelectronics, renewable energy, and quantum information technologies. Meanwhile, exponentially growing digital data coupled with the ubiquity of artificial intelligence algorithms have generated significant interest in edge neuromorphic computing as an alternative to centralized cloud computing. The drive to incorporate neuroscience principles into computing hardware is motivated by the low power consumption, parallel processing, and reconfigurability of the human brain. The diverse library of 2D materials with atomic-level thicknesses, exceptional electrostatic tunability, and integration versatility is particularly well-suited for realizing bio-realistic synaptic and neuronal functionality. Here, we summarize past and present work in this field and outline the frontier challenges that have not yet been overcome. We also delineate potential solutions and suggest that the neuroscience principles of criticality and synchrony have the potential to inspire breakthrough applications of 2D materials in neuronal computing networks.
AB - Two-dimensional (2D) van der Waals materials have found broad utility in a diverse range of applications including electronics, optoelectronics, renewable energy, and quantum information technologies. Meanwhile, exponentially growing digital data coupled with the ubiquity of artificial intelligence algorithms have generated significant interest in edge neuromorphic computing as an alternative to centralized cloud computing. The drive to incorporate neuroscience principles into computing hardware is motivated by the low power consumption, parallel processing, and reconfigurability of the human brain. The diverse library of 2D materials with atomic-level thicknesses, exceptional electrostatic tunability, and integration versatility is particularly well-suited for realizing bio-realistic synaptic and neuronal functionality. Here, we summarize past and present work in this field and outline the frontier challenges that have not yet been overcome. We also delineate potential solutions and suggest that the neuroscience principles of criticality and synchrony have the potential to inspire breakthrough applications of 2D materials in neuronal computing networks.
KW - artificial intelligence
KW - layered materials
KW - machine learning
KW - neuromorphic computing
KW - van der Waals heterojunction
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U2 - 10.1016/j.matt.2022.10.017
DO - 10.1016/j.matt.2022.10.017
M3 - Review article
AN - SCOPUS:85143990591
SN - 2590-2393
VL - 5
SP - 4133
EP - 4152
JO - Matter
JF - Matter
IS - 12
ER -
