journal article·2024-11-20

Atom-Vacancy-Defect-Derived Electric Hysteresis Loops and Stochastic Low-Frequency Noises in Few-Atom Layer MoS2

Mioko Kosugi, Shunta Furuichi, Yung-Chang Lin, Yusuke Kobayashi, Keita Takaki, Takashi Kikkawa, Takashi Taniguchi, Kenji Watanabe, Takashi Kohno, Kazu Suenaga, Eiji Saitoh, Shigeo Maruyama, Junji Haruyama

ACS Applied Materials & Interfaces· Volume 16· Issue 46
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Abstract

Atom-vacancy-defects present in various materials yield numerous interesting physical phenomena, even obstructing high performance in some cases. On the other hand, their valuable applications to novel devices, such as nitrogen vacancy centers in diamond for quantum bits, have gathered significant attention. In particular, these tendencies become more substantial in two-dimensional (2D) (atomically) thin van der Waals layers. However, correlations with various kinds of atom defects are still under exploration. Herein, we find the stochastic behaviors of large hysteresis loops with strong photoresponse in the static electrical properties in few-atom layer semiconductors, molybdenum disulfide (MoS 2 ). The temperature dependence and transmission electron microscopy reveal that they arise from pairs of two neighboring in-plane S-vacancy defects, which predominantly present only around the interface at the MoS 2 flake/substrate, with activation energies ∼0.35 eV. The low-frequency ( f ) (LF) noise measurements clarify a high f shift in the two 1/ f 2 -dependent regimes, implying stochastic behaviors of electric charges through the S-vacancy pairs with high-speed charge(spin) transitions across low kinetic energy barriers between narrow discrete states. The shallow energy sates are formed from the highly uniform S-vacancy pairs interacting with Mo atoms, which act like quantum dots. The observed stochastic operation holds promise for various application, particularly for probabilistic neuromorphic computation in artificial intelligence.
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Research context

OpenAlex topics: Advanced Memory and Neural Computing · Machine Learning in Materials Science · Molecular Junctions and Nanostructures

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Faculty of Science and Engineering, Aoyama Gakuin University, 5-10-1 Fuchinobe, Sagamihara, Kanagawa 252-5258, Japan

Department of Electrical Engineering and Information Systems, The University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8505, Japan

National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba 305-8565, Japan

Department of Applied Physics, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan

Research Center for Electronic and Optical Materials, National Institute for Materials Science, 1-1 Namiki, Tsukuba 305-0044, Japan

Research Center for Materials Nanoarchitectonics, National Institute for Materials Science, 1-1 Namiki, Tsukuba 305-0044, Japan

Institute for Industrial Sciences, The University of Tokyo, 4-6-1 Komaba Meguro-ku, Tokyo 153-8505, Japan

The Institute of Scientific and Industrial Research, Osaka University, Mihogaoka 8-1, Osaka, Ibaraki 567-0047, Japan

Institute for AI and Beyond, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan

WPI Advanced Institute for Materials Research, Tohoku University, 2-1-1 Katahira, Aoba-ku, Sendai 980-8577, Japan

Advanced Science Research Center, Japan Atomic Energy Agency, 2-4 Shirakata, Tokai-mura, Naka-gun, Ibaraki 319-1195, Japan

Department of Mechanical Engineering, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan

Funding

Ministry of Education, Culture, Sports, Science and Technology · Research Institute, Aoyama Gakuin University · Core Research for Evolutional Science and Technology · Japan Society for the Promotion of Science

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