Janus Electronic Devices with Ultrathin High-κ Gate Dielectric Directly Integrated on 1T′-MoTe<sub>2</sub>

Integrating high-quality dielectrics with two-dimensional (2D) transition metal chalcogenides (TMDCs) is crucial for high-performance electronics. However, the lack of dangling bonds on 2D material surfaces complicates direct dielectric deposition. We propose using atomic layer deposition (ALD) to integrate ultrathin high-κ dielectric directly on 1T'-MoTe<sub>2</sub> surfaces, facilitating the creation of high-performance back-gated field-effect transistors (FETs). Exploiting 1T'-MoTe<sub>2</sub>'s natural oxidation in ambient conditions, we directly deposit dense and uniform HfO<sub>2</sub> dielectric films below 5 nm, achieving an equivalent oxide thickness (EOT) of 0.97 nm. The resulting back-gate transistors, with a monolayer MoSSe on HfO<sub>2</sub>/1T'-MoTe<sub>2</sub>, show a current on/off ratio over 10<sup>5</sup> and operate at low voltages (<1 V), indicating high gating efficiency and a charge carrier mobility of 2.93 cm<sup>2</sup>V<sup>-1</sup>s<sup>-1</sup>. Additionally, we demonstrate a 6 × 5 bottom-gated array of MoSSe transistors using all-1T'-MoTe<sub>2</sub> electrodes, achieving an 86.7% sample yield. Our approach also enables the creation of various integrated logic circuits such as inverters, NAND, and NOR gates. This research offers a feasible method for integrating high-κ dielectric films using industrially compatible ALD processes, providing excellent thickness control, uniformity, and scalability for 2D electronic devices.

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Publication Details

Journal
ACS Applied Materials & Interfaces
Published
2024-11-27
DOI
https://doi.org/10.1021/acsami.4c15216
Citations
6
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
1.25

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article

Janus Electronic Devices with Ultrathin High-κ Gate Dielectric Directly Integrated on 1T′-MoTe2

Junhao Tang, Runze Zhan, Xi Wan, Yaoyu Duan et al.
6 citations
ACS Applied Materials & Interfaces
Advanced Memory and Neural Computing
1.25
article

Janus Electronic Devices with Ultrathin High-κ Gate Dielectric Directly Integrated on 1T′-MoTe2

Junhao Tang, Runze Zhan, Xi Wan, Yaoyu Duan, Enzi Chen, Qing Zhu, Shaozhi Deng, Kun Chen, Jingwen Huang
article en
6 citations

Abstract

Integrating high-quality dielectrics with two-dimensional (2D) transition metal chalcogenides (TMDCs) is crucial for high-performance electronics. However, the lack of dangling bonds on 2D material surfaces complicates direct dielectric deposition. We propose using atomic layer deposition (ALD) to integrate ultrathin high-κ dielectric directly on 1T'-MoTe<sub>2</sub> surfaces, facilitating the creation of high-performance back-gated field-effect transistors (FETs). Exploiting 1T'-MoTe<sub>2</sub>'s natural oxidation in ambient conditions, we directly deposit dense and uniform HfO<sub>2</sub> dielectric films below 5 nm, achieving an equivalent oxide thickness (EOT) of 0.97 nm. The resulting back-gate transistors, with a monolayer MoSSe on HfO<sub>2</sub>/1T'-MoTe<sub>2</sub>, show a current on/off ratio over 10<sup>5</sup> and operate at low voltages (<1 V), indicating high gating efficiency and a charge carrier mobility of 2.93 cm<sup>2</sup>V<sup>-1</sup>s<sup>-1</sup>. Additionally, we demonstrate a 6 × 5 bottom-gated array of MoSSe transistors using all-1T'-MoTe<sub>2</sub> electrodes, achieving an 86.7% sample yield. Our approach also enables the creation of various integrated logic circuits such as inverters, NAND, and NOR gates. This research offers a feasible method for integrating high-κ dielectric films using industrially compatible ALD processes, providing excellent thickness control, uniformity, and scalability for 2D electronic devices.

ACS Applied Materials & InterfacesVol. 16(49)
Jiangnan University (CN), Sun Yat-sen University (CN)
National Natural Science Foundation of China, Guangdong Provincial Pearl River Talents Program, Basic and Applied Basic Research Foundation of Guangdong Province
Affordable and clean energy
Openalex Percentile: Top 20%
Advanced Memory and Neural Computing
1.25
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