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Reconfigurable Phototransistors Driven by Gate-Dependent Carrier Modulation in WSe<sub>2</sub>/Ta<sub>2</sub>NiSe<sub>5</sub> van der Waals Heterojunctions

Tingting Guo, Zhidong Pan, Jing Li, Zixu Sa, Xusheng Wang, Yehui Shen, Jialin Yang, Chuyao Chen, Tong Zhao, Zhi Li, Xiang Chen, Zaixing Yang, Gangyi Zhu, Nengjie Huo, Xiufeng Song, Shengli Zhang, Haibo Zeng

2024ACS Nano22 citationsDOI

Abstract

Reconfigurable field-effect transistors (RFETs) offer notable benefits on electronic and optoelectronic logic circuits, surpassing the integration, flexibility, and cost-efficiency of conventional complementary metal-oxide semiconductor transistors. The low on/off current ratio of these transistors remains a considerable impediment in the practical application of RFETs. To overcome these limitations, a van der Waals heterojunction (vdWH) transistor composed of WSe 2 /Ta 2 NiSe 5 has been proposed. By modulating a single back-gate voltage and source-drain voltage inputs, the transistor achieves a switchable polarity configuration and bidirectional rectification, making it capable of functioning as a gate-controlled bidirectional half-wave rectifier. The proposed RFET exhibits tunable positive/negative photovoltaic responses, advanced optoelectronic performance, and a gate-voltage-dependent reversal of the photodetector position. Detailed energy band diagram studies have shown that the reconfigurability of the device arises from carrier blockage resulting from the type-I band structure and carrier injection modulated by gate-dependent Schottky barriers. Consequently, the reconfigurable WSe 2 /Ta 2 NiSe 5 vdWH holds significant promise for advanced multifunctional optoelectronic device applications.

Topics & Concepts

TransistorHeterojunctionvan der Waals forceMaterials scienceOptoelectronicsFlexibility (engineering)Field-effect transistorElectronic circuitSemiconductorNanotechnologyElectrical engineeringPhysicsMoleculeVoltageEngineeringMathematicsStatisticsQuantum mechanics2D Materials and ApplicationsAdvanced Memory and Neural ComputingMXene and MAX Phase Materials