Zhanjun Qiu

Chongqing University of Posts and Telecommunications

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Dengfeng Li

Chongqing University of Posts and Telecommunications

Yanxiao Hu

Chongqing University of Posts and Telecommunications

Tao Hu

Shanghai University

Xiaotian Wang

University of Wollongong

Ding Li

Chongqing University of Posts and Telecommunications

Jie Li

Peking University

Chunbao Feng

Chongqing University of Posts and Telecommunications

Gang Zhang

Sichuan Cancer Hospital

Bo-Lin Li

University of Electronic Science and Technology of China

Guangyu Yang

Jilin University of Chemical Technology

Cooperative Institutions

Chongqing University of Posts and Telecommunications

Chongqing University

Southwest University

Shanghai University

Huazhong University of Science and Technology

Xi'an Jiaotong University

Nankai University

Hohai University

Beijing Institute of Technology

University of Electronic Science and Technology of China

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Cr₃X₄ (X = Se, Te) monolayers as a new platform to realize robust spin filters, spin diodes and spin valves

Physical Chemistry Chemical Physics (2022)

Qihong Wu Rongkun Liu Zhanjun Qiu Dengfeng Li Jie Li

Two-dimensional ferromagnetic (FM) half-metals are promising candidates for advanced spintronic devices with small size and high capacity. Motivated by a recent report on controlling the synthesis of FM Cr3Te4 nanosheets, herein, to explore their potential application in spintronics, we designed spintronic devices based on Cr3X4 (X = Se, Te) monolayers and investigated their spin transport properties. We found that the Cr3Te4 monolayer based device shows spin filtering and a dual-spin diode effect when applying a bias voltage, while the Cr3Se4 monolayer is an excellent platform to realize a spin valve. These different transport properties are primarily ascribed to the semiconducting spin channel, which is close to and away from the Fermi level in Cr3Te4 and Cr3Se4 monolayers, respectively. Interestingly, the current in the Cr3Se4 monolayer based device also displays a negative differential resistance effect (NDRE) and a high magnetoresistance ratio (up to 2 × 103). Moreover, we found a thermally induced spin filtering effect and a NDRE at the Cr3Se4 junction under a temperature gradient instead of a bias voltage. These theoretical findings highlight the potential of Cr3X4 (X = Se, Te) monolayers in spintronic applications and put forward realistic materials to realize nanoscale spintronic devices.

Spin pumping

Spin valve

Biasing

10.1039/d2cp03615k

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Thermal transport properties of two-dimensional boron dichalcogenides from a first-principles and machine learning approach

Chinese Physics B (2023)

Zhanjun Qiu Yanxiao Hu Ding Li Tao Hu Hong Xiao

The investigation of thermal transport is crucial to the thermal management of modern electronic devices. To obtain the thermal conductivity through solution of the Boltzmann transport equation, calculation of the anharmonic interatomic force constants has a high computational cost based on the current method of single-point density functional theory force calculation. The recent suggested machine learning interatomic potentials (MLIPs) method can avoid these huge computational demands. In this work, we study the thermal conductivity of two-dimensional MoS 2 -like hexagonal boron dichalcogenides (H-B 2 VI 2 ; VI = S, Se, Te) with a combination of MLIPs and the phonon Boltzmann transport equation. The room-temperature thermal conductivity of H-B 2 S 2 can reach up to 336 W⋅m −1 ⋅K −1 , obviously larger than that of H-B 2 Se 2 and H-B 2 Te 2 . This is mainly due to the difference in phonon group velocity. By substituting the different chalcogen elements in the second sublayer, H-B 2 VIVI ′ have lower thermal conductivity than H-B 2 VI 2 . The room-temperature thermal conductivity of B 2 STe is only 11% of that of H-B 2 S 2 . This can be explained by comparing phonon group velocity and phonon relaxation time. The MLIP method is proved to be an efficient method for studying the thermal conductivity of materials, and H-B 2 S 2 -based nanodevices have excellent thermal conduction.

10.1088/1674-1056/acb9e6

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Abnormal strain-dependent thermal conductivity in biphenylene monolayer using machine learning interatomic potential

Applied Physics Letters (2023)

Guangyu Yang Yanxiao Hu Zhanjun Qiu Bo-Lin Li Ping Zhou

Applying tensile strain on an intrinsic lattice always results in the reduction in thermal conductivity due to the red-shift of phonon frequency and enhanced phonon anharmonicity. However, in this work, we explored an unexpected strain-enhanced thermal conductivity of a planar biphenylene network (BPN) in the frame of a Boltzmann transport equation combined with the machine learning interatomic potential. Under 5% biaxial tensile strain, the room temperature thermal conductivity of BPN reaches to about 4–5 times of that in an intrinsic sample. This phenomenon can be understood by considering a mirror symmetry induced phonon selection rule. This work highlights the significant effect of the selection rule on thermal transport and enriches the understanding of the thermal conductivity regulation in strained two-dimensional materials.

10.1063/5.0140014

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