Adaptive genetic algorithm-based design of gamma-graphyne nanoribbon incorporating diamond-shaped segment with high thermoelectric conversion efficiency  

作　　者：陆静远 崔春凤 欧阳滔 李金 何朝宇 唐超 钟建新 Jingyuan Lu;Chunfeng Cui;Tao Ouyang;Jin Li;Chaoyu He;Chao Tang;Jianxin Zhong(School of Physics and Optoelectronics,Xiangtan University,Xiangtan 411105,China;Hunan Key Laboratory for Micro-Nano Energy Materials and Device,Xiangtan University,Xiangtan 411105,China)

机构地区：[1]School of Physics and Optoelectronics,Xiangtan University,Xiangtan 411105,China [2]Hunan Key Laboratory for Micro-Nano Energy Materials and Device,Xiangtan University,Xiangtan 411105,China

出　　处：《Chinese Physics B》2023年第4期109-117,共9页中国物理B（英文版）

基　　金：Project supported by the National Natural Science Foundation of China(Grant Nos.11974300,11974299,12074150);the Natural Science Foundation of Hunan Province,China(Grant No.2021JJ30645);Scientific Research Fund of Hunan Provincial Education Department(Grant Nos.20K127,20A503,and 20B582);Program for Changjiang Scholars and Innovative Research Team in University(Grant No.IRT13093);the Hunan Provincial Innovation Foundation for Postgraduate(Grant No.CX20220544);Youth Science and Technology Talent Project of Hunan Province,China(Grant No.2022RC1197)。

摘　　要：The gamma-graphyne nanoribbons(γ-GYNRs) incorporating diamond-shaped segment(DSSs) with excellent thermoelectric properties are systematically investigated by combining nonequilibrium Green’s functions with adaptive genetic algorithm. Our calculations show that the adaptive genetic algorithm is efficient and accurate in the process of identifying structures with excellent thermoelectric performance. In multiple rounds, an average of 476 candidates(only 2.88% of all16512 candidate structures) are calculated to obtain the structures with extremely high thermoelectric conversion efficiency.The room temperature thermoelectric figure of merit(ZT) of the optimal γ-GYNR incorporating DSSs is 1.622, which is about 5.4 times higher than that of pristine γ-GYNR(length 23.693 nm and width 2.660 nm). The significant improvement of thermoelectric performance of the optimal γ-GYNR is mainly attributed to the maximum balance of inhibition of thermal conductance(proactive effect) and reduction of thermal power factor(side effect). Moreover, through exploration of the main variables affecting the genetic algorithm, it is revealed that the efficiency of the genetic algorithm can be improved by optimizing the initial population gene pool, selecting a higher individual retention rate and a lower mutation rate. The results presented in this paper validate the effectiveness of genetic algorithm in accelerating the exploration of γ-GYNRs with high thermoelectric conversion efficiency, and could provide a new development solution for carbon-based thermoelectric materials.

关 键 词：adaptive genetic algorithm thermoelectric material diamond-like quantum dots gamma-graphyne nanoribbon 

分 类 号：TQ127.11[化学工程—无机化工] TB383.1[一般工业技术—材料科学与工程] TP18[自动化与计算机技术—控制理论与控制工程]