The discovery of graphene has opened a new research space into 2D carbon materials and has gained tremendous scientific attention about their fundamental properties and potential applications. [1-6] Up to now, numerous 2D carbon allotropes have been proposed and investigated, for instance, pentaheptites R 57-1 and R 57-2 , [7,8] Haeckelite sheets H 567 and O 567 , [8] octite SC, [9] SW-graphene, [10,11] Ψ-graphene, [12,13] T-graphene, [14] POgraphene, [15,16] HOP-graphene, [17] and pha-graphene. [18] These unique 2D carbon allotropes provide rich material platforms for designing and fabricating optoelectronic devices and realizing novel topological phenomena. [10,11,18] Among 2D carbon systems, the graphynes containing both sp and sp 2 hybridized carbon atoms form one of the biggest branches of graphene allotropes. [19] Early in 1987, this low-energy layered phase of carbon was predicted to be of hightemperature kinetic stability by Baughman. [20] The successful synthesis of γ-graphdiyne, β-graphdiyne, carbon ene-yne, and their derivants in experiments further inspired interest in such sp-sp 2 hybridized 2D carbon materials. [21-25] Due to the presence of acetylenic bonds associated with sp states, graphyne possesses exceptional flexibility in the geometric structure and thus exhibits many diverse allotropes, for instance, α-graphyne, β-graphyne, γ-graphyne, R-graphyne, and 6,6,12graphyne. [26-28] In addition to the various structures, fascinating physical and chemical properties have also been predicted for the graphyne family. Because of the Kekule-distortion effect, γ-graphyne and graphdiyne are semiconductors with a moderate bandgap and excellent carrier mobility. [27,29] Benefiting from the insertion of acetylenic linkages, the thermal conductance of graphyne is fundamentally lower than that of graphene, and thus leads to its preeminent thermoelectric conversion efficiency. [30-32] Due to the intrinsic hollow structures, graphyne can adsorb ions effectively or filter molecular selectively, making it a promising candidate material for electrodes or molecular sieves. [33,34] More interestingly, Dirac-cone-characterized electronic band structures are revealed not only in hexagonal graphyne (α-graphyne, [27] Pal-graphyne, [35] δ-graphyne, [36] and circumcoro-graphyne [37]), but also in orthorhombic crystal structures (β-graphyne, [27] 6,6,12-graphyne, [19] S-graphynes, [38] cp-graphyne, [39] 14,14,14-graphyne, [40] and 14,14,18-graphyne [40]).
In this paper, 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 all 16512 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 genetic algorithm, it is revealed that the efficiency of 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 pa-per 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.
Ferroelastic materials possess two or more equally stable orientation variants and can be effectively modulated via external fields, including stress and electronic field. In this paper, taking the VA-N ferroelastic materials as examples, we propose a thermal switch device based on their ferroelastic characteristics. The results show that the VA-N binary compound exhibits excellent ferroelasticity, high reversible elastic strain (5.5%–54.1%), and suitable switching energy barriers (0.012–0.386 eV/atom) in both δ and α phases. Utilizing the advanced on-the-fly machine learning potential, we obtain physically well-defined quadratic dispersion curves in the long-wavelength limit and further evaluate their lattice thermal conductivity of δ and α phase VA-N binary compounds. Due to the difference in phonon group velocities, the lattice thermal conductivity of VA-N binary compounds along the armchair direction is obviously smaller than that along the zigzag direction. Such remarkable anisotropy and easily switchable features based on ferroelasticity endow reversible and real-time regulation of thermal conductivity of VA-N binary compounds. The ferroelastic-based thermal switch hosts high switch ratios range from 2.08 to 5.99 and does not require additional energy to maintain the modulation state. The results presented herein provide a pavement for designing next-generation thermal switches and propose a reliable solution for eliminating the nonphysical pseudo-phenomenon of phonon dispersion curve violation of quadratic dispersion in the long-wavelength limit.
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