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Author |
Chen, X.; Bouhon, A.; Li, L.; Peeters, F.M.; Sanyal, B. |
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Title |
PAI-graphene : a new topological semimetallic two-dimensional carbon allotrope with highly tunable anisotropic Dirac cones |
Type |
A1 Journal article |
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Year  |
2020 |
Publication |
Carbon |
Abbreviated Journal |
Carbon |
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Volume |
170 |
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Pages |
477-486 |
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Keywords |
A1 Journal article; Condensed Matter Theory (CMT) |
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Abstract |
Using evolutionary algorithm for crystal structure prediction, we present a new stable two-dimensional (2D) carbon allotrope composed of polymerized as-indacenes (PAI) in a zigzag pattern, namely PAI-graphene whose energy is lower than most of the reported 2D allotropes of graphene. Crucially, the crystal structure realizes a nonsymmorphic layer group that enforces a nontrivial global topology of the band structure with two Dirac cones lying perfectly at the Fermi level. The absence of electron/hole pockets makes PAI-graphene a pristine crystalline topological semimetal having anisotropic Fermi velocities with a high value of 7.0 x 10(5) m/s. We show that while the semimetallic property of the allotrope is robust against the application of strain, the positions of the Dirac cone and the Fermi velocities can be modified significantly with strain. Moreover, by combining strain along both the x- and y-directions, two band inversions take place at G leading to the annihilation of the Dirac nodes demonstrating the possibility of strain-controlled conversion of a topological semimetal into a semiconductor. Finally we formulate the bulk-boundary correspondence of the topological nodal phase in the form of a generalized Zak-phase argument finding a perfect agreement with the topological edge states computed for different edge-terminations. (C) 2020 The Author(s). Published by Elsevier Ltd. |
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Wos |
000579779800047 |
Publication Date |
2020-08-21 |
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ISSN |
0008-6223 |
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Additional Links |
UA library record; WoS full record; WoS citing articles |
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Impact Factor |
10.9 |
Times cited |
43 |
Open Access |
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Notes |
; We thank S. Nahas, for helpful discussions. This work is supported by the project grant (2016e05366) and Swedish Research Links program grant (2017e05447) from the Swedish Research Council, the Fonds voor Wetenschappelijk Onderzoek (FWO-Vl), the FLAG-ERA project TRANS 2D TMD. Linyang Li acknowledges financial support from the Natural Science Foundation of Hebei Province (Grant No. A2020202031). X.C. thanks China scholarship council for financial support (No. 201606220031). X.C. and B.S. acknowledge SNIC-UPPMAX, SNIC-HPC2N, and SNIC-NSC centers under the Swedish National Infrastructure for Computing (SNIC) resources for the allocation of time in high-performance supercomputers. Moreover, supercomputing resources from PRACE DECI-15 project DYNAMAT are gratefully acknowledged. ; |
Approved |
Most recent IF: 10.9; 2020 IF: 6.337 |
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Call Number |
UA @ admin @ c:irua:173513 |
Serial |
6577 |
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