4.5 Article

C-57 carbon: A two-dimensional metallic carbon allotrope with pentagonal and heptagonal rings

期刊

COMPUTATIONAL MATERIALS SCIENCE
卷 160, 期 -, 页码 115-119

出版社

ELSEVIER
DOI: 10.1016/j.commatsci.2018.12.035

关键词

Two-dimensional; Carbon allotrope; Metallicity; Carbon nanotube

资金

  1. National Natural Science Foundation of China [11504332]
  2. Outstanding Young Talent Research Fund of Zhengzhou University [1521317006]

向作者/读者索取更多资源

By means of the first-principles calculations, we have theoretically investigated the structural stability and electronic properties of a two-dimensional planar metallic carbon allotrope named C-57 carbon which possesses the P (6) over bar 2m (D-3h(3)) symmetry. This carbon allotrope is an all-sp(2) hybridized bonding network consisting of 5-7 rings of carbon atoms. The stability of C-57 carbon is confirmed through phonon-mode analysis, total energy and elastic constants calculations, as well as first-principles molecular dynamics simulations. We conceived that the metallicity of C-57 carbon is attributed to the large states across Fermi-level contributed by p(y) orbital due to the bond distortion, which is much different from that of graphite. This new carbon sheet can also serve as a precursor for stable one-dimensional nanotubes with metallic character. These results broaden our understanding of two-dimensional carbon allotropes and will attract more researchers to focus the research on the field of two-dimensional carbon materials. Besides, the C-57 carbon may be useful for designing of nano-electronic devices.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.5
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

Article Physics, Multidisciplinary

Activating MoS2 basal planes for hydrogen evolution through the As doping and strain

Yi-Qi Yang, Chun-Xiang Zhao, Shou-Yan Bai, Cai-Ping Wang, Chun-Yao Niu

PHYSICS LETTERS A (2019)

Article Physics, Applied

Ferromagnetic, antiferromagnetic, and Peierls distortion states in IVA-VA nanoribbons

Shouyan Bai, Chun-Yao Niu, Chong Li, Chunxiang Zhao, Yu Jia

APPLIED PHYSICS LETTERS (2019)

Article Physics, Condensed Matter

Arsenic K4 crystal: A new stable direct-gap semiconductor allotrope

Caiping Wang, Shouyan Bai, Chunxiang Zhao, Weiyang Yu, Yi Yang, Youmei Chen, Chun-Yao Niu

Summary: Researchers have identified a new phase of arsenic, named K-4 arsenic, through ab initio calculations, which has been confirmed to be a direct-gap semiconductor that can effectively modulate its band gap by pressure. The material exhibits strong light absorption in the visible region, showing potential applications in photocatalysts and optoelectronics.

SOLID STATE COMMUNICATIONS (2021)

Article Multidisciplinary Sciences

Structural, Topological, and Superconducting Properties of Two-Dimensional Tellurium Allotropes from Ab Initio Predictions

Chunxiang Zhao, Xiaolin Cai, Liangliang Liu, Chengyan Liu, Zaiping Zeng, Chunyao Niu, Congxin Xia, Yu Jia

Summary: The discovery of 31 2D tellurium allotropes with different cohesive energies and properties, including semiconductors, topological insulators, and superconductors, enriches the field of 2D elemental materials. One of these allotropes exhibits both topological and superconducting properties, which is unique in the reported elemental 2D materials. This research provides rich possibilities for exploring novel functionalities for future device applications.

ADVANCED THEORY AND SIMULATIONS (2021)

Article Physics, Multidisciplinary

Computational Prediction of a Novel Superhard sp 3 Trigonal Carbon Allotrope with Bandgap Larger than Diamond

Ruoyun Lv, Xigui Yang, Dongwen Yang, Chunyao Niu, Chunxiang Zhao, Jinxu Qin, Jinhao Zang, Fuying Dong, Lin Dong, Chongxin Shan

Summary: The study identified and verified a new superhard carbon phase, tri-C-18 carbon, with high bulk modulus and Vickers hardness, as well as potential applications in deep ultraviolet electronic or optoelectronic devices based on its electronic band structure.

CHINESE PHYSICS LETTERS (2021)

Article Chemistry, Multidisciplinary

Equally Spaced Quantum States in van der Waals Epitaxy-Grown Nanoislands

Chaofei Liu, Chunxiang Zhao, Shan Zhong, Cheng Chen, Zhenyu Zhang, Yu Jia, Jian Wang

Summary: The study reveals equally spaced, sharp, and densely distributed quantum well states near the Fermi energy on Pb(111) nanoislands, explained as quantized energy of confined linearly dispersive [111] electrons with enhanced relativistic nature due to spin-orbit coupling. This finding provides a new theoretical basis for the unique quantum states in electronic systems beyond Landau levels.

NANO LETTERS (2021)

Article Chemistry, Physical

Computational and experimental studies on band alignment of ZnO/InxGa2-xO3/GaN heterojunctions

Xilai Liu, Chunxiang Zhao, Chunyao Niu, Yu Jia

Summary: In this study, n-ZnO/beta-InxGa(2-x)O(3)/p-GaN heterojunctions were successfully fabricated using atomic layer deposition methods, and it was demonstrated that the band edges of the heterojunctions can be effectively tuned by In doping. First-principle calculations revealed that with increasing In contents, the bandgap of β-InxGa(2-x)O(3) decreased linearly, accompanied by movements of the valence band maximum and the conduction band minimum. In doping induced a broad, reddish yellow-green emission, confirming the effect of band alignment. This work provides a pathway to tunable heterojunctions with adjustable band offsets, which can be employed for the further development of direct white light-emitting diodes without phosphors.

JOURNAL OF CHEMICAL PHYSICS (2023)

Article Physics, Multidisciplinary

Solving 2D and 3D Lattice Models of Correlated Fermions-Combining Matrix Product States with Mean-Field Theory

Gunnar Bollmark, Thomas Kohler, Lorenzo Pizzino, Yiqi Yang, Johannes S. Hofmann, Hao Shi, Shiwei Zhang, Thierry Giamarchi, Adrian Kantian

Summary: Correlated electron states are crucial for understanding unconventional superconductivity. However, calculating their properties accurately remains a challenge. In this work, we propose a framework combining matrix product states (MPS) with mean field (MF) to compute the properties of quasi-one-dimensional (Q1D) systems. We demonstrate the effectiveness of this framework by calculating the critical temperature for superconductivity in Q1D fermions. This approach allows for the quantitative study of correlated phases and the treatment of competing macroscopic orders.

PHYSICAL REVIEW X (2023)

Article Chemistry, Physical

White light emitting diodes based on lanthanide ions doped Cs2NaInCl6 double perovskites

Xueguo Li, Hao Liang, Changbo Zheng, Chunxiang Zhao, Songchao Bai, Xueqing Zhao, Hao Zhang, Yongsheng Zhu

Summary: Lead-free halide double perovskite crystals (Cs2NaInCl6:Sb3+) with excellent blue emission and the ability for multicolor emissions through lanthanide ion doping were prepared. The emission colors can be continuously adjusted by altering the doping levels of lanthanide ions. The findings provide deep insights for the designing of multicolor double perovskite phosphors.

JOURNAL OF ALLOYS AND COMPOUNDS (2023)

Article Chemistry, Physical

The structural, electronic and optical properties of four α-Se-based heterostructures with hyperbolic characteristics

Chunxiang Zhao, Jiaqi Wang, Xiaolin Cai, Panpan Wang, Zhili Zhu, Chunyao Niu, Yu Jia

Summary: In this work, the structural, electronic, and optical properties of four alpha-Se-based VDWHs were systematically investigated using first-principles calculations based on density functional theory. The results showed that the electronic properties and optical absorption of these VDWHs can be effectively modulated by interlayer coupling, biaxial strain, and an external electric field, enhancing their potential applications in electronic and optoelectronic devices.

PHYSICAL CHEMISTRY CHEMICAL PHYSICS (2022)

Article Chemistry, Physical

Formation of stable polonium monolayers with tunable semiconducting properties driven by strong quantum size effects

Chunxiang Zhao, Xiaolin Cai, Xilai Liu, Junfei Wang, Weiguang Chen, Liying Zhang, Yinuo Zhang, Zhili Zhu, Chengyan Liu, Chunyao Niu, Yu Jia

Summary: This study demonstrates that polonium can form stable 2D monolayers with strong semiconducting properties. The monolayers can be achieved through a spontaneous phase transition of ultrathin films and exhibit unique van der Waals interactions. These findings contribute to the understanding of the formation mechanism of 2D materials.

PHYSICAL CHEMISTRY CHEMICAL PHYSICS (2022)

Review Physics, Condensed Matter

Tellurene: An elemental 2D monolayer material beyond its bulk phases without van der Waals layered structures

Xiaolin Cai, Xiaoyu Han, Chunxiang Zhao, Chunyao Niu, Yu Jia

JOURNAL OF SEMICONDUCTORS (2020)

Article Physics, Multidisciplinary

A superhard carbon allotrope: sc-C46 carbon

Chunxiang Zhao, Jiaqi Wang, Caiping Wang, Chunyao Niu, Jiantao Wang, Yu Jia

Correction Materials Science, Multidisciplinary

Efficiency and accuracy of GPU-parallelized Fourier spectral methods for solving phase-field models (vol 228, ,112313, 2023)

A. D. Boccardo, M. Tong, S. B. Leen, D. Tourret, J. Segurado

COMPUTATIONAL MATERIALS SCIENCE (2024)

Article Materials Science, Multidisciplinary

Deep learning interatomic potential for thermal and defect behaviour of aluminum nitride with quantum accuracy

Tao Li, Qing Hou, Jie-chao Cui, Jia-hui Yang, Ben Xu, Min Li, Jun Wang, Bao-qin Fu

Summary: This study investigates the thermal and defect properties of AlN using molecular dynamics simulation, and proposes a new method for selecting interatomic potentials, developing a new model. The developed model demonstrates high computational accuracy, providing an important tool for modeling thermal transport and defect evolution in AlN-based devices.

COMPUTATIONAL MATERIALS SCIENCE (2024)

Article Materials Science, Multidisciplinary

Illuminating the mechanical responses of amorphous boron nitride through deep learning: A molecular dynamics study

Shin-Pon Ju, Chao-Chuan Huang, Hsing-Yin Chen

Summary: Amorphous boron nitride (a-BN) is a promising ultralow-dielectric-constant material for interconnect isolation in integrated circuits. This study establishes a deep learning potential (DLP) for different forms of boron nitride and uses molecular dynamics simulations to investigate the mechanical behaviors of a-BN. The results reveal the structure-property relationships of a-BN, providing useful insights for integrating it in device applications.

COMPUTATIONAL MATERIALS SCIENCE (2024)

Article Materials Science, Multidisciplinary

Multiscale modeling of shape memory polymers foams nanocomposites

M. Salman, S. Schmauder

Summary: Shape memory polymer foams (SMPFs) are lightweight cellular materials that can recover their undeformed shape through external stimulation. Reinforcing the material with nano-clay filler improves its physical properties. Multiscale modeling techniques can be used to study the thermomechanical response of SMPFs and show good agreement with experimental results.

COMPUTATIONAL MATERIALS SCIENCE (2024)

Article Materials Science, Multidisciplinary

DFT study on zeolites' intrinsic Brønsted acidity: The case of BEA

Laura Gueci, Francesco Ferrante, Marco Bertini, Chiara Nania, Dario Duca

Summary: This study investigates the acidity of 30 Bronsted sites in the beta-zeolite framework and compares three computational methods. The results show a wide range of deprotonation energy values, and the proposed best method provides accurate calculations.

COMPUTATIONAL MATERIALS SCIENCE (2024)

Article Materials Science, Multidisciplinary

Unveiling the CO2 adsorption capabilities of biphenylene network monolayers through DFT calculations

K. A. Lopes Lima, L. A. Ribeiro Junior

Summary: Advancements in nanomaterial synthesis and characterization have led to the discovery of new carbon allotropes, including biphenylene network (BPN). The study finds that BPN lattices with a single-atom vacancy exhibit higher CO2 adsorption energies than pristine BPN. Unlike other 2D carbon allotropes, BPN does not exhibit precise CO2 sensing and selectivity by altering its band structure configuration.

COMPUTATIONAL MATERIALS SCIENCE (2024)

Article Materials Science, Multidisciplinary

Ab-initio study of quaternary Heusler alloys LiAEFeSb (AE = Be, Mg, Ca, Sr or Ba) and prediction of half-metallicity in LiSrFeSb and LiBaFeSb

Jay Kumar Sharma, Arpita Dhamija, Anand Pal, Jagdish Kumar

Summary: In this study, the quaternary Heusler alloys LiAEFeSb were investigated for their crystal structure, electronic properties, and magnetic behavior. Density functional theory calculations revealed that LiSrFeSb and LiBaFeSb exhibit half-metallic band structure and 100% spin polarization, making them excellent choices for spintronic applications.

COMPUTATIONAL MATERIALS SCIENCE (2024)

Article Materials Science, Multidisciplinary

Graph neural networks for predicting structural stability of Cd- and Zn-doped-CsPbI3

Roman A. Eremin, Innokentiy S. Humonen, Alexey A. Kazakov, Vladimir D. Lazarev, Anatoly P. Pushkarev, Semen A. Budennyy

Summary: Computational modeling of disordered crystal structures is essential for studying composition-structure-property relations. In this work, the effects of Cd and Zn substitutions on the structural stability of CsPbI3 were investigated using DFT calculations and GNN models. The study achieved accurate energy predictions for structures with high substitution contents, and the impact of data subsampling on prediction quality was comprehensively studied. Transfer learning routines were also tested, providing new perspectives for data-driven research of disordered materials.

COMPUTATIONAL MATERIALS SCIENCE (2024)

Article Materials Science, Multidisciplinary

Insight into effect of high pressure on the structural, electronic, and optical properties of KH2PO4

Zhixin Sun, Hang Dong, Yaohui Yin, Ai Wang, Zhen Fan, Guangyong Jin, Chao Xin

Summary: In this study, the crystal structure, electronic structure, and optical properties of KH2PO4: KDP crystals under different pressures were investigated using the generalized gradient approximate. It was found that high pressure caused a phase transition in KDP and greatly increased the band gap. The results suggest that high pressure enhances the compactness of KDP and improves the laser damage threshold.

COMPUTATIONAL MATERIALS SCIENCE (2024)

Article Materials Science, Multidisciplinary

Phenomenon of anti-driving force during grain boundary migration

Tingting Yu

Summary: This study presents atomistic simulations revealing that an increase in driving force may result in slower grain boundary movement and switches in the mode of grain boundary shear coupling migration. Shear coupling behavior is found to effectively alleviate stress and holds potential for stress relaxation and microstructure manipulation in materials.

COMPUTATIONAL MATERIALS SCIENCE (2024)

Article Materials Science, Multidisciplinary

The electronic properties of C2N/antimonene heterostructure regulated by the horizontal and vertical strain, external electric field and interlayer twist

Y. Zhang, X. Q. Deng, Q. Jing, Z. S. Zhang

Summary: The electronic properties of C2N/antimonene van der Waals heterostructure are investigated using density functional theory. The results show that by applying horizontal strain, vertical strain, electric field, and interlayer twist, the electronic structure can be adjusted. Additionally, the band alignment and energy states of the heterostructure can be significantly changed by applying vertical strain on the twisted structure. These findings are important for controlling the electronic properties of heterostructures.

COMPUTATIONAL MATERIALS SCIENCE (2024)

Article Materials Science, Multidisciplinary

Functionalized carbophenes as high-capacity versatile gas adsorbents: An ab initio study

Chad E. Junkermeier, Evan Larmand, Jean-Charles Morais, Jedediah Kobebel, Kat Lavarez, R. Martin Adra, Jirui Yang, Valeria Aparicio Diaz, Ricardo Paupitz, George Psofogiannakis

Summary: This study investigates the adsorption properties of carbon dioxide (CO2), methane (CH4), and dihydrogen (H2) in carbophenes functionalized with different groups. The results show that carbophenes can be promising adsorbents for these gases, with high adsorption energies and low desorption temperatures. The design and combination of functional groups can further enhance their adsorption performance.

COMPUTATIONAL MATERIALS SCIENCE (2024)

Article Materials Science, Multidisciplinary

Insights from symmetry: Improving machine-learned models for grain boundary segregation

Y. Borges, L. Huber, H. Zapolsky, R. Patte, G. Demange

Summary: Grain boundary structure is closely related to solute atom segregation, and machine learning can predict the segregation energy density. The study provides a fresh perspective on the relationship between grain boundary structure and segregation properties.

COMPUTATIONAL MATERIALS SCIENCE (2024)

Article Materials Science, Multidisciplinary

Phase-field dislocation dynamics simulations of temperature-dependent glide mechanisms in niobium

M. R. Jones, L. T. W. Fey, I. J. Beyerlein

Summary: In this work, a three-dimensional ab-initio informed phase-field-dislocation dynamics model combined with Langevin dynamics is used to investigate glide mechanisms of edge and screw dislocations in Nb at finite temperatures. It is found that the screw dislocation changes its mode of glide at two distinct temperatures, which coincides with the thermal insensitivity and athermal behavior of Nb yield strengths.

COMPUTATIONAL MATERIALS SCIENCE (2024)

Article Materials Science, Multidisciplinary

Spline-based neural network interatomic potentials: Blending classical and machine learning models

Joshua A. Vita, Dallas R. Trinkle

Summary: This study introduces a new machine learning model framework that combines the simplicity of spline-based potentials with the flexibility of neural network architectures. The simplified version of the neural network potential can efficiently describe complex datasets and explore the boundary between classical and machine learning models. Using spline filters for encoding atomic environments results in interpretable embedding layers that can incorporate expected physical behaviors and improve interpretability through neural network modifications.

COMPUTATIONAL MATERIALS SCIENCE (2024)