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Rhombohedral B$_{12}$ unit is viewed as a host matrix embedding linear tri-atomic arrangements of elements (E) resulting in a relatively large family of boron-rich compounds with B$_{12}${E-E-E} generic formulation. The present work focuses…

Materials Science · Physics 2021-01-13 Samir F. Matar , Vladimir L. Solozhenko

Possible crystalline modifications of chemical compounds at low temperatures correspond to local minima of the energy landscape. Determining these minima via simulated annealing is one method for the prediction of crystal structures, where…

Materials Science · Physics 2008-10-31 K. Doll , J. C. Schoen , M. Jansen

We report the growth of high quality rhombohedral boron nitride (rBN) crystals by the iron flux method at atmospheric pressure. In contrast to the lamellar structure of standard hexagonal boron nitride (hBN) covering the metal ingot, the…

Materials Science · Physics 2025-09-23 W. Desrat , M. Moret , J. Plo , T. Michel , A. Ibanez , P. Valvin , V. Jacques , I. Philip-Robert , G. Cassabois , B. Gil

Hexagonal boron nitride (hBN) is an emerging layered material that plays a key role in a variety of two-dimensional devices, and has potential applications in nanophotonics and nanomechanics. Here, we demonstrate the first cavity…

Microstructure and mechanical properties of bulk polycristalline rhombohedral boron subnitride B13N2 synthesized by crystallization from the B-BN melt at 7 GPa have been systematically studied by micro- and nanoindentation, atomic force…

Materials Science · Physics 2017-12-08 Vladimir L. Solozhenko , Volodymyr Bushlya

Monolayer hexagonal boron nitride (hBN) has recently become the focus of intense research as a material to host quantum emitters. Although it is well known that such emission is associated with point defects, so far no conclusive…

Optically-active spin defects in hexagonal boron nitride (hBN) are promising quantum systems for the design of two-dimensional quantum sensing units offering optimal proximity to the sample being probed. In this work, we first demonstrate…

Improving the film quality in the synthesis of large-area hexagonal boron nitride films (h-BN) for two-dimensional material devices remains a great challenge. The measurement of electrical breakdown dielectric strength (EBD) is one of the…

Materials Science · Physics 2017-01-04 Yoshiaki Hattori , Takashi Taniguchi , Kenji Watanabe , Kosuke Nagashio

Boron nitride structures have excellent thermal and chemical stabilities. Based on state-of-art theoretical calculations, we propose a wide gap semiconducting BN crystal with a three-dimensional hyperhoneycomb structure (Hp-BN), which is…

Materials Science · Physics 2017-10-18 Jin Yu , Lihua Qu , Edo van Veen , Mikhail I. Katsnelson , Shengjun Yuan

Two-dimensional boron (borophene) is featured by its structural polymorphs and distinct in-plane anisotropy, opening opportunities to achieve tailored electronic properties by intermixing different phases. Here, using scanning tunneling…

Materials Science · Physics 2019-04-23 Longjuan Kong , Liren Liu , Lan Chen , Qing Zhong , Peng Cheng , Hui Li , Zhuhua Zhang , Kehui Wu

We present an ab-initio study of boron nitride as well as carbon allotropes. Their relative thermodynamic stabilities and structural phase transitions from low- to high-density phases are investigated. Pressure-temperature phase diagrams…

Materials Science · Physics 2019-02-22 Thomas Gruber , Andreas Grüneis

In this paper, three novel metallic sp2/sp3 -hybridized Boron Nitride (BN) polymorphs are proposed by first-principles calculations. One of them, named as tP-BN, is predicted based on the evolutionary particle swarm structural search. tP-BN…

Materials Science · Physics 2019-12-12 Mei Xiong , Zhibin Gao , Kun Luo , FeiFei Ling , YuFei Gao , Chong Chen , Dongli Yu , Zhisheng Zhao , Shizhong Wei

In the wide world of 2D materials, hexagonal boron nitride (hBN) holds a special place due to its excellent characteristics. In addition to its thermal, chemical and mechanical stability, hBN demonstrates high thermal conductivity, low…

Boron nitride is a promising material for nanotechnology applications due to its two-dimensional graphene-like, insulating, and highly-resistant structure. Recently it has received a lot of attention as a substrate to grow and isolate…

Materials Science · Physics 2013-09-25 Claudio Attaccalite , Ludger Wirtz , Andrea Marini , Angel Rubio

Carbon nanomembranes (CNMs) are nanometer-thin disordered carbon materials that are suitable for a range of applications, from energy generation and storage, through to water filtration. The structure-property relationships of these…

Hexagonal boron nitride (hBN) and black phosphorus (bP) are crystalline materials that can be seen as ordered stackings of two-dimensional layers, which lead to outstanding anisotropic physical properties. The knowledge of the thermal…

We apply first-principles calculations to study the electronic structure of boron nitride nanocones with disclinations of different angles $\theta=n\pi/3$. Nanocones with odd values of $n$ present antiphase boundaries that cause a reduction…

Materials Science · Physics 2007-05-23 Sergio Azevedo , Mario S. C. Mazzoni , H. Chacham , R. W. Nunes

Nonlinear light-matter interactions in structured materials are the source of exciting properties and enable vanguard applications in photonics. However, the magnitude of nonlinear effects is generally small, thus requiring high optical…

Materials Science · Physics 2022-03-22 Fadil Iyikanat , Andrea Konečná , F. Javier García de Abajo

We investigate theoretically the electronic structure of graphene and boron nitride (BN) lateral heterostructures, which were fabricated in recent experiments. The first-principles density functional calculation demonstrates that a huge…

Mesoscale and Nanoscale Physics · Physics 2016-07-04 Dong Zhang , Maosheng Miao , Fuhua Yang , Haiqing Lin , Kai Chang

We generate representative structural models of amorphous carbon (a-C) from constant-volume quenching from the liquid with subsequent relaxation of internal stresses in molecular dynamics simulations using empirical and machine-learning…

Materials Science · Physics 2020-01-07 Richard Jana , Daniele Savio , Volker L. Deringer , Lars Pastewka
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