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The electronic properties of two-dimensional materials and their heterostructures can be dramatically altered by varying the relative angle between the layers. This makes it theoretically possible to realize a new class of twistable…

Mesoscale and Nanoscale Physics · Physics 2018-09-03 Rebeca Ribeiro-Palau , Changjian Zhang , Kenji Watanabe , Takashi Taniguchi , James Hone , Cory R. Dean

Surface phonon-polaritons can carry energy on the surface of dielectric films and thus are expected to contribute to heat conduction. However, the contribution of surface phonon-polaritons (SPhPs) to thermal transport has not been…

Mesoscale and Nanoscale Physics · Physics 2019-08-06 Yunhui Wu , Jose Ordonez-Miranda , Sergei Gluchko , Roman Anufriev , Sebastian Volz , Masahiro Nomura

We present a fast method to fabricate high quality heterostructure devices by picking up crystals of arbitrary sizes. Bilayer graphene is encapsulated with hexagonal boron nitride to demonstrate this approach, showing good electronic…

Mesoscale and Nanoscale Physics · Physics 2015-06-18 P. J. Zomer , M. H. D. Guimarães , J. C. Brant , N. Tombros , B. J. van Wees

We report on the fabrication and electrical characterization of both single layer graphene micron-sized devices and nanoribbons on a hexagonal boron nitride substrate. We show that the micron-sized devices have significantly higher mobility…

Mesoscale and Nanoscale Physics · Physics 2013-02-06 Dominik Bischoff , Tobias Krähenmann , Susanne Dröscher , Michelle A. Gruner , Clément Barraud , Thomas Ihn , Klaus Ensslin

Hexagonal boron nitride is the only substrate that has so far allowed graphene devices exhibiting micron-scale ballistic transport. Can other atomically flat crystals be used as substrates for making quality graphene heterostructures? Here…

In this work, electrically and thermally conductive poly (butylene terephthalate) nanocomposites were prepared by in-situ ring-opening polymerization of cyclic butylene terephthalate (CBT) in presence of a tin-based catalyst. One type of…

Materials Science · Physics 2016-10-28 S. Colonna , O. Monticelli , J. Gomez , C. Novara , G. Saracco , A. Fina

The synthesis of wafer-scale two-dimensional amorphous carbon monolayers has been recently demonstrated. This material presents useful properties when integrated as coating of metals, semiconductors or magnetic materials, such as enabling…

Materials Science · Physics 2020-12-03 Aleandro Antidormi , Luciano Colombo , Stephan Roche

We calculate theoretically the disorder-limited conductivity of monolayer and bilayer graphene on hexagonal boron nitride (h-BN) substrates, comparing our theoretical results with the recent experimental results. The comparison leads to a…

Mesoscale and Nanoscale Physics · Physics 2011-03-17 S. Das Sarma , E. H. Hwang

Aiming to improve fabrication protocols for boron nitride and graphene (h-BNG) lateral heterostructures, we studied the growth of h-BNG thin films on platinum and their behavior in an oxygen environment. We employed a surface science…

Transition Metal Nitrides are a versatile class of materials, combining chemical robustness, high hardness, and superconducting behaviour with critical temperatures between 2 to 10 K. While several binary TMNs have been explored,…

Employing graphene as a template, we fabricate moir\'e superlattices by stacking bilayer or folded bilayer-bilayer graphene (BLG or fBBLG) and hexagonal boron nitride (hBN), i.e., hBN/BLG/hBN or hBN/fBBLG/hBN stacks, with a small twist…

We study silicene on hexagonal boron nitride, using first principles calculations. Since hexagonal boron nitride is semiconducting, the interaction with silicene is weaker than for metallic substrates. It therefore is possible to open a 50…

Mesoscale and Nanoscale Physics · Physics 2013-12-19 T. P. Kaloni , S. Gangopadhyay , N. Singh , B. Jones , U. Schwingenschlögl

Ballistic heat transport and second sound propagation in solids is of direct relevance in electronic and energy applications at short length scales and low temperatures. Measurement or calculation of thermal conductivity, which is typically…

Statistical Mechanics · Physics 2025-12-17 Patrick K. Schelling , Antonio Martinez Margolles , Logan Echazabal

Strain engineering has quickly emerged as a viable option to modify the electronic, optical and magnetic properties of 2D materials. However, it remains challenging to arbitrarily control the strain. Here we show that by creating…

The inherent trade-off between ultra-low thermal conductivity and high mechanical rigidity in natural materials limits their utility in advanced applications. Inspired by the unique architecture of layered honeycomb structures, this study…

Applied Physics · Physics 2026-03-23 Hossein Rokni , Patrick Singleton , Yuanlong Zheng , Connor Blake , Haoran Lin , Shuolong Yang

In recent years, enhanced light-matter interactions through a plethora of dipole-type polaritonic excitations have been observed in two-dimensional (2D) layered materials. In graphene, electrically tunable and highly confined…

The two-dimensional atomically thin insulator hexagonal boron nitride (h-BN) constitutes a new paradigm in tunnel based devices. A large band gap along with its atomically flat nature without dangling bonds or interface trap states makes it…

Mesoscale and Nanoscale Physics · Physics 2014-11-14 André Dankert , M. Venkata Kamalakar , Abdul Wajid , R. S. Patel , Saroj P. Dash

Adding thermal conductivity enhancements to increase thermal power in solid-liquid phase-change thermal energy storage modules compromises volumetric energy density and often times reduces the mass and volume of active phase change material…

Materials Science · Physics 2020-11-26 Darin J. Sharar , Asher C. Leff , Adam A. Wilson , Andrew Smith

High carrier mobilities play a fundamental role for high-frequency electronics, integrated optoelectronics as well as for sensor and spintronic applications, where device performance is directly linked to the magnitude of the carrier…

We introduce an interatomic potential for hexagonal boron nitride (hBN) based on the Gaussian approximation potential (GAP) machine learning methodology. The potential is based on a training set of configurations collected from density…

Materials Science · Physics 2020-10-06 Fabian L. Thiemann , Patrick Rowe , Erich A. Müller , Angelos Michaelides