Graphene hot-electron light bulb: incandescence from hBN-encapsulated graphene in air

The excellent electronic and mechanical properties of graphene allow it to sustain very large currents, enabling its incandescence through Joule heating in suspended devices. Although interesting scientifically and promising technologically, this process is unattainable in ambient environment, because graphene quickly oxidises at high temperatures. Here, we take the performance of graphene-based incandescent devices to the next level by encapsulating graphene with hexagonal boron nitride (hBN). Remarkably, we found that the hBN encapsulation provides an excellent protection for hot graphene filaments even at temperatures well above 2000 K. Unrivalled oxidation resistance of hBN combined with atomically clean graphene/hBN interface allows for a stable light emission from our devices in atmosphere for many hours of continuous operation. Furthermore, when confined in a simple photonic cavity, the thermal emission spectrum is modified by a cavity mode, shifting the emission to the visible range spectrum. We believe our results demonstrate that hBN/graphene heterostructures can be used to conveniently explore the technologically important high-temperature regime and to pave the way for future optoelectronic applications of graphene-based systems

Computational modeling of thermal interfaces in graphene based nanostructures

L'abstract è presente nell'allegato / the abstract is in the attachmen

The 1999 Center for Simulation of Dynamic Response in Materials Annual Technical Report

Introduction: This annual report describes research accomplishments for FY 99 of the Center for Simulation of Dynamic Response of Materials. The Center is constructing a virtual shock physics facility in which the full three dimensional response of a variety of target materials can be computed for a wide range of compressive, ten- sional, and shear loadings, including those produced by detonation of energetic materials. The goals are to facilitate computation of a variety of experiments in which strong shock and detonation waves are made to impinge on targets consisting of various combinations of materials, compute the subsequent dy- namic response of the target materials, and validate these computations against experimental data

Kinetics of the inner ring in the exciton emission pattern in GaAs coupled quantum wells

We report on the kinetics of the inner ring in the exciton emission pattern. The formation time of the inner ring following the onset of the laser excitation is found to be about 30 ns. The inner ring was also found to disappear within 4 ns after the laser termination. The latter process is accompanied by a jump in the photoluminescence (PL) intensity. The spatial dependence of the PL-jump indicates that the excitons outside of the region of laser excitation, including the inner ring region, are efficiently cooled to the lattice temperature even during the laser excitation. The ring formation and disappearance are explained in terms of exciton transport and cooling.Comment: 19 pages, 6 figure

Exploring Thermal Transport in Electrochemical Energy Storage Systems Utilizing Two-Dimensional Materials: Prospects and Hurdles

Two-dimensional materials and their heterostructures have enormous applications in Electrochemical Energy Storage Systems (EESS) such as batteries. A comprehensive and solid understanding of these materials' thermal transport and mechanism is essential for the practical design of EESS. Experiments have challenges in providing improved control and characterization of complex structures, especially for low dimensional materials. Theoretical and simulation tools such as first-principles calculations, boltzmann transport equations, molecular dynamics simulations, lattice dynamics simulation, and non-equilibrium Green's function provide reliable predictions of thermal conductivity and physical insights to understand the underlying thermal transport mechanism in materials. However, doing these calculations require high computational resources. The development of new materials synthesis technology and fast-growing demand for rapid and accurate prediction of physical properties require novel computational approaches. The machine learning (ML) method provides a promising solution to address such needs. This review details the recent development in atomistic/molecular studies and ML of thermal transport in EESS. The paper also addresses the latest significant experimental advances. However, designing the best low-dimensional materials-based heterostructures is like a multivariate optimization problem. For example, a particular heterostructure may be suitable for thermal transport but can have lower mechanical strength/stability. For bi/multilayer structures, the interlayer distance may influence the thermal transport properties and interlayer strength. Therefore, the last part addresses the future research direction in low-dimensional materials-based heterostructure design for thermal transport in EESS.Comment: 48 pages, 16 figures, Perspective Review Pape