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Register a new userOptical identification using imperfections in 2D materials
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The ability to uniquely identify an object or device is important for authentication. Imperfections, locked into structures during fabrication, can be used to provide a fingerprint that is challenging to reproduce. In this paper, we propose a simple optical technique to read unique information from nanometer-scale defects in 2D materials. Flaws created during crystal growth or fabrication lead to spatial variations in the bandgap of 2D materials that can be characterized through photoluminescence measurements. We show a simple setup involving an angle-adjustable transmission filter, simple optics and a CCD camera can capture spatially-dependent photoluminescence to produce complex maps of unique information from 2D monolayers. Atomic force microscopy is used to verify the origin of the optical signature measured, demonstrating that it results from nanometer-scale imperfections. This solution to optical identification with 2D materials could be employed as a robust security measure to prevent counterfeiting.
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In this paper, we have built a numerical p-n Si/GaAs heterojunction model using a quantum-mechanical tunneling theory with various quantum tunneling interfacial materials including two-dimensional semiconductors such as hexagonal boron nitride (h-BN) and graphene and ALD-enabled oxide materials such as HfO2, Al2O3, and SiO2. Their tunneling efficiencies and tunneling current with different thicknesses were systematically calculated and compared. Multiphysics modeling was used with the aforementioned tunneling interfacial materials to analyze changes in strain under different temperature conditions. Considering the transport properties and thermal-induced strain analysis, Al2O3 among three oxide materials and graphene in 2D materials are favorable material choices that offer the highest heterojunction quality. Overall, our results offer the viable route to guide the selection of quantum tunneling materials for myriad possible combinations of new heterostructures that can be obtained via remote epitaxy and the UO method.
We review recent progress on spins and magnetism in 2D materials including graphene, transition metal dichalcogenides, and 2D magnets. We also discuss challenges and prospects for the future of spintronics with 2D van der Waals heterostructures.
The high mechanical strength and excellent flexibility of 2D materials such as graphene are some of their most important properties [1]. Good flexibility is key for exploiting 2D materials in many emerging technologies, such as wearable electronics, bioelectronics, protective coatings and composites [1] and recently bending has been suggested as a route to tune electronic transport behaviour [2]. For virtually all crystalline materials macroscopic deformation is accommodated by the movement of dislocations and through the formation of twinning defects [3]; it is the geometry of the resulting microstructure that largely determines the mechanical and electronic properties. Despite this, the atomic microstructure of 2D materials after mechanical deformation has not been widely investigated: only by understanding these deformed microstructures can the resulting properties be accurately predicted and controlled. In this paper we describe the different structural features that can form as a result of bending in van der Waals (vdW) crystals of 2D materials. We show that twin boundaries, an important class of crystal defect, are delocalised by several nm and not atomically sharp as has been assumed for over half a century [4]. In addition, we demonstrate that different classes of microstructure are present in the deformed material and can be predicted from just the atomic structure, bend angle, and flake thickness. We anticipate that this new knowledge of the deformation structure for 2D materials will provide foundations for tailoring transport behaviour[2], mechanical properties, liquid-phase [5,6] and scotch-tape exfoliation [7,8], and crystal growth.
We study the binding energies and optical properties of direct and indirect excitons in monolayers and double layer heterostructures of Xenes: silicene, germanene, and stanene. It is demonstrated that an external electric field can be used to tune the eigenenergies and optical properties of excitons by changing the effective mass of charge carriers. The Schr{o}dinger equation with field-dependent exciton reduced mass is solved by using the Rytova-Keldysh (RK) potential for direct excitons, while both the RK and Coulomb potentials are used for indirect excitons. It is shown that for indirect excitons, the choice of interaction potential can cause huge differences in the eigenenergies at large electric fields and significant differences even at small electric fields. Furthermore, our calculations show that the choice of material parameters has a significant effect on the binding energies and optical properties of direct and indirect excitons. These calculations contribute to the rapidly growing body of research regarding the excitonic and optical properties of this new class of two dimensional semiconductors.
Thin nanomaterials are key constituents of modern quantum technologies and materials research. Identifying specimens of these materials with properties required for the development of state of the art quantum devices is usually a complex and lengthy human task. In this work we provide a neural-network driven solution that allows for accurate and efficient scanning, data-processing and sample identification of experimentally relevant two-dimensional materials. We show how to approach classification of imperfect imbalanced data sets using an iterative application of multiple noisy neural networks. We embed the trained classifier into a comprehensive solution for end-to-end automatized data processing and sample identification.
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