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Determining the dimensions of nanostructures is critical to ensuring the maximum performance of many geometry-sensitive nanoscale functional devices. However, accurate metrology at the nanoscale is difficult using optics-based methods due…

Two-dimensional (2D) transition metal dichalcogenides (TMDs), such as MoS2, have the potential to be widely used in electronic devices and sensors due to their high carrier mobility and tunable band structure. In 2D TMD devices, surface and…

Two-dimensional (2D) materials have received extensive research attentions over the past two decades due to their intriguing physical properties (such as the ultrahigh mobility and strong light-matter interaction at atomic thickness) and a…

Studying porous rock materials with X-Ray Computed Tomography (XRCT) has been established as a standard procedure for the non-destructive visualization of flow and transport in opaque porous media. Despite the recent advances in the field…

In this paper we derive a formalism allowing us to separate inter-layer contributions to the polarizability of a periodic array of 2D materials from intra-layer ones. To this aim, effective profile functions are introduced. They constitute…

This paper is devoted to the problem of identification of colloidal assemblies using the example of two-dimensional coatings (monolayer assemblies). Colloidal systems are used in various fields of science and technology, for example, in…

Two-dimensional (2D) transition metal dichalcogenides (TMDs), especially MoS2 and WS2 recently attract extensive attentions due to their rich physics and great potential applications. Superior to graphene, MS2 (M = Mo/W) monolayers have a…

Purpose: Magnetic resonance imaging (MRI) exams include multiple series with varying contrast and redundant information. For instance, T2-FLAIR contrast is based upon tissue T2 decay and the presence of water, also present in T2- and…

Among the large number of promising two-dimensional (2D) atomic layer crystals, true metallic layers are rare. Through combined theoretical and experimental approaches, we report on the stability and successful exfoliation of atomically…

Moire patterns in van der Waals bilayer materials complicate the analysis of atomic-resolution images, hindering the atomic-scale insight typically attainable with scanning transmission electron microscopy. Here, we report a method to…

The possibility of tailoring the critical strain of 2D materials will be crucial for the fabrication of flexible devices. In this paper, the fracture in polycrystalline MoS2 films with two different grain orientations is studied at the…

Deep Learning models are easily disturbed by variations in the input images that were not observed during the training stage, resulting in unpredictable predictions. Detecting such Out-of-Distribution (OOD) images is particularly crucial in…

Interpreting the mineralogical aspects of rock thin sections is an important task for oil and gas reservoirs evaluation. However, human analysis tend to be subjective and laborious. Technologies like QEMSCAN(R) are designed to automate the…

Transition metal di-iodides such as FeI2, NiI2 and CoI2 are an emerging class of 2D magnets exhibiting rich and diverse magnetic behaviour, but their study at the monolayer limit has been severely hindered by fabrication challenges due to…

Atomically thin two-dimensional (2D) transition metal dichalcogenides (TMDCs) are attractive materials for next generation nanoscale optoelectronic applications. Understanding nanoscale optical behavior of the edges and grain boundaries of…

In this paper, we propose multi-stage and deformable deep convolutional neural networks for object detection. This new deep learning object detection diagram has innovations in multiple aspects. In the proposed new deep architecture, a new…

In powder diffraction data analysis, phase identification is the process of determining the crystalline phases in a sample using its characteristic Bragg peaks. For multiphasic spectra, we must also determine the relative weight fraction of…

We demonstrate the use of deep learning for fast spectral deconstruction of speckle patterns. The artificial neural network can be effectively trained using numerically constructed multispectral datasets taken from a measured spectral…

In this paper, we present an application of 2-D convolutional neural networks (2-D CNNs) designed to perform both feature extraction and classification stages as a single organism to solve the highlighted problems. The method uses a network…

Modification of physical properties of materials and design of materials with on-demand characteristics is at the heart of modern technology. Rare application relies on pure materials--most devices and technologies require careful design of…