Related papers: Intelligent Identification of Two-Dimensional Stru…
In drug discovery, knowledge of the graph structure of chemical compounds is essential. Many thousands of scientific articles in chemistry and pharmaceutical sciences have investigated chemical compounds, but in cases the details of the…
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…
Two-dimensional materials such as graphene and transition metal dichalcogenides (TMDs) are ideal candidates to create ultra-thin electronics suitable for flexible substrates. Although optoelectronic devices based on TMDs have demonstrated…
Layered materials (LMs) are at the centre of an ever increasing research effort due to their potential use in a variety of applications. The presence of imperfections, such as bi- or multilayer areas, holes, grain boundaries, isotropic and…
Two-dimensional materials and their van der Waals heterostructures enable a large range of applications, including label-free biosensing. Lattice mismatch and work function difference in the heterostructure material result in strain and…
Classifying chemicals according to putative modes of action (MOAs) is of paramount importance in the context of risk assessment. However, current methods are only able to handle a very small proportion of the existing chemicals. We address…
Electronic and optoelectronic applications of two-dimensional (2D) semiconductors demand precise control over material quality, including thickness, composition, doping, and defect density. Conventional benchmarking methods (e.g., charge…
The concept of alloy engineering has emerged as a viable technique towards tuning the bandgap as well as engineering the defect levels in two-dimensional transition metal dichalcognides (TMDC). Possibility to synthesize these ultrathin TMDC…
Light inherently consists of multiple dimensions beyond intensity, including spectrum, polarization, etc. The coupling among these high-dimensional optical features provides a compressive characterization of intrinsic material properties.…
Atomically thin two-dimensional (2D) materials provide a wide range of basic building blocks with unique properties, making them ideal for heterogeneous integration with a mature chip platform for advances in optical communication…
It is difficult to quantify structure-property relationships and to identify structural features of complex materials. The characterization of amorphous materials is especially challenging because their lack of long-range order makes it…
Infrared detection and sensing is deeply embedded in modern technology and human society and its development has always been benefitting from the discovery of new photoelectric response materials. The rise of two-dimensional (2D) materials,…
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…
This study presents a multisensory machine learning architecture for object recognition by employing a novel dataset that was constructed with the iCub robot, which is equipped with three cameras and a depth sensor. The proposed…
The computational discovery and design of new crystalline materials, particularly metal-organic frameworks (MOFs), heavily relies on high-quality, computation-ready structural data. However, recent studies have revealed significant error…
Identifying local structural motifs and packing patterns of molecular solids is a challenging task for both simulation and experiment. We demonstrate two novel approaches to characterize local environments in different polymorphs of…
We use machine learning methods on local structure to identify flow defects - or regions susceptible to rearrangement - in jammed and glassy systems. We apply this method successfully to two disparate systems: a two dimensional experimental…
A central challenge in the development of nanophotonic structures is identifying the optimal design for a target functionality, and understanding the physical mechanisms that enable the optimized device's capabilities. Previously…
Due the alarming rate of climate change, the implementation of efficient CO$_2$ capture has become crucial. This project aims to create an algorithm that predicts the uptake of CO$_2$ adsorbing Metal-Organic Frameworks (MOFs) by using…
The combination of two-dimensional (2D) materials into vertical heterostructures has emerged as a promising path to designer quantum materials with exotic properties. Here, we extend this concept from inorganic 2D materials to 2D…