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Vanadium dioxide (VO2) is an adjustable refractive index material and has capability of behaving as semiconductor or conductor depending on its temperature. Such condition makes it as a material which can be employed in fabricating…
Transmission electron diffraction is a powerful and versatile structural probe for the characterization of a broad range of materials, from nanocrystalline thin films to single crystals. With recent developments in fast electron detectors…
Ruthenium dioxide (RuO$_2$) has been proposed as a prototypical metallic $d$-wave altermagnet, a N\'eel-ordered compensated antiferromagnetic state exhibiting nonrelativistic momentum-dependent spin splitting; yet, its magnetic ground state…
The discovery of new structural and functional materials is driven by phase identification, often using X-ray diffraction (XRD). Automation has accelerated the rate of XRD measurements, greatly outpacing XRD analysis techniques that remain…
Thin films of inorganic materials as Tin-doped indium oxide, titanium oxide, Niobium doped titanium oxide, were deposited for comparison on glass and Polyethylene terephthalate (PET) substrates with a DC sputtering method. These thin films…
The confluence of state-of-the-art electronic-structure computations and modern synthetic materials growth techniques is proving indispensable in the search for and discovery of new functionalities in oxide thin films and heterostructures.…
Glass surface segmentation from RGB images is a challenging task, since glass as a transparent material distinctly lacks visual characteristics. However, glass segmentation is critical for scene understanding and robotics, as transparent…
Efficient characterization of surface compositions across high-dimensional materials spaces is critical for accelerating the discovery of surface-dominated functional materials. While X-ray photoelectron spectroscopy allows detailed surface…
Ruthenium (Ru) is a promising candidate for the next-generation of electronic interconnects due to its low resistivity, small mean free path, and superior electromigration reliability at nanometer scales. Additionally, Ru exhibits…
This study presents a deep learning approach to predicting structural and electronic properties of materials using Graph Neural Networks (GNNs). Leveraging data from the Materials Project database, we construct graph representations of…
Sculptured copper thin films were deposited on glass substrates, using different deposition rates. The nano-structure and morphology of the films were obtained, using X-ray diffraction (XRD), atomic force microscopy (AFM) and scanning…
Many properties of commonly used materials are driven by their microstructure, which can be influenced by the composition and manufacturing processes. To optimise future materials, understanding the microstructure is critically important.…
An accurate road surface friction prediction algorithm can enable intelligent transportation systems to share timely road surface condition to the public for increasing the safety of the road users. Previously, scholars developed multiple…
Structural damage detection has become an interdisciplinary area of interest for various engineering fields, while the available damage detection methods are being in the process of adapting machine learning concepts. Most machine learning…
To contemplate an alternative approach for the minimization of diffusion at high temperature depositions, present findings impart viability of room-temperature deposited reactively sputtered ScN thin film samples. The adopted room…
This study presents a comprehensive methodology for determining the thermal conductivity (TC) of materials with high reliability. The methodology addresses issues such as surface topographical variations and substrate interference by…
Grazing incidence X-ray diffraction (GIXD) is widely used for the structural characterization of thin films, particularly for analyzing phase composition and the orientation distribution of crystallites. While various tools exist for…
Materials characterization remains a labor-intensive process, with a large amount of expert time required to post-process and analyze micrographs. As a result, machine learning has become an essential tool in materials science, including…
The influence of edge roughness in angle resolved scatterometry at periodically structured surfaces is investigated. A good description of the radiation interaction with structured surfaces is crucial for the understanding of optical…
Diffraction experiments with holographic gratings recorded in SiO$_2$ nanoparticle-polymer composites have been carried out with slow neutrons. The influence of parameters such as nanoparticle concentration, grating thickness and grating…