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Recurrent Neural Network (RNN) has been successfully applied in many sequence learning problems. Such as handwriting recognition, image description, natural language processing and video motion analysis. After years of development,…
Current video denoising methods perform temporal fusion by designing convolutional neural networks (CNN) or combine spatial denoising with temporal fusion into basic recurrent neural networks (RNNs). However, there have not yet been works…
The study of thin films and 2D materials, including transition metal dichalcogenides such as WSe$_2$ offers opportunities to leverage their properties in advanced sensors, quantum technologies, and device to optimize functional performance.…
Thin film oxides are a source of endless fascination for the materials scientist. These materials are highly flexible, can be integrated into almost limitless combinations, and exhibit many useful functionalities for device applications.…
A systematic first-principles study has been performed to understand the magnetism of thin film SrRuO$_3$ which lots of research efforts have been devoted to but no clear consensus has been reached about its ground state properties. The…
While structure refinement is routinely achieved for simple bulk materials, the accurate structural determination still poses challenges for thin films due on the one hand to the small amount of material deposited on the thicker substrate…
We develop a polycrystal graph neural network (PGNN) model for predicting the effective properties of polycrystalline materials, using the Li7La3Zr2O12 ceramic as an example. A large-scale dataset with >5000 different three-dimensional…
The depth dependence of crystalline structure within thin films is critical for many technological applications, but has been impossible to measure directly using common techniques. In this work, by monitoring diffraction peak intensity and…
Machine learning has revolutionized materials discovery, but data scarcity remains a critical bottleneck for complex functional properties. As emerging systems, two-dimensional (2D) materials possess limited overall data volumes. Evaluating…
High-energy X-ray diffraction methods can non-destructively map the 3D microstructure and associated attributes of metallic polycrystalline engineering materials in their bulk form. These methods are often combined with external stimuli…
The complex perovskite oxide SrRuO3 shows intriguing transport properties at low temperatures due to the interplay of spin, charge, and orbital degrees of freedom. One of the open questions in this system is regarding the origin and nature…
This paper presents an accurate and fast algorithm for road segmentation using convolutional neural network (CNN) and gated recurrent units (GRU). For autonomous vehicles, road segmentation is a fundamental task that can provide the…
Recent advances in computed tomography (CT) imaging, especially with dual-robot systems, have introduced new challenges for scan trajectory optimization. This paper presents a novel approach using Gated Recurrent Units (GRUs) to optimize CT…
The microstructure critically governs the properties of materials used in energy and chemical engineering technologies, from catalysts and filters to thermal insulators and sensors. Therefore, accurate design is based on quantitative…
Glass transitions are widely observed in various types of soft matter systems. However, the physical mechanism of these transitions remains {elusive}, despite years of ambitious research. In particular, an important unanswered question is…
Hard coatings play a critical role in industry, with ceramic materials offering outstanding hardness and thermal stability for applications that demand superior mechanical performance. However, deploying artificial intelligence (AI) for…
Competition between electronic and atomic reconstruction is a constantly recurring theme in transition-metal oxides. We use density functional theory calculations to study this competition for a model system consisting of a thin film of the…
Electroactive polymer thin films undergo repeated reversible structural change during operation in electrochemical applications. While synchrotron X-ray scattering is powerful for the characterization of stand-alone and ex-situ organic thin…
The magnetization as a function of magnetic field showed hysteretic behavior at room temperature. According to the temperature dependence of the magnetization, the Curie temperature $(T_{C})$ is higher than 350 K. Ferromagnetic Mn-doped tin…
With the rise of AI-assisted materials screening, extraordinary properties are now frequently predicted in experimentally uncharted material systems, highlighting the need to develop new synthesis methods for unconventional materials beyond…