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Different types of spectroscopies, such as X-ray absorption near edge structure (XANES) and Raman spectroscopy, play a very important role in analyzing the characteristics of different materials. In scientific literature, XANES/Raman data…

Computer Vision and Pattern Recognition · Computer Science 2021-07-08 Weixin Jiang , Eric Schwenker , Trevor Spreadbury , Kai Li , Maria K. Y. Chan , Oliver Cossairt

Through a combination of monitoring the Raman spectral characteristics of 2D materials grown on copper catalyst layers, and wafer scale automated detection of the fraction of transferred material, we reproducibly achieve transfers with over…

Deep-learning algorithms enable precise image recognition based on high-dimensional hierarchical image features. Here, we report the development and implementation of a deep-learning-based image segmentation algorithm in an autonomous…

Image and Video Processing · Electrical Eng. & Systems 2020-03-26 Satoru Masubuchi , Eisuke Watanabe , Yuta Seo , Shota Okazaki , Takao Sasagawa , Kenji Watanabe , Takashi Taniguchi , Tomoki Machida

Raman spectroscopy is a valuable characterization tool for two-dimensional materials. Starting from model Hamiltonians for Chern insulators and magnetized monolayers of transition metal dichalcogenides, we theoretically predict two…

Mesoscale and Nanoscale Physics · Physics 2025-01-29 Selçuk Parlak , Ion Garate

Nonlinear optical (NLO) phenomena such as harmonic generation, Kerr, and Pockels effects are of great technological importance for lasers, frequency converters, modulators, switches, etc. Recently, two-dimensional (2D) materials have drawn…

Autonomous synthesis and characterization of inorganic materials requires the automatic and accurate analysis of X-ray diffraction spectra. For this task, we designed a probabilistic deep learning algorithm to identify complex multi-phase…

Materials Science · Physics 2021-05-27 Nathan J. Szymanski , Christopher J. Bartel , Yan Zeng , Qingsong Tu , Gerbrand Ceder

Raman spectroscopy is an integral part of graphene research. It is used to determine the number and orientation of layers, the quality and types of edge, and the effects of perturbations, such as electric and magnetic fields, strain,…

Materials Science · Physics 2015-06-16 Andrea C. Ferrari , Denis M. Basko

Despite being only a few atoms thick, single-layer two-dimensional (2D) materials display strong electron-photon interactions that could be utilized in efficient light modulators on extreme subwavelength scales. In various applications…

Mesoscale and Nanoscale Physics · Physics 2018-09-21 Sunny Gupta , Sharmila N. Shirodkar , Alex Kutana , Boris I. Yakobson

Machine learning methods have found many applications in Raman spectroscopy, especially for the identification of chemical species. However, almost all of these methods require non-trivial preprocessing such as baseline correction and/or…

Machine Learning · Computer Science 2018-02-07 Jinchao Liu , Margarita Osadchy , Lorna Ashton , Michael Foster , Christopher J. Solomon , Stuart J. Gibson

The most important bands for the evaluation of strain in graphene (the 2D and 2D prime modes) are investigated. It is shown that for Bernal-stacked bilayers, the two-phonon Raman features have three different components that can be assigned…

Materials Science · Physics 2021-07-27 Sara D Costa , Johan Ek Weis , Otakar Frank , Michaela Fridrichová , Martin Kalbac

The vibrational and electronic properties of 2-dimensinal (2D) materials can be efficiently tuned by external strain due to their good stretchability. Resonant Raman spectroscopy is a versatile tool to study the physics of phonons,…

Mesoscale and Nanoscale Physics · Physics 2019-06-05 Chaoyu Song , Fengren Fan , Ningning Xuan , Shenyang Huang , Chong Wang , Guowei Zhang , Fanjie Wang , Qiaoxia Xing , Yuchen Lei , Zhengzong Sun , Hua Wu , Hugen Yan

Raman spectroscopy is an appealing technique that probes molecular vibrations in a wide variety of materials with virtually no sample preparation. However, accurate and reliable Raman measurements are still a challenge and require more…

Optics · Physics 2020-02-14 Hugo Kerdoncuff , Mikael Lassen , Jan C. Petersen

As "2D" materials (i.e. materials just a few atoms thick) continue to gain prominence, understanding their symmetries is critical for unlocking their full potential. In this work, we present comprehensive tables that tabulate the rod group…

Materials Science · Physics 2025-06-17 Bernard Field , Sinéad M. Griffin

The last decade has seen intense research in materials with reduced dimensionality. The low dimensionality leads to interesting electronic behavior due to electronic confinement and reduced screening. The investigations have to a large…

Materials Science · Physics 2019-03-27 Peter Mahler Larsen , Mohnish Pandey , Mikkel Strange , Karsten Wedel Jacobsen

Magnetic resonance imaging is a three-dimensional imaging technique, where a gradient of the magnetic field is used to interrogate spin resonances with spatial resolution. The application of this technique to probe the coherence of atoms…

Quantum Physics · Physics 2025-02-24 Mateusz Mazelanik , Adam Leszczyński , Tomasz Szawełło , Michał Parniak

Raman spectroscopy is a powerful tool for material characterization. However, careful preprocessing is required for the identification and handling of noise, baseline drift, and random spikes. This paper presents a comprehensive approach to…

Remarkable optical and electrical properties of two-dimensional (2D) materials, such as graphene and transition-metal dichalcogenide (TMDC) monolayers, offer vast technological potential for novel and improved optoelectronic nanodevices,…

Optics · Physics 2016-07-22 Martin Weismann , Nicolae C. Panoiu

Two-dimensional (2D) materials, such as graphene and MoS2, have been attracting wide interest in surface enhancement Raman spectroscopy. This perspective gives an overview of recent developments in 2D materials' application in surface…

Materials Science · Physics 2017-07-19 Ming Xia

Infrared and Raman spectroscopies are ubiquitous techniques employed in many experimental laboratories, thanks to their fast and non-destructive nature able to capture materials' features as spectroscopic fingerprints. Nevertheless, these…

Materials Science · Physics 2024-05-08 Lorenzo Bastonero , Nicola Marzari

The detection and classification of exfoliated two-dimensional (2D) material flakes from optical microscope images can be automated using computer vision algorithms. This has the potential to increase the accuracy and objectivity of…

Computer Vision and Pattern Recognition · Computer Science 2026-02-06 Jan-Lucas Uslu , Alexey Nekrasov , Alexander Hermans , Bernd Beschoten , Bastian Leibe , Lutz Waldecker , Christoph Stampfer