0000000000638221

AUTHOR

Bingnan Han

showing 2 related works from this author

Deep-Learning-Enabled Fast Optical Identification and Characterization of 2D Materials.

2020

© 2020 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim Advanced microscopy and/or spectroscopy tools play indispensable roles in nanoscience and nanotechnology research, as they provide rich information about material processes and properties. However, the interpretation of imaging data heavily relies on the “intuition” of experienced researchers. As a result, many of the deep graphical features obtained through these tools are often unused because of difficulties in processing the data and finding the correlations. Such challenges can be well addressed by deep learning. In this work, the optical characterization of 2D materials is used as a case study, and a neural-network-based algorithm is de…

Materials scienceSpeedupbusiness.industryMechanical EngineeringDeep learningProbability and statistics02 engineering and technology010402 general chemistry021001 nanoscience & nanotechnologyMachine learningcomputer.software_genre01 natural sciencesImaging data0104 chemical sciencesMechanics of MaterialsGeneral Materials ScienceOptical identificationArtificial intelligence0210 nano-technologybusinessTransfer of learningcomputerIntuitionAdvanced materials (Deerfield Beach, Fla.)
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Deep-Learning-Enabled Fast Optical Identification and Characterization of Two-Dimensional Materials

2019

Advanced microscopy and/or spectroscopy tools play indispensable role in nanoscience and nanotechnology research, as it provides rich information about the growth mechanism, chemical compositions, crystallography, and other important physical and chemical properties. However, the interpretation of imaging data heavily relies on the "intuition" of experienced researchers. As a result, many of the deep graphical features obtained through these tools are often unused because of difficulties in processing the data and finding the correlations. Such challenges can be well addressed by deep learning. In this work, we use the optical characterization of two-dimensional (2D) materials as a case stu…

Condensed Matter - Materials SciencePhysics - Data Analysis Statistics and ProbabilityMaterials Science (cond-mat.mtrl-sci)FOS: Physical sciencesApplied Physics (physics.app-ph)Physics - Applied PhysicsData Analysis Statistics and Probability (physics.data-an)
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