Graphene grown by a sublimation technique was studied by Scanning Electron Microscopy (SEM) and micro-Raman spectroscopy. The measurement area of a sample was marked and investigated using both systems, as a result of which SEM images were directly compared with Raman maps. In this work we show that a correlative analysis of Energy Selective Backscattered electrons detector (EsB), In-Lens figures and Raman maps of shape and intensity of the 2D band is adequate to determine graphene layer thickness with the precision of SEM and reliability of Raman spectroscopy.
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http://dx.doi.org/10.1016/j.micron.2015.05.013 | DOI Listing |
Transl Vis Sci Technol
January 2025
School of Optometry and Vision Science, University of New South Wales, Sydney, Australia.
Purpose: The purpose of this study was to develop and validate a deep-learning model for noninvasive anemia detection, hemoglobin (Hb) level estimation, and identification of anemia-related retinal features using fundus images.
Methods: The dataset included 2265 participants aged 40 years and above from a population-based study in South India. The dataset included ocular and systemic clinical parameters, dilated retinal fundus images, and hematological data such as complete blood counts and Hb concentration levels.
J Chem Phys
January 2025
Department of Chemistry, Boston University, 590 Commonwealth Avenue, Boston, Massachusetts 02215, USA.
The computational spectroscopy of water has proven to be a powerful tool for probing the structure and dynamics of chemical systems and for providing atomistic insight into experimental vibrational spectroscopic results. However, such calculations have been limited for biochemical systems due to the lack of empirical vibrational frequency maps for the TIP3P water model, which is used in many popular biomolecular force fields. Here, we develop an empirical map for the TIP3P model and evaluate its efficacy for reproducing the experimental vibrational spectroscopy of water.
View Article and Find Full Text PDFTalanta
April 2025
Department of Chemistry and Research Institute for Convergence of Basic Science, Hanyang University, Seoul, 04763, Republic of Korea. Electronic address:
This study explored convolutional autoencoder (CAE)-based feature extraction from entire two-trace two-dimensional (2T2D) correlation maps as a promising tool to enhance the accuracy of vibrational spectroscopy-based discriminant analysis. Although 2T2D correlation maps constructed using only a pair of spectra were effective to highlight minute spectral differences, there was an excessive number of features (variables). Thus, only slice spectra at a wavenumber chosen from the map were typically used for discriminant analysis.
View Article and Find Full Text PDFACS Omega
December 2024
Physics Department, Laboratory of Biophysics and Nanosystems, Federal University of Maranhão, São Luís, MA 65085-580, Brazil.
Mayaro virus (MAYV) is an emerging mosquito-borne viral pathogen whose infection results in arthritogenic disease. Despite ongoing research efforts, MAYV biology is largely unknown. Physical virology can assess MAYV nanoparticle metastability, assembly/disassembly, and polymorphism, allowing us to understand virion architecture and dynamics.
View Article and Find Full Text PDFAppl Spectrosc
December 2024
Key Laboratory of Drugs Analysis & Intelligent-Monitoring, Narcotics Technology Center of Shaanxi Provincial Public Security Department, National Narcotics Laboratory Shaanxi Regional Center, Shaanxi, China.
Raman spectroscopy is widely used for material detection due to its specificity, but its application to spectral recognition often faces limitations due to insufficient training data, unlike fields such as image recognition. Traditional machine learning or basic neural networks are commonly used, but they have limited ability to achieve high precision. We have proposed a novel approach that combines the Triplet network (TN) and K-nearest neighbor (KNN) techniques to address this issue.
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