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Modern scattering-type scanning near-field optical microscopy (s-SNOM) has become an indispensable tool in material research. However, as the s-SNOM technique marches into the far-infrared (IR) and terahertz (THz) regimes, emerging…

Dense photonic integration promises to revolutionize optical computing and communications. However, efforts towards this goal face unacceptable attenuation of light caused by surface roughness in microscopic devices. Here we address this…

Optics · Physics 2015-05-30 M. Sumetsky , J. M. Fini

Scattering-based single-particle tracking (S-SPT) has opened new avenues for highly sensitive label-free detection and characterization of nanoscopic objects, making it particularly attractive for various analytical applications. However, a…

Machine learning has emerged as a powerful tool in materials discovery, enabling the rapid design of novel materials with tailored properties for countless applications, including in the context of energy and sustainability. To ensure the…

Optical spectroscopy plays an essential role across scientific research and industry for non-contact materials analysis1-3, increasingly through in-situ or portable platforms4-6. However, when considering low-light-level applications,…

Spectral imaging is a method in medical x-ray imaging to extract information about the object constituents by the material-specific energy dependence of x-ray attenuation. Contrast-enhanced spectral imaging has been thoroughly investigated,…

Medical Physics · Physics 2021-01-26 Erik Fredenberg , Magnus Aslund , Bjorn Cederstrom , Mats Lundqvist , Mats Danielsson

Hyperspectral sensors enable the study of the chemical properties of scene materials remotely for the purpose of identification, detection, and chemical composition analysis of objects in the environment. Hence, hyperspectral images…

Computer Vision and Pattern Recognition · Computer Science 2019-02-12 Utsav B. Gewali , Sildomar T. Monteiro , Eli Saber

Today, machine learning tools, particularly artificial neural networks, have become crucial for diverse applications. However, current digital computing tools to train and deploy artificial neural networks often struggle with massive data…

Emerging Technologies · Computer Science 2025-02-14 Bora Çarpınlıoğlu , Uğur Teğin

Machine learning techniques are utilised in several areas of astrophysical research today. This dissertation addresses the application of ML techniques to two classes of problems in astrophysics, namely, the analysis of individual…

Astrophysics · Physics 2009-01-06 N. Daniel Kumar

We present a detailed theoretical study of the recent proposal for selective nanomanipulation of nanometric particles above a substrate using near-field optical forces [Chaumet {\it et al.} Phys. Rev. Lett. {\bf 88}, 123601 (2002)].…

Optics · Physics 2009-11-10 Patrick C. Chaumet , Adel Rahmani , Manuel Nieto-Vesperinas

Microplastics (MPs) are ubiquitous pollutants with demonstrated potential to impact ecosystems and human health. Their microscopic size complicates detection, classification, and removal, especially in biological and environmental samples.…

Computer Vision and Pattern Recognition · Computer Science 2025-10-22 Paul-Tiberiu Miclea , Martin Sboron , Hardik Vaghasiya , Hoang Thinh Nguyen , Meet Gadara , Thomas Schmid

Light scattering detection in the near field, a rapidly expanding family of scattering techniques, has recently proved to be an appropriate procedure for performing dynamic measurements. Here we report an innovative algorithm, based on the…

Early detection of cancer is essential for timely diagnosis and improved patient outcomes. Among emerging technologies, intra-body nanoscale communication offers an innovative solution to identify molecular cues within the human…

Emerging Technologies · Computer Science 2026-03-12 Abdollah Rezagholi , Sergi Abadal , Filip Lemic , Eduard Alarcon , Ethungshan Shitiri

Scanning Transmission Electron Microscopy (STEM) has become the main stay for materials characterization on atomic level, with applications ranging from visualization of localized and extended defects to mapping order parameter fields. In…

Instrumentation and Detectors · Physics 2019-01-15 Xin Li , Ondrej Dyck , Sergei V. Kalinin , Stephen Jesse

Over the past 30 years, numerous large-scale photometric astronomical surveys have been conducted, including SDSS, Pan-STARRS, Gaia,2MASS, WISE, and others. These surveys provide extensive photometric measurements that can be used to infer…

Instrumentation and Methods for Astrophysics · Physics 2025-11-03 Mateusz Kapusta

Helium-ion beams (HIB) focused to sub-nanometer scales have emerged as powerful tools for high-resolution imaging as well as nano-scale lithography, ion milling or deposition. Quantifying irradiation effects is essential for reliable device…

Mesoscale and Nanoscale Physics · Physics 2017-03-21 Adrian Gozar , Nicholas E. Litombe , Jennifer E. Hoffman , Ivan Bozovic

Making material experiments more efficient is a high priority for materials scientists who seek to discover new materials with desirable properties. In this paper, we investigate how to optimize the laborious sequential measurements of…

Materials Science · Physics 2019-10-24 Takuya Kanazawa , Akinori Asahara , Hidekazu Morita

Laser cutting is a widely adopted technology in material processing across various industries, but it generates a significant amount of dust, smoke, and aerosols during operation, posing a risk to both the environment and workers' health.…

Computer Vision and Pattern Recognition · Computer Science 2025-11-21 Mohamed Abdallah Salem , Hamdy Ahmed Ashur , Ahmed Elshinnawy

Optical microscopy has a diffraction limited resolution of about 250 nm. Fluorescence methods (e.g. PALM, STORM, STED) beat this, but they are still limited to 10 s of nm, and the images are an indirect pointillist representation of only…

Machine learning and artificial intelligence (ML/AI) are rapidly becoming an indispensable part of physics research, with domain applications ranging from theory and materials prediction to high-throughput data analysis. In parallel, the…