Abstract
This paper describes the development of an optical tweezers system that operates in fully automatic mode. It features image recognition for particle tracking, allowing for the optical trapping and analysis of identified targets. The system can perform analysis of forward scattered light and Raman spectroscopy of the trapped particles, facilitating the automated analysis of a large number of samples without manual intervention. By leveraging combined analytical methods and AI for robust classification, this system contributes to the advancement of automated diagnostic tools. Preliminary results demonstrate the system's effectiveness using different kinds of standard and biofunctionalized PMMA microparticles.

Abstract
Mineral identification is a challenging task in geological sciences, which often implies multiple analyses of the physical and chemical properties of the samples for an accurate result. This task is particularly critical for the mining industry, where proper and fast mineral identification may translate into major efficiency and performance gains, such as in the case of the lithium mining industry. In this study, a mineral identification algorithm optimized for analyzing lithium-bearing samples using Laser-induced breakdown spectroscopy (LIBS) imaging, is put to the test with a set of representative samples. The algorithm incorporates advanced spectral processing techniques-baseline removal, Gaussian filtering, and data normalization-alongside unsupervised clustering to generate interpretable classification maps and auxiliary charts. These enhancements facilitate rapid and precise labelling of mineral compositions, significantly improving the interpretability and interactivity of the user interface. Extensive testing on diverse mineral samples with varying complexities confirmed the algorithm's robustness and broad applicability. Challenges related to sample granulometry and LIBS resolution were identified, suggesting future directions for optimizing system resolution to enhance classification accuracy in complex mineral matrices. The integration of this advanced algorithm with LIBS technology holds the potential to accelerate the mineral evaluation, paving the way for more efficient and sustainable mineral exploration.

Abstract
Traditionally, uorescence-based analytical methods were associated with high-cost bulky laboratory equipment. However, a diversity of technological advances taking place over the last 20 years concurred to change this picture. In the eld of optoelectronics, the advent of low-cost blue and UV lasers and LEDs, together with new miniature CCD spectrometers and high-sensitivity avalanche photodiodes (APDs), is enabling a new generation of spectroscopy tools to be developed and deployed in eld applications. On the other hand, chemistry and material sciences are delivering new types of uorescent materials with enhanced sensing properties, such as long-lived metallo-organic complexes or highly photostable quantum dots (QDs). Such developments are expanding the uses of uorescence and enabling new applications such as long-term multiwavelength imaging, ow cytometry analysis in microuidic chips, high-throughput DNA sequencing, and ber-optic-based diagnostic probes. © 2015 by Taylor and Francis Group, LLC.

Abstract

Abstract
Thin films of Ag/Fe were deposited on the core of multimode optical fibers. The deposited film shows sensitivity to both refractive index and MF changes. Simulation work based on TMM formalism confirms experimental response. © Optica Publishing Group 2023, © 2023 The Author(s)

Abstract
Electrochemical impedance spectroscopy (EIS) is a reliable technique for gathering information about electrochemical process occurring at the electrode surface and investigating properties of materials. Furthermore, EIS technique can be a very versatile and valuable tool in analytical assays for detection and quantification of several chemically and biologically relevant (bio)molecules. The first part of this Review (Introduction) provides brief insights into (i) theoretical aspects of EIS, (ii) the instrumentation required to perform the EIS studies and (iii) the most relevant representations of impedance experimental data (such as Nyquist and Bode plots). In the end of this section, (iv) theoretical aspects regarding the fitting of the Randles circuit to experimental data are addressed, not only to obtain information about electrochemical processes but also to illustrate its utility for analytical purposes. The second part of the Review (Impedimetric Detection of Disease Biomarkers) focuses on the applications of EIS in the biomedical field, particularly as analytical technique in electrochemical sensors and biosensors for screening disease biomarkers. In the last section (Conclusions and Perspectives), we discuss main achievements of EIS technique in analytical assays and provide some perspectives, challenges and future applications in the biomedical field.