Abstract
Optical tweezers are an interesting tool to enable single cell analysis, especially when coupled with optical sensing and advanced computational methods. Nevertheless, such approaches are still hindered by system operation variability, and reduced amount of data, resulting in performance degradation when addressing new data sets. In this manuscript, we describe the deployment of an automatic and intelligent optical tweezers setup, capable of trapping, manipulating, and analyzing the physical properties of individual microscopic particles in an automatic and autonomous manner, at a rate of 4 particle per min, without user intervention. Reproducibility of particle identification with the help of machine learning algorithms is tested both for manual and automatic operation. The forward scattered signal of the trapped PMMA and PS particles was acquired over two days and used to train and test models based on the random forest classifier. With manual operation the system could initially distinguish between PMMA and PS with 90% accuracy. However, when using test datasets acquired on a different day it suffered a loss of accuracy around 24%. On the other hand, the automatic system could classify four types of particles with 79% accuracy maintaining performance (around 1% variation) even when tested with different datasets. Overall, the automated system shows an increased reproducibility and stability of the acquired signals allowing for the confirmation of the proportionality relationship expected between the particle size and its friction coefficient. These results demonstrate that this approach may support the development of future systems with increased throughput and reliability, for biosciences applications.

Abstract
Laser-induced breakdown spectroscopy (LIBS) imaging has now a well-established position in the subject of spectral imaging, leveraging multi-element detection capabilities and fast acquisition rates to support applications both at academic and technological levels. In current applications, the standard processing pipeline to explore LIBS imaging data sets revolves around identifying an element that is suspected to exist within the sample and generating maps based on its characteristic emission lines. Such an approach requires some previous expert knowledge both on the technique and on the sample side, which hinders a wider and more transparent accessibility of the LIBS imaging technique by non-specialists. To address this issue, techniques based on visual analysis or peak finding algorithms are applied on the average or maximum spectrum, and may be employed for automatically identifying relevant spectral regions. Yet, maps containing relevant information may often be discarded due to low signal-to-noise ratios or interference with other elements. In this context, this work presents an agnostic processing pipeline based on a spatial information ratio metric that is computed in the Fourier space for each wavelength and that allows for the identification of relevant spectral ranges in LIBS. The results suggest a more robust and streamlined approach to feature extraction in LIBS imaging compared with traditional inspection of the spectra, which can introduce novel opportunities not only for spectral data analysis but also in the field of data compression.

Abstract
This paper presents an approach to enhancing sensitivity in optical sensors by integrating self-image theory and graphene oxide coating. The sensor is specifically engineered to quantitatively assess glucose concentrations in aqueous solutions that simulate the spectrum of glucose levels typically encountered in human saliva. Prior to sensor fabrication, the theoretical self-image points were rigorously validated using Multiphysics COMSOL 6.0 software. Subsequently, the sensor was fabricated to a length corresponding to the second self-image point (29.12 mm) and coated with an 80 mu m/mL graphene oxide film using the Layer-by-Layer technique. The sensor characterization in refractive index demonstrated a wavelength sensitivity of 200 +/- 6 nm/RIU. Comparative evaluations of uncoated and graphene oxide-coated sensors applied to measure glucose in solutions ranging from 25 to 200 mg/dL showed an eightfold sensitivity improvement with one bilayer of Polyethyleneimine/graphene. The final graphene oxide-based sensor exhibited a sensitivity of 10.403 +/- 0.004 pm/(mg/dL) and demonstrated stability with a low standard deviation of 0.46 pm/min and a maximum theoretical resolution of 1.90 mg/dL.

Abstract
The potential of ultrafast laser machining for the design of integrated optical devices in ULE (R) glass, a material known for its low coefficient of thermal expansion (CTE), is addressed. This was done through laser direct writing and characterization of optical waveguides and through the fabrication of 3D cavities inside the glass by following laser irradiation with chemical etching. Type I optical waveguides were produced and their internal loss mechanisms at 1550 nm were studied. Coupling losses lower than 0.2 dB cm-1 were obtained within a wide processing window. However, propagation loss lower than 4.2-4.3 dB cm-1 could not be realized, unlike in other glasses, due to laser-induced photodarkening. Selective-induced etching was observed over a large processing window and found to be maximum when irradiating the glass with a fs-laser beam linearly polarised orthogonally to the scanning direction, akin to what is observed in fused silica laser-machined microfluidic channels. In fact, the etching selectivity and surface roughness of laser-machined ULE (R) glass was found to be similar to that of fused silica, allowing some of the already reported microfluidic and optofluidic devices to be replicated in this low CTE glass. An example of a 3D cavity with planar-spherically convex interfaces is given. Due to the thermal properties of ULE (R) glass, these cavities can be employed as interferometers for wavelength and/or temperature referencing.

Abstract
Continuous monitoring of hydrogen (H2) concentration is critical for safer use, which can be done using optical sensors. Palladium (Pd) is the most commonly used transducer material for this monitoring. This material absorbs H2 leading to an isotropic expansion. This process is reversible but is affected by the interaction with interferents, and the lifetime of Pd thin films is a recurring issue. Fiber Bragg Grating (FBG) sensors are used to follow the strain induced by H2 on Pd thin films. In this work, it is studied the stability of Pd-coated FBGs, protected with a thin Polytetrafluoroethylene (PTFE) layer, 10 years after their deposition to assess their viability to be used as H2 sensors for long periods of time. It was found that Pd coatings that were PTFE-protected after deposition had a longer lifetime than unprotected films, with the same sensitivities that they had immediately after their deposition, namely 23 and 10 pm/vol% for the sensors with 150 and 100 nm of Pd, respectively, and a saturation point around 2 kPa. Furthermore, the Pd expansion was analyzed in the presence of H2, nitrogen (N2), carbon dioxide (CO2), methane (CH4) and water vapor (H2O), finding that H2O is the main interferent. Finally, an exhaustive test for 90 h is also done to analyze the long-term stability of Pd films in dry and humid environments, with only the protected sensor maintaining the long-term response. As a result, this study emphasizes the importance of using protective polymeric layers in Pd films to achieve the five-year lifetime required for a real H2 monitoring application.

Abstract
An optical fiber pH sensor based on a long-period fiber grating (LPFG) is reported. Two oppositely charged polymers, polyethylenimine (PEI) and polyacrylic acid (PAA), were alternately deposited on the sensing structure through a layer-by-layer (LbL) electrostatic self-assembly technique. Since the polymers are pH sensitive, their refractive index (RI) varies when the pH of the solution changes due to swelling/deswelling phenomena. The fabricated multilayer coating retained a similar property, enabling its use in pH-sensing applications. The pH of the PAA dipping solution was tuned so that a coated LPFG achieved a pH sensitivity of (6.3 +/- 0.2) nm/pH in the 5.92-9.23 pH range. Only two bilayers of PEI/PAA were used as an overlay, which reduces the fabrication time and increases the reproducibility of the sensor, and its reversibility and repeatability were demonstrated by tracking the resonance band position throughout multiple cycles between different pH solutions. With simulation work and experimental results from a low-finesse Fabry-Perot (FP) cavity on a fiber tip, the coating properties were estimated. When saturated at low pH, it has a thickness of 200 nm and 1.53 +/- 0.01 RI, expanding up to 310 nm with a 1.35 +/- 0.01 RI at higher pH values, mostly due to the structural changes in the PAA.