Abstract
New paths to increase the sensing performance of plasmonic sensors have been reported in recent years. There are several methodologies to achieve such purpose, namely by optimizing the nanostructure, nanomaterial and even the sensing platform. Recently the use nanoparticles over plasmonic thin films have been reported and shown sensitivity enhancement, when compared to a bare thin film. Nevertheless, a nanomaterial combination between NP and thin film has not been studied. In this work it was studied such plasmonic materials in order to optimize not only refractometric sensitivity but also decrease the resultant plasmonic band width. It was found that for Au, Ag and Cu thin films, the deposition of plasmonic nanoparticles resulted in an overall refractometric sensitivity and figure of merit (FOM) increase. The larger FOM increase was obtained for the Ag thin film, from 42 to 162 when coupled to Si nanoparticles. The greater sensitivity increase was achieved for a Cu thin film coupled to a Si nanoparticle, with an increase from 1745 to 3230 nm/RIU. © Published under licence by IOP Publishing Ltd.

Abstract
The identification of olive-tree cultivars is a lengthy and expensive process, therefore, the proposed work presents a new strategy for identifying different cultivars of olive trees using their leaf and machine learning algorithms. In this initial case, four autochthonous cultivars of the Tras-os-Montes region in Portugal are identified (Cobrancosa, Madural, Negrinha e Verdeal). With the use of this type of algorithm, it is expected to replace the previous techniques, saving time and resources for farmers. Three different machine learning algorithms (Decision Tree, SVM, Random Forest) were also compared and the results show an overall accuracy rate of the best algorithm (Random Forest) of approximately 93%.

Abstract
A new (bio)sensing platform based on differential refractometric measurements was developed. The sensing scheme is based on the combination LPFGs/MIP/NIP, involving a dual channel system for real-time compensation of non-specific interactions. The correction system improves the sensor behavior by reducing the response to interferents by 30%. © 2022 The Author(s).

Abstract
The phase-matching conditions for exciting surface plasmon resonances (SPR) in plasmonic films are typically satisfied via prism, optical fibers or grating-assisted coupling. We recently showed that plasmonic nanospheres can act as local emitters, exciting SPR waves on thin films-termed nanoparticle-induced SPR (NPI-SPR). This structure holds promise for sensing, but the effects of optical fiber geometry and nanoparticle anisotropy on the response were unexplored. This study examines these factors, showing that an etched multimode fiber with a 200 mu m core diameter, taper ratio of 4, and etching angle of 20 degrees optimizes interaction with plasmonic nanoparticles. Tuning the nanoparticle aspect ratio from 1 to 3 shifts the NPI-SPR band from 780 to 1580 nm, with excitation highly dependent on the incident light angle. Notably, for light incident parallel to the film plane, a refractive index sensitivity exceeding 1000 nm/RIU is achieved. This efficient light emission combines the field locality enhancements of plasmonic nanoparticle-on-film structures with the emission efficiency of plasmonic nanoantennas, advancing plasmonic optical fiber chemical and biosensors.

Abstract
Reinforced concrete structures form the backbone of civil infrastructure due to their durability, longevity, affordability, and availability. However, aging concrete poses challenges, with decay often beginning internally and becoming visible only at advanced stages, leading to costly repairs, restricted functionality, and safety risks. To address these challenges, sensors are crucial for enhancing infrastructure resilience and optimizing repairs. This study employs multimode optical fibers to monitor concrete curing, water ingress, relative humidity (RH), cement paste carbonation, and rebar corrosion. Four sensors monitor changes in reflection at the fiber tip of a 600 mu m multimode fiber (MMF) using LEDs and photodiodes, connected via a fiber bundle containing two 200 mu m MMF. Variations in the refractive index around the fiber tip are used to monitor water throughout the concrete lifecycle, including curing, RH changes and water intrusion. Colorimetric changes in a cement paste layer and an iron-thin film are used to monitor carbonation and corrosion. The curing sensor is temperature-independent and correlates strongly with cumulative heat release from cement hydration (R=0.95). The RH sensor monitors up to and beyond 100% RH, detecting water intrusion. The corrosion sensor detects early corrosion stages and distinguishes between reflection losses from corrosion and mechanical changes. The layer of cement paste for carbonation monitoring increases reflected intensity by 17% due to carbonation, with 63% of the increase occurring in 80 minutes in a 3% CO2 atmosphere. The broad monitoring scope and low implementation cost make this sensor a unique option among commercially available solutions for structural health monitoring of reinforced concrete.

Abstract
This study investigates the fabrication of plasmonic optical fiber sensors for glyphosate detection, employing silver thin film coatings deposited via the Tollens' reaction and further enhanced with protective gold plating. Silver films were produced through electroless deposition, forming rough plasmonic surfaces with localized hotspots that amplify the electromagnetic field. Surface roughness effects on the creation of hotspots were first evaluated numerically using the finite element method (FEM) and later experimentally assessed the impact on optical response. Furthermore, to address the inherent susceptibility of silver to oxidation and corrosion, a gold plating was applied using the Kirkendall effect, selectively replacing surface silver atoms with gold. This approach significantly improved the chemical stability of the sensors while preserving their plasmonic properties. This configuration was applied in developing a biosensor, using aptamers, for detecting glyphosate in concentrations ranging from 10(-1) to 10(4) mu g/L. The results demonstrated a sensitivity of 25.08 +/- 0.22 nm/(mu g/L) and a limit of detection (LOD) of 0.04 mu g/L, nearly ten times lower than the European Union's safety limit for glyphosate. Experimental results highlight the potential of this fabrication approach for developing sensitive, stable, and scalable plasmonic sensors tailored for environmental and agricultural monitoring applications.