Shearography is a contactless, full-field, and laser-based optical nondestructive testing (NDT) method capable of measuring deformation fields. However, due to its interferometric nature, it is susceptible to environmental noise factors. Therefore, quantifying the amount of noise contained in the interferograms is a leading factor in increasing the robustness of shearography systems. In addition, noise measurement can be used as a determining parameter for the feasibility of shearographic inspections, allowing the establishment of practical limits conducive to reliable and accurate shearography inspections. This work introduces a novel, streamlined, and efficient method for evaluating random noise. To the best of our knowledge, this is the first demonstration of a noise evaluation routine directly on wrapped phase difference maps, eliminating the necessity for phase unwrapping algorithms. This not only reduces one step in the entire procedure but also mitigates potential errors associated with the unwrapping step, thereby simplifying and refining the entire process. The proposed method was initially applied to simulated wrapped phase difference maps containing Gaussian noise, leading to relative errors smaller than 1% for synthetic maps with noise levels below 62 gray levels. An upper limit of 65 gray levels was observed, as the image are then completely degraded. Finally, the proposed method was applied to real phase maps acquired experimentally with a one-shot shearography device, where results showed that the method is capable of measuring noise with amplitudes up to 0.07 mu m (70 nm).

Nitrogen-doped carbon nanodots synthesized from l-arginine and ethylenediamine (NCNDs); citric acid-derived carbon nanodots with carboxylic surface groups (α-CDs); and Silica-Cdots hybrids produced through coupling α-CDs to SiO2 nanoparticles were used for the fabrication of fluorescent PMMA-CDs optical films. The nanoparticles occlusion allows the conversion of a broader UV bandwidth to the visible by enhancing PMMA’s natural fluorescence. This UV-to-Visible conversion boost can enhance the efficiency of solar energy concentrators and generators and, as a proof-of-concept, photovoltaic cells were coated with NCNDs-doped PMMA films. Experiments show an 11.3

We study the application of a large-core hollow fiber as a platform for displacement sensing. The sensor is assembled by inserting and appropriately moving a single-mode fiber in the empty core of the hollow fiber. Such a construction allows attaining a speckled intensity profile at the hollow fiber output, which is evaluated while one controllably displaces the single-mode fiber in its interior. Our results allow identifying this scheme as a promising means for exploring the multimode characteristics of hollow fibers in sensing contexts.

Nitrogen-doped carbon nanodots synthesized from L-arginine and ethylenediamine (NCNDs) were combined to PMMA for obtaining fluorescent nanocomposites. Since this photoluminescence could increase the efficiency of solar energy concentrators and generators, photovoltaic cells were coated with such materials. Even using a setup with low contact of the optical polymer film on silicon surface, a promising 11.3% increase of cell efficiency was observed, showing the feasibility and potential for application of these environmentally friendly materials.

The research enterprise towards achieving high-performance hollow-core photonic crystal fibers has led to impressive advancements in the latest years. Indeed, using this family of fibers becomes nowadays an over-arching strategy for building a multitude of optical systems ranging from beam delivery devices to optical sources and sensors. In most applications, an effective single-mode operation is desired and, as such, the fiber micro-structure or the light launching setups are typically designed for achieving such a behavior. Alternatively, one can identify the use of large-core multimode hollow-core fibers as a promising avenue for the development of new photonic devices. Thus, in this manuscript, we propose and demonstrate the utilization of a large-core tubular-lattice fiber for accomplishing a speckle-based displacement sensor, which has been built up by insert-ing and suitably dislocating a single-mode fiber inside the void core of the hollow fiber. The work reported herein encompasses both simulation and experimental studies on the evolution of the multimode intensity distributions within the device as well as the demonstration of a displacement sensor with an estimated resolution of 0.7 mu m. We understand that this investigation identifies a new opportunity for the employment of large-core hollow fibers within the sensing framework hence widening the gamut of applications of this family of fibers.

Optical fiber specklegram sensors (FSSs) for magnetic field measurements are reported. The probes are compact, with only a fiber length of $\sim $ 100 mm exposed to a magnetic field and comprised of no-core fibers doped with terbium oxide (Tb4O7), so the Verdet constant is dramatically improved in comparison to regular commercial fibers ( $\sim 20\times $ increase, 10-mol% fiber), greatly enhancing the modulation of the output specklegram. The response to static magnetic fields was evaluated for different concentrations (6–10 mol%) of Tb4O7, yielding an increase in sensitivity of up to $59\times $ ( $8.78\times 10^{-2}$ mT $^{-{1}}$ , 10 mol%) and $6\times $ resolution ( $1.86\times 10^{-{2}}$ mT, 6 mol%) in relation to a regular silica multimode fiber (MMF). A simple setup with a He–Ne laser and inexpensive webcam charge-coupled device (CCD) camera was employed, producing results comparable to fiber sensors based on more complicated setups such as fiber interferometers. To the best of our knowledge, this comprises the first demonstration of highly multimode magnetic field FSS based on magneto-optical (MO) glass to capitalize on both the Faraday rotation and the polarization mode conversion.

Laser speckle-based systems provide sensitive measurements of displacement and stain. However, the typical saturation of correlation functions restricts the application of such techniques regarding their dynamic range. Therefore, this paper proposes using the extended zero-mean normalized cross-correlation (EZNCC) algorithm to automatically update the reference speckle image according to a programmable threshold, allowing for exceeding the decorrelation limit. Experiments investigated the effect of rigid body displacements and thermal strain at the light scattering surface (a ceramic container). The EZNCC yielded similar to 30 mu m resolution over a continuous 1500 mu m range for displacement measurements, and similar to 0.2 degrees C resolution between 21.5 degrees C and 61.5 degrees C for the temperature analysis. As this method requires minor updates to the traditional correlation algorithms, the ENZCC does not require modifications to the optical setups, improving the dynamic range and ensuring the high sensitivity of speckle correlation systems in a feasible, straightforward approach.

We present a multi-point curvature sensor based on optical fiber specklegram measurements. Apart from the current approaches, the proposed system uses an ordinary multimode fiber excited with visible light as a reflection-type probe. Besides, this method discretizes the waveguide into segments connected by joints and assumes sequential bend events, simplifying the specklegram referencing for correlation analyses and avoiding laborious deep learning processing. Sensor characterization yielded a linear response with ∼ 1.3 ∘ resolution for single curvatures, whereas shape prediction experiments in the plane resulted in maximum errors of ∼ 3.5 ∘ and ∼ 5.4 m m for angular and linear positioning, respectively. Furthermore, exploratory tests indicated errors < 2.3 ∘ regarding probe curvatures in the space. This research introduces a feasible, straightforward alternative to the available shape sensors, enabling applications in medical probes and soft robotics.

Fiber specklegram sensors (FSSs) traditionally use statistical methods to analyze specklegrams obtained from fibers for sensing purposes, but can suffer from limitations such as vulnerability to noise and lack of dynamic range. In this paper we demonstrate that deep learning improves the analysis of specklegrams for sensing, which we show here for both air temperature and water immersion length measurements. Two deep neural networks (DNNs); a convolutional neural network and a multi-layer perceptron network, are used and compared to a traditional correlation technique on data obtained from a multimode fiber exposed-core fiber. The ability for the DNNs to be trained against a random noise source such as specklegram translations is also demonstrated.

A novel strategy for online real-time remote monitoring of air/vacuum valves in water pipelines is proposed and validated. The sensing setup consists of a fiber Bragg grating operating as an optical strain gauge and embedded into a 3D-printed thermoplastic polyurethane casing, which is then fixed to the intake/exhaust port of an air/vacuum valve and allowed to bend in response to the airflow. Experimentation with a test bench simulating water adductor piping systems shows that the proposed strategy can detect and discriminate between air purge and intake events, measure their duration, and possibly quantify the volume of displaced air. The proposed all-optical setup was compared against an orifice plate approach, producing consistent results while being more compact, robust, reliable, and requiring a single fiber optic sensor to achieve all measurements, as opposed to the four or up electronic pressure sensors with the orifice plate.

Carbon nanodots (CNDs) are interesting materials due to their intrinsic fluorescence, electron-transfer properties, and low toxicity. Here, we report a sustainable, cheap, and scalable methodology to obtain CNDs from sugarcane syrup using a domestic microwave oven. The CNDs were characterized by infrared spectroscopy, dynamic light scattering, atomic force microscopy, absorption, and emission spectroscopies. The CNDs have 3 nm in diameter with low polydispersity and are fluorescent. A fluorescent hydrogel–CNDs composite was obtained using gelatin polypeptide as the polymeric matrix. The new hydrogel–CNDs composite was incorporated in the cavities of a double-clad optical fiber using an innovative approach that resulted in a microstructured polymer optical fiber with intrinsic fluorescence. This work shows a promising alternative for the fabrication of fluorescent materials since the CNDs synthesis is sustainable and environmentally friendly. These CNDs might substitute the rare-earth and other heavy metals of high cost and toxicity, which are usually incorporated in double-clad fibers for applications on lasers, amplifiers, and spectroscopy.

This paper presents a practical laboratory approach on polymer melt flow rate and stress-strain testing to teach undergraduate students how to measure important properties of molten and solid plastics. They may learn how to obtain parameters that are important for: quality control; processing; engineering design on polymer and petrochemical industries; and even in materials selection for engineering applications. Starting from a database obtained from this traditional practice, statistical tools for data analysis were applied. Four different grades of commercial polypropylene were studied, and the 95 % confidence intervals of different parameters were compared with the suppliers’ catalogue data. This pedagogical approach aims to add a statistical point of view to laboratory experiments and to complement the learning.

This paper presents a practical laboratory approach on polymer melt flow rate and stress-strain testing to teach undergraduate students how to measure important properties of molten and solid plastics. They may learn how to obtain parameters that are important for: quality control; processing; engineering design on polymer and petrochemical industries; and even in materials selection for engineering applications. Starting from a database obtained from this traditional practice, statistical tools for data analysis were applied. Four different grades of commercial polypropylene were studied, and the 95 % confidence intervals of different parameters were compared with the suppliers’ catalogue data. This pedagogical approach aims to add a statistical point of view to laboratory experiments and to complement the learning.

The fabrication of a biodegradable and fluorescent cylindrical waveguide with doped hybrid nanoparticles (silica-carbon nanodots) is reported. The fluorescent hybrids were obtained by coupling amino-functionalized fumed silica nanoparticles with the carboxylic acid surface groups of amorphous carbon nanodots obtained from the thermolysis of citric acid. The hybrid nanoparticles present diameters lower than 10 nm, maximum fluorescence at 465 nm, and excitation-wavelength-dependent behavior. They were occluded into an agarose matrix, providing a low-cost and easily scalable sensor capable of detecting pH variations with maximum sensitivity of 5.61 nm/(pH unit) when excited by a 403 nm UV light-emitting diode (LED).

Bioreactors are employed in several industries, such as pharmaceutics, energy, biomedic and food. To ensure the proper operation of these bioreactors, Enzyme-Linked Immunosorbent Assay (ELISA) and High-Performance Liquid Chromatography (HPLC) systems are commonly used. Although ELISA and HPLC provide very precise results, they are incapable of real-time monitoring and present high operational costs. Given this context, in this work, we discuss the technical and economic viability of implementing fiber optics-based monitoring systems in lieu of traditional ELISA and HPLC systems. We selected fed-batch ethanol fermentative systems for our analysis, as the fed-batch mode is not only prevalent in different fermentative industries, but ethanol production represents a major sector of the Brazilian economy, with annual production in excess of 35 billion liters. Then, a simple fiber sensing system for measuring the refractive index of the fermentation broth, capable of real-time monitoring the fermentation process, is proposed and the advantages of the real-time process control are discussed. Afterward, we present the long-term economic gains of implementing such a system. We estimate that, by using readily commercially available components, the typical Brazilian ethanol plants will see a return for their investment in a time as short as 50 days, with a 5-year Internal Rate of Return (IRR) of 742%/year by setting up a fiber-optic monitoring system over HPLC. With the provided list of components, these numbers can be easily adjusted for industries worldwide, providing incredibly attractive economic prospects.

The inception of photonic crystal fibers (PCFs) allowed for unprecedented tailoring of waveguide properties for specialty sensing probes. Exposed core microstructured fibers (ECFs) represent a natural evolution of the PCF design for practical liquid and gas sensing. Until now, to the best of our knowledge, only single-mode or few-modes ECFs have been explored. In this Letter, we demonstrate a highly multimode ECF with a lateral access that extends throughout the whole length of the fiber. The ECF is operated as a fiber specklegram sensor for assessing properties of fluids and interrogated using a simple and low-cost setup. The probe exhibits a refractive index resolution and sensitivity of at least 4.6×10-4 refractive index units (RIUs) and -10.97RIU-1, respectively. A maximum temperature resolution up to 0.017°C with a -0.20∘C-1 temperature sensitivity over the 23°C-28°C range and a liquid level sensing resolution up to 0.12 mm with -0.015mm-1 sensitivity over the 0.0-50.0 mm bathed the length range in water.

Offshore oil and gas platforms present a harsh environment for their installed infrastructure, with pipelines that are subjected to both a corrosive atmosphere and transport of aggressive chemicals being the most critical. These conditions have prompted the industry to substitute metallic pipelines for composite counterparts, often made from fiber-reinforced plastics assembled with bonded joints. Various technologies have emerged in recent years to assess the health of these composite pipelines. In particular, robust speckle metrology techniques such as shearography, although not capable of long-term monitoring, have produced very satisfactory results. However, these inspection techniques require specialized equipment and trained personnel to be flown to offshore platforms, which can incur in non-trivial inspection costs. In this paper, we propose and demonstrate a robust and cost-effective approach to monitor pipeline bonded joints during assembly and operation using fiber Bragg grating (FBG) sensors embedded into the joints' adhesive layer. This approach allows for informed decisions on when to perform targeted in-depth inspections (e.g., with shearography) based on both real-time and long-term feedback of the FBG sensors data, resulting in lower monitoring costs, a severe increase in monitoring uptime (up to full uptime), and increased operational security.

Measuring multiphase flows is essential in the oil and gas industry and medicine, as well as to microfluidic-based analyses. This article presents an optical fiber sensor for assessing the speed of two-phase flows based on tilted fiber Bragg grating (TFBG). As the dispersed slugs pass by the grating, resonance dips of cladding modes shift and work like a notch filter for a given wavelength; therefore, the TBFG can be interrogated in real-time according to an intensity-based, single-wavelength setup. The system is validated for samples comprised of water, oil, and air, yielding maximum relative error of 4.4% for speed measurements, whereas the sensor response can be tailored for different fluids by choosing the wavelength of the input light.

Biocompatible and resorbable optical fibres emerge as promising technologies for in vivo applications like imaging, light delivery for phototherapy and optogenetics, and localised drug-delivery, as well as for biochemical sensing, wherein the probe can be implanted and then completely absorbed by the organism. Biodegradable waveguides based on glasses, hydrogels, and silk have been reported, but most of these devices rely on complex fabrication procedures. In this sense, this paper proposes a novel structured optical fibre made of agarose, a transparent, edible material used in culture media and tissue engineering. The fibre is obtained by pouring food-grade agar into a mould with stacked rods, forming a solid core surrounded by air holes in which the refractive index and fibre geometry can be tailored by choosing the agarose solution composition and mould design, respectively. Besides exhibiting practical transmittance at 633nm in relation to other hydrogel waveguides, the fibre is also validated for chemical sensing either by detecting volume changes due to agar swelling/dehydration or modulating the transmitted light by inserting fluids into the air holes. Therefore, the proposed agarose-based structured optical fibre is an easy-to-fabricate, versatile technology with possible applications for medical imaging and in vivo biochemical sensing.

Industry is currently in a period of great expansion, the so-called “Industry 4.0”. This period relies on the development of new sensor technologies for the generation of systems capable of collecting, distributing, and delivering information. Particularly in chemical and biochemical industries, the development of portable monitoring devices can improve many process parameters, such as safety and productivity. In this work, the design of a smartphone-based optical fiber sensing platform for the online assessment of fed-batch fermentation systems is reported. The setup is comprised of a smartphone equipped with a 3D-printed case that couples optical fibers to the phone, and of an application for collecting images from the camera and then analyzing the pixel intensity. Finally, the obtained intensities are correlated to the broth refraction index, which is function of the sucrose concentration. We calculated the sensitivity of this sensor as 85.83 RIU−1 (refractive index units), and then compared its performance to results obtained with a handheld refractometer and with Monod model predictions. It showed to be a reliable, portable, and low-cost instrument for the online monitoring of bioreactors that can be easily reproducible on-site by simply printing it.