Search Results (11)

This work presents an intrinsic optical fiber sensor based on plasmonic phenomena in modified plastic optical fibers (POFs). The sensing area is achieved by replacing the polymethyl methacrylate (PMMA) core with a molecularly imprinted polymer (MIP) containing gold nanorods (GNRs). Thus, in the sensing area, the MIP acts as both a selective recognition element and an optically sensitive guiding medium where plasmonic phenomena occur. This optical–chemical configuration has been developed as a proof-of-concept for the detection of furfural in aqueous solution. The proposed sensor achieves a limit of detection (LOD) of 27 pM, demonstrates high selectivity for the analyte of interest, and is applicable even in real-world scenarios, as demonstrated by experimental results (a commercially available infant milk). The proposed sensor presents a significant enhancement of the sensor response, of about six orders of magnitude, compared to a conventional configuration where the same (or a similar) mixture of MIP/GNRs is spun over the exposed PMMA of a D-shaped POF area for comparison. Notably, even if this study has been carried out via a proof-of-concept in furfural detection, this substantial improvement is achieved while preserving a simple, portable, and cost-effective optical setup, highlighting the potential of this sensing strategy for the development of highly selective sensors by changing the MIP template. Full article

Optical–chemical sensors based on optical fibers can be made in reflection or transmission schemes. In the reflection scheme, the sensing area is typically present at the end of the fiber, and the light source and the detector are placed on the same side of the fiber. This approach can be exploited to achieve chemical probes useful in several application fields where remote sensing is required. In this work, to obtain an extrinsic optical fiber chemical sensor in a reflection scheme, two optical fibers are used to monitor a chemically sensitive region achieved by a C-shaped waveguide with a molecularly imprinted polymer (MIP) as a core between the optical fibers. The proposed micrometer-sized probe is developed and tested as a proof of concept via a MIP for 2-Furaldehyde (2-FAL) detection of interest in food and industrial applications. The experimental results of the proposed sensing approach showed several advantages, such as a nanomolar detection limit and an ultra-wide concentration detection range due to different kinds of MIP recognition sites in the optical path between the fibers. Full article

Molecularly imprinted polymers (MIPs) can be combined with optical fibers (OFs) to create various sensor configurations, yielding low-cost and highly sensitive extrinsic and intrinsic sensors. In this work, an MIP-based extrinsic optical fiber sensor is obtained by two silica OFs connected via an optical waveguide using an MIP as a core of micrometer size (micro OF-MIP-OF sensor). The proposed sensing approach can be used only with MIP receptors and implements an intensity-based sensor configuration. MIPs present several advantages over bio-receptors and can be exploited to realize novel sensing methods. The MIP used in this work is specifically designed for 2-furaldehyde (2-FAL) detection, and the experimental results demonstrate that the micro-probe performs well in terms of sensitivity and selectivity, with capabilities applicable to several application fields. In particular, a nanomolar detection range, from 1.5 nM to 150 nM, has been achieved. Moreover, the results are comparable to or better than those of other previously proposed MIP optical fiber sensors for 2-FAL, which employ more complex sensing principles or fabrication steps. Full article

2-Furaldehyde (2-FAL) is one of the main by-products of the degradation of hemicellulose, which is the solid material of the oil–paper insulating system of oil-filled transformers. For this reason, it has been suggested as a marker of the degradation of the insulating system; sensing devices for 2-FAL analysis in a wide concentration range are of high interest in these systems. An optical sensor system is proposed; this consists of a chemical chip, able to capture 2-FAL from the insulating oil, coupled with a surface plasmon resonance (SPR) probe, both realized on multimode plastic optical fibers (POFs). The SPR platform exploits gold nanofilm or, alternatively, a double layer of gold and silicon oxide to modulate the sensor sensitivity. The capturing chip is always based on the same molecularly imprinted polymer (MIP) as a receptor specific for 2-FAL. The system with the SPR probe based on a gold nanolayer had a higher sensitivity and a lower detection limit of fractions of μg L⁻¹. Instead, the SPR probe, based on a double layer (gold and silicon oxide), has a lower sensitivity with a worse detection limit, and it is suitable for the detection of 2-FAL at concentrations of 0.01–1 mg L⁻¹. Full article

An optical–chemical sensor based on two modified plastic optical fibers (POFs) and a molecularly imprinted polymer (MIP) is realized and tested for the detection of 2-furaldehyde (2-FAL). The 2-FAL measurement is a scientific topic of great interest in different application fields, such as human health and life status monitoring in power transformers. The proposed sensor is realized by using two POFs as segmented waveguides (SW) coupled through a micro-trench milled between the fibers and then filled with a specific MIP for the 2-FAL detection. The experimental results show that the developed intensity-based sensor system is highly selective and sensitive to 2-FAL detection in aqueous solutions, with a limit of detection of about 0.04 mg L⁻¹. The proposed sensing approach is simple and low-cost, and it shows performance comparable to that of plasmonic MIP-based sensors present in the literature for 2-FAL detection. Full article

This article presents an ultramodern modelling algorithm for predicting the remnant cellulose life cycle for oil-submerged power transformers based on the adaptive neuro-fuzzy interference system (ANFIS). The polymer characteristics, degree of polymerization (DP), and 2-furaldehyde (2FAL) of 100 power transformers were measured and collated, which were apportioned into 70 training databanks and 30 as testing datasets. The remnant cellulose life cycle of the transformer was predicted using the proposed ANFIS model characterized by polymer characteristics, DP and 2FAL as inputs. The proposed approach returns 98.23% training and 99.86% testing reliability. The proposed model was applied to 10 transformer case studies in predicting their remnant cellulose life cycle. To corroborate the proposed ANFIS, a comparative study was carried out by employing existing approaches in predicting the remnant life cycle of the case studies, and significant error margins were observed. At large, the results presented in this article certify the dominance of the proposed ANFIS algorithm over compared models. The proposed ANFIS furnishes a pathway to obliterate the constraints of classical techniques in evaluating the transformer DP and remnant cellulose life cycle. Full article

In this work, the application of a feed-forward artificial neural network (FFANN) in predicting the degree of polymerization (DP) and loss of life (LOL) in oil-submerged transformers by using the solid insulation evaluation method is presented. The solid insulation evaluation method is a reliable technique to assess and predict the DP and LOL as it furnishes bountiful information in examining the transformer condition. Herein, two FFANN models are proposed. The first model is based on predicting the DP when only the 2-Furaldehyde (2FAL) concentration measured from oil samples is available for new and existing transformers. The second FFANN model proposed is based on predicting the transformer LOL when the 2FAL and DP are available to the utility owner, typically for the transformer operating at a site where un-tanking the unit is a daunting and unfeasible task. The development encompasses constructing numerous FFANN designs and picking networks with superlative performance. The training and testing procedures databank is based on the dataset of the 2FAL and DP from a fleet of transformers and measured from laboratory analysis. The correlation coefficient of 0.964 was ascertained when the DP was predicted using the 2FAL measured in oil. In the FFANN model, a correlation coefficient of 0.999 against the practical data where one can make a reliable prediction of transformer LOL concerning 2FAL was generated and the amount of DP present produced. This model can be used to predict the DP and LOL of new and existing transformers at the manufacturer’s premises and operating in the field, respectively. To the knowledge of the authors, no research work has been published addressing the methods proposed in this work. Full article

An innovative optical-chemical sensor has been used to detect the 2-furaldehyde (2-FAL) in milk. The proposed sensing approach exploits the refractive index changing in a microstructured chip based on a plastic optical fiber (POF) with orthogonal micro-holes containing a specific molecularly imprinted polymer (MIP). This POF-MIP chemical chip modifies the surface plasmon resonance (SPR) phenomena excited in another sensor chip realized in POFs (SPR-POF) and connected in series. The proposed sensor configuration exploits MIP receptors avoiding any modification of the gold film of the SPR platform. This work reports the performance, particularly the high sensitivity and low detection limit, in complex matrices such as buffalo milk fortified with 2-FAL and in different commercial kinds of cow milk thermally treated for pasteurization. The measurements were carried out in about ten minutes by dropping the solution under-test on the planar D-shaped POF surface of the chemical chip. In contrast, on the gold surface of the SPR-POF platform, a water drop is always placed to excite the SPR phenomenon, which is modulated by the chemical chip via MIP-2-FAL binding. Furthermore, the experimental results demonstrated the pros and cons of the proposed sensor system. Thanks to the high sensitivity of the sensor system, the detection of 2-FAL in the diluted milk sample (1:50) was achieved. The dilution is required to reduce the interferent effect of the complex matrix. Full article

The life expectancy of power transformers is primarily determined by the integrity of the insulating oil and cellulose paper between the conductor turns, phases and phase to earth. During the course of their in-service lifetime, the solid insulating system of windings is contingent on long-standing ageing and decomposition. The decomposition of the cellulose paper insulation is strikingly grievous, as it reduces the tensile strength of the cellulose paper and can trigger premature failure. The latter can trigger premature failure, and to realize at which point during the operational life this may occur is a daunting task. Various methods of estimating the DP have been proposed in the literature; however, these methods yield different results, making it difficult to accurately estimate a reliable DP. In this work, a novel approach based on the Feedforward Backpropagation Artificial Neural Network has been proposed to predict the amount of DP in transformer cellulose insulation. Presently, no ANN model has been proposed to predict the remaining DP using 2FAL concentration. A databank comprising 100 data sets—70 for training and 30 for testing—is used to develop the proposed ANN using 2-furaldehyde (2FAL) as an input and DP as an output. The proposed model yields a correlation coefficient of 0.958 for training, 0.915 for validation, 0.996 for testing and an overall correlation of 0.958 for the model. Full article

2-FAL (2-furaldehyde) and furanic derivatives are the main by-products of the thermal degradation of cellulose paper insulation of power transformers’ windings. The detection of these compounds in the insulating oil of transformers is essential to investigate the ageing of the oil-paper system in order to avoid failures. To this aim, a non-conventional surface plasmon resonance (SPR) platform in plastic optical fiber (POF) was proposed for the monitoring of a biomimetic receptor specific to detect 2-FAL in transformer oil. In particular, the investigation was performed in mineral oil, which is currently the main insulating liquid for power transformers. A molecularly imprinted polymer (MIP) receptor was used, giving the sensor device a noticeable selectivity and many advantages with respect to the biological counterparts. Furthermore, the study was extended to safer and more environmentally acceptable insulating fluids representing an alternative to mineral oil (i.e., esters). To this aim, the principle and limitations of the SPR chemo-sensor performances have been discussed in this work. Full article

The possibility of investigating the binding properties of the same molecularly imprinted polymer (MIP), most probably heterogeneous, at various concentration levels by different methods such as batch equilibration and sensing, is examined, considering two kinds of sensors, based respectively on electrochemical and surface plasmon resonance (SPR) transduction. As a proof of principle, the considered MIP was obtained by non-covalent molecular imprinting of 2-furaldehyde (2-FAL). It has been found that different concentration ranges of 2-FAL in aqueous matrices can be measured by the two sensing methods. The SPR sensor responds in a concentration range from 1 × 10⁻⁴ M down to about 1 × 10⁻⁷ M, while the electrochemical sensor from about 5 × 10⁻⁶ M up to about 9 × 10⁻³ M. The binding isotherms have been fit to the Langmuir adsorption model, in order to evaluate the association constant. Three kinds of sites with different affinity for 2-FAL have been detected. The sites at low affinity are similar to the interaction sites of the corresponding NIP since they have a similar association constant. This is near to the affinity evaluated by batch equilibration too. The same association constant has been evaluated in the same concentration range. The sensing methods have been demonstrated to be very convenient for the characterization of the binding properties of MIP in comparison to the batch equilibration, in terms of reproducibility and low amount of material required for the investigation. Full article