Polysaccharides as the Sensing Material for Metal Ion Detection-Based Optical Sensor Applications

Chitosan-based aerogels: A new paradigm of advanced green materials for remediation of contaminated water

Chitosan (CS) aerogels are highly porous (∼99 %), exhibit ultralow density, and are excellent sorbents for removing ionic pollutants and oils/organic solvents from water. Their abundant hydroxyl and amino groups facilitate the adsorption of ionic pollutants through electrostatic interaction, complexation and chelation mechanisms. Selection of suitable surface wettability is the way to separate oils/organic solvents from water. This review summarizes the most recent developments in improving the adsorption performance, mechanical strength and regeneration of CS aerogels. The structure of the paper follows the extraction of chitosan, preparation and sorption characteristics of CS aerogels for heavy metal ions, organic dyes, and oils/organic solvents, sequentially. A detailed analysis of the parameters that influence the adsorption/absorption performance of CS aerogels is carried out and their effective control for improving the performance is suggested. The analysis of research outcomes of the recently published data came up with some interesting facts that the unidirectional pore structure and characteristics of the functional group of the aerogel and pH of the adsorbate have led to the enhanced adsorption performance of the CS aerogel. Finally, the excerpts of the literature survey highlighting the difficulties and potential of CS aerogels for water remediation are proposed.

Recent advances in exploiting carrageenans as a versatile functional material for promising biomedical applications

Carrageenans are a group of biopolymers widely found in red seaweeds. Commercial carrageenans have been traditionally used as emulsifiers, stabilizers, and thickening and gelling agents in food products. Carrageenans are regarded as bioactive polysaccharides with disease-modifying and microbiota-modulating activities. Novel biomedical applications of carrageenans as biocompatible functional materials for fabricating hydrogels and nanostructures, including carbon dots, nanoparticles, and nanofibers, have been increasingly exploited. In this review, we describe the unique structural characteristics of carrageenans and their functional relevance. We summarize salient physicochemical features, including thixotropic and shear-thinning properties, of carrageenans. Recent results from clinical trials in which carrageenans were applied as both antiviral and antitumor agents and functional materials are discussed. We also highlight the most recent advances in the development of carrageenan-based targeted drug delivery systems with various pharmaceutical formulations. Promising applications of carrageenans as a bioink material for 3D printing in tissue engineering and regenerative medicine are systematically evaluated. We envisage some key hurdles and challenges in the commercialization of carrageenans as a versatile material for clinical practice. This comprehensive review of the intimate relationships among the structural features, unique rheological properties, and biofunctionality of carrageenans will provide novel insights into their biomedicine application potential.

Nitrate Classification Based on Optical Absorbance Data Using Machine Learning Algorithms for a Hydroponics System

Nutrient solution plays an essential role in providing macronutrients to hydroponic plants. Determining nitrogen in the form of nitrate is crucial, as either a deficient or excessive supply of nitrate ions may reduce the plant yield or lead to environmental pollution. This work aims to evaluate the performance of feature reduction techniques and conventional machine learning (ML) algorithms in determining nitrate concentration levels. Two features reduction techniques, linear discriminant analysis (LDA) and principal component analysis (PCA), and seven ML algorithms, for example, k-nearest neighbors (KNN), support vector machine, decision trees, naïve bayes, random forest (RF), gradient boosting, and extreme gradient boosting, were evaluated using a high-dimensional spectroscopic dataset containing measured nitrate-nitrite mixed solution absorbance data. Despite the limited and uneven number of samples per class, this study demonstrated that PCA outperformed LDA on the high-dimensional spectroscopic dataset. The classification accuracy of ML algorithms combined with PCA ranged from 92.7% to 99.8%, whereas the classification accuracy of ML algorithms combined with LDA ranged from 80.7% to 87.6%. The PCA with the RF algorithm exhibited the best performance with 99.8% accuracy.

Cu2+-imprinted optical fiber SPR sensor for intelligent recognition

An optical fiber surface plasma resonance (SPR) sensor with MMF-TCF-MMF structure was designed to realize intelligent recognition of copper ions (Cu²⁺), and the selective adsorption sensitization was achieved by plating a layer of Cu²⁺-imprinted film on the surface of gold film excitation layer. Combining the principle of optical fiber interference and SPR, the proposed sensor realized the detection of the copper ions concentration through measuring the refractive index changes caused by ions adsorption on imprinted film. The Cu²⁺-imprinted optical fiber SPR sensor can realize the intelligent recognition and detection of copper ions in the complex environment and exhibits a detection sensitivity of -10.05 pm/ppm. The proposed sensor has tremendous development potential in practical application, and provides new ideas for the field of metal ions detection.

Biomolecule-Based Optical Metamaterials: Design and Applications

Metamaterials are broadly defined as artificial, electromagnetically homogeneous structures that exhibit unusual physical properties that are not present in nature. They possess extraordinary capabilities to bend electromagnetic waves. Their size, shape and composition can be engineered to modify their characteristics, such as iridescence, color shift, absorbance at different wavelengths, etc., and harness them as biosensors. Metamaterial construction from biological sources such as carbohydrates, proteins and nucleic acids represents a low-cost alternative, rendering high quantities and yields. In addition, the malleability of these biomaterials makes it possible to fabricate an endless number of structured materials such as composited nanoparticles, biofilms, nanofibers, quantum dots, and many others, with very specific, invaluable and tremendously useful optical characteristics. The intrinsic characteristics observed in biomaterials make them suitable for biomedical applications. This review addresses the optical characteristics of metamaterials obtained from the major macromolecules found in nature: carbohydrates, proteins and DNA, highlighting their biosensor field use, and pointing out their physical properties and production paths.

SARS-CoV-2 Morphometry Analysis and Prediction of Real Virus Levels Based on Full Recurrent Neural Network Using TEM Images

The SARS-CoV-2 virus is responsible for the rapid global spread of the COVID-19 disease. As a result, it is critical to understand and collect primary data on the virus, infection epidemiology, and treatment. Despite the speed with which the virus was detected, studies of its cell biology and architecture at the ultrastructural level are still in their infancy. Therefore, we investigated and analyzed the viral morphometry of SARS-CoV-2 to extract important key points of the virus's characteristics. Then, we proposed a prediction model to identify the real virus levels based on the optimization of a full recurrent neural network (RNN) using transmission electron microscopy (TEM) images. Consequently, identification of virus levels depends on the size of the morphometry of the area (width, height, circularity, roundness, aspect ratio, and solidity). The results of our model were an error score of training network performance 3.216 × 10^-11 at 639 epoch, regression of -1.6 × 10^-9, momentum gain (Mu) 1 × 10^-9, and gradient value of 9.6852 × 10^-8, which represent a network with a high ability to predict virus levels. The fully automated system enables virologists to take a high-accuracy approach to virus diagnosis, prevention of mutations, and life cycle and improvement of diagnostic reagents and drugs, adding a point of view to the advancement of medical virology.

Chlorophyll Detection by Localized Surface Plasmon Resonance Using Functionalized Carbon Quantum Dots Triangle Ag Nanoparticles

An optical sensor-based localized surface plasmon resonance (LSPR) sensor was demonstrated for sensitive and selective chlorophyll detection through the integration of amino-functionalized carbon quantum dots (NCQD) and triangle silver nanoparticles (AgNPs). The additions of amino groups to the CQD enhance the detection of chlorophyll through electrostatic interactions. AgNPs-NCQD composite was fabricated on the surface of the silanized glass slide using the self-assembly technique. The experimental results showed that the AgNPs-NCQD film-based LSPR sensor detects better than AgNPs and AgNPs-CQD films with a good correlation coefficient (R² = 0.9835). AgNPs-NCQD showed a high sensitivity response of 2.23 nm ppm^-1. The detection and quantification limits of AgNPs-NCQD are 1.03 ppm and 3.40 ppm, respectively, in the range of 0.05 to 6 ppm. Throughout this study, no significant interference was observed among the other ionic species (NO₂^-, PO₄^-, NH₄⁺, and Fe³⁺). This study demonstrates the applicability of the proposed sensor (AgNPs-NCQD) as a sensing material for chlorophyll detection in oceans.

Improved Metal Cation Optosensing Membranes through the Incorporation of Sulphated Polysaccharides

Optosensing chitosan-based membranes have been applied for the detection of heavy metals, especially in drinking water. The novelty of this study is based on the use of sulphated polysaccharides, in such optosensing membranes, aiming at an improved analytical performance. The sulphated polysaccharides, such as ulvan, fucoidan and chondroitin sulfate, were extracted from by-products and wastes of marine-related activities. The membranes were developed for the analysis of aluminum. The variation in the visible absorbance of the sensor membranes after the contact between the chromophore and the aluminum cation was studied. The membranes containing sulphated polysaccharides showed improved signals when compared to the chitosan-only membrane. As for the detection limits for the membranes containing ulvan, fucoidan and chondroitin sulfate, 0.17 mg L⁻¹, 0.21 mg L⁻¹ and 0.36 mg L⁻¹ were obtained, respectively. The values were much lower than that obtained for the chitosan-only membrane, 0.52 mg L⁻¹, which shows the improvement obtained from the sulphated polysaccharides. The results were obtained with the presence of CTAB in analysis solution, which forms a ternary complex with the aluminum cation and the chromophore. This resulted in an hyperchromic and batochromic shift in the absorption band. When in the presence of this surfactant, the membranes showed lower detection limits and higher selectivity.

A Critical Review of Analytical Applications of Chitosan as a Sustainable Chemical with Functions Galore

Biomass and biowastes stand as sustainable and cost-effective environmentally benign alternative feedstock. Chitosan is a biocompatible, bioactive, and biodegradable biopolymer derived from chitin to achieve eight aspects out of the 12 green chemistry principles. Chitosan got significant attention in several fields including chemical analysis, in addition to chemical functionally, which enabled its use as adsorbent and its structural crosslinking using various crosslinkers. The physicochemical, technological, and optical properties of chitosan have been extensively exploited in analysis. Mainly, deacetylation degree and molecular weight are controlling its properties and hence controlling its functions. This review presents a structure, properties, and functions relationships of chitosan. It also aims to provide an overview of the different functions that chitosan can serve in each analytical technique such as supporting matrix, catalyst…etc. The contribution of chitosan in improving the ecological performance is discussed in each technique.

Optical Detection of Copper Ions via Structural Dissociation of Plasmonic Sugar Nanoprobes

Heavy metal ions are known to cause environmental pollution and several human diseases because of their inherent toxicity. Among them, Cu²⁺ is an essential element for the human body, but its continuous exposure and accumulation may cause adverse effects. Thus, copper ion levels in aquatic environments are strictly regulated by international standards. Herein, we demonstrate a simple optical method for detecting Cu²⁺ using plasmonic sugar nanoprobes (PSNs) composed of gold nanoparticles and polysaccharides. Gold precursors were reduced to nanoparticles and spontaneously embedded in the sugar-based polymeric network with the sulfated residues of carrageenan during the polymerization procedure. Owing to the abundant functional residues of PSNs and their affinity toward Cu²⁺, we observed the Cu²⁺-mediated preferential dissociation of the PSNs, resulting in absorbance spectral shifts and scattering shifts of the PSNs. Based on these plasmon band shifts, Cu²⁺ below the EPA regulation level of 20 μM can be easily detected by the optimized experimental condition. Additionally, the reaction mechanism between the PSNs and Cu²⁺ was elucidated by indepth spectroscopic analyses, which revealed that the increased binding of Cu²⁺ to the sulfate groups in the PSNs induces the eventual decomposition of the PSNs.

Succinyl-κ-carrageenan Silver Nanotriangles Composite for Ammonium Localized Surface Plasmon Resonance Sensor

This research investigates the physicochemical properties of biopolymer succinyl-κ-carrageenan as a potential sensing material for NH4+ Localized Surface Plasmon Resonance (LSPR) sensor. Succinyl-κ-carrageenan was synthesised by reacting κ-carrageenan with succinic anhydride. FESEM analysis shows succinyl-κ-carrageenan has an even and featureless topology compared to its pristine form. Succinyl-κ-carrageenan was composited with silver nanoparticles (AgNP) as LSPR sensing material. AFM analysis shows that AgNP-Succinyl-κ-carrageenan was rougher than AgNP-Succinyl-κ-carrageenan, indicating an increase in density of electronegative atom from oxygen compared to pristine κ-carrageenan. The sensitivity of AgNP-Succinyl-κ-carrageenan LSPR is higher than AgNP-κ-carrageenan LSPR. The reported LOD and LOQ of AgNP-Succinyl-κ-carrageenan LSPR are 0.5964 and 2.7192 ppm, respectively. Thus, AgNP-Succinyl-κ-carrageenan LSPR has a higher performance than AgNP-κ-carrageenan LSPR, broader detection range than the conventional method and high selectivity toward NH4+. Interaction mechanism studies show the adsorption of NH4+ on κ-carrageenan and succinyl-κ-carrageenan were through multilayer and chemisorption process that follows Freundlich and pseudo-second-order kinetic model.

Localized Surface Plasmon Resonance Decorated with Carbon Quantum Dots and Triangular Ag Nanoparticles for Chlorophyll Detection

This paper demonstrates carbon quantum dots (CQDs) with triangular silver nanoparticles (AgNPs) as the sensing materials of localized surface plasmon resonance (LSPR) sensors for chlorophyll detection. The CQDs and AgNPs were prepared by a one-step hydrothermal process and a direct chemical reduction process, respectively. FTIR analysis shows that a CQD consists of NH₂, OH, and COOH functional groups. The appearance of C=O and NH₂ at 399.5 eV and 529.6 eV in XPS analysis indicates that functional groups are available for adsorption sites for chlorophyll interaction. A AgNP-CQD composite was coated on the glass slide surface using (3-aminopropyl) triethoxysilane (APTES) as a coupling agent and acted as the active sensing layer for chlorophyll detection. In LSPR sensing, the linear response detection for AgNP-CQD demonstrates R² = 0.9581 and a sensitivity of 0.80 nm ppm^-1, with a detection limit of 4.71 ppm ranging from 0.2 to 10.0 ppm. Meanwhile, a AgNP shows a linear response of R² = 0.1541 and a sensitivity of 0.25 nm ppm^-1, with the detection limit of 52.76 ppm upon exposure to chlorophyll. Based on these results, the AgNP-CQD composite shows a better linearity response and a higher sensitivity than bare AgNPs when exposed to chlorophyll, highlighting the potential of AgNP-CQD as a sensing material in this study.

Detection of COVID-19 Virus on Surfaces Using Photonics: Challenges and Perspectives

The propagation of viruses has become a global threat as proven through the coronavirus disease (COVID-19) pandemic. Therefore, the quick detection of viral diseases and infections could be necessary. This study aims to develop a framework for virus diagnoses based on integrating photonics technology with artificial intelligence to enhance healthcare in public areas, marketplaces, hospitals, and airfields due to the distinct spectral signatures from lasers' effectiveness in the classification and monitoring of viruses. However, providing insights into the technical aspect also helps researchers identify the possibilities and difficulties in this field. The contents of this study were collected from six authoritative databases: Web of Science, IEEE Xplore, Science Direct, Scopus, PubMed Central, and Google Scholar. This review includes an analysis and summary of laser techniques to diagnose COVID-19 such as fluorescence methods, surface-enhanced Raman scattering, surface plasmon resonance, and integration of Raman scattering with SPR techniques. Finally, we select the best strategies that could potentially be the most effective methods of reducing epidemic spreading and improving healthcare in the environment.

Detection of COVID-19 Virus on Surfaces Using Photonics: Challenges and Perspectives

The propagation of viruses has become a global threat as proven through the coronavirus disease (COVID-19) pandemic. Therefore, the quick detection of viral diseases and infections could be necessary. This study aims to develop a framework for virus diagnoses based on integrating photonics technology with artificial intelligence to enhance healthcare in public areas, marketplaces, hospitals, and airfields due to the distinct spectral signatures from lasers’ effectiveness in the classification and monitoring of viruses. However, providing insights into the technical aspect also helps researchers identify the possibilities and difficulties in this field. The contents of this study were collected from six authoritative databases: Web of Science, IEEE Xplore, Science Direct, Scopus, PubMed Central, and Google Scholar. This review includes an analysis and summary of laser techniques to diagnose COVID-19 such as fluorescence methods, surface-enhanced Raman scattering, surface plasmon resonance, and integration of Raman scattering with SPR techniques. Finally, we select the best strategies that could potentially be the most effective methods of reducing epidemic spreading and improving healthcare in the environment.

Optical Chemical Sensor Based on 2,2-Furildioxime in Sol-Gel Matrix for Determination of Ni2+ in Water

A new optical chemical sensor was fabricated based on incorporation of 2,2-furildioxime as a sensitive reagent into the nanopore of a transparent glasslike material through the sol-gel method which was suitable for determination of Ni2+ ions in aqueous solutions. The prepared sensors were composed of tetraethoxysilane (TEOS), 2,2-furildioxime, methanol, hydrochloric acid and Triton X-100. The sensors were constructed by dip coating onto glass substrates. The optimum response of the sensor toward Ni2+ ions was reached at pH 8.5 and the contact time for the formation of the complex at 10 min. The linear concentration of the calibration curve was in the range of 1–5 mg L−1 with a detection limit of 0.111 mg L−1, and quantification limit of 0.337 mg L−1. In addition, the relative standard deviation (RSD) was less than 5% in determination of Ni2+ with ten slide sensor membranes. The developed sensor was tested on Ni2+ determination in real water samples which was confirmed by the atomic absorption spectrophotometer method.

Analytical performance of functional nanostructured biointerfaces for sensing phenolic compounds

Electrochemical biointerfaces are constructed with a wide range of nanomaterials and conducting polymers that strongly affect the analytical performance of biosensors. The analysis of progress toward electrochemical sensing platforms offers opportunities to provide devices for commercial use. The investigation of different methods for the synthesis of phenol biointerfaces leads to design challenges in the field of monitoring phenolic compounds. This paper review the innovative strategies and feature techniques in the construction of phenolic compound biosensors. The focus was made on the preparation methods of nanostructures and nanomaterials design for catalytic improvements of sensing interfaces. The paper also provides a comprehensive overview in the field of enzyme immobilization approaches at solid supports and technical formation of polymer nanocomposites, as well as applications of hybrid organic-inorganic nanocomposites in phenolic biosensors. This review also highlights the recent progress in the electrochemical detection of phenolic compounds and summarizes analytical performance parameters including sensitivity, storage stability, limit of detection, linear range, and Michaelis-Menten kinetic analysis. It also emphasizes advances from the past decade including technical challenges for the construction of suitable biointerfaces for monitoring phenolic compounds.

Effect of Active Site Modification towards Performance Enhancement in Biopolymer κ-Carrageenan Derivatives

This research demonstrates a one-step modification process of biopolymer carrageenan active sites through functional group substitution in κ-carrageenan structures. The modification process improves the electronegative properties of κ-carrageenan derivatives, leading to enhancement of the material's performance. Synthesized succinyl κ-carrageenan with a high degree of substitution provides more active sites for interaction with analytes. The FTIR analysis of succinyl κ-carrageenan showed the presence of new peaks at 1068 cm-1, 1218 cm-1, and 1626 cm-1 that corresponded to the vibrations of C-O and C=O from the carbonyl group. A new peak at 2.86 ppm in 1H NMR represented the methyl proton neighboring with C=O. The appearance of new peaks at 177.05 and 177.15 ppm in 13C NMR proves the substitution of the succinyl group in the κ-carrageenan structure. The elemental analysis was carried out to calculate the degree of substitution with the highest value of 1.78 at 24 h of reaction. The XRD diffractogram of derivatives exhibited a higher degree of crystallinity compared to pristine κ-carrageenan at 23.8% and 9.2%, respectively. Modification of κ-carrageenan with a succinyl group improved its interaction with ions and the conductivity of the salt solution compared to its pristine form. This work has a high potential to be applied in various applications such as sensors, drug delivery, and polymer electrolytes.