Gas Sensors Based on Localized Surface Plasmon Resonances: Synthesis of Oxide Films with Embedded Metal Nanoparticles, Theory and Simulation, and Sensitivity Enhancement Strategies

Fibrous Structures: An Overview of Their Responsiveness to External Stimuli towards Intended Application

In recent decades, the interest in responsive fibrous structures has surged, propelling them into diverse applications: from wearable textiles that adapt to their surroundings, to filtration membranes dynamically altering selectivity, these structures showcase remarkable versatility. Various stimuli, including temperature, light, pH, electricity, and chemical compounds, can serve as triggers to unleash physical or chemical changes in response. Processing methodologies such as weaving or knitting using responsive yarns, electrospinning, as well as coating procedures, enable the integration of responsive materials into fibrous structures. They can respond to these stimuli, and comprise shape memory materials, temperature-responsive polymers, chromic materials, phase change materials, photothermal materials, among others. The resulting effects can manifest in a variety of ways, from pore adjustments and altered permeability to shape changing, color changing, and thermal regulation. This review aims to explore the realm of fibrous structures, delving into their responsiveness to external stimuli, with a focus on temperature, light, and pH.

Gold Nanoparticle-Based Colorimetric Biosensing for Foodborne Pathogen Detection

Ensuring safe high-quality food is an ongoing priority, yet consumers face heightened risk from foodborne pathogens due to extended supply chains and climate change in the food industry. Nanomaterial-based assays are popular and have recently been developed to ensure food safety and high quality. This review discusses strategies for utilizing gold nanoparticles in colorimetric biosensors. The visible-signal biosensor proves to be a potent sensing technique for directly measuring targets related to foodborne pathogens in the field of food analysis. Among visible-signal biosensors, the localized surface plasmon resonance (LSPR) biosensor has garnered increasing attention and experienced rapid development in recent years. This review succinctly introduces the origin of LSPR theory, providing detailed insights into its fundamental principles. Additionally, this review delves into the application of nanotechnology for the implementation of the LSPR biosensor, exploring methods for utilizing gold nanoparticles and elucidating the factors that influence the generation of visible signals. Several emerging technologies aimed at simple and rapid immunoassays for onsite applications have been introduced in the food industry. In the foreseeable future, field-friendly colorimetric biosensors could be adopted in food monitoring systems. The onsite and real-time detection of possible contaminants and biological substances in food and water is essential to ensure human health and safety.

Deep Learning for Optical Sensor Applications: A Review

Over the past decade, deep learning (DL) has been applied in a large number of optical sensors applications. DL algorithms can improve the accuracy and reduce the noise level in optical sensors. Optical sensors are considered as a promising technology for modern intelligent sensing platforms. These sensors are widely used in process monitoring, quality prediction, pollution, defence, security, and many other applications. However, they suffer major challenges such as the large generated datasets and low processing speeds for these data, including the high cost of these sensors. These challenges can be mitigated by integrating DL systems with optical sensor technologies. This paper presents recent studies integrating DL algorithms with optical sensor applications. This paper also highlights several directions for DL algorithms that promise a considerable impact on use for optical sensor applications. Moreover, this study provides new directions for the future development of related research.

Towards Digital Twins of Plasmonic Sensors: Constructing the Complex Numerical Model of a Plasmonic Sensor Based on Hexagonally Arranged Gold Nanoparticles

In this work, we aim to design the digital twin of a plasmonic sensor based on hexagonally arranged ellipsoidal gold nanoparticles fixed to a glass substrate. Based on electron microscopy images of three experimentally realized nanoparticle arrangement types, we constructed numerical models in environments based on finite element method (FEM) and boundary element method (BEM), namely COMSOL Multiphysics for FEM and the MNPBEM Matlab Toolbox for BEM. Models with nonperiodic and periodic boundary conditions with different unit cells were constructed to study the plasmonic behavior of both the single ellipsoidal particles and the hexagonal nanoparticle arrangements. The effect of the geometrical parameters, namely the interparticle distance, the nanoparticle diameter and thickness, on the resulting LSPR peak positions and bulk refractive index sensitivities were studied in detail, also taking into account the effect of the SiO₂ substrate (pillars) under the ellipsoidal particles. We have demonstrated that by optimizing the models, the LSPR peak positions (and sensitivities) can match the experimentally measured values within 1 nm (nm/RIU) precision. The comparison of simulation conditions and the detailed discussion of the effect of the geometrical parameters and used gold dielectric functions on the obtained sensitivities can be very beneficial for the optimization of plasmonic sensor constructions through numerical simulations.

Lightweight Gas Sensor Based on MEMS Pre-Concentration and Infrared Absorption Spectroscopy Inside a Hollow Fiber

This paper reports on a compact and lightweight sensor for analysis of gases/vapors by means of a MEMS-based pre-concentrator coupled to a miniaturized infrared absorption spectroscopy (IRAS) module. The pre-concentrator was utilized to sample and trap vapors in a MEMS cartridge filled with sorbent material and to release them once concentrated by fast thermal desorption. It was also equipped with a photoionization detector for in-line detection and monitoring of the sampled concentration. The vapors released by the MEMS pre-concentrator are injected into a hollow fiber, which acts as the analysis cell of the IRAS module. The miniaturized internal volume of the hollow fiber of about 20 microliters keeps the vapors concentrated for analysis, thus allowing measurement of their infrared absorption spectrum with a signal to noise ratio high enough to identify the molecule, despite the short optical path, starting from sampled concentration in air down to parts per million. Results obtained for ammonia, sulfur hexafluoride, ethanol and isopropanol are reported to illustrate the sensor detection and identification capability. A limit of identification (LoI) of about 10 parts per million was validated in the lab for ammonia. The lightweight and low power consumption design of the sensor allowed operation onboard unmanned aerial vehicles (UAVs). The first prototype was developed within the EU Horizon 2020 project ROCSAFE for the remote assessment and forensic examination of a scene in the aftermath of industrial or terroristic accidents.

High-Performance Room-Temperature NO2 Gas Sensor Based on Au-Loaded SnO2 Nanowires under UV Light Activation

Optical excitation is widely acknowledged as one of the most effective means of balancing sensor responses and response/recovery properties at room temperature (RT, 25 °C). Moreover, noble metals have been proven to be suitable as photosensitizers for optical excitation. Localized surface plasmon resonance (LSPR) determines the liberalization of quasi-free electrons in noble metals under light irradiation, and numerous injected electrons in semiconductors will greatly promote the generation of chemisorbed oxygen, thus elevating the sensor response. In this study, pure SnO₂ and Au/SnO₂ nanowires (NWs) were successfully synthesized through the electrospinning method and validated using XRD, EDS, HRTEM, and XPS. Although a Schottky barrier led to a much higher initial resistance of the Au/SnO₂ composite compared with pure SnO₂ at RT in the dark, the photoinduced resistance of the Au/SnO₂ composite became lower than that of pure SnO₂ under UV irradiation with the same intensity, which confirmed the effect of LSPR. Furthermore, when used as sensing materials, a detailed comparison between the sensing properties of pure SnO₂ and Au/SnO₂ composite toward NO₂ in the dark and under UV irradiation highlighted the crucial role of the LSPR effects. In particular, the response of Au/SnO₂ NWs toward 5 ppm NO₂ could reach 65 at RT under UV irradiation, and the response/recovery time was only 82/42 s, which far exceeded those under Au modification-only or optical excitation-only. Finally, the gas-sensing mechanism corresponding to the change in sensor performance in each case was systematically proposed.

Chitosan Micro-Membranes with Integrated Gold Nanoparticles as an LSPR-Based Sensing Platform

Currently, there is an increasing need to develop highly sensitive plasmonic sensors able to provide good biocompatibility, flexibility, and optical stability to detect low levels of analytes in biological media. In this study, gold nanoparticles (Au NPs) were dispersed into chitosan membranes by spin coating. It has been demonstrated that these membranes are particularly stable and can be successfully employed as versatile plasmonic platforms for molecular sensing. The optical response of the chitosan/Au NPs interfaces and their capability to sense the medium's refractive index (RI) changes, either in a liquid or gas media, were investigated by high-resolution localized surface plasmon resonance (HR-LSPR) spectroscopy, as a proof of concept for biosensing applications. The results revealed that the lowest polymer concentration (chitosan (0.5%)/Au-NPs membrane) presented the most suitable plasmonic response. An LSPR band redshift was observed as the RI of the surrounding media was incremented, resulting in a sensitivity value of 28 ± 1 nm/RIU. Furthermore, the plasmonic membrane showed an outstanding performance when tested in gaseous atmospheres, being capable of distinguishing inert gases with only a 10^-5 RI unit difference. The potential of chitosan/Au-NPs membranes was confirmed for application in LSPR-based sensing applications, despite the fact that further materials optimization should be performed to enhance sensitivity.

Optimization of Au:CuO Thin Films by Plasma Surface Modification for High-Resolution LSPR Gas Sensing at Room Temperature

In this study, thin films composed of gold nanoparticles embedded in a copper oxide matrix (Au:CuO), manifesting Localized Surface Plasmon Resonance (LSPR) behavior, were produced by reactive DC magnetron sputtering and post-deposition in-air annealing. The effect of low-power Ar plasma etching on the surface properties of the plasmonic thin films was studied, envisaging its optimization as gas sensors. Thus, this work pretends to attain the maximum sensing response of the thin film system and to demonstrate its potential as a gas sensor. The results show that as Ar plasma treatment time increases, the host CuO matrix is etched while Au nanoparticles are uncovered, which leads to an enhancement of the sensitivity until a certain limit. Above such a time limit for plasma treatment, the CuO bonds are broken, and oxygen is removed from the film's surface, resulting in a decrease in the gas sensing capabilities. Hence, the importance of the host matrix for the design of the LSPR sensor is also demonstrated. CuO not only provides stability and protection to the Au NPs but also promotes interactions between the thin film's surface and the tested gases, thereby improving the nanocomposite film's sensitivity. The optimized sensor sensitivity was estimated at 849 nm/RIU, which demonstrates that the Au-CuO thin films have the potential to be used as an LSPR platform for gas sensors.

An LSPR Sensor Integrated with VCSEL and Microfluidic Chip

The work introduces a localized surface plasmon resonance (LSPR) sensor chip integrated with vertical-cavity surface-emitting lasers (VCSELs). Using VCSEL as the light source, the hexagonal gold nanoparticle array was integrated with anodic aluminum oxide (AAO) as the mask on the light-emitting end face. The sensitivity sensing test of the refractive index solution was realized, combined with microfluidic technology. At the same time, the finite-difference time- domain (FDTD) algorithm was applied to model and simulate the gold nanostructures. The experimental results showed that the output power of the sensor was related to the refractive index of the sucrose solution. The maximum sensitivity of the sensor was 1.65 × 106 nW/RIU, which gives it great application potential in the field of biomolecular detection.

Special Issue on Optical Sensors and Gauges Based on Plasmonic Resonance

A surface plasmon is a plasmon that propagates through a surface; i [...]

Immobilization of Streptavidin on a Plasmonic Au-TiO2 Thin Film towards an LSPR Biosensing Platform

Optical biosensors based on localized surface plasmon resonance (LSPR) are the future of label-free detection methods. This work reports the development of plasmonic thin films, containing Au nanoparticles dispersed in a TiO₂ matrix, as platforms for LSPR biosensors. Post-deposition treatments were employed, namely annealing at 400 °C, to develop an LSPR band, and Ar plasma, to improve the sensitivity of the Au-TiO₂ thin film. Streptavidin and biotin conjugated with horseradish peroxidase (HRP) were chosen as the model receptor–analyte, to prove the efficiency of the immobilization method and to demonstrate the potential of the LSPR-based biosensor. The Au-TiO₂ thin films were activated with O₂ plasma, to promote the streptavidin immobilization as a biorecognition element, by increasing the surface hydrophilicity (contact angle drop to 7°). The interaction between biotin and the immobilized streptavidin was confirmed by the detection of HRP activity (average absorbance 1.9 ± 0.6), following a protocol based on enzyme-linked immunosorbent assay (ELISA). Furthermore, an LSPR wavelength shift was detectable (0.8 ± 0.1 nm), resulting from a plasmonic thin-film platform with a refractive index sensitivity estimated to be 33 nm/RIU. The detection of the analyte using these two different methods proves that the functionalization protocol was successful and the Au-TiO₂ thin films have the potential to be used as an LSPR platform for label-free biosensors.

Design of Two-Mode Spectroscopic Sensor for Biomedical Applications: Analysis and Measurement of Relative Intensity Noise through Control Mechanism

The design of an intracavity spectroscopy based two-mode biomedical sensor involves a thorough investigation of the system. For this purpose, the individual components that are present in the system must be examined. This work describes the principle of two very important gadgets, namely the Fibre Bragg Grating (FBG), and the tunable coupler. We adhere to a Petri network scheme to model and analyze the performance of the FBG, and the results mirror strikingly low difference in the values of Bragg Wavelength during its ascending and descending operational principle, thereby maintaining the accuracy of the sensor’s results. Next, a pseudocode is developed and implemented for the investigation of the optical coupler in LabView. The values of its maximum output power are determined, and the coupling ratio for various values of controlling voltage is determined at three different wavelengths. The hysteresis results mirror an extremely low difference between the forward and reverse values in the results. Both the results of the FBG and the coupler are thereby extremely reliable to use them in the laser system, as evident from the respective intensity noise outcomes, as well as the experimentation on substances of interest (Dichloro Methane and Propofol).

Plasmonic Strain Sensors Based on Au-TiO2 Thin Films on Flexible Substrates

This study aimed at introducing thin films exhibiting the localized surface plasmon resonance (LSPR) phenomenon with a reversible optical response to repeated uniaxial strain. The sensing platform was prepared by growing gold (Au) nanoparticles throughout a titanium dioxide dielectric matrix. The thin films were deposited on transparent polymeric substrates, using reactive magnetron sputtering, followed by a low temperature thermal treatment to grow the nanoparticles. The microstructural characterization of the thin films’ surface revealed Au nanoparticle with an average size of 15.9 nm, an aspect ratio of 1.29 and an average nearest neighbor nanoparticle at 16.3 nm distance. The plasmonic response of the flexible nanoplasmonic transducers was characterized with custom-made mechanical testing equipment using simultaneous optical transmittance measurements. The higher sensitivity that was obtained at a maximum strain of 6.7%, reached the values of 420 nm/ε and 110 pp/ε when measured at the wavelength or transmittance coordinates of the transmittance-LSPR band minimum, respectively. The higher transmittance gauge factor of 4.5 was obtained for a strain of 10.1%. Optical modelling, using discrete dipole approximation, seems to correlate the optical response of the strained thin film sensor to a reduction in the refractive index of the matrix surrounding the gold nanoparticles when uniaxial strain is applied.

Developing GLAD Parameters to Control the Deposition of Nanostructured Thin Film

In this paper, we describe the device developed to control the deposition parameters to manage the glancing angle deposition (GLAD) process of metal-oxide thin films for gas-sensing applications. The GLAD technique is based on a set of parameters such as the tilt, rotation, and substrate temperature. All parameters are crucial to control the deposition of nanostructured thin films. Therefore, the developed GLAD controller enables the control of all parameters by the scientist during the deposition. Additionally, commercially available vacuum components were used, including a three-axis manipulator. High-precision readings were tested, where the relative errors calculated using the parameters provided by the manufacturer were 1.5% and 1.9% for left and right directions, respectively. However, thanks to the formula developed by our team, the values were decreased to 0.8% and 0.69%, respectively.

Maximizing the Surface Sensitivity of LSPR Biosensors through Plasmon Coupling-Interparticle Gap Optimization for Dimers Using Computational Simulations

The bulk and surface refractive index sensitivities of LSPR biosensors, consisting of coupled plasmonic nanosphere and nano-ellipsoid dimers, were investigated by simulations using the boundary element method (BEM). The enhancement factor, defined as the ratio of plasmon extinction peak shift of multi-particle and single-particle arrangements caused by changes in the refractive index of the environment, was used to quantify the effect of coupling on the increased sensitivity of the dimers. The bulk refractive index sensitivity (RIS) was obtained by changing the dielectric medium surrounding the nanoparticles, while the surface sensitivity was modeled by depositing dielectric layers on the nanoparticle in an increasing thickness. The results show that by optimizing the interparticle gaps for a given layer thickness, up to ~80% of the optical response range of the nanoparticles can be utilized by confining the plasmon field between the particles, which translates into an enhancement of ~3-4 times compared to uncoupled, single particles with the same shape and size. The results also show that in these cases, the surface sensitivity enhancement is significantly higher than the bulk RI sensitivity enhancement (e.g., 3.2 times vs. 1.8 times for nanospheres with a 70 nm diameter), and thus the sensors' response for molecular interactions is higher than their RIS would indicate. These results underline the importance of plasmonic coupling in the optimization of nanoparticle arrangements for biosensor applications. The interparticle gap should be tailored with respect to the size of the used receptor/target molecules to maximize the molecular sensitivity, and the presented methodology can effectively aid the optimization of fabrication technologies.

Recent Developments in Plasmonic Sensors of Phenol and Its Derivatives

Many scientists are increasingly interested in on-site detection methods of phenol and its derivatives because these substances have been universally used as a significant raw material in the industrial manufacturing of various chemicals of antimicrobials, anti-inflammatory drugs, antioxidants, and so on. The contamination of phenolic compounds in the natural environment is a toxic response that induces harsh impacts on plants, animals, and human health. This mini-review updates recent developments and trends of novel plasmonic resonance nanomaterials, which are assisted by various optical sensors, including colorimetric, fluorescence, localized surface plasmon resonance (LSPR), and plasmon-enhanced Raman spectroscopy. These advanced and powerful analytical tools exhibit potential application for ultrahigh sensitivity, selectivity, and rapid detection of phenol and its derivatives. In this report, we mainly emphasize the recent progress and novel trends in the optical sensors of phenolic compounds. The applications of Raman technologies based on pure noble metals, hybrid nanomaterials, and metal–organic frameworks (MOFs) are presented, in which the remaining establishments and challenges are discussed and summarized to inspire the future improvement of scientific optical sensors into easy-to-operate effective platforms for the rapid and trace detection of phenol and its derivatives.