Enhancement Of Sensing Performance Research Articles

A Review on Small Molecule Based Fluorescence Chemosensors for Bioimaging Applications.

This review provides a thorough examination of small molecule-based fluorescence chemosensors tailored for bioimaging applications, showcasing their unique ability to visualize biological processes with exceptional sensitivity and selectivity. It explores recent advancements, methodologies, and applications in this domain, focusing on various designs rooted in anthracene, benzothiazole, naphthalene, quinoline, and Schiff base. Structural modifications and molecular engineering strategies are emphasized for enhancing sensor performance, including heightened sensitivity, selectivity, and biocompatibility. Additionally, the review offers valuable insights into the ongoing development and utilization of these chemosensors, addressing current challenges and charting future directions in this rapidly evolving field.

Nanostructured transition metal dichalcogenides-based colorimetric sensors: Synthesis, characterization, and emerging applications.

Nanostructured transition metal dichalcogenides (TMDCs) have garnered significant attention as prospective materials for the development of highly sensitive and versatile colorimetric sensors. This work explores the synthesis, characterization, and emerging applications of TMDC-based sensors, focusing on their unique structural aspects and inherent properties. The synthesis methods involve tailored fabrication techniques, such as chemical vapor deposition and hydrothermal processes, aimed at producing well-defined nanostructures that enhance sensor performance. Characterization techniques, including microscopy, spectroscopy, and surface analysis, are employed to elucidate the structural and chemical features of the nanostructured TMDCs. These analyses provide insights into the correlation between the material's morphology and its sensing capabilities. The colorimetric sensing mechanism relies on the modulation of optical properties in response to specific analytes, enabling rapid and visual detection. The emerging applications of TMDC-based colorimetric sensors span diverse fields, including environmental monitoring, healthcare, and industrial processes. The sensors exhibit high sensitivity, selectivity, and real-time response, making them ideal candidates for detecting various target analytes. Furthermore, their integration with complementary technologies such as microfluidics, can facilitate the development of on-site and point-of-care applications. This work highlights the interdisciplinary significance of nanostructured TMDC-based colorimetric sensors and underscores their potential contributions to addressing contemporary challenges in sensing technology.

Nanoplasmonic sensor optimization via digital imaging analysis and antibody evolution

Localized surface plasmon resonance (LSPR) biosensors have emerged as powerful analytical tools for detecting biomolecules like proteins, DNA, and RNA across biomedical research and diagnostics, owing to their exquisite sensitivity. While optimizing nanostructures, surface functionalization, and optics have enhanced sensor performance, LSPR imaging facilitates multi-parametric quantitative analysis by acquiring supplementary spatial, chromatic, and luminance data, improving detection precision and sensitivity. Here, we introduce an innovative integrated multi-molecular dynamics (MD) simulation approach to optimize surface functionalization, circumventing limitations of singular MD methods that may ignore system complexities. Exemplifying this strategy through affinity maturation of a SARS-CoV-2 spike protein-targeting human neutralizing antibody (hNAb), we employed a comprehensive MD simulation suite to engineer an hNAb variant (MT2) exhibiting significantly augmented binding affinity (KD = 9.2 nM) compared to wild-type (20.6 nM). Consequently, MT2 enabled more sensitive SARS-CoV-2 pseudovirion detection, limits of detection (LOD) is 2524 vp/mL (wild-type LOD = 4039 vp/mL). Furthermore, our multi-parametric hue-based analysis, leveraging chromatic variations in microscopic images, optimized the LSPR optical system, demonstrating heightened sensitivity in detecting pseudovirions (765 vp/mL) and spike protein (64.25 ng/mL).

Nanofibrous Conductive Sensor for Limonene: One-Step Synthesis via Electrospinning and Molecular Imprinting.

Detecting volatile organic compounds (VOCs) emitted from different plant species and their organs can provide valuable information about plant health and environmental factors that affect them. For example, limonene emission can be a biomarker to monitor plant health and detect stress. Traditional methods for VOC detection encounter challenges, prompting the proposal of novel approaches. In this study, we proposed integrating electrospinning, molecular imprinting, and conductive nanofibers to fabricate limonene sensors. In detail, polyvinylpyrrolidone (PVP) and polyacrylic acid (PAA) served here as fiber and cavity formers, respectively, with multiwalled carbon nanotubes (MWCNT) enhancing conductivity. We developed one-step monolithic molecularly imprinted fibers, where S(-)-limonene was the target molecule, using an electrospinning technique. The functional cavities were fixed using the UV curing method, followed by a target molecule washing. This procedure enabled the creation of recognition sites for limonene within the nanofiber matrix, enhancing sensor performance and streamlining manufacturing. Humidity was crucial for sensor working, with optimal conditions at about 50% RH. The sensors rapidly responded to S(-)-limonene, reaching a plateau within 200 s. Enhancing fiber density improved sensor performance, resulting in a lower limit of detection (LOD) of 137 ppb. However, excessive fiber density decreased accessibility to active sites, thus reducing sensitivity. Remarkably, the thinnest mat on the fibrous sensors created provided the highest selectivity to limonene (Selectivity Index: 72%) compared with other VOCs, such as EtOH (used as a solvent in nanofiber development), aromatic compounds (toluene), and two other monoterpenes (α-pinene and linalool) with similar structures. These findings underscored the potential of the proposed integrated approach for selective VOC detection in applications such as precision agriculture and environmental monitoring.

Design and Optimization of Mechano transduction Sensors for effective analysis of proteins with Robotic interference

Méchano transduction sensors convert mechanical inputs into electrical signals, allowing robots to detect and interact with their environments in various bio-imaging applications. Current bio-sensor systems have some drawbacks that prevent them from being widely used in robotic applications. These include low sensitivity, short durability, and expensive manufacturing costs regarding picture prediction and categorization. To overcome these obstacles and improve robotic mechanotransduction sensors for efficient protein analysis, this work suggests Unique Sensor Fabrication Techniques (USFT). These methods enhance sensor performance in protein analysis while keeping costs low and scalability high via integrating complex micro- and nano-scale materials and architectures. In comparison to traditional sensor designs, comprehensive evaluations based on predefined parametric criteria show significant improvements in areas such as sensitivity, response time, and predictability in protein biomolecules. In addition, assessments of scalability and manufacturability point to the possibility of widespread use in robotic systems for protein categorization and prediction. In bioimaging applications, this study helps advance sensor technology for reliable and efficient robot-environment interaction.

Improved ammonia gas sensing performance at room temperature of polypyrrole by polyoxometalate decoration

Here, we introduced polyoxometalate (POMs) into polypyrrole (PPy) gas sensitive material for the first time to restrain the electron-hole recombination process and enhance the gas sensing performances. At room temperature, the sensing response value of PPy/POMs composite nanoparticles to 100 ppm NH3 gas can be improved to 80.85 %, 2.99 times than that of pure PPy nanoparticles. PPy/3 % SiW12 sensor response-recovery time was 39 s/166 s. It had good linearity (R2 = 0.9958), the LOD of NH3 was 85 ppb. In 21 days, the sensor still maintained over 90 % of the initial ammonia response value. Selectivity, repeatability and other sensing parameters were systematically investigated. In addition, the mechanism of sensing performance enhancement was analyzed and discussed. The study proved that POMs can separate electrons and holes, finally improved gas sensing properties. This work provides a new idea for the design and construction of high sensitivity PPy-based gas sensor by introducting polyoxometalates.

MOF-derived metal oxide (Cu, Ni, Zn) gas sensors with excellent selectivity towards H2S, CO and H2 gases

Metal-organic framework (MOF)-derived metal oxides blend the sensing properties of metal oxides with MOF porosity, enhancing gas sensing capabilities. In this study, M-MOFs (M = Cu, Ni and Zn) were synthesized and then calcined at different temperatures to obtain their corresponding metal oxides (CuO, NiO and ZnO). The synthesis method incorporated novel approaches to enhance sensor performance, such as optimizing calcination temperatures for improved selectivity. Structural and morphological analyses confirmed the high surface area and porosity of the metal oxide materials, facilitating efficient gas adsorption and promoting enhanced sensor response. Gas sensing studies revealed significantly enhanced performance of MOF-derived metal oxides over M-MOFs, strongly influenced by calcination temperature. Moreover, CuO, NiO and ZnO MOF-derived metal oxides showed improved selectivity towards H2S, CO and H2 gases, respectively. This study demonstrates that tuning MOF and calcination parameters can tailor sensor selectivity effectively.

Wearable Devices for Respiratory Monitoring

AbstractRespiratory diseases are currently monitored through traditional pulmonary function tests, such as spirometry. However, the restrictions of these procedures, particularly in the context of the COVID‐19 pandemic, have underscored the need for alternative approaches to respiratory health assessment. Wearable devices have emerged as a promising solution, providing continuous data collection, and overcoming the limitations posed by conventional methods. This review explores the multifaceted field of wearable devices for respiratory monitoring, presenting the most common sensing technologies applied to pulmonary ventilation, their constituent materials, fabrication techniques, and diverse morphologies to enhance sensor performance. The role of machine learning algorithms and ethical data sharing is highlighted, contributing to the forthcoming patient‐centered healthcare landscape. Ultimately, the importance of validation and calibration protocols for wearable devices is underlined. In anticipation of evolving healthcare needs, this in‐depth study addresses the current challenges in wearable respiratory monitoring while laying a robust foundation for a personalized, connected, and ethically sound future for respiratory care.

Non-Invasive Multi-Gas Detection Enabled by Cu-CuO/PEDOT Microneedle Sensor.

Metal-oxide-based gas sensors are extensively utilized across various domains due to their cost-effectiveness, facile fabrication, and compatibility with microelectronic technologies. The copper (Cu)-based multifunctional polymer-enhanced sensor (CuMPES) represents a notably tailored design for non-invasive environmental monitoring, particularly for detecting diverse gases with a low concentration. In this investigation, the Cu-CuO/PEDOT nanocomposite was synthesized via a straightforward chemical oxidation and vapor-phase polymerization. Comprehensive characterizations employing X-ray photoelectron spectroscopy (XPS), scanning electron microscopy (SEM), X-ray diffraction (XRD), and micro Raman elucidated the composition, morphology, and crystal structure of this nanocomposite. Gas-sensing assessments of this CuMPES based on Cu-CuO/PEDOT revealed that the response current of the microneedle-type CuMPES surpassed that of the pure Cu microsensor by nearly threefold. The electrical conductivity and surface reactivity are enhanced by poly (3,4-ethylenedioxythiophene) (PEDOT) polymerized on the CuO-coated surface, resulting in an enhanced sensor performance with an ultra-fast response/recovery of 0.3/0.5 s.

Controlled Insertion of Silver Nanoparticles in LbL Nanostructures: Fine-Tuning the Sensing Units of an Impedimetric E-Tongue

Silver nanoparticles (AgNPs) possess unique characteristics ideal for enhancing device sensitivity, primarily due to their high surface-to-volume ratio facilitating heightened interaction with analytes. Integrating AgNPs into polymers or carbon-based materials results in nanocomposites with synergistic properties, enabling the detection of minute changes in the environment across various applications. In this study, we investigate the adsorption kinetics of AgNPs within multilayered layer-by-layer (LbL) structures, specifically examining the impact of AgNPs concentration in the LbL film formation that is further explored as sensing units in an impedimetric microfluidic e-tongue. Although absorption kinetic studies are infrequent, they are crucial to optimize the AgNPs adsorption and distribution within LbL structures, significantly influencing upcoming applications. Through systematic variation of AgNPs concentration within identical LbL architectures, we applied the films as sensing units in a microfluidic e-tongue capable of distinguishing food enhancers sharing the umami taste profile. Across all tested scenarios, our approach consistently achieves robust sample separation, evidenced by silhouette coefficient, principal component analyses, and long-term stability. This work contributes to exploring controlled nanomaterial-based developments, emphasizing the importance of precise parameter control for enhanced sensor performance across diverse analytical applications.

Grain boundary-induced drastic sensing performance enhancement of Fe2O3 gas sensors for acetone

Grain boundary-induced drastic sensing performance enhancement of Fe2O3 gas sensors for acetone

Enhancing Structural Integrity, Optical Properties, and Room Temperature Formaldehyde Sensing Through Optimized Spray Deposition Rates

This study explores the impact of deposition rate on the properties of TiO2 thin films produced via spray pyrolysis, focusing on their application in gas sensors. The analysis covers structural, morphological, optical, and gas sensing characteristics of TiO2 films deposited at rates between 1 and 2.5 ml min−1. Studies show optimizing TiO2 film deposition rates at 2 ml min−1 significantly enhances formaldehyde detection, improving selectivity and achieving a rapid response of 7.52 at 20 ppm concentration. This study underscores the pivotal role of deposition rate optimization in augmenting the gas-sensing efficacy of TiO2 films, particularly for formaldehyde detection at ambient conditions. Optimal deposition rates are instrumental in enhancing sensor performance. The synergistic application of XRD and Raman spectroscopy unequivocally confirmed the presence of the TiO2 anatase phase, which is of paramount significance in gas sensing applications. FESEM furnished high-resolution insights into the surface morphology, revealing a spherical architecture. Furthermore, UV–vis spectroscopy was employed to assess the optical band gap of the films, which exhibited a decrement correlating with the rate of deposition. Notably, a deposition rate of 2 ml min−1 markedly improved the TiO2 films’ sensing performance. These insights are critical for developing cost-effective, high-performance gas sensors for cutting-edge applications.

Surface oxygen vacancy adjustment and acetone sensing performance enhancement of ZIF-67 derived Co3O4 with trace Ni-doping

The adjustment of surface oxygen vacancy was realized by doping the trace Ni element into the lattice of ZIF-67 derived Co3O4. The material characterizations indicated that ZIF-67 derived Co3O4 samples have porous square structure and the trace Ni elements successfully enter the lattice of Co3O4 crystal. Because of the increased oxygen vacancies caused by Ni-doping, the content of oxygen species chemically adsorbed on the surface of the optimized sample increased by 12.14 %. Compare with the pure Co3O4, the optimum operating temperatures of all the samples with trace Ni-doping were reduced by 20 °C. The response to 50 ppm acetone of the optimized sample was 30.02 with good selectivity and stability, and the response was 1.67 times higher than that of the pure one. The response-recovery rate was also improved. The response and recovery time of the optimized sample were 38 s and 35 s less than that of the pure one. The influences of oxygen vacancy and Co2+ were analyzed to understand the mechanism of the enhanced sensing properties.

Synergistic enhancement of wearable biosensor through Pt single-atom catalyst for sweat analysis

Real-time monitoring of biological markers in sweat is a valuable tool for health assessment. In this study, we have developed an innovative wearable biosensor for precise analysis of glucose in sweat during physical activities. The sensor is based on a single-atom catalyst of platinum (Pt) uniformly dispersed on tricobalt tetroxide (Co3O4) nanorods and reduced graphene oxide (rGO), featuring a unique three-dimensional nanostructure and excellent glucose electrocatalytic performance with a wide detection range of 1–800 μM. Additionally, density functional theory calculations have revealed the synergetic role of Pt active sites in the Pt single-atom catalyst (Co3O4/rGO/Pt) in glucose adsorption and electron transfer, thereby enhancing sensor performance. To enable application in wearable devices, we designed an S-shaped microfluidic chip and a point-of-care testing (POCT) device, both of which were validated for effectiveness through actual use by volunteers. This research provides valuable insights and innovative approaches for analyzing sweat glucose using wearable devices, contributing to the advancement of personalized healthcare.

A Review of Fabrication Techniques and Optimization Strategies for Microbial Biosensors

Challenges of stability and specificity associated with early generation sensors necessitate the fabrication and optimization of microbial biosensors. More so, the global biosensors market size currently valued at USD25.5 billion in 2021 is expected to grow at a compound annual growth rate (CAGR) of 7.5% to USD36.7 billion in 2026. Microbial biosensors are bioanalytical systems that integrate microorganisms with a physical transducer to generate signals, thus, aiding the identification of analytes. The biosensors are fabricated through a series of steps comprising microbe selection, immobilization onto a matrix, microfabrication, calibration, and validation. The transducers integrated microorganisms generate quantifiable signals, enabling real-time monitoring of a diversity of analytes within food samples. The optimization strategies are scrutinized, with a particular focus on the integration of sundry nanoparticles, such as magnetic, gold, and quantum-dot nanoparticles, which enhance sensor performance. Distinct advantages offered by microbial biosensors promise to revolutionize food quality assessment via cost-effectiveness, rapid sample testing, and the ability to provide access to real-time data. Literature have highlighted certain limitations including interference from complex matrices, instability of microorganisms, and microbial lifespan. In assessing their economic importance, a comparative analysis is presented against conventional food analytical methods like ELISA, PCR, and HPLC; thus, highlighting the unique strengths of microbial biosensors. The future perspectives focus on the potential of the technology in addressing the need for continuous monitoring challenges, and research for further improvements in the biocompatibility of fabrication processes and long-term reusability.

Enhanced cysteine sensor based on modified gold nanoparticles with synergistic role of pH-responsive poly (N,N-dimethylaminoethyl methacrylate)

The development of a highly sensitive and easy-to-prepare sensor for the detection of cysteine (Cys) is of great importance. Gold nanoparticles (AuNPs) have been frequently utilized as a Cys sensor owing to high affinity of the thiol group to gold. However, the presence of additional materials, such as stabilizers, can impact the sensitivity of this sensor. Herein, pH-sensitive gold nanoparticles (Au-PDA) were synthesized using poly (N,N-dimethylaminoethyl methacrylate) (PDMAEMA) for the purpose of Cys detection based on the aggregation size-dependent optical property of gold nanoparticles. Detection of cysteine was also followed by UV–Vis analysis, showing a decrease in intensity of localized surface plasmon resonance (LSPR) peak, a red shift from 525 to 550 nm as well as the appearance of a new peek at 650 nm. To enhance sensor performance, systematic investigations were conducted to optimize sensing conditions, focusing on pH, gold concentration, and ionic strength of the medium. Remarkably, the proposed sensor exhibited excellent selectivity towards Cys compared to other amino acids. The sensitivity of the sensor was evaluated using two methods: changes in the absorption intensity and the LSPR shift. The pH-sensitivity of PDMAEME led to a significant improvement in sensing parameters through a synergistic effect on the Au-Cys interaction, leading to a remarkably low LOD of 0.0004 nM, which is the lowest ever reported LOD for detection of Cys. Finally, practical application of the proposed sensor was validated in human blood serum.

Gas-phase synthesis of MoO3 nanoclusters with helium-induced high energy (060) crystal facet: Enhancing oxygen adsorption for improved gas-sensing

Adsorbed oxygen species on the surface of metal oxide semiconductors (MOS) play an important role in the field of gas-sensing. However, considering the large number of possible MOS, manipulating surface oxygen species by exposing high-energy crystal facets often requires strict experimental conditions and may not be efficiently repeated for nano MOS. This poses a huge challenge to the rational design of advanced gas-sensing materials. This study explores the fabrication of MoO3 nanocluster (NC) film by cluster beam deposition. Helium (He) is co-fed with argon (Ar) into the aggregation chamber to influence the nucleation and growth of Mo NCs. This unique process facilitated the exposure of the high-energy (060) crystal facet in MoO3 during the aging phase. This exposed crystal facet greatly reduces the oxygen adsorption energy barrier and increases the adsorbed oxygen content, resulting in a significant improvement in gas-sensing performance. The study examined the impact of energetic facets on gas sensor sensitivity by using ethanol, ammonia, and toluene as target gases. The results indicate that exposing high-energy crystal facets significantly enhances sensor performance. This approach to creating NCs with high-energy crystal facets has broad potential for advancing MOS nanostructure-based gas sensors.

Modulating the majority charge carrier type and performance of organic heterojunction ammonia sensors by increasing peripheral fluorination of the silicon phthalocyanine sublayer

Silicon phthalocyanines (R2-SiPcs) are an emerging class of high-performance organic semiconductors which have recently found application in highly sensitive and selective bilayer organic heterojunction devices for ammonia (NH3) sensing. We report bilayer heterojunction devices based on axially-substituted bis(pentafluorophenoxy)silicon phthalocyanines of increasing peripheral fluorination ((F5PhO)2-FXSiPc) as a bottom layer and lutetium bis-phthalocyanine (LuPc2) and demonstrate how increased peripheral fluorination changes device operation from p-type to n-type in response to NH3. Sensors fabricated with (F5PhO)2-F16SiPc exhibits the smallest apparent energy barrier for interfacial charge transport by impedance spectroscopy due to better alignment of the semiconductor molecular orbitals with the semi-occupied molecular orbital of LuPc2. Bilayer heterojunction devices all demonstrated a limit of detection (LOD) below 1 ppm with (F5PhO)2-SiPc/LuPc2 yielding an LOD of 307 ppb and a sensitivity of −0.72%·ppm−1. Postdeposition thermal annealing of the (F5PhO)2-SiPc/LuPc2 device is shown to further enhance sensor performance with a 1.5-fold increase in sensitivity to −1.15%·ppm−1 and a LOD of 198 ppb.

STARS-ISAC: How Many Sensors Do We Need?

A simultaneously transmitting and reflecting surface (STARS) enabled two-phase integrated sensing and communications (ISAC) framework is proposed, where a novel bi-directional sensing-STARS architecture is devised to facilitate the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">full-space</i> communication and sensing in a time-switching manner. Based on the proposed framework, a joint optimization problem is formulated, where the Cramér-Rao bound (CRB) for estimating the 2-dimension direction-of-arrival of the sensing target is minimized. Two cases are considered for sensing performance enhancement. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1) For the two-user case</i> with the fixed number of sensors, an alternating optimization algorithm is proposed. In particular, the maximum number of deployable sensors is obtained in the closed-form expressions, where the maximum number of sensors is revealed to be only relevant to the QoS requirements of communications. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2) For the multi-user case</i> with the variable number of sensors, an extended CRB (ECRB) metric is proposed to characterize the impact of the number of sensors on the sensing performance. A generic decoupling approach is proposed to convexify the non-convex ECRB expression. Based on this, a novel penalty-based double-loop (PDL) algorithm is proposed. Simulation results reveal that 1) the proposed PDL algorithm achieves a near-optimal performance with consideration of sensor deployment; 2) it is preferable to deploy more passive elements than sensors in terms of achieving optimal sensing performance.

Hybrid Nanomaterials: A Brief Overview of Versatile Solutions for Sensor Technology in Healthcare and Environmental Applications.

The integration of nanomaterials into sensor technologies not only poses challenges but also opens up promising prospects for future research. These challenges include assessing the toxicity of nanomaterials, scalability issues, and the seamless integration of these materials into existing infrastructures. Future development opportunities lie in creating multifunctional nanocomposites and environmentally friendly nanomaterials. Crucial to this process is collaboration between universities, industry, and regulatory authorities to establish standardization in this evolving field. Our perspective favours using screen-printed sensors that employ nanocomposites with high electrochemical conductivity. This approach not only offers cost-effective production methods but also allows for customizable designs. Furthermore, incorporating hybrids based on carbon-based nanomaterials and functionalized Mxene significantly enhances sensor performance. These high electrochemical conductivity sensors are portable, rapid, and well-suited for on-site environmental monitoring, seamlessly aligning with Internet of Things (IoT) platforms for developing intelligent systems. Simultaneously, advances in electrochemical sensor technology are actively working to elevate sensitivity through integrating nanotechnology, miniaturization, and innovative electrode designs. This comprehensive approach aims to unlock the full potential of sensor technologies, catering to diverse applications ranging from healthcare to environmental monitoring. This review aims to summarise the latest trends in using hybrid nanomaterial-based sensors, explicitly focusing on their application in detecting environmental contaminants.