Sensors International最新文献

Graphene and its derivatives have become essential materials in modern biomedical research due to their positive impact on various applications. Moreover, the integration of graphene-based materials with microfluidics technology has opened up new possibilities. The novelty of the current review is considering comprehensive analysis of the transformative impact of graphene and its derivatives in biomedical applications, particularly highlighting the integration with microfluidics technology. While many studies have focused on individual applications of graphene, this review uniquely present a holistic view of its potential across various biomedical fields, including drug delivery, gene delivery, tissue engineering, and photothermal treatment, detection, sensor with respect to conventional and microfluidics techniques. In this review, we analysed published research to unveil the increasing interest in graphene's potential applications in healthcare and medicine, as well as its prospects for further exploration. We explore the fundamental concepts of graphene, its properties, and its latest applications in medical implants and biological fields within the context of microfluidics and conventional prospects. The review also addresses the challenges and limitations of these materials and their promising future, recognizing that graphene research is still in its early stages compared to commercial applications.

The uncontrolled use of ciprofloxacin (CIP) has led to increased resistance in patients and potential health issues such as kidney disorders, digestive disorder, and liver complications. This study addresses these concerns by introducing an innovative electrochemical sensor utilizing a screen-printed electrode (SPE) enhanced with a novel rGO-SnO₂ nanocomposite for the precise monitoring of CIP concentration. Through square wave voltammetry (SWV), this sensor demonstrates unparalleled sensitivity and accuracy in determining CIP levels. These analyses validated the superior performance of the SPE/rGO-SnO₂ electrode, revealing CIP potential range of 0.85–1.50 V with irreversible oxidation reaction and an exceptional signal-to-background (S/B) ratio of 1.91, surpassing the 1.21 ratio achieved by the SPE/rGO electrode. The SPE/rGO-SnO₂ electrode also exhibited the highest active surface area (0.0252 cm²), facilitating faster transfer electron. Crucially, the SPE/rGO-SnO₂ electrode exhibited an impressively low limit of detection (LOD) at 2.03 μM within a concentration range of 30–100 μM for CIP, setting a new benchmark for sensitivity (9.348 μA/μM) in CIP detection. The %RSD value was less than 5 % indicating that this modified electrodes exhibit good precision and stability. The real-world applicability of this developed methods was exemplified through its successful implementation in the analysis of river water and milk, achieving remarkable recovery rates of 101.2 % and 97.7 %, respectively. Consequently, the SPE modified with rGO-SnO₂ nanocomposite emerges as a highly promising and effective tool for precise and sensitive CIP measurement, offering unparalleled performance metrics and opening avenues for enhanced environmental and health monitoring.

A facile method for trivalent chromium (Cr³⁺) ion determination using optical silver nanoparticles capped carbon dots (Ag@CDs) was developed. The optical responses via absorption and fluorescence of Ag@CDs in the presence of Cr³⁺ ion were detected. The nanocomposite showed maximum absorption wavelength at 406.0 nm, while emission wavelength appeared at 526.0 nm when excited at 406.0 nm. Optimal conditions for the Ag@CDs activity on Cr³⁺ ion detection were at pH 6, volume ratio between Ag@CDs and Cr³⁺ ion of 1.0:4.0, and reaction time of 20 min. The linearity range of the detection was 0.1–10.0 mg/L. In the absorption mode, the limit of detection (LOD) and limit of quantification (LOQ) were 0.10 mg/L and 0.31 mg/L, respectively. The fluorescence mode of detection showed LOD and LOQ of 0.06 mg/L and 0.18 mg/L, respectively. The dual-mode sensor was applied for Cr³⁺ ion quantification in dietary supplement samples because it is an essential micronutrient and widely used as supplement products. The recovery study of the spiked sample extracts was in the range of 96.86–103.05 %. The results showed good agreement with those from a conventional method of atomic emission spectrometry. The optical changing mechanism of the nanocomposite could be explained by the electron transfer from Ag@CDs to Cr³⁺.

The current study demonstrates the manufacturing of highly sensitive aptasensr for the robust and effective detection of dengue virus antigen. The proposed electrochemical aptasensor employs both types of electrodes, namely commercialized screen-printed electrodes (C-SPEs) and self-fabricated screen-printed electrodes (SF-SPEs), were efficiently diagnose dengue virus antigen (DENV-Ag) and shows a lower limit of detection (LOD) i.e., 0.1 μg/ml. Both the electrode types were coated with chemically synthesized ZnO-Nanomaterial, which aids in electron transport, and to make it more selective highly specific DNA-aptamer was used against the DENV antigen. SEM and Uv–Vis spectra approaches were used to characterize the synthesized nanomaterial. To confirm the DENV-antigen detection results, electrochemical analysis was performed and the sensor cross-reactivity was also checked by a close member of the dengue virus i.e., chikungunya virus (CHIKV). The developed platform based on SF-SPEs & C-SPEs performed well in human serum. This investigation found that the SF-SPEs system had advanced sensitivity and responded very well to the C-SPEs. Consequently, the SF-SPEs system has emerged as a feasible choice for low-cost and highly sensitive DENV-detection and is also applicable for other analytes diagnostics.

Air pollution is a significant problem in big cities due to the rapid increase of anthropogenic activities and severe traffic congestion. Therefore, real-time and micro tools for air monitoring are urgently necessary for fast and better policy decision-making. The current city air monitoring tool is typically static and serves a macro area. This study introduces technology development to integrate the air quality sensor with the satellite-based navigation receiver. This study used a carbon dioxide (CO₂) MH-Z19C sensor and real-time kinematic global navigation satellite system (RTK GNSS) U-Blox F9P with GNSS Trimble NetR9 receiver. The field air quality monitoring (CO₂ observed in ppm) and the movement velocity (vehicle speed observed in km/h) were recorded on two main roads of Jakarta by using a survey vehicle. The study compares the observation results of the non-integrated system (NIS) and integrated technology system (IS). The two systems generated the CSV database (CO₂ and vehicle speed); however, IS generated the automatic synchronized and error-free data output. The statistical regression analysis of CSV data (CO₂ and vehicle speed) between the NIS and IS reported significant results, which means both are reliable. Still, the NIS did not require manual synchronization, with some possibility of error. The R square values show a significant gap (speed 0.99 over CO₂ 0.144), indicating that IS needs further development as the CO₂ data varies due to technicality. The finding presents that integrating the CO₂ sensor and GNSS receiver generates a more effective time synchronization process and a reliable error removal technique in developing the CSV data. This finding is a significant reference in developing the integrated satellite-based receiver system with external environmental sensors.

Owing to their significant roles in multiple sectors, the demand for high-performance, rapid, user-friendly, and low-cost sensors is crucial for biosensing. This paper reports the performance of a commercial chip-based tunneling magnetoresistance (TMR) sensor for detecting green-synthesized magnetic nanoparticles (MNP) as potential magnetic labels. A Simple and low-cost design consisting of a TMR chip ALT-025 integrated with an Arduino microcontroller and a basic differential amplifier was developed to provide real-time and measurable digital readouts. Three kinds of ferrite MNPs (Fe₃O₄, CoFe₂O₄ and MnFe₂O₄) was synthesized by the coprecipitation method on the green synthesis approach utilizing Moringa Oleifera extracts. All sample have a face-centered cubic inverse spinel structure with average grain size of 10.3 nm, 9.2 nm and 6.1 nm for Fe₃O₄, CoFe₂O₄ and MnFe₂O₄, respectively. Furthermore, soft ferromagnetic behavior is identified for all sample with magnetization saturation of 55.3 emu/g, 37.6 emu/g, 19.3 emu/g for Fe₃O₄, CoFe₂O₄ and MnFe₂O₄, respectively. The sensor showed a promising performance in the detection of MNPs. For the three particles, the sensitivity exhibited a linear function of the MNPs concentration. The sensitivity is related not only to the particle size but also to the magnetization of the nanoparticles in the bias field. The change in the output voltage was proportional to the bias magnetization (M_Bias), indicating that particles with a higher bias magnetization can produce a stronger magnetic stray field on the TMR sensor surface. The sensor system successfully detected MNPs at different stray field intensities. Furthermore, a low limit of detection was achieved using these methods. Moreover, the remarkable stability and repeatability of the sensor is further validated by the steady signal acquired for 30s with an RSD of 0.5–28.5 %. Therefore, the integration of commercial chip-based TMR sensors and green-synthesized MNPs has great potential for advancing the detection of various biomolecules.

In this investigation, we employed a cost-efficient co-precipitation technique to synthesize nanostructures of Indium-doped ZnO, incorporating varying percentages of Indium (0.25 %, 0.5 %, 1 %, 2 %, and 4 %) into the ZnO lattice. These Indium atoms were introduced either by replacing oxygen (O₂) or occupying tetrahedral interstitial spaces within the structure. The resultant materials exhibited an average crystal size ranging from approximately 5 to 10 nm and displayed a highly crystalline nature. The UV–visible spectroscopy of these synthesized materials, revealing an excitation spectrum spanning 380 nm–395 nm. Photoluminescence measurements showed two distinct emission peaks at 390 nm and 471 nm, originates from the recombination of the free excitons through an exciton-exciton collision process and the presence of defects or impurities in the In–ZnO nanostructures. Defects in the crystal lattice, such as oxygen vacancies or interstitial defects, can create energy levels within the bandgap. Subsequently, we evaluated the suitability of these Indium-doped ZnO nanostructures for light sensor applications. Response and recovery times to infrared (IR), visible, and ultraviolet (UV) light was recorded. Remarkably, the nanostructures exhibited exceptional response and recovery times, in UV light compared to their performance with IR and visible light. This significant performance of synthesized materials in UV light shows the cost-effective co-precipitation method in fabricating Indium-doped ZnO nanostructures for UV light sensing applications.

In this paper, we present and investigate a novel approach for self-referenced sensing using a multilayer structure in Kretschmann configuration. The obtained results show that the structure can support two modes, plasmon-induced transparency and waveguide mode. The sensing performance of the structure was evaluated by calculating the sensor Sensitivity, Quality Factor, and Figure of Merit. Moreover, to quantify the capability of our approach for self-referencing sensing we calculated the self-referencing figure of merit. We demonstrate that the PIT mode-based approach has the best simulation results in terms of Figure of Merit of 5950/RIU, Quality Factor of 292.5/RIU, and Self-Referencing Figure of Merit of 5.7. The designed biosensors can be used for accurate and reliable sensing applications.

The effectiveness and dependability of network communication within the Internet of Things (IoT) depends on the energy-harvesting capabilities of IoT sensors. It is imperative to efficiently handle energy resources to fulfill computational requirements, ensuring optimal performance and continuous operation of IoT sensors across various applications. This investigation examines the challenges associated with energy harvesting in commonly used IoT sensors and their corresponding communication technologies. This encompasses wireless communication, cyber–physical systems (CPS), machine-to-gateway communication (M2G), wireless power transmission (WPT), and IoT infrastructure and protocols such as IPv6, 6LoWPAN, MQTT, CoAP. Furthermore, the study explores routing algorithms within the IoT network context, recognizing their crucial role in addressing challenges related to sensor battery lifespan and energy conservation. Challenges in energy resource management, which include considerations of sensor types, spatial relationships, and connection stability, are also discussed. The study investigates the energy consumption of different types of connections in an IoT network during data transfer, considering factors such as jitter, packet loss, overhead, congestion, distance between nodes, network protocol (MQTT), and data size (32MB). Two scenarios are explored: one where the minimum frequency band and data rate are fixed, revealing that Sigfox consumes more energy than others, while Bluetooth v5.0 is more energy-efficient; and another where the maximum frequency band and data size are fixed, showing that 5G consumes more energy, whereas NB-IoT is more energy-efficient. Finally, the research investigates the energy consumption increments for various network connections (2G, 3G, 4G, 5G, Bluetooth V5.0, Sigfox, WiMAX, LoRaWAN, Zigbee, and NB-IoT) as the frequency band and network data rate increase from minimum to maximum values, revealing increments within the range of 7% to 71%.