Search Results (106)

Copper-thiolate nanostructures, formed through the self-assembly of cysteine (Cys) and glutathione (GSH) with copper ions, offer a versatile platform for redox-active applications due to their structural stability and chemical functionality. In this study, Cu-Cys-GSH nanoparticles were synthesized and employed to develop a capacitive biosensor for the ultralow concentration detection of hydrogen peroxide (H₂O₂). The detection mechanism leverages a Fenton-like reaction, where H₂O₂ interacts with Cu-Cys-GSH nanoparticles to generate hydroxyl radicals (·OH) through redox cycling between Cu²⁺ and Cu⁺ ions. These redox processes induce changes in the sensor’s surface charge and dielectric properties, enabling highly sensitive capacitive sensing at gold interdigitated electrodes (IDEs). The influence of chirality on sensing performance was investigated by synthesizing nanoparticles with both L- and D-cysteine enantiomers. Comparative analysis revealed that the stereochemistry of cysteine impacts the catalytic activity and sensor response, with Cu-L-Cys-GSH nanoparticles exhibiting superior performance. Specifically, the biosensor achieved a linear detection range from 1.0 fM to 1.0 pM and demonstrated an ultra-sensitive detection limit of 21.8 aM, outperforming many existing methods for H₂O₂ detection. The sensor’s practical performance was further validated using milk and saliva samples, yielding high recovery rates and confirming its robustness and accuracy for real-world applications. This study offers a disposable, low-cost sensing platform compatible with sustainable healthcare practices and facilitates easy integration into point-of-care diagnostic systems. Full article

A user-friendly, portable, low-cost readout system for the on-site or point-of-care characterization of chemo- and biosensors based on an electrolyte–insulator–semiconductor capacitor (EISCAP) has been developed using a thumb-drive-sized commercial impedance analyzer. The system is controlled by a custom Python script and allows to characterize EISCAP sensors with different methods (impedance spectra, capacitance-voltage, and constant-capacitance modes), which are selected in a user interface. The performance of the portable readout system was evaluated by pH measurements and the detection of the antibiotic penicillin, hereby using EISCAPs consisting of Al/p-Si/SiO₂/Ta₂O₅ structures and compared to the results obtained with a stationary commercial impedance analyzer. Both the portable and the commercial systems provide very similar results with almost perfectly overlapping recorded EISCAP signals. The new portable system can accelerate the transition of EISCAP sensors from research laboratories to commercial end-user devices. Full article

Interleukin-8 (IL-8) is a critical biomarker associated with inflammation and disability in both adults and newborns. Conventional detection methods are often labor-intensive, time-consuming, and require highly trained personnel. Non-Faradaic impedimetric biosensors offer a label-free, rapid, and direct approach for IL-8 detection. While previous studies have primarily focused on capacitance and phase changes, the potential of other impedimetric parameters remains underexplored. In this study, a gold interdigitated electrode (Au-IDE)-based non-Faradaic biosensor was developed for IL-8 detection, evaluating multiple impedimetric parameters, including capacitance, impedance magnitude (Z_mod), real impedance (Z_real), and imaginary impedance (Z_imag). Among these, Z_imag exhibited the lowest limit of detection (LoD) at 90 pg/mL, followed by Z_mod at 120 pg/mL, and capacitance at 140 pg/mL, all significantly below the clinical threshold of 600 pg/mL. In contrast, Z_real displayed the highest LoD at 1.3 ng/mL. Sensitivity analysis revealed that Z_imag provided the highest sensitivity at 13.1 kΩ/log (ng/mL), making it the most effective parameter for detecting IL-8 at low concentrations. The sensitivity of Z_mod and Z_real was lower, while capacitance sensitivity was measured at 20 nF/log (ng/mL). These findings highlight the importance of investigating alternative impedimetric parameters beyond capacitance to optimize biosensor performance for biomarker detection. This study demonstrates that non-Faradaic biosensors, despite their capacitive-based nature, can achieve enhanced sensitivity and detection limits by leveraging additional impedimetric parameters, offering a promising approach for rapid and effective IL-8 detection. Full article

The global market increasingly demands alternative rapid diagnostic tools, such as disposable biosensors, to meet the growing need for point-of-care clinical testing of infectious diseases. Bacterial vaginosis (BV), a common infection caused by Gardnerella vaginalis, requires efficient and accurate detection methods to improve patient outcomes and prevent complications. However, existing diagnostic approaches often lack sensitivity, specificity, or rapid response times, highlighting the need for innovative biosensing solutions. In response to this challenge, we developed a peptide-based electrochemical biosensor for the specific detection of Gardnerella vaginalis. The sensor was designed to achieve high sensitivity, selectivity, and stability, with detection performed through electrochemical techniques. Cyclic voltammetry (CV) was employed to monitor electron transfer kinetics at the electrode surface, while electrochemical impedance spectroscopy (EIS) provided insights into changes in resistance and capacitance during peptide binding. The sensor fabrication involved covalently bonding anti-Gardnerella vaginalis peptides to a gold nanoparticle (AuNP)-modified graphene electrode, significantly enhancing bioreceptor immobilization stability and increasing the surface area for target binding interactions. The incorporation of AuNPs improved signal amplification due to their high surface-to-volume ratio and excellent conductivity, leading to enhanced sensor performance. The biosensor demonstrated a low detection limit (LOD) of 0.02305 μg/mL, with a rapid response time of 5 min across various concentrations of the target Gardnerella vaginalis antigen. The results confirmed specific and selective binding to the pathogen marker, with minimal interference from non-target species, ensuring high accuracy. The combination of graphene, AuNPs, and peptide bioreceptors resulted in robust signal enhancement, making this biosensor a promising tool for fast and reliable point-of-care diagnostics in clinical settings. Full article

Biosensors are transforming point-of-care diagnostics by simplifying the detection process and enabling rapid, accurate testing. This study introduces a novel, reusable biosensor designed for direct viral RNA detection from unfiltered saliva, targeting SARS-CoV-2. Unlike conventional methods requiring filtration, our biosensor leverages a unique electrode design that prevents interference from saliva debris, allowing precise measurements. The biosensor is based on electrochemical principles, employing oligonucleotide probes immobilized on a hydrophobic-coated electrode, which prevents air bubbles and salt crystal formation. During validation, the biosensor demonstrated a sensitivity and specificity of 100%, accurately identifying SARS-CoV-2 in saliva samples without false positives or negatives. Cross-validation with RT-qPCR, the gold standard for COVID-19 diagnostics, confirmed the reliability of our device. The biosensor’s performance was tested on 60 participants, yielding 12 true positive results and 48 true negatives, aligning perfectly with RT-qPCR outcomes. This reusable, easy-to-use biosensor offers significant potential for point-of-care applications in various healthcare settings, providing a fast, efficient, and cost-effective method for detecting viral infections such as COVID-19. Its robust design, minimal sample preparation requirements, and multiple-use capability mark a significant advancement in biosensing technology. Full article

In this paper, a new label-free DNA nanosensor based on a top-gated (TG) metal–ferroelectric–metal (MFM) graphene nanoribbon field-effect transistor (TG-MFM GNRFET) is proposed through a simulation approach. The DNA sensing principle is founded on the dielectric modulation concept. The computational method employed to evaluate the proposed nanobiosensor relies on the coupled solutions of a rigorous quantum simulation with the Landau–Khalatnikov equation, considering ballistic transport conditions. The investigation analyzes the effects of DNA molecules on nanodevice behavior, encompassing potential distribution, ferroelectric-induced gate voltage amplification, transfer characteristics, subthreshold swing, and current ratio. It has been observed that the feature of ferroelectric-induced gate voltage amplification using the integrated MFM structure can significantly enhance the biosensor’s sensitivity to DNA molecules, whether in terms of threshold voltage shift or drain current variation. Additionally, we propose the current ratio as a sensing metric due to its ability to consider all DNA-induced modulations of electrical parameters, specifically the increase in on-state current and the decrease in off-state current and subthreshold swing. The obtained results indicate that the proposed negative-capacitance GNRFET-based DNA nanosensor could be considered an intriguing option for advanced point-of-care testing. Full article

Despite the direct, redox-free and simple detection non-faradaic impedimetric biosensors offer, considerable optimizations are required to enhance their performance for the detection of various biomarkers. Non-faradaic EIS sensors’ performance depends on the interfacial capacitance between a polarized biosensor surface and the tested sample solution. Careful engineering and design of the interfacial capacitance is encouraged to magnify the redout signal upon bioreceptor–antigen interactions. One of the methods to achieve this goal is by optimizing the self-assembled monolayer concentration, which has not been reported for non-faradaic impedimetric sensors. Here, the impact of alkanethiolate (cysteamine) concentration on the performance of gold (Au) interdigitated electrode (Au-IDE) biosensors is reported. Six sets of biosensors were prepared, each with a different cysteamine concentration: 100 nM, 1 μM, 10 μM, 100 μM, 1 mM, and 10 mM. The biosensors were prepared for the direct detection of LDL cholesterol by attaching LDL antibodies on top of the cysteamine via a glutaraldehyde cross-linker. As the concentration of cysteamine increased from 100 nM to 100 μM, the sensitivity of the biosensor increased from 6.7 to 16.2 nF/ln (ng/mL). As the cysteamine concentration increased from 100 μM to 10 mM, the sensitivity deteriorated. The limit of detection (LoD) of the biosensor improved as the cysteamine increased from 100 nM to 100 μM (i.e., 400 ng/mL to 59 pg/mL). However, the LoD started to increase to 67 pg/mL and 16 ng/mL for 1 mM and 10 mM cysteamine concentrations, respectively. This shows that the cysteamine concentration has a detrimental effect on redox-free biosensors. The cysteamine layer has to be as thin as possible and uniformly cover the electrode surfaces to maximize positive readout signals and reduce negative signals, significantly improving both sensitivity and LoD. Full article

Herein, we investigate the potential application of a composite consisting of PEDOT:PSS/Graphene, deposited via spray coating on a flexible substrate, as an autonomous conducting film for applications in wearable biosensor devices. The stability of PEDOT:PSS/Graphene is assessed through electrochemical impedance spectroscopy (EIS), cyclic voltammetry (CV) and linear polarization (LP) during exposure to an artificial sweat electrolyte, while scanning electron microscopy (SEM) was employed to investigate the morphological changes in the layer following these. The results indicate that the layers exhibit predominant capacitive behavior in the potential range of −0.3 to 0.7 V vs. Ag/AgCl, with a cut-off frequency of approximately 1 kHz and retain 90% capacity after 500 cycles. Aging under exposure to air for 6 months leads only to a minor increase in impedance, demonstrating potential for storage under non-demanding conditions. However, prolonged exposure (>48 h) to the artificial sweat causes significant degradation, resulting in an impedance increase of over 1 order of magnitude. The observed degradation raises important considerations for the long-term viability of these layers in wearable biosensor applications, prompting the need for additional protective measures during prolonged use. These findings contribute to ongoing efforts to enhance the stability and reliability of conducting materials for biosensors in health care and biotechnology applications. Full article

This study presents a novel data-driven modeling approach employing machine learning to develop predictive “soft sensors” for real-time monitoring of ethanol and substrate levels during bioethanol fermentation processes. By utilizing readily measurable parameters such as pH, redox potential, capacitance, and temperature, the model enables continuous prediction of less frequently measured variables including ethanol, substrate, and cell concentrations. Eleven fermentations were conducted, focusing on intensified ethanol production from sugarcane substrate, utilizing cell cycling techniques to augment output. Despite the importance of fermentation data, its acquisition is often constrained by limitations in availability and resources. To address these challenges, this research integrates synthetic time series data generation, thereby enhancing the applicability of machine learning. Through the use of a variational autoencoder (VAE), synthetic time series data was successfully generated, facilitating training and testing of a deep neural network on both original and synthetic datasets. Results demonstrate a significant 30% increase in prediction robustness with the incorporation of generated data, while maintaining comparable accuracy levels. The augmented data effectively enhances the generalization ability of trained models, mitigating overfitting and expanding decision boundaries, thereby overcoming challenges associated with small datasets and inevitable data deviations. This innovative approach offers a promising avenue for enhancing the reliability and scalability of bioethanol fermentation monitoring through AI-based biosensors. Full article

Insects destroy approximately one third of the world’s annual crop production. Their early detection enables the implementation of appropriate measures to prevent excessive infestation. Insects use species-specific chemical signals known as pheromones to communicate and attract their conspecifics. Interestingly, these pheromones are used to lure insects into traps for pest control purposes. Despite its effectiveness, this method is laborious and time-consuming as it requires frequent observations to identify and count the captures. As an alternative, the detection of pheromones is a promising solution for insect surveillance. In this context, we are developing biosensors based on pheromone receptors (PRs) immobilized on diamond-based capacitive micromachined ultrasonic transducers (CMUT) with the aim of achieving highly selective detection of pest insect pheromones. Full article

This paper presents a comprehensive study focusing on the detection and characterization of droplets with volumes in the nanoliter range. Leveraging the precise control of minute liquid volumes, we introduced a novel spectroscopic on-chip microsensor equipped with integrated microfluidic channels for droplet generation, characterization, and sensing simultaneously. The microsensor, designed with interdigitated ring-shaped electrodes (IRSE) and seamlessly integrated with microfluidic channels, offers enhanced capacitance and impedance signal amplitudes, reproducibility, and reliability in droplet analysis. We were able to make analyses of droplet length in the range of 1.0–6.0 mm, velocity of 0.66–2.51 mm/s, and volume of 1.07 nL–113.46 nL. Experimental results demonstrated that the microsensor’s performance is great in terms of droplet size, velocity, and length, with a significant signal amplitude of capacitance and impedance and real-time detection capabilities, thereby highlighting its potential for facilitating microcapsule reactions and enabling on-site real-time detection for chemical and biosensor analyses on-chip. This droplet-based microfluidics platform has great potential to be directly employed to promote advances in biomedical research, pharmaceuticals, drug discovery, food engineering, flow chemistry, and cosmetics. Full article

Heart failure represents a primary cause of hospitalization and mortality in both developed and developing countries, often necessitating heart transplantation as the only viable recovery path. Despite advances in transplantation medicine, organ rejection remains a significant post-operative challenge, traditionally monitored through invasive endomyocardial biopsies (EMB). This study introduces a rapid prototyping approach to organ rejection monitoring via a sensor-integrated flexible patch, employing electrical impedance spectroscopy (EIS) for the non-invasive, continuous assessment of resistive and capacitive changes indicative of tissue rejection processes. Utilizing titanium-dioxide-coated electrodes for contactless impedance sensing, this method aims to mitigate the limitations associated with EMB, including procedural risks and the psychological burden on patients. The biosensor’s design features, including electrode passivation and three-dimensional microelectrode protrusions, facilitate effective monitoring of cardiac rejection by aligning with the heart’s curvature and responding to muscle contractions. Evaluation of sensor performance utilized SPICE simulations, scanning electron microscopy, and cyclic voltammetry, alongside experimental validation using chicken heart tissue to simulate healthy and rejected states. The study highlights the potential of EIS in reducing the need for invasive biopsy procedures and offering a promising avenue for early detection and monitoring of organ rejection, with implications for patient care and healthcare resource utilization. Full article

Electrochemical impedance spectroscopy (EIS) is becoming more and more relevant for the characterization of biosensors employing interdigitated electrodes. We compare four different sensor topologies for an exemplary use case of ion sensing to extract recommendations for the design optimizations of impedimetric biosensors. Therefore, we first extract how sensor design parameters affect the sensor capacitance using analytical calculations and finite element (FEM) simulations. Moreover, we develop equivalent circuit models for our sensor topologies and validate them using FEM simulations. As a result, the impedimetric sensor response is better understood, and sensitive and selective frequency ranges can be determined for a given sensor topology. From this, we extract design optimizations for different sensing principles. Full article

Biosensors based on ion-sensitive field effect transistors (ISFETs) combined with aptamers offer a promising and convenient solution for point-of-care testing applications due to the ability for fast and label-free detection of a wide range of biomarkers. Mobile and easy-to-use readout devices for the ISFET aptasensors would contribute to further development of the field. In this paper, the development of a portable PC-controlled device for detecting aptamer-target interactions using ISFETs is described. The device assembly allows selective modification of individual ISFETs with different oligonucleotides. Ta₂O₅-gated ISFET structures were optimized to minimize trapped charge and capacitive attenuation. Integrated CMOS readout circuits with linear transfer function were used to minimize the distortion of the original ISFET signal. An external analog signal digitizer with constant voltage and superimposed high-frequency sine wave reference voltage capabilities was designed to increase sensitivity when reading ISFET signals. The device performance was demonstrated with the aptamer-driven detection of troponin I in both reference voltage setting modes. The sine wave reference voltage measurement method reduced the level of drift over time and enabled a lowering of the minimum detectable analyte concentration. In this mode (constant voltage 2.4 V and 10 kHz 0.1Vp-p), the device allowed the detection of troponin I with a limit of detection of 3.27 ng/mL. Discrimination of acute myocardial infarction was demonstrated with the developed device. The ISFET device provides a platform for the multiplexed detection of different biomarkers in point-of-care testing. Full article

This study presents a biosensor fabricated based on integrated passive device (IPD) technology to measure microbial growth on solid media in real-time. Yeast (Pichia pastoris, strain GS115) is used as a model organism to demonstrate biosensor performance. The biosensor comprises an interdigital capacitor in the center with a helical inductive structure surrounding it. Additionally, 12 air bridges are added to the capacitor to increase the strength of the electric field radiated by the biosensor at the same height. Feasibility is verified by using a capacitive biosensor, and the change in capacitance values during the capacitance detection process with the growth of yeast indicates that the growth of yeast can induce changes in electrical parameters. The proposed IPD-based biosensor is used to measure yeast drop-added on a 3 mm medium for 100 h at an operating frequency of 1.84 GHz. The resonant amplitude of the biosensor varies continuously from 24 to 72 h due to the change in colony height during vertical growth of the yeast, with a maximum change of 0.21 dB. The overall measurement results also fit well with the Gompertz curve. The change in resonant amplitude between 24 and 72 h is then analyzed and reveals a linear relationship with time with a coefficient of determination of 0.9844, indicating that the biosensor is suitable for monitoring yeast growth. Thus, the proposed biosensor is proved to have potential in the field of microbial proliferation detection. Full article