Graphene-based Electrochemical Sensors Research Articles

Advances in Nanomaterial-Based Sensors for Early Disease Detection

Nanomaterial-based sensors are emerging as highly promising tools for the early detection of diseases, offering superior sensitivity, specificity, and miniaturization compared to traditional diagnostic methods. By leveraging the unique properties of nanomaterials such as gold nanoparticles, carbon nanotubes, graphene, and quantum dots, these sensors can detect disease biomarkers at much lower concentrations, enabling earlier diagnosis and intervention. This paper reviews the latest advancements in nanomaterial-based sensors, focusing on their applications in cancer, infectious diseases, and neurological disorders. Key developments include gold nanoparticle-based colorimetric sensors for cancer biomarker detection, graphene-based electrochemical sensors for prostate cancer and other malignancies, and quantum dot-based fluorescence sensors for both cancer and pathogen detection. Despite their promise, challenges remain, including issues with sensitivity, selectivity, reproducibility, biocompatibility, and scalability. Future directions for nanomaterial-based sensors involve improving their performance, developing multiplexed platforms for simultaneous detection of multiple biomarkers, and integrating these sensors into wearable or point-of-care devices. Overcoming these challenges and achieving regulatory approval will be crucial for the widespread clinical adoption of these advanced sensors, ultimately transforming healthcare by enabling more effective, rapid, and accessible early disease detection.

Computationally Optimized Graphene-Based Electrochemical Sensor with Enhanced Signal Stability for the Determination of the Antimicrobial Agent 9-aminoacridine

A hydrophobic aryl diazonium salt has been synthesized from 3,5-bis(trifluoromethyl)aniline and utilized to covalently modify graphene nanoplatelets and carbon nanotubes. The modified nanomaterials were applied on a screen-printed electrode/ion sensing membrane interface resulting in reduced potential drift to 100 μV h−1 compared to control sensors. Characterization was achieved through X-ray photoelectron spectroscopy. The electrode’s response was optimized using response surface methodology and then utilized for determination of 9-Aminoacridine (9-AA) in pharmaceutical gel dosage form and spiked human plasma without prior extraction steps. 9-AA is a fluorescent dye with antimicrobial activity that eradicates a range of microorganisms that can cause oral sores or broken skin and it has been recently used as anticancer among other uses as fluorescent dye and pH indicator. Accurate determination of 9-AA could help in adjusting dosages for each application. The optimized sensor was validated per IUPAC guidelines and obtained a wide linearity range from 1.0 × 10–7 M to 1.0 × 10–2 M, correlation coefficient of 0.9997, improved Nernstian slope 59.72, long term stability, and lower limit of detection (9.0 × 10–8 M). Furthermore, Analytical Eco-scale and AGREE methods were utilized to evaluate the presented method’s greenness.

Eco-Friendly Graphene-Based Electrochemical Sensor for Selective Determination of Lesinurad in Its Pharmaceutical Formulation and in the Presence of Its Degradation Products

The objective of the present study was to create solid contact ion selective electrodes (SC-ISEs) for the purpose of selectively determining lesinurad (LES) in both its pure form and pharmaceutical dosage form where potential degradation products and impurities may be present. To achieve that goal, an electrochemical sensor with graphene nanomaterial as an ion-to-electron transducer was constructed using the glassy carbon electrode (GCE) as a substrate. A number of plasticizers were tested to find the best plasticizer for creating the potentiometric sensors, where 2-nitrophenyloctyl ether (o-NPOE) revealed the optimum response and nearly Nernstian slope. Sensor was characterized and the linear range was 5.0 × 10−7 to 1.0 × 10−3 M, and the calculated LOD was found to be 4.9 × 10−7 M. The developed sensor’s performance was evaluated as per the IUPAC requirements. Lesinurad was successfully determined in its pharmaceutical tablets using the proposed sensor. Additionally, statistical comparison of the developed method with the reported HPLC results has been carried out using student’s t-test and F-value, where no significant difference was found. Using the AGREE tool, the suggested method’s greenness was assessed and contrasted with the published HPLC one.

Mechanistic Insight into Intestinal α-Synuclein Aggregation in Parkinson's Disease Using a Laser-Printed Electrochemical Sensor.

Aggregated deposits of the protein α-synuclein and depleting levels of dopamine in the brain correlate with Parkinson's disease development. Treatments often focus on replenishing dopamine in the brain; however, the brain might not be the only site requiring attention. Aggregates of α-synuclein appear to accumulate in the gut years prior to the onset of any motor symptoms. Enteroendocrine cells (specialized gut epithelial cells) may be the source of intestinal α-synuclein, as they natively express this protein. Enteroendocrine cells are constantly exposed to gut bacteria and their metabolites because they border the gut lumen. These cells also express the dopamine metabolic pathway and form synapses with vagal neurons, which innervate the gut and brain. Through this connection, Parkinson's disease pathology may originate in the gut and spread to the brain over time. Effective therapeutics to prevent this disease progression are lacking due to a limited understanding of the mechanisms by which α-synuclein aggregation occurs in the gut. We previously proposed a gut bacterial metabolic pathway responsible for the initiation of α-synuclein aggregation that is dependent on the oxidation of dopamine. Here, we develop a new tool, a laser-induced graphene-based electrochemical sensor chip, to track α-synuclein aggregation and dopamine level over time. Using these sensor chips, we evaluated diet-derived catechols dihydrocaffeic acid and caffeic acid as potential inhibitors of α-synuclein aggregation. Our results suggest that these molecules inhibit dopamine oxidation. We also found that these dietary catechols inhibit α-synuclein aggregation in STC-1 enteroendocrine cells. These findings are critical next steps to reveal new avenues for targeted therapeutics to treat Parkinson's disease, specifically in the context of functional foods that may be used to reshape the gut environment.

Progress in graphene-based electrochemical sensors for antibiotic residue detection

Progress in graphene-based electrochemical sensors for antibiotic residue detection

Empowering an Acute Kidney Injury 3D Graphene-Based Sensor Using Extreme Learning Machine.

This study reports on the application of an extreme learning machine (ELM) in near-real-time kidney monitoring via urine neutrophil gelatinase-associated lipocalin (NGAL) detection with a 3D graphene electrode. This integration marks the first instance of combining a graphene-based electrode with machine learning to enhance the NGAL detection accuracy, building on our group's 2020 research. The methodology involves two key components: a graphene electrode functionalized with a lipocalin-2 antibody for NGAL detection and the ELM application for improved prediction accuracy by using urine analysis data. The results show a significant 15% increase in the area under the curve (AUC) for NGAL determination, with error reduction from ±6 to 0.54 ng/mL within a linear range of 2.7-140 ng/mL. The ELM also lowered the detection limit from 14.8 to 0.89 ng/mL and increased accuracy, precision, sensitivity, specificity, and F1 score for AKI prediction by 8.89, 30.69, 6.78, 9.94, and 19.07%, respectively. These findings underscore the efficacy of simple neural networks in enhancing graphene-based electrochemical sensors for AKI biomarkers. ELM was chosen for its optimal performance-resource balance, with a comparative analysis of ELM, support vector machines, multilayer perceptron, and random forest algorithms also included. This research suggests the potential for miniaturizing AI-enhanced sensors for practical applications.

Harnessing Graphene-Modified Electrode Sensitivity for Enhanced Ciprofloxacin Detection.

Increased evidence has documented a direct association between Ciprofloxacin (CFX) intake and significant disruption to the normal functions of connective tissues, leading to severe health conditions (such as tendonitis, tendon rupture and retinal detachment). Additionally, CFX is recognized as a potential emerging pollutant, as it seems to impact both animal and human food chains, resulting in severe health implications. Consequently, there is a compelling need for the precise, swift and selective detection of this fluoroquinolone-class antibiotic. Herein, we present a novel graphene-based electrochemical sensor designed for Ciprofloxacin (CFX) detection and discuss its practical utility. The graphene material was synthesized using a relatively straightforward and cost-effective approach involving the electrochemical exfoliation of graphite, through a pulsing current, in 0.05 M sodium sulphate (Na2SO4), 0.05 M boric acid (H3BO3) and 0.05 M sodium chloride (NaCl) solution. The resulting material underwent systematic characterization using scanning electron microscopy/energy dispersive X-ray analysis, X-ray powder diffraction and Raman spectroscopy. Subsequently, it was employed in the fabrication of modified glassy carbon surfaces (EGr/GC). Linear Sweep Voltammetry studies revealed that CFX experiences an irreversible oxidation process on the sensor surface at approximately 1.05 V. Under optimal conditions, the limit of quantification was found to be 0.33 × 10-8 M, with a corresponding limit of detection of 0.1 × 10-8 M. Additionally, the developed sensor's practical suitability was assessed using commercially available pharmaceutical products.

Highly sensitive and disposable screen-printed graphene-based electrochemical sensor coupled with monolithic micro-solid-phase extraction for the determination of 3,4-methylenedioxymethamphetamine in forensic applications

The development of a productive assay to quantify 3,4-methylenedioxymethamphetamine (MDMA) levels in human urine samples is crucial in forensic applications. In this work, we examine the use of a disposable screen-printed graphene electrode coupled with in-tip monolithic micro-solid-phase extraction (µ-SPE) for the highly selective and sensitive determination of MDMA. To satisfy this requirement, we employ a sensor based on graphene nanomaterials integrated into a compact electrochemical device to enhance the sensitivity. In-tip monolithic µ-SPE is a facile and highly effective route for extraction and preconcentration (enrichment factor ∼ 10) to improve the sensitivity. The combination of our µ-SPE and an electrochemical sensor exhibits a remarkable performance in terms of sensitivity and selectivity for MDMA analysis. A wide linear range is observed within 0.10–10.00 µg mL−1, and the lowest limit of detection is calculated to be 0.03 µg mL−1. Moreover, no interference effect from other substances is observed for MDMA detection. The feasibility of the proposed assay is evaluated, and it is successfully used in MDMA determination in human urine samples with high accuracy, precision, reproducibility, stability, and reliability. Therefore, this novel proposed method is well suited as a compact disposable device for MDMA determination in forensic applications and can be employed by relevant government organizations to correctly identify MDMA levels in narcotic addicts.

Detection of Perfluorooctanoic and Perfluorodecanoic Acids on a Graphene-Based Electrochemical Sensor Aided by Computational Simulations

Detection of Perfluorooctanoic and Perfluorodecanoic Acids on a Graphene-Based Electrochemical Sensor Aided by Computational Simulations

Graphene-based electrochemical sensors for antibiotics: sensing theories, synthetic methods, and on-site monitoring applications.

Owing to the extensive use of antibiotics for treating infectious diseases in livestock and humans, the resulting residual antibiotics are a burden to the ecosystem and human health. Hence, for human health and ecological safety, it is critical to determine the residual antibiotics with accuracy and convenience. Graphene-based electrochemical sensors are an effective tool to detect residual antibiotics owing to their advantages, such as, high sensitivity, simplicity, and time efficiency. In this work, we comprehensively summarize the recent advances in graphene-based electrochemical sensors used for detecting antibiotics, including modifiers for electrode fabrication, theoretical elaboration of electrochemical sensing mechanisms, and practical applications of portable electrochemical platforms for the on-site monitoring of antibiotics. It is anticipated that the current review will be a valuable reference for comprehensively comprehending graphene-based electrochemical sensors and further promoting their applications in the fields of healthcare, environmental protection, and food safety.

Graphene nanocomposites for real-time electrochemical sensing of nitric oxide in biological systems.

Nitric oxide (NO) signaling plays many pivotal roles impacting almost every organ function in mammalian physiology, most notably in cardiovascular homeostasis, inflammation, and neurological regulation. Consequently, the ability to make real-time and continuous measurements of NO is a prerequisite research tool to understand fundamental biology in health and disease. Despite considerable success in the electrochemical sensing of NO, challenges remain to optimize rapid and highly sensitive detection, without interference from other species, in both cultured cells and in vivo. Achieving these goals depends on the choice of electrode material and the electrode surface modification, with graphene nanostructures recently reported to enhance the electrocatalytic detection of NO. Due to its single-atom thickness, high specific surface area, and highest electron mobility, graphene holds promise for electrochemical sensing of NO with unprecedented sensitivity and specificity even at sub-nanomolar concentrations. The non-covalent functionalization of graphene through supermolecular interactions, including π-π stacking and electrostatic interaction, facilitates the successful immobilization of other high electrolytic materials and heme biomolecules on graphene while maintaining the structural integrity and morphology of graphene sheets. Such nanocomposites have been optimized for the highly sensitive and specific detection of NO under physiologically relevant conditions. In this review, we examine the building blocks of these graphene-based electrochemical sensors, including the conjugation of different electrolytic materials and biomolecules on graphene, and sensing mechanisms, by reflecting on the recent developments in materials and engineering for real-time detection of NO in biological systems.

Advances in graphene-based electrochemical biosensors for on-site pesticide detection

The infiltration of pesticides into agricultural soils has emerged as a critical concern, posing substantial threats to the agriculture industry due to soil and water contamination. The detection of these contaminants is critical towards implementing effective environmental remediation strategies and achieving ecosystem sustainability. Electrochemical sensor technology has been demonstrated to be highly promising for this application. Graphene and its derivatives and composites are widely used as modifying materials in these sensors to enhance their analytical performance. This short review discusses recent progress in the application of graphene-based electrochemical sensors in three-electrode and field-effect transistor configurations for the detection of pesticides posing significant risks to the agricultural sector. It highlights the growing significance of graphene-based sensors in mitigating pesticide-related environmental challenges and underscores their role in ensuring the health and diversity of agricultural ecosystems.

Microplotter-Printed Graphene-Based Electrochemical Sensor for Detecting Phosphates

Microplotter-Printed Graphene-Based Electrochemical Sensor for Detecting Phosphates

Amplifying sensing performance through gold micropatterns-induced modulation of graphene's vertical electron transfer

High-quality graphene monolayers exhibit limited vertical electron transfer properties due to their inert basal plan structure, hampering their use in electrochemical sensing devices. Overcoming this limitation while maintaining the graphene's basal plane electrical conductivity is crucial for developing sensitive and efficient electrochemical sensors. In this study, we demonstrate that incorporating a gold support beneath graphene enhances its electrochemical activity by facilitating effective hybridizations between carbon atoms in graphene and gold atoms. To achieve this, micrometer-sized gold micropatterns were fabricated on Si/SiO2 substrates to support the graphene monolayer. The presence of gold significantly improved the electrochemical activity of graphene towards redox probes in solution (ferri-/ferrocyanide) as well as for adsorbed ferrocene, indicating a synergistic effect between graphene and gold. We further investigated the adsorption effects of double-stranded DNA on pristine graphene, bare gold, and graphene with a gold underlayer, revealing that the graphene-gold combination achieved a significantly lower limit of detection for DNA hybridization events, surpassing the other configurations. These findings highlight the importance of appropriate substrate selection in the design of graphene-based electrochemical sensors, particularly in the context of DNA recognition events. The proposed approach of incorporating a gold support beneath graphene holds promise for enhancing the performance of electrochemical sensing devices without compromising the intrinsic properties of graphene.

SARS-CoV-2 Spike N-Terminal Domain Engages 9-O-Acetylated α2-8-Linked Sialic Acids.

SARS-CoV-2 viruses engage ACE2 as a functional receptor with their spike protein. The S1 domain of the spike protein contains a C-terminal receptor binding domain (RBD) and an N-terminal domain (NTD). The NTD of other coronaviruses includes a glycan binding cleft. However, for the SARS-CoV-2 NTD, protein-glycan binding was only observed weakly for sialic acids with highly sensitive methods. Amino acid changes in the NTD of variants of concern (VoC) show antigenic pressure, which can be an indication of NTD-mediated receptor binding. Trimeric NTD proteins of SARS-CoV-2, alpha, beta, delta, and omicron did not reveal a receptor binding capability. Unexpectedly, the SARS-CoV-2 beta subvariant strain (501Y.V2-1) NTD binding to Vero E6 cells was sensitive to sialidase pretreatment. Glycan microarray analyses identified a putative 9-O-acetylated sialic acid as a ligand, which was confirmed by catch-and-release ESI-MS, STD-NMR analyses, and a graphene-based electrochemical sensor. The beta (501Y.V2-1) variant attained an enhanced glycan binding modality in the NTD with specificity toward 9-O-acetylated structures, suggesting a dual-receptor functionality of the SARS-CoV-2 S1 domain, which was quickly selected against. These results indicate that SARS-CoV-2 can probe additional evolutionary space, allowing binding to glycan receptors on the surface of target cells.

Highly Sensitive Graphene-Based Electrochemical Sensor for Nitrite Assay in Waters.

The importance of nitrite ions has long been recognized due to their extensive use in environmental chemistry and public health. The growing use of nitrogen fertilizers and additives containing nitrite in processed food items has increased exposure and, as a result, generated concerns about potential harmful health consequences. This work presents the development of an electrochemical sensor based on graphene/glassy carbon electrode (EGr/GC) with applicability in trace level detection of nitrite in water samples. According to the structural characterization of the exfoliated material, it appears as a mixture of graphene oxide (GO; 21.53%), few-layers graphene (FLG; 73.25%) and multi-layers graphene (MLG; 5.22%) and exhibits remarkable enhanced sensing response towards nitrite compared to the bare electrode (three orders of magnitude higher). The EGr/GC sensor demonstrated a linear range between 3 × 10-7 and 10-3 M for square wave voltammetry (SWV) and between 3 × 10-7 and 4 × 10-4 M for amperometry (AMP), with a low limit of detection LOD (9.9 × 10-8 M). Excellent operational stability, repeatability and interference-capability were displayed by the modified electrode. Furthermore, the practical applicability of the sensor was tested in commercially available waters with excellent results.

Porous carbon fabricated by a residue from Longquan lignite ethanolysis as an electrochemical sensor for simultaneous detection of hydroquinone and catechol in the presence of resorcinol

Catechol (CC), resorcinol (RS), and hydroquinone (HQ) are regarded as both important raw materials widely applied in chemical industry and highly toxic organic pollutants, so accurately detecting them is very necessary. In this work, Longquan lignite residue with low added value was fabricated as highly active porous carbons (PCs). The morphology, specific surface area (SSA), and electrocatalytic oxidation performance of the PCs prepared at different activated temperatures (600 ∼ 900 °C) were studied in detail. All PCs have different portions of micropores and mesoporous, and their SSAs can reach up to 3028 m2/g. Such well-developed microporous and mesoporous structures can provide abundant active sites to facilitate ion and electron transport, and thereby improving the electrocatalytic performance. Among them, the PC prepared at 800 °C shows the best detection performance. It can successfully detect HQ and CC simultaneously in the presence of RS, with detection limits of 0.15 and 0.81 µM for HQ, 0.09 and 0.53 µM for CC comparable to some graphene-based electrochemical sensors. Additionally, the constructed electrochemical sensor also displays a good reproducibility, stability, and anti-interference, which makes it a promising candidate material for monitoring phenolic compounds in actual water samples.

Conducting polymer functionalized graphene-based electrochemical sensors for sensing pollutants in water

Recent trends in electrochemical sensors based on conducting polymer functionalized graphene for the detection of pollutants in water are highlighted in this review. Graphene has been the subject of a lot of scientific research to be composited with conducting polymers. Researchers are interested in graphene and its variants because they have a lot of good qualities, like good electrical and mechanical properties and very high surface area. With this review, we intend to arouse interest in the important topic of graphene and conducting polymer nanocomposite that is making significant advances in electrochemical sensing, especially for sensing pollutants in water.

Laser-Scribed Graphene-Based Electrochemical Sensors: A Review

Laser scribing is a technique that converts carbon-rich precursors into 3D-graphene nanomaterial via direct, single-step, and maskless laser writing in environmental conditions and using a scalable approach. It allows simple, fast, and reagentless production of a promising material with outstanding physicochemical features to create novel electrochemical sensors and biosensors. This review addresses different strategies for fabricating laser-scribed graphene (LSG) devices and their association with nanomaterials, polymers, and biological molecules. We provide an overview of their applications in environmental and health monitoring, food safety, and clinical diagnosis. The advantages of their integration with machine learning models to achieve low bias and enhance accuracy for data analysis is also addressed. Finally, in this review our insights into current challenges and perspectives for LSG electrochemical sensors are presented.

Functionalized graphene-based electrochemical array sensors for the identification of distinct conformational states of Amyloid Beta in Alzheimer's disease

Aβ oligomers have been widely accepted as significant biomarkers for Alzheimer's disease (AD) detection, monitoring, and therapy since they are highly correlated with AD development. In this work, an electrochemical array-based sensing platform was successfully built using a group of functionalized graphene with different physicochemical features. Since the electro-insulated Aβ peptide species severely interfered with the electron transport on the electrode surface, the presence of Aβ led to a significant change in the electrochemical impedance signal. The resulting variety of the impedance was then classified and processed by linear discriminant analysis. The constructed sensing platform can discriminate different Aβ forms, the mixture of various Aβ forms, and different ratios of Aβ42 to Aβ40 with 100% accuracy by only the combination of dual probes. Furthermore, it also exhibited excellent performance for screening Aβ inhibitors and metal chelators. The strategy utilizes the infinitesimal general discrepancy instead of specific biomarker recognition, exhibiting the advantage of no requirement to know the exact information about the specific ligand and receptor in advance, which is promising to be widened for the other biosensing detection fields.