On Monolayer Formation of Pyrenebutyric Acid on Graphene

Systematic Study of Various Functionalization Steps for Ultrasensitive Detection of SARS-CoV-2 with Direct Laser-Functionalized Au-LIG Electrochemical Sensors

The 2019 coronavirus (COVID-19) pandemic impaired global health, disrupted society, and slowed the economy. Early detection of the infection using highly sensitive diagnostics is crucial in preventing the disease's spread. In this paper, we demonstrate electrochemical sensors based on laser induced graphene (LIG) functionalized directly with gold (Au) nanostructures for the detection of SARS-CoV-2 with an outstanding limit of detection (LOD) of ∼1.2 ag·mL-1. To achieve the optimum performance, we explored various functionalization parameters to elucidate their impact on the LOD, sensitivity, and linearity. Specifically, we investigated the effect of (i) gold precursor concentration, (ii) cross-linker chemistry, (iii) cross-linker and antibody incubation conditions, and (iv) antigen-sensor interaction (diffusion-dominated incubation vs pipette-mixing), as there is a lack of a systematic study of these parameters. Our benchmarking analysis highlights the critical role of the antigen-sensor interaction and cross-linker chemistry. We showed that pipette-mixing enhances sensitivity and LOD by more than 1.6- and 5.5-fold, respectively, and also enables multimodal readout compared to diffusion-dominated incubation. Moreover, the PBA/Sulfo-NHS: EDC cross-linker improves the sensitivity and LOD compared to PBASE. The sensors demonstrate excellent selectivity against other viruses, including HCoV-229E, HCoV-OC43, HCoV-NL63, and influenza H5N1. Beyond the ability to detect antigen fragments, our sensors enable the detection of antigen-coated virion mimics (which are a better representative of the real infection) down to an ultralow concentration of ∼5 particles·mL-1.

Succinimide-Functionalized Reduced Graphene Oxide Nanosheets: A High-throughput Resistive Sensing Platform for Age-Related Macular Degeneration Biomarker Determination Using Human Tears

Age-related macular degeneration (AMD) is a well-recognized affliction among the elderly, causing vision impairment ranging from blurred vision to complete blindness. This underscores the critical need for accurate, precise, and early detection methods. Herein, we developed a noninvasive, label-free electrical biosensor, constructed on an economical printed circuit board (PCB) substrate, designed specifically for the precise quantification of AMD biomarker: complement component III (C3). The hydrothermally reduced graphene oxide (rGO) was deposited between gold-interdigitated microelectrodes, forming a conductive channel. The fabricated C3 biosensor exhibits a low detection limit of 0.4342 ng/mL and an impressive sensitivity of 9.238 ((ΔR/R)/ng.mL-1)/cm2 with a regression coefficient of 0.9815 calibrated within the clinical C3 range of 10-30 ng/mL. This excellent performance is ascribed to the synergistic effects of 1-pyrenebutanoic acid succinimidyl ester (PBASE) linker and conducting properties of rGO as they generate large active sites for higher anti-C3 antibody immobilization, thereby enhancing sensitivity and specificity. Furthermore, the performance of this proposed C3 sensor chip was validated with enzyme-linked immunosorbent assay (ELISA) using five human tear samples exhibiting an outstanding correlation of a regression value of 0.9774. The unparalleled merits of this newly crafted C3 biosensor transcend those of preceding platforms, boasting superior accuracy and precision in quantifying C3 levels in human tears, accelerated operational speed with results attainable within a mere 15 min, cost-effectiveness, and excellent sensitivity.

Polyaromatic Hydrocarbon-Functionalized 2D MXene-Based 3D Porous Antifouling Nanocomposite with Long Shelf Life for High-Performance Electrochemical Immunosensor Applications

Affinity-based electrochemical (AEC) biosensors have gained more attention in the field of point-of-care management. However, AEC sensing is hampered by biofouling of the electrode surface and degradation of the antifouling material. Therefore, a breakthrough in antifouling nanomaterials is crucial for the fabrication of reliable AEC biosensors. Herein, for the first time, we propose 1-pyrenebutyric acid-functionalized MXene to develop an antifouling nanocomposite to resist biofouling in the immunosensors. The nanocomposite consisted of a 3D porous network of bovine serum albumin cross-linked with glutaraldehyde with functionalized MXene as conductive nanofillers, where the inherited oxidation resistance property of functionalized MXene improved the electrochemical lifetime of the nanocomposite. On the other hand, the size-extruded porous structure of the nanocomposite inhibited the biofouling activity on the electrode surface for up to 90 days in real samples. As a proof of concept, the antifouling nanocomposite was utilized to fabricate a multiplexed immunosensor for the detection of C-reactive protein (CRP) and ferritin biomarkers. The fabricated sensor showed good selectivity over time and an excellent limit of detection for CRP and ferritin of 6.2 and 4.2 pg/mL, respectively. This research successfully demonstrated that functionalized MXene-based antifouling nanocomposites have great potential to develop high-performance and low-cost immunosensors.

Single-Step Functionalization Strategy of Graphene Microtransistor Array with Chemically Modified Aptamers for Biosensing Applications

Graphene solution-gated field-effect transistors (gSGFETs) offer high potential for chemical and biochemical sensing applications. Among the current trends to improve this technology, the functionalization processes are gaining relevance for its crucial impact on biosensing performance. Previous efforts are focused on simplifying the attachment procedure from standard multi-step to single-step strategies, but they still suffer from overreaction, and impurity issues and are limited to a particular ligand. Herein, a novel strategy for single-step immobilization of chemically modified aptamers with fluorenylmethyl and acridine moieties, based on a straightforward synthetic route to overcome the aforementioned limitations is presented. This approach is benchmarked versus a standard multi-step strategy using thrombin as detection model. In order to assess the reliability of the functionalization strategies 48-gSGFETs arrays are employed to acquire large datasets with multiple replicas. Graphene surface characterization demonstrates robust and higher efficiency in the chemical coupling of the aptamers with the single-step strategy, while the electrical response evaluation validates the sensing capability, allowing to implement different alternatives for data analysis and reduce the sensing variability. In this work, a new tool capable of overcome the functionalization challenges of graphene surfaces is provided, paving the way toward the standardization of gSGFETs for biosensing purposes.

Using Machine Learning to Overcome Interfering Oxygen Effects in a Graphene Volatile Organic Compound Sensor

Discriminating between volatile organic compounds (VOCs) for applications including disease diagnosis and environmental monitoring, is often complicated by the presence of interfering compounds such as oxygen. Graphene sensors are effective at detecting VOCs; however, they are also known to be highly sensitive to oxygen. Therefore, the combined effects of each of these gases on graphene sensors must be understood. In this work, we use graphene variable capacitor (varactor) sensors to examine the cross-selectivity of oxygen at 3 concentrations and 3 VOCs (ethanol, methanol, and methyl ethyl ketone) at 5 concentrations each. The sensor responses exhibit distinct shapes dependent on the relative concentrations in mixtures of oxygen and VOCs. Because the entire response shape is therefore informative for distinguishing between each gas mixture, a classification algorithm that utilizes entire sequences of data is needed. Accordingly, a long short-term memory (LSTM) network is used to classify the mixtures and VOC concentrations. The model achieves 100% accurate classification of the VOC type, even in the presence of varying levels of oxygen. When the VOC type and VOC concentration are classified, we show that the sensors can provide VOC concentration resolution within approximately 200 ppm. Throughout this work, we also demonstrate that an effective gas mixture classification can be achieved, even while the sensors exhibit varied drift patterns typical of graphene sensors. This is made possible due to the data analysis and machine learning methods employed.

Toward the Ultimate Limit of Analyte Detection, in Graphene-Based Field-Effect Transistors

The ultimate sensitivity of field-effect-transistor (FET)-based devices for ionic species detection is of great interest, given that such devices are capable of monitoring single-electron-level modulations. It is shown here, from both theoretical and experimental perspectives, that for such ultimate limits to be approached the thermodynamic as well as kinetic characteristics of the (FET surface)-(linker)-(ion-receptor) ensemble must be considered. The sensitivity was probed in terms of optimal packing of the ensemble, through a minimal charge state/capacitance point of view and atomic force microscopy. Through the fine-tuning of the linker and receptor interaction with the sensing surface, a record limit of detection as well as specificity in the femtomolar range, orders of magnitude better than previously obtained and in excellent accord with prediction, was observed.

Redox Cycling Amplified Electrochemical Lateral-Flow Immunoassay: Toward Decentralized Sensitive Insulin Detection

While paper-based lateral-flow immunoassays (LFA) offer considerable promise for centralized diagnostic applications, the analytical capability of conventional LFA remains constrained due to the low sensitivity of its common optical detection strategy. To address these issues, we report a simple electrochemical LFA (eLFA) with nanocatalytic redox cycling for decentralized insulin detection. Simultaneous binding of insulin with detection antibodies and capture antibodies through the capillary flow at the LFA platform and signal amplification through the rapid nanocatalytic reduction of [Fe(CN)6]3- (Fe3+) with Au nanoparticles (AuNP) and ammonia-borane (AB), coupled to electrochemical redox cycling reactions involving Fe3+, AuNP, and AB on the carbon working electrode, offer higher sensitivity than conventional colorimetric LFA and enzymatic redox cycling. The resulting integrated eLFA strip allows the detection of low insulin concentrations (LOD = 12 pM) and offers considerable promise for highly sensitive decentralized assays of different biological fluids (saliva and serum) without additional pretreatment or washing steps.

Sensitive label-free detection of the biomarker phosphorylated tau-217 protein in Alzheimer's disease using a graphene-based solution-gated field effect transistor

Alzheimer's disease (AD) is generally diagnosed using advanced imaging, but recent research suggests early screening using biomarkers in peripheral blood is feasible; among them, plasma tau proteins phosphorylated at threonine 231, threonine 181, and threonine 217 (p-tau217) are potential targets. A recent study indicates that the p-tau217 protein is the most efficacious biomarker. However, a clinical study found a pg/ml threshold for AD screening beyond standard detection methods. A biosensor with high sensitivity and specificity p-tau217 detection has not yet been reported. In this study, we developed a label-free solution-gated field effect transistor (SGFET)-based biosensor featuring a graphene oxide/graphene (GO/G) layered composite. The top layer of bilayer graphene grown using chemical vapor deposition was functionalized with oxidative groups serving as active sites for forming covalent bonds with the biorecognition element (antibodies); the bottom G could act as a transducer to respond to the attachment of the target analytes onto the top GO conjugated with the biorecognition element via π-π interactions between the GO and G layers. With this unique atomically layered G composite, we obtained a good linear electrical response in the Dirac point shift to p-tau217 protein concentrations in the range of 10 fg/ml to 100 pg/ml. The biosensor exhibited a high sensitivity of 18.6 mV/decade with a high linearity of 0.991 in phosphate-buffered saline (PBS); in human serum albumin, it showed approximately 90% of the sensitivity (16.7 mV/decade) in PBS, demonstrating high specificity. High stability of the biosensor was also displayed in this study.

High-intensity vector signals for detecting SARS-CoV-2 RNA using CRISPR/Cas13a couple with stabilized graphene field-effect transistor

False detection of SARS-CoV-2 is detrimental to epidemic prevention and control. The scalar nature of the detected signal and the imperfect target recognition property of developed methods are the root causes of generating false signals. Here, we reported a collaborative system of CRISPR-Cas13a coupling with the stabilized graphene field-effect transistor, providing high-intensity vector signals for detecting SARS-CoV-2. In this collaborative system, SARS-CoV-2 RNA generates a "big subtraction" signal with a right-shifted feature, whereas any untargets cause the left-shifted characteristic signal. Thus, the false detection of SARS-CoV-2 is eliminated. High sensitivity with 0.15 copies/μL was obtained. In addition, the wide concerned instability of the graphene field-effect transistor for biosensing in solution environment was solved by the hydrophobic treatment to its substrate, which should be a milestone in advancing it's engineering application. This collaborative system characterized by the high-intensity vector signal and amazing stability significantly advances the accurate SARS-CoV-2 detection from the aspect of signal nature.

Investigation and comparison of graphene nanoribbon and carbon nanotube based SARS-CoV-2 detection sensors: An ab initio study

The rapid detection of SARS-CoV-2, the pathogen of the Covid-19 pandemic, is obviously of great importance for stopping the spread of the virus by detecting infected individuals. Here, we report the ab initio analysis results of graphene nanoribbon (GNR) and carbon nanotube (CNT) based SARS-CoV-2 detection sensors which are experimentally demonstrated in the literature. The investigated structures are the realistic molecular models of the sensors that are employing 1-pyrenebutyric acid N-hydroxysuccinimide ester as the antibody linker. Density functional theory in conjunction with non-equilibrium Green's function formalism (DFT-NEGF) is used to obtain the transmission spectra, current-voltage and resistance-voltage characteristics of the sensors before and after the attachment of the SARS-CoV-2 spike protein. The operation mechanism of the GNR and CNT based SARS-CoV-2 sensors are exposed using the transmission spectrum analysis. Moreover, it is observed that GNR based sensor has more definitive detection characteristics compared to its CNT based counterpart.

Machine Learning-Based Rapid Detection of Volatile Organic Compounds in a Graphene Electronic Nose

Rapid detection of volatile organic compounds (VOCs) is growing in importance in many sectors. Noninvasive medical diagnoses may be based upon particular combinations of VOCs in human breath; detecting VOCs emitted from environmental hazards such as fungal growth could prevent illness; and waste could be reduced through monitoring of gases produced during food storage. Electronic noses have been applied to such problems, however, a common limitation is in improving selectivity. Graphene is an adaptable material that can be functionalized with many chemical receptors. Here, we use this versatility to demonstrate selective and rapid detection of multiple VOCs at varying concentrations with graphene-based variable capacitor (varactor) arrays. Each array contains 108 sensors functionalized with 36 chemical receptors for cross-selectivity. Multiplexer data acquisition from 108 sensors is accomplished in tens of seconds. While this rapid measurement reduces the signal magnitude, classification using supervised machine learning (Bootstrap Aggregated Random Forest) shows excellent results of 98% accuracy between 5 analytes (ethanol, hexanal, methyl ethyl ketone, toluene, and octane) at 4 concentrations each. With the addition of 1-octene, an analyte highly similar in structure to octane, an accuracy of 89% is achieved. These results demonstrate the important role of the choice of analysis method, particularly in the presence of noisy data. This is an important step toward fully utilizing graphene-based sensor arrays for rapid gas sensing applications from environmental monitoring to disease detection in human breath.

The critical experimental aspects for developing pathogen electrochemical biosensors: A lesson during the COVID-19 pandemic

Though the bitter global pandemic posed a severe public health threat, it set an unprecedented stage for different research teams to present various technologies for detecting SARS-CoV-2, providing a rare and hard-won lesson for one to comprehensively survey the core experimental aspects in developing pathogens electrochemical biosensors. Apart from collecting all the published biosensor studies, we focused on the effects and consequences of using different receptors, such as antibodies, aptamers, ACE 2, and MIPs, which are one of the core topics of developing a pathogen biosensor. In addition, we tried to find an appropriate and distinctive application scenario (e.g., wastewater-based epidemiology) to maximize the advantages of using electrochemical biosensors to detect pathogens. Based on the enormous amount of information from those published studies, features that fit and favor wastewater pathogen detection can be picked up and integrated into a specific strategy to perform quantitative measurements in wastewater samples.

Chondro-Inductive b-TPUe-Based Functionalized Scaffolds for Application in Cartilage Tissue Engineering

Osteoarthritis is a disease with a great socioeconomic impact and mainly affects articular cartilage, a tissue with reduced self-healing capacity. In this work, 3D printed 1,4 butanediol thermoplastic polyurethane (b-TPUe) scaffolds are functionalized and infrapatellar mesenchymal stem cells are used as the cellular source. Since b-TPUe is a biomaterial with mechanical properties similar to cartilage, but it does not provide the desired environment for cell adhesion, scaffolds are functionalized with two methods, one based on collagen type I and the other in 1-pyrenebutiric acid (PBA) as principal components. Alamar Blue and confocal assays display that PBA functionalized scaffolds support higher cell adhesion and proliferation for the first 21 days. However, collagen type I functionalization induces higher proliferation rates and similar cell viability than the PBA method. Further, both functionalization methods induce extracellular matrix synthesis, and the presence of chondrogenic markers (Sox9, Col2a, and Acan). Finally, SEM images probe that functionalized 3D printed scaffolds present much better cell/biomaterial interactions than controls and confirm early chondrogenesis. These results indicate that the two methods of functionalization in the highly hydrophobic b-TPUe enhance the cell-biomaterial interactions and the improvement in the chondro-inductive properties, which have great potential for application in cartilage tissue engineering.

Theoretical Analysis on the Stability of 1-Pyrenebutanoic Acid Succinimidyl Ester Adsorbed on Graphene

The adsorbed structure of 1-pyrenebutanoic acid succinimidyl ester (PASE) on graphene was investigated based on density functional theory. We found two locally stable structures: a straight structure with the chainlike part of butanoic acid succinimidyl ester (BSE) lying down and a bent structure with the BSE part directed away from graphene, keeping the pyrene (Py) part adsorbed on graphene. Then, to elucidate the adsorption mechanism, we separately estimated the contributions of the Py and BSE parts to the entire PASE adsorption, and the adsorption effect of the BSE part was found to be secondary in comparison to the contribution of the Py. Next, the mobility of the BSE part at room temperature was confirmed by the activation energy barrier between straight and bent structures. To take account of the external environment, we considered the presence of amino acids and the hydration effect by a three-dimensional reference interaction site model. The contributions of glycine molecules and the solvent environment to stabilizing the bent PASE structure relative to the straight PASE structure were found. Therefore, the effect of the external environment around PASE is of importance when the standing-up process of the BSE part from graphene is considered.

Light-Powered Self-Sustained Oscillators of Graphene Oxide/Liquid Crystalline Network Composites Showing Amplitude and Frequency Superposition

Light-activated self-oscillators have drawn enormous attention for their potential applications in mobile machines, energy harvesting, signal modulation, etc. Herein, we report one graphene oxide (GO)/liquid crystalline network (LCN) actuator that presents a unique light-activated oscillation with amplitude and frequency superposition. The GO/LCN composite film is prepared by the one-step polymerization of LC monomers, which favors a splay orientation in LC cells made by gluing together two glass sheets, one coated with photothermal agent GO and the other coated with a rubbed polyimide alignment layer. Owing to the asymmetric contraction/expansion, changing the cutting direction gives rise to notably different actuation behaviors for GO/LCN composite films. Moreover, it twists a little during the deflection process as a result of experimental error during the cutting process, which may cause the strip to be cut inaccurately. When the composite film is embedded in a self-shadowing system, it produces an unconventional hybrid oscillation mode upon near-infrared light irradiation, i.e., bending and twisting oscillation coupled. Furthermore, when the aspect ratio of the film decreases, the twisting mode is suppressed and the actuator changes from a coupled mode to a single bending mode. The proposed strategy may extend the application of GO/LCN composite materials and enrich light-activated self-oscillating behaviors.

The Interplay of Conjugation and Metal Coordination in Tuning the Electron Transfer Abilities of NTA-Graphene Based Interfaces

An artificial leaf is a concept that not only replicates the processes taking place during natural photosynthesis but also provides a source of clean, renewable energy. One important part of such a device are molecules that stabilize the connection between the bioactive side and the electrode, as well as tune the electron transfer between them. In particular, nitrilotriacetic acid (NTA) derivatives used to form a self-assembly monolayer chemisorbed on a graphene monolayer can be seen as a prototypical interface that can be tuned to optimize the electron transfer. In the following work, interfaces with modifications of the metal nature, backbone saturation, and surface coverage density are presented by means of theoretical calculations. Effects of the type of the metal and the surface coverage density on the electronic properties are found to be key to tuning the electron transfer, while only a minor influence of backbone saturation is present. For all of the studied interfaces, the charge transfer flow goes from graphene to the SAM. We suggest that, in light of the strength of electron transfer, Co2+ should be considered as the preferred metal center for efficient charge transfer.

Real-time label-free detection of DNA hybridization using a functionalized graphene field effect transistor: a theoretical study

Detection of DNA hybridization with high sensitivity and accuracy plays a major role in clinical diagnosis and treatment. Despite intense experimental studies of graphene field effect transistor as DNA hybridization detector, the mechanism of detection and changes in the electrical properties of the device is not investigated in detail. To this end, we have investigated an armchair graphene nanoribbon (AGNR) interconnected between gold electrodes as a detector of DNA hybridization. Using non-equilibrium Green's function method and density functional theory, the effect of 1-pyrenebutanoic acid succinimidyl ester (PBASE) linker, probe, and target DNA on the electrical properties of the device has been investigated at zero bias voltage. The results show that, after functionalization of AGNR with PBASE, the conductance of the device increases while functionalization with probe and target DNA leads to a decrease in conductance. The changes in the projected density of states on the AGNR and transmission around Fermi energy are the reason for the change in conductance of the system. In all cases, both charge transfer and electrostatic gating are responsible for the change in the electrical properties of the system. The results show that our device detects DNA hybridization with a sensitivity of 10% at zero bias voltage, and by applying a suitable gate voltage, it can show higher sensitivity.

Development of an aptamer-based SPR-biosensor for the determination of kanamycin residues in foods

A biosensor in which an affinity reaction occurs in the sensitive microzone through the use of specific aptamers to determine kanamycin residues in agri-food samples has been developed. It is an irreversible and continuous flow aptameric biosensor (aptasensor) in which the signal variations are monitored by surface plasmon resonance (SPR) measurements based on the specific interaction of the aptamer with the antibiotic. The signal variation is proportional to the analyte concentration. Graphene is known for efficient binding of molecules with its π-electron system, so a monolayer of graphene prepared from chemical vapor deposition (CVD) has been compared to a multilayer of graphene made from reduced graphene oxide (rGO) for immobilization of the aptamer on the gold surface of the physicochemical transducer. The best results have been obtained with CVD graphene. The dynamic range was between 1 and 100 μmol L^-1 of kanamycin concentration (r² = 0.9981, n = 7, r = 4), with a limit of detection of 285 nmol L^-1 and a sampling frequency of 6 h^-1. The precision, expressed as relative standard deviation (RSD%), was established in the range of 1.49 and 3.89%, calculated for 1, 10, and 50 μmol L^-1. The selectivity was studied applying the described method to determine other antibiotics, obtaining no significant difference in the analytical signal. The method was applied to determine kanamycin residues in milk samples with recovery values ranging between 90 and 96%.

SARS-CoV-2 RapidPlex: A Graphene-Based Multiplexed Telemedicine Platform for Rapid and Low-Cost COVID-19 Diagnosis and Monitoring

The COVID-19 pandemic is an ongoing global challenge for public health systems. Ultrasensitive and early identification of infection is critical in preventing widespread COVID-19 infection by presymptomatic and asymptomatic individuals, especially in the community and in-home settings. We demonstrate a multiplexed, portable, wireless electrochemical platform for ultra-rapid detection of COVID-19: the SARS-CoV-2 RapidPlex. It detects viral antigen nucleocapsid protein, IgM and IgG antibodies, as well as the inflammatory biomarker C-reactive protein, based on our mass-producible laser-engraved graphene electrodes. We demonstrate ultrasensitive, highly selective, and rapid electrochemical detection in the physiologically relevant ranges. We successfully evaluated the applicability of our SARS-CoV-2 RapidPlex platform with COVID-19-positive and COVID-19-negative blood and saliva samples. Based on this pilot study, our multiplexed immunosensor platform may allow for high-frequency at-home testing for COVID-19 telemedicine diagnosis and monitoring.

Concentration-Dominated Orientation of Phenyl Groups at the Polystyrene/Graphene Interface

The interfacial orientation of aromatic groups plays a crucial role in determining the properties of graphene-based aromatic polymer nanocomposites. Here, the interfacial orientation of the polystyrene (PS) phenyl groups in contact with graphene is revealed by sum frequency generation (SFG) vibrational spectroscopy. The SFG spectra showed that the orientation of the phenyl groups is closely related to the interfacial concentration as the chains reach the quasi-equilibrium state. The phenyl groups remain in a relatively unrestricted state at a low concentration of the PS phenyl groups, and they prefer to recline to more favorably interact with graphene via a face-to-face configuration. Densely stacked phenyl groups are too crowded to form multilayer face-to-face interactions with graphene, and they prefer to remain upright, while π-π interactions are formed among the phenyl groups themselves in addition to the edge-to-face interactions to maximize the bonding energy of the π-π interactions. This is enthalpically favorable and driven mainly by the π-π interactions. This work provides important knowledge for the design and optimization of functional graphene-based aromatic polymer nanocomposites.

Layered material platform for surface plasmon resonance biosensing

Plasmonic biosensing has emerged as the most sensitive label-free technique to detect various molecular species in solutions and has already proved crucial in drug discovery, food safety and studies of bio-reactions. This technique relies on surface plasmon resonances in ~50 nm metallic films and the possibility to functionalize the surface of the metal in order to achieve selectivity. At the same time, most metals corrode in bio-solutions, which reduces the quality factor and darkness of plasmonic resonances and thus the sensitivity. Furthermore, functionalization itself might have a detrimental effect on the quality of the surface, also reducing sensitivity. Here we demonstrate that the use of graphene and other layered materials for passivation and functionalization broadens the range of metals which can be used for plasmonic biosensing and increases the sensitivity by 3-4 orders of magnitude, as it guarantees stability of a metal in liquid and preserves the plasmonic resonances under biofunctionalization. We use this approach to detect low molecular weight HT-2 toxins (crucial for food safety), achieving phase sensitivity~0.5 fg/mL, three orders of magnitude higher than previously reported. This proves that layered materials provide a new platform for surface plasmon resonance biosensing, paving the way for compact biosensors for point of care testing.

Aggregation Enhanced Excimer Emission Supported, Monomeric Fluorescence Quenching of Dendritic Hyperbranched Polyglycerol Coupled 1-Pyrene Butyric Acid Lumophore as a Sensing Probe for Fe2O3 Nanoparticles

Pyrene butyric acid (PBA) is a well studied lumophore for its exciting fluorescent properties. The current study focussed on a dendritic modification of PBA with hyperbranched polyglycerols (HPG) by Steglich esterification and further doping with iron oxide nanoparticles (IONP) of α-Fe₂O₃ phase. The covalent coupling between HPG and PBA was confirmed by FTIR and ¹H-NMR spectra. The main objective of the study was to monitor the fluorescent properties of the modified and doped products. Steady state PL emission studies showed a considerable decrease in fluorescence intensity on HPG modification which almost completely disappeared on doping with IONP. This suggests that this fluorosensing property can be explored in identification and estimation of iron oxide nanoparticles which has a great significance in biomedical field both in diagnostics and therapeutics. Lifetime measurements with TCSPC suggested an aggregation enhanced quenching of HPG-PBA conjugates and mixed static and dynamic mechanisms in IONP doped HPG-PBA conjugates. Graphical Abstract ᅟ.

Initial Studies Directed toward the Rational Design of Aqueous Graphene Dispersants

This study presents preliminary experimental data suggesting that sodium 4-(pyrene-1-yl)butane-1-sulfonate (PBSA), 5, an analogue of sodium pyrene-1-sulfonate (PSA), 1, enhances the stability of aqueous reduced graphene oxide (RGO) graphene dispersions. We find that RGO and exfoliated graphene dispersions prepared in the presence of 5 are approximately double the concentration of those made with commercially available PSA, 1. Quantum mechanical and molecular dynamics simulations provide key insights into the behavior of these molecules on the graphene surface. The seemingly obvious introduction of a polar sulfonate head group linked via an appropriate alkyl spacer to the aromatic core results in both more efficient binding of 5 to the graphene surface and more efficient solvation of the polar head group by bulk solvent (water). Overall, this improves the stabilization of the graphene flakes by disfavoring dissociation of the stabilizer from the graphene surface and inhibiting reaggregation by electrostatic and steric repulsion. These insights are currently the subject of further investigations in an attempt to develop a rational approach to the design of more effective dispersing agents for rGO and graphene in aqueous solution.

Electrochemically stimulated molecule release associated with interfacial pH changes

Molecular release was activated with an electrochemical signal, resulting in the hydrolysis of a linker.

Graphene and Graphene-Based Nanomaterials for DNA Detection: A Review

DNA detection with high sensitivity and specificity has tremendous potential as molecular diagnostic agents. Graphene and graphene-based nanomaterials, such as graphene nanopore, graphene nanoribbon, graphene oxide, and reduced graphene oxide, graphene-nanoparticle composites, were demonstrated to have unique properties, which have attracted increasing interest towards the application of DNA detection with improved performance. This article comprehensively reviews the most recent trends in DNA detection based on graphene and graphene-related nanomaterials. Based on the current understanding, this review attempts to identify the future directions in which the field is likely to thrive, and stimulate more significant research in this subject.