Nanotube Sensors Research Articles

Platinum-supported NiO nanotubes enabled by self-sacrificial templating with enhanced electrochemical determination of glucose

NiO/Pt nanotubes were obtained by firstly preparing the NiO nanotube with self-sacrificial templating methods and subsequently loading Pt nanoparticles with microwave assistant procedures. The as-prepared NiO/Pt nanotubes sensors displayed better electrocatalytic activities for glucose oxidation. The detection limit and sensitivity for glucose detection are 0.3 [Formula: see text]M and 418.28 [Formula: see text]A⋅ mM[Formula: see text]⋅cm[Formula: see text] in the range of 1 [Formula: see text]M-4000 [Formula: see text]M. In addition, the practicality of NiO/Pt nanotubes was also confirmed by determining the glucose in serum specimen.

Intrinsically conducting polymer nanocomposite as the vigorous material for the health monitoring

Individual poly(methyl methacrylate)/MWCNT doped with sulfuric acid were polymerized in situ to yield individual nanotubes with increased electrical conductivity. In the presence of aliphatic alcohol vapors of various diameters, the Nanocomposites were measured as a function of time. These sensor responses are particularly rapid due to the huge surface to volume ratio, consistent diameter, and limited amount of active material employed in the design. Individual nanotube sensors demonstrate actual saturation when exposed to and removed from the detecting gas. In addition, a chemical sensing system was created employing a nanocomposite film in both air and vapor alcohol gas. When exposed to alcohol, the surface reaction was immediate, with virtually total current recovery after pumping out the alcohol, making it a reusable sensor with rectifying behaviour.

A wavelength-induced frequency filtering method for fluorescent nanosensors in vivo

Fluorescent nanosensors hold the potential to revolutionize life sciences and medicine. However, their adaptation and translation into the in vivo environment is fundamentally hampered by unfavourable tissue scattering and intrinsic autofluorescence. Here we develop wavelength-induced frequency filtering (WIFF) whereby the fluorescence excitation wavelength is modulated across the absorption peak of a nanosensor, allowing the emission signal to be separated from the autofluorescence background, increasing the desired signal relative to noise, and internally referencing it to protect against artefacts. Using highly scattering phantom tissues, an SKH1-E mouse model and other complex tissue types, we show that WIFF improves the nanosensor signal-to-noise ratio across the visible and near-infrared spectra up to 52-fold. This improvement enables the ability to track fluorescent carbon nanotube sensor responses to riboflavin, ascorbic acid, hydrogen peroxide and a chemotherapeutic drug metabolite for depths up to 5.5 ± 0.1 cm when excited at 730 nm and emitting between 1,100 and 1,300 nm, even allowing the monitoring of riboflavin diffusion in thick tissue. As an application, nanosensors aided by WIFF detect the chemotherapeutic activity of temozolomide transcranially at 2.4 ± 0.1 cm through the porcine brain without the use of fibre optic or cranial window insertion. The ability of nanosensors to monitor previously inaccessible in vivo environments will be important for life-sciences research, therapeutics and medical diagnostics.

Water Quality Carbon Nanotube-Based Sensors Technological Barriers and Late Research Trends: A Bibliometric Analysis

Water is the key element that defines and individualizes our planet. Relative to body weight, water represents 70% or more for the majority of all species on Earth. Taking care of water as a whole is equivalent with taking care of the entire biodiversity or the whole of humanity itself. Water quality is becoming an increasingly important component of terrestrial life, hence intensive work is being conducted to develop sensors for detecting contaminants and assessing water quality and characteristics. Our bibliometric analysis is focused on water quality sensors based on carbon nanotubes and highlights the most important objectives and achievements of researchers in recent years. Due to important measurement characteristics such as sensitivity and selectivity, or low detection limit and linearity, up to the ability to measure water properties, including detection of heavy metal content or the presence of persistent organic compounds, carbon nanotube (CNT) sensors, taking advantage of available nanotechnologies, are becoming increasingly attractive. The conducted bibliometric analysis creates a visual, more efficient keystones mapping. CNT sensors can be integrated into an inexpensive real-time monitoring data acquisition system as an alternative for classical expensive and time-consuming offline water quality monitoring. The conducted bibliometric analysis reveals all connections and maps all the results in this water quality CNT sensors research field and gives a perspective on the approached methods on this specific type of sensor. Finally, challenges related to integration of other trends that have been used and proven to be valuable in the field of other sensor types and capable to contribute to the development (and outlook) for future new configurations that will undoubtedly emerge are presented.

Analysis of Staphylococcus aureus Molecules in Non-Treated Blood Using Mercury Immobilized Carbon Nanotube Sensor.

Staphylococcus aureus bacteria is a ubiquitous Gram-positive microorganism that causes infections related to the sudden infant death syndrome. Recently, basic detection methods depend on complicated PCR amplification, electric separation, spectric adsorption and other detection systems. However, in this study, simplified sensitive voltammetric skills are developed. To identify an effective diagnostic method for Staphylococcus aureus (SA), a voltammetric sensing probe was sought using mercury immobilized on a carbon nanotube sensor (MCN). The voltammetric MCN conditions were optimized through stripping and cyclic voltammetry. Diagnostic electrolyte was used on non-treated blood sera as an electrolyte solution. The optimum cyclic and stripping analytical working range was 0.5–4.0 mL (3 × 102~5 × 102 CFU/0.5 mL) SA. The statistic relative standard deviation of 0.1 mL SA was observed to be 0.0078 (n = 5). Using the optimum parameters, a diagnostic test was performed by the direct assay of SA in non-treated human blood and patient sera. Here, the developed results can be used for the direct assay of non-treated blood sera, organ monitoring, in-vivo diagnosis, and other assays requiring SA detection.

Detection of ovarian cancer via the spectral fingerprinting of quantum-defect-modified carbon nanotubes in serum by machine learning.

Serum biomarkers are often insufficiently sensitive or specific to facilitate cancer screening or diagnostic testing. In ovarian cancer, the few established serum biomarkers are highly specific, yet insufficiently sensitive to detect early-stage disease and to impact the mortality rates of patients with this cancer. Here we show that a 'disease fingerprint' acquired via machine learning from the spectra of near-infrared fluorescence emissions of an array of carbon nanotubes functionalized with quantum defects detects high-grade serous ovarian carcinoma in serum samples from symptomatic individuals with 87% sensitivity at 98% specificity (compared with 84% sensitivity at 98% specificity for the current best clinical screening test, which uses measurements of cancer antigen 125 and transvaginal ultrasonography). We used 269 serum samples to train and validate several machine-learning classifiers for the discrimination of patients with ovarian cancer from those with other diseases and from healthy individuals. The predictive values of the best classifier could not be attained via known protein biomarkers, suggesting that the array of nanotube sensors responds to unidentified serum biomarkers.

A Carbon Nanotube Sensor Array for the Label-Free Discrimination of Live and Dead Cells with Machine Learning

Developing robust cell recognition strategies is important in biochemical research, but the lack of well-defined target molecules creates a bottleneck in some applications. In this paper, a carbon nanotube sensor array was constructed for the label-free discrimination of live and dead mammalian cells. Three types of carbon nanotube field-effect transistors were fabricated, and different features were extracted from the transfer characteristic curves for model training with linear discriminant analysis (LDA) and support-vector machines (SVM). Live and dead cells were accurately classified in more than 90% of samples in each sensor group using LDA as the algorithm. The recursive feature elimination with cross-validation (RFECV) method was applied to handle the overfitting and optimize the model, and cells could be successfully classified with as few as four features and a higher validation accuracy (up to 97.9%) after model optimization. The RFECV method also revealed the crucial features in the classification, indicating the participation of different sensing mechanisms in the classification. Finally, the optimized LDA model was applied for the prediction of unknown samples with an accuracy of 87.5-93.8%, indicating that live and dead cell samples could be well-recognized with the constructed model.

An electronic nose based on carbon nanotube -titanium dioxide hybrid nanostructures for detection and discrimination of volatile organic compounds

Detection and classification of Volatile Organic Compounds (VOCs) that pose risks to human health even at very low concentrations, is a common requirement in the industry. Herein, we apply a modification to the aligned Carbon Nanotubes (CNTs) grown at low temperature (250 °C) using Plasma Enhanced Chemical Vapor Deposition (PECVD). CNTs are used to identify VOCs in an improved sensitivity condition to gas at room temperature. We improve the sensitivity and stability of carbon nanotube sensors via growing Titanium Dioxide Nanowires (TiO2-NW) on the surface of CNTs through the hydrothermal method. A threefold increase in sensitivity and a 30-second decrease in response time were observed as a result of the CNT-TiO2 sensor compared to the pristine CNT sensor. In order to obtain new data, we deposit four different electrodes on the TiO2 surface as virtual arrays of Electronic nose (E-nose). Temperature modulation and Discrete Wavelet Transform (DWT) of virtual arrays, extract new features of the E-nose data. We select 14 different features from E-nose data and apply Principle Component Analysis (PCA) method for data reduction. We categorize the extracted features by using Support Vector Machine (SVM) algorithms and data covariance properties. This paper achieves 97.5% accuracy in classifying four different VOC gases.

Wearable E-Textile and CNT Sensor Wireless Measurement System for Real-Time Penile Erection Monitoring

Erection measurements are the most important indicator of male urological disease diagnosis, treatment, and results. Rigiscan has been used widely in studies and diagnoses for nocturnal penile tumescence for evaluating erectile dysfunction by measuring the number and timing of erectile dysfunctions during sleep. However, this device has limitations such as the weight and bulk of the device and has been questioned for its role as a standard for ED Erectile Dysfunction (ED) diagnosis. In this study, we propose a real-time wearable monitoring system that can quantitatively measure the length and circumference of the penis using electronic textiles (E-textile) and carbon nanotube (CNT) sensors. The E-textile sensor is used to measure the length, circumference, and gradient with portability, convenience, and comfort. Sensors were created by coating CNTs on latex for flexibility. The CNT-based latex condom-type sensor in our proposed system shows the length, circumference, and curvature measurements with changes in resistance, and the E-textile performance shows a 1.44% error rate and a cavity radius of 110 to 300. The results of this conceptual study are for supplementary sensor development with a combination of new technologies with alternatives or existing methods for measuring erection function.

Discovery of DNA-Carbon Nanotube Sensors for Serotonin with Machine Learning and Near-infrared Fluorescence Spectroscopy.

DNA-wrapped single walled carbon nanotube (SWNT) conjugates have distinct optical properties leading to their use in biosensing and imaging applications. A critical limitation in the development of DNA-SWNT sensors is the current inability to predict unique DNA sequences that confer a strong analyte-specific optical response to these sensors. Here, near-infrared (nIR) fluorescence response data sets for ∼100 DNA-SWNT conjugates, narrowed down by a selective evolution protocol starting from a pool of ∼1010 unique DNA-SWNT candidates, are used to train machine learning (ML) models to predict DNA sequences with strong optical response to neurotransmitter serotonin. First, classifier models based on convolutional neural networks (CNN) are trained on sequence features to classify DNA ligands as either high response or low response to serotonin. Second, support vector machine (SVM) regression models are trained to predict relative optical response values for DNA sequences. Finally, we demonstrate with validation experiments that integrating the predictions of ensembles of the highest quality neural network classifiers (convolutional or artificial) and SVM regression models leads to the best predictions of both high and low response sequences. With our ML approaches, we discovered five DNA-SWNT sensors with higher fluorescence intensity response to serotonin than obtained previously. Overall, the explored ML approaches, shown to predict useful DNA sequences, can be used for discovery of DNA-based sensors and nanobiotechnologies.

Protrusion Microstructure-Induced Sensitivity Enhancement for Zinc Oxide–Carbon Nanotube Flexible Pressure Sensors

Carbon nanotubes (CNTs) have broad application prospects in flexible pressure sensors because of their superior mechanical and electrical performance. However, the pressure sensitivity of a pure CNT sensor needs to be enhanced. Herein, a zinc oxide–carbon nanotube (ZnO–CNT) sensor with a protrusion microstructure was prepared to improve the pressure sensitivity of a pure CNT sensor. The results show that the ZnO–CNT sensor achieves a higher pressure sensitivity (8.79 times) than that of the pure CNT sensor. In addition, the ZnO–CNT sensor achieves fast response (125.28 ms), good durability (over 6000 cycles), and a high upper detection limit (up to 422.22 kPa). The enhancement in sensitivity of the ZnO–CNT sensor is explained by the finite element simulation. Benefiting from these characteristics, the ZnO–CNT sensor is expected to be applied in human physiological signs and motion monitoring.

Single-walled Carbon Nanotube Chemiresistive Sensors for the Identification and Quantification of Disinfectants

Disinfectants are essential to keep water safe as they kill pathogens by oxidizing the cell membrane. Free chlorine, potassium permanganate, monochloramine, hydrogen peroxide, chlorine dioxide, ozone, and hypobromous acid are the most commonly used disinfectants for the disinfection of water.1 Monitoring the concentration of the disinfectant is crucial as the effectiveness mainly depends on the amount of disinfectants present in water.2 Insufficient levels of disinfectant in drinking water could impose health risks as pathogens could regrow in the distribution system. Standard methods for measuring the disinfectant levels are colorimetric and titrimetric.3 For free chlorine, DPD colorimetric method is well established.1 , 4 For potassium permanganate (KMnO4), colorimetric methods (persulfate and periodate) and spectroscopic methods are available.1 , 5 Currently, the monitoring of disinfectants is done on samples collected at the treatment plant and in different locations throughout the distribution system. This reagent-based measurement of discrete samples requires reagents and spectroscopic readout devices and can suffer from interference. Therefore, these methods are not suitable for the continuous monitoring of the disinfectant.6 Furthermore, there is no known method that can differentiate between multiple disinfectants in real samples without any previous knowledge.Two of the most important water quality parameters are pH and oxidation-reduction potential (ORP). Disinfectants undergo different reactions at different pH, resulting in different active species for different pH. ORP measurement can be used to monitor whether the disinfection was successful as oxidants’ reactivity in water depends on redox conditions.7 ORP of a solution is associated with the pH and the concentration of the disinfectant. At a fixed pH, the ORP of a disinfectant will depend on the concentration. Therefore, just by knowing the ORP, we cannot distinguish disinfectant unless the pH or concentration of the oxidant is known.8 , 9 To sort out these parameters, we propose to introduce a chemiresistive sensing array capable of distinguishing and quantifying disinfectants. Due to simpler fabrication techniques, lower cost and the ability to sense various analytes through appropriate ligand, chemiresistors have great promise in water quality sensing.6 , 10 Previously reported chemiresistive sensor for continuous measurement of free chlorine used carbon nanotube (CNT) substrate functionalized with a redox-active aniline oligomer named phenyl capped aniline tetramer (PCAT).11 Oxidation of PCAT attached to the surface of CNT by free chlorine leads to a change in the oxidation state of the oligoaniline; this change in oxidation state in the molecule changes the doping characteristics of CNT leading to a change in resistance of the CNT film. This resistance change was used to quantify the concentration of free chlorine.11 In this work, we have constructed an array of single-walled carbon nanotubes (SWCNT) sensors functionalized with five redox-active molecules. Structurally different from each other, these molecules will create different active sites. Upon interaction with analytes, each molecule will give different magnitudes of responses. Sensor responses are collected for free chlorine and KMnO4 over a range of concentrations for pH 6.5 and 7.5. In general, sensors give increasing responses to the increasing concentration and decreasing pH of the solution. Though the responses from the sensors have a similar trend to the change of the parameters their varied magnitudes make them suitable for an array. Sensor responses are then analyzed with principal component analysis (PCA). PCA analysis shows clear separation between the analytes and as well as to different pH and concentrations of the solutions (figure). We have therefore demonstrated an array of chemiresistive sensors that can distinguish and quantify disinfectants.

Facile Fabrication of Hybrid Carbon Nanotube Sensors by Laser Direct Transfer.

Ammonia is one of the most frequently produced chemicals in the world, and thus, reliable measurements of different NH3 concentrations are critical for a variety of industries, among which are the agricultural and healthcare sectors. The currently available technologies for the detection of NH3 provide accurate identification; however, they are limited by size, portability, and fabrication cost. Therefore, in this work, we report the laser-induced forward transfer (LIFT) of single-walled carbon nanotubes (SWCNTs) decorated with tin oxide nanoparticles (SnO2 NPs), which act as sensitive materials in chemiresistive NH3 sensors. We demonstrate that the LIFT-fabricated sensors can detect NH3 at room temperature and have a response time of 13 s (for 25 ppm NH3). In addition, the laser-fabricated sensors are fully reversible when exposed to multiple cycles of NH3 and have an excellent theoretical limit of detection of 24 ppt.

CuO-decorated ZnO nanotube-based sensor for detecting CO gas: a first-principles study.

Understanding the effect of copper oxide (CuO)-decorated zinc oxide nanotube on carbon monoxide (CO) adsorption is crucial for designing a high-performance CO gas sensor. In this work, CO sensing properties of copper oxide-decorated zinc oxide (CuO-ZnO) nanotube are studied theoretically by employing first-principles density functional theory for the first time. The stability, adsorption mechanism, density of states, and change in electrical conductivity are studied. The results of calculating the adsorption energy show strong chemical adsorption of CO on CuO-ZnO nanotubes. The adsorption energy of CO on CuO-ZnO nanotube is calculated as 7.5 times higher than that on ZnO nanotube. The results of the Mulliken charge analysis reveal that electron transfer occurs from CO molecules to CuO-ZnO nanotubes. Additionally, the electrical conductivity of CuO-ZnO nanotubes significantly changes after adsorption of CO at room temperature. According to these studies, CuO-ZnO nanotube sensors can be used for the detection of CO gas. The results are in excellent agreement with the reported experimental results.

Carbon Nanotube Wearable Sensors for Health Diagnostics.

This perspective article highlights a recent surge of interest in the application of textiles containing carbon nanotube (CNT) sensors for human health monitoring. Modern life puts more and more pressure on humans, which translates into an increased number of various health disorders. Unfortunately, this effect either decreases the quality of life or shortens it prematurely. A possible solution to this problem is to employ sensors to monitor various body functions and indicate an upcoming disease likelihood at its early stage. A broad spectrum of materials is currently under investigation for this purpose, some of which already entered the market. One of the most promising materials in this field are CNTs. They are flexible and of high electrical conductivity, which can be modulated upon several forms of stimulation. The article begins with an illustration of techniques for how wearable sensors can be built from them. Then, their application potential for tracking various health parameters is presented. Finally, the article ends with a summary of this field’s progress and a vision of the key directions to domesticate this concept.

PEI-Functionalized Carbon Nanotube Thin Film Sensor for CO2 Gas Detection at Room Temperature.

In this study, a polyethyleneimine (PEI)-functionalized carbon nanotube (CNT) sensor was fabricated for carbon dioxide detection at room temperature. Uniform CNT thin films prepared using a filtration method were used as resistive networks. PEI, which contains amino groups, can effectively react with CO2 gas by forming carbamates at room temperatures. The morphology of the sensor was observed, and the properties were analyzed by scanning electron microscope (SEM), Raman spectroscopy, and fourier transform infrared (FT-IR) spectroscopy. When exposed to CO2 gas, the fabricated sensor exhibited better sensitivity than the pristine CNT sensor at room temperature. Both the repeatability and selectivity of the sensor were studied.

Simple and sensitive electrochemical analysis of riboflavin at functionalized carbon nanofiber modified carbon nanotube sensor

Simple and sensitive electrochemical analysis of riboflavin at functionalized carbon nanofiber modified carbon nanotube sensor

Mo-doped SnO2 nanotubes sensor with abundant oxygen vacancies for ethanol detection

This work describes a synthesizing method for Mo-doped SnO2 nanotubes (NTs) with uniform morphology by combining electrostatic spinning and air sintering. The method uses Mo ions to do substitutional doping of Sn ions in SnO2 to construct new lattice defects (such as oxygen vacancies), which provides more active sites for gas adsorption. Ethanol was taken as an example to study gas sensitivity characteristics of synthesized products. The analysis showed that 5 mol% of Mo-doped SnO2 nanotubes sensor exhibited the highest response (46.8) to 100 ppm ethanol at a lower optimum temperature (220 °C) and reduced the response/recovery time to 7/103 s. Also, it manifested excellent selectivity and long-term stability. The functionalized nanotubes structure and optimized parameters (oxygen vacancies concentration, metal vacancies defects, carrier concentration, catalytic sites, and base resistance increased) are the reasons for enhancing gas-sensing performance. This work provides direction that the optimal doping concentration of transition metal elements for metal-oxide NTs gas sensors can achieve the best sensing response.

Investigation of Photo-induced enhancement of sensitivity and electrochemical surface phenomenon of multileg TiO2 nanotubes sensor device towards H2O2

• Photoelectrochemical bio-sensor for the sensing of H 2 O 2 is developed based on electrochemically anodised TiO 2 multi-leg nanotubes, which offers both light activity as well as higher specific surface area. • TiO 2 multileg nanotubes in Ti/ML-TNT/HRP/Nafion© photo-electrode configuration, shows enhanced sensitivity, wide range of detection, low detection limit and better selectivity towards H 2 O 2 at lower concentrations. • Upto 10 µM of the analyte, the diffusion resistance and the charge transfer resistance are low, after which, both increase due to the bubble crowding at the surface. • The effect of bubble crowding at the electrode surface of the device is studied using electrochemical impedance spectroscopy, which provide an excellent insight into this behaviour. Ti/ML-TNT/HRP/Nafion© sensor device is fabricated using TiO 2 multileg nanotubes (ML-TNT). This device is used for photoelectrochemical enzymatic detection of hydrogen peroxide for different concentrations and the electrochemical surface phenomenon was studied using electrochemical impedance spectroscopy. The device shows a photo-induced enhancement of biosensing performance towards increasing concentration of the analyte, which is analyzed with cyclic voltammetry and enzyme kinetics. The non-turn over condition cyclic voltammetry shows reversible one-electron transfer reaction due to Fe 2+/3+ reaction of the heme co-factor while the turn over shows two electrons reaction because of the reduction of H 2 O 2. Further analysis shows an enhanced sensitivity of 3.302 mA/mM.cm 2 , selectivity towards H 2 O 2 , range of detection 41.2 × 10 −9 – 6.0 × 10 −3 M and limit of detection 12.0 × 10 −9 M. The limitation of this electrode towards high concentration of H 2 O 2 is analysed with Michaelis-Menten fit of the enzymatic reaction and Randles circuit of electrochemical impedance spectra.

Highly sensitive and flexible pressure sensors using position- and dimension-controlled ZnO nanotube arrays grown on graphene films

A facile and novel technique for the fabrication of pressure sensors is reported based on the hybridization of one-dimensional nanomaterials and two-dimensional graphene film. In particular, piezoelectric pressure sensors are fabricated by using vertically aligned and position- and dimension-controlled ZnO nanotube arrays grown on graphene layers. Graphene layers act not only as substrates for catalyst-free growth of high-quality ZnO nanotubes but also as flexible conduction channels connecting ZnO nanotubes and metal electrodes. Freestanding and flexible sensors have been efficiently obtained via mechanical lift-off of hybrid ZnO nanotube/graphene film structures and by exploiting the weak van der Waals forces existing between the graphene film and the original substrates. A prototype of such devices shows a high pressure sensitivity (−4.4 kPa−1), which would enable the detection of weak flows of inert gas. The relatively low wall thickness and large length of the ZnO nanotubes suggest a relatively high sensitivity to external pressures. The obtained nanotube sensors are attached to the philtrum and wrist of a volunteer and used to monitor his breath and heart rate. Overall, the prototype hybrid sensing device has great potential as wearable technology, especially in the sector of advanced healthcare devices.