Carbon Nanotube Sensors Research Articles

High deformation/damage localization accuracy of fibrous composites through deep-learning of single channel data from carbon nanotube sensors

A convolutional neural network (CNN) model by deep-learning single channel data from a serpentine carbon nanotube sensor (S-CNT) with gradient distributed CNTs is proposed for locating deformation/damage in carbon fiber reinforced plastic (CFRP). The real-time resistance-time data caused by bending deformation of CFRP embedded with S-CNT are encoded into more discriminative 2D images for training the CNN. The results show that an accurate deformation localization within 1.5 mm for the trained positions can be obtained. Moreover, static-indentation loading reveals that the CNN model also has high localization accuracy for new deformation/damage locations in CFRP, with an error of less than 5.5 mm.

Affordable surfactant modified carbon nanotube sensor for the enhanced electrochemical detection of eugenol

Affordable surfactant modified carbon nanotube sensor for the enhanced electrochemical detection of eugenol

CTAC Self-Assembled Alkylated β-Cyclodextrin Loaded onto Functionalized MWCNTs Electrochemical Sensor for NP Detection.

Nonylphenol (NP) is an important fine chemical raw material and intermediate that is widely utilized in industry and may be distributed in aquatic ecosystems. Following its entry into the food and water cycles, it can subsequently enter the human body and potentially harm the human reproductive system. For the purpose of monitoring NP in water, it is thus essential to build a straightforward, affordable, and robust electrochemical sensor. Based on a two-step chemical modification proceeding and an electrostatic self-assembly effect, a double-modified β-cyclodextrin functionalized multiwalled carbon nanotube sensor (HE-β-CD-CTAC/F-MWCNTs) has been successfully constructed. It incorporates the excellent host-guest interaction ability of β-cyclodextrin and the high chemical activity of cetyltrimethylammonium chloride (CTAC), and the carbon nanotubes have an enormous particular surface area and strong electrical conductivity. The electrochemical oxidation reaction of NP with the sensor is controlled by a surface adsorption process of equal numbers of protons and electrons. In accordance with the optimized experimental parameters, the limit of detection (LOD) for the sensor is 0.13 μM, and it responds linearly to NP in the concentration range of 1-200 μM. Meanwhile, the sensor has excellent repeatability, stability, and immunity to interference. For the detection of NP in real water samples, the sensor also showed an excellent recovery rate (92.8%-98.5%) and relative standard deviation (1.16%-3.26%).

Development of a 3D printed liquid-core hydrogel platform for real-time carbon nanotube sensors

Development of a 3D printed liquid-core hydrogel platform for real-time carbon nanotube sensors

Development of a Plasma-Based Nanosensor Platform for Triage of Neurological Tumors

Neurological tumors have diverse etiologies and treatments. Presently, diagnostic technologies such as MRI or CT scans are limited by poor resolution, and thus imprecise identification of tumor classes. As a result, diagnostic methods rely on highly invasive intracranial biopsies for conclusive tumor identification. Development of non-invasive methods to accurately identify tumor class may lead to earlier and more accurate diagnoses, enabling prompt and targeted treatment strategies. To address this unmet clinical need, we report the development a molecular-recognition-based nanosensor array that can accurately identify a molecular fingerprint of glioma and meningioma from plasma. We developed this capability using sensor arrays of chemically modified carbon nanotubes that can transduce subtle differences in the physicochemical properties of molecules in biofluids via sensitive molecular binding interactions. Using high-throughput near-infrared fluorescence spectroscopy, we screened 23 chemically modified (6,5) carbon nanotubes sensors in 324 patient plasma samples. We trained machine learning models to classify sensor responses as coming from either glioma or meningioma tumors. The best performing models were able to achieve a positive predictive value of 0.75. Sensor feature analysis revealed a set of spectral features positively associated with class differentiation. This work has the potential to aid clinical care by facilitating the early triage of different types of tumors to provide better treatment options for patients.

(Invited) Conjugation of Polyethylene Glycol to Single Wall Carbon Nanotube Sensor Platforms to Decrease Extracellular Protein Interactions

Single wall carbon nanotube (SWNT) sensors can be used to quantify extracellular analytes, but proteins released by cells interact with the SWNT and decrease the efficacy of the sensors. We have conjugated a 5 kDa polyethylene glycol (PEG) to SWNT sensor platforms to decrease the impact of extracellular proteins on the SWNT sensors. The development of this PEGylated SWNT sensor platform will allow for quantification of extracellular analytes without signal inhibition from cell associated proteins, providing a more accurate way of analyzing both in vitro and in vivo signaling molecules.

A New Technology for Industrial Strain Mapping Using Single-Wall Carbon Nanotube Sensors

Measurements of mechanical strain are widely used in heavy industry to design and test new structures and to ensure the safety of installed infrastructure. However, the few practical methods for strain measurement all have serious limitations. To complement these methods, we have developed a new strain technology, called S4 for “strain-sensing smart skin,” which uses single-wall carbon nanotubes (SWCNTs) as microscopic sensors. Nanotubes dilutely embedded in a polymer are applied as a thin film to specimen surfaces of interest. Subsequent strains in the specimen are transmitted by load transfer through the film to the nanotubes, inducing axial compression or extension. Those small structural deformations of the SWCNTs alter the semiconducting band gaps in predictable ways, causing proportional shifts in the peak wavelengths of their near-infrared fluorescence emission. Shifts are quantified by optically exciting the specimen surface and spectrally analyzing the resulting fluorescence to deduce strain values at the probed locations. The S4 method has recently been implemented using hyperspectral imaging. We demonstrate measurements in less than one minute of strain maps containing hundreds of thousands of pixels with 50 microstrain noise levels and 0.2 mm spatial resolution. This technology has promising potential to become a large-scale commercialized application of carbon nanotechnology.

Development of a 3D Printed Liquid-Core Hydrogel Platform for Real-Time Carbon Nanotube Sensors: A Breakthrough in Minimally Invasive Health Monitoring

The need for minimally invasive, real-time, and low-cost medical sensors holds great potential to revolutionize the healthcare industry. Single-walled carbon nanotube (SWNT)-based near-infrared (nIR) sensors are a relatively new field, able to provide high-quality spatial and temporal information regarding a wide range of cellular signaling molecules, including nitric oxide (NO), and hydrogen peroxide (H2O2). However, their use for in vitro and in vivo applications has been limited due to challenges related to their compatibility with packaging or immobilization techniques. Approaches like surface immobilization on solid substrates and dialysis bag confinement are costly, unstable, and unsuitable for use in settings with limited resources. SWNT sensors have recently been implanted into a large animal model as a proof-of-concept, but the challenge of retaining SWNT is currently restricting the advancement of hydrogel technology in wearable/implantable biosensors. We have developed and optimized a 3D printed liquid-core self-healing hydrogel platform that encapsulates the (AT)15 wrapped-SWNT, a NO sensor, and studied its mechanical and optical characterizations. Notably, after 90-days at 37 °C, the fluorescence intensity exhibited a negligible decrease. Statistical analysis indicates that the change in intensity from day 1 to day 90 was statistically insignificant, highlighting the sensor's robust and stable performance over the extended testing period. A linear calibration curve was obtained when the percent quenching was plotted against the logarithm of NO concentration. Furthermore, a polyvinyl alcohol (PVA) wrapped SWNT, a non-reactive sensor, was implanted into 3D printed liquid-core hydrogel platform and no quenching was observed when it was exposed to NO. Therefore, 3D printed liquid-core hydrogel platforms offer a solution for on-site detection of small-molecule analytes, overcoming a major challenge in real-time medical diagnostics and environmental monitoring.

Imaging Dopamine Modulation in Brain Acute Slices for Cocaine Addiction Study with Near-Infrared Carbon Nanotube Sensors

Drug addiction is a pressing issue in modern American society that demands thorough research into its mechanisms. Cocaine locomotor sensitization is a well-established model for understanding the physiological effects of cocaine abuse. Previous studies have established loss of dopamine D2 autoreceptors in striatal tissue as a consequence of locomotor sensitization, yet how these differences in autoreceptor expression affect dopamine signaling remains unclear. Herein, we utilized non-genetically encoded near-infrared fluorescent nanosensors based on carbon nanotubes to image dopamine modulation in live acute coronal brain slices. By leveraging dopamine D2 receptor agonists along with the dopamine nanosensor, we developed a method to identify changes in density of functional D2 autoreceptors and dopamine signaling aberrations that accompany addiction, at the level of individual dopamine synapses. We apply the method to compare changes in D2 autoreceptor activity in the Nucleus Accumbens core in cocaine sensitized and saline (control) mice after prolonged cocaine exposure (5 days). Our preliminarily data indicates the decrease in the number of D2 autoreceptor in cocaine sensitized mice, consistent with the previous studies, and suggests that it leads to higher level of dopamine signaling. Furthermore, we confirm dopamine signaling changes by application of D2 Agonists (quinpirole) are from loss of individual dopamine release sites rather than changes in the quantity of dopamine released, or changes in dopamine reuptake kinetics. Our study provides a route to understand the changes in neuromodulation that underlie the neurobiology of addiction and other dopamine-centric neurological conditions.

Near-Infrared Fluorescent Carbon Nanotube Sensors for the Plant Hormone Family Gibberellins

Gibberellins (GAs) are a class of phytohormones, important for plant growth, and very difficult to distinguish because of their similarity in chemical structures. Herein, we develop the first nanosensors for GAs by designing and engineering polymer-wrapped single-walled carbon nanotubes (SWNTs) with unique corona phases that selectively bind to bioactive GAs, GA3 and GA4, triggering near-infrared (NIR) fluorescence intensity changes. Using a new coupled Raman/NIR fluorimeter that enables self-referencing of nanosensor NIR fluorescence with its Raman G-band, we demonstrated detection of cellular GA in Arabidopsis, lettuce, and basil roots. The nanosensors reported increased endogenous GA levels in transgenic Arabidopsis mutants that overexpress GA and in emerging lateral roots. Our approach allows rapid spatiotemporal detection of GA across species. The reversible sensor captured the decreasing GA levels in salt-treated lettuce roots, which correlated remarkably with fresh weight changes. This work demonstrates the potential for nanosensors to solve longstanding problems in plant biotechnology.

Fluorescence changes in carbon nanotube sensors correlate with THz absorption of hydration

Single wall carbon nanotubes (SWCNTs) functionalized with (bio-)polymers such as DNA are soluble in water and sense analytes by analyte-specific changes of their intrinsic fluorescence. Such SWCNT-based (bio-)sensors translate the binding of a molecule (molecular recognition) into a measurable optical signal. This signal transduction is crucial for all types of molecular sensors to achieve high sensitivities. Although there is an increasing number of SWCNT-based sensors, there is yet no molecular understanding of the observed changes in the SWCNT’s fluorescence. Here, we report THz experiments that map changes in the local hydration of the solvated SWCNT upon binding of analytes such as the neurotransmitter dopamine or the vitamin riboflavin. The THz amplitude signal serves as a measure of the coupling of charge fluctuations in the SWCNTs to the charge density fluctuations in the hydration layer. We find a linear (inverse) correlation between changes in THz amplitude and the intensity of the change in fluorescence induced by the analytes. Simulations show that the organic corona shapes the local water, which determines the exciton dynamics. Thus, THz signals are a quantitative predictor for signal transduction strength and can be used as a guiding chemical design principle for optimizing fluorescent biosensors.

Real Time Defect Identification using Advanced Artificial Intelligence based Material Strain Sensors for Environmental Safety

Advanced materials find applications in various fields of engineering and medicine. Many advanced materials are synthesized characterised to design sensors for various application including environmental protection. This work explores the possibility of real time defect identification using advanced materials such as graphene composite based sensor for Environment safety. Advanced materials like Graphene composite based sensor were prepared using solvent casting technique. Possibility of using graphene-PVDF based sensors as non- destructive probes to identify surface defects of materials were evaluated by probing on materials with pre-machined defects. Defects were induced artificially in different materials such as (SS316 LN stainless steel) flat plate and cylindrical disc plate. Defects vary both in size and depth. Nanocomposite films were cut in to small pieces of equal dimension and pasted over the various defects. The variation in size and depth of the defects is measured in terms of variation in resistance and suitably calibration graphs were obtained. Using advanced materials for environmental protection, Industry environment safety can be monitored and essential measures can be carried out. This work also explores the change in absorption property of carbon based nanocomposite films on addition of different weight percentage of advanced material based fillers such as Multiwalled carbon nanotubes and graphene. Filler weight percentage increases in matrix which is indicated by red shift in the absorption spectra.In this research work the use of advanced materials for environmental protection in the Metallurgical Industry is explored . Development of advanced functional materials were carried out . Characterization of these advanced material were also carried out . Sensitivity of these advanced material based sensors were analyzed and calibarated. By using these advanced material based senors catastrophic disorders can be avoided and environmental safety is ensured.The non-destructive evaluation (NDE) method that is being presented uses a Carbon Nanotube (CNT) and graphene-based sensor to identify defects in pre-machined stainless steel plates is innovative and straightforward. Utilizing nano composites is meant to combine the advantageous qualities of the filler and matrix. It was decided to use PVDF, a piezoelectric polymer, because of its benefits including low cost, versatility, and quick response time. A small amount (weight%) of MWCNTs and graphene are employed as filler to improve the material's shortcomings, such as delayed electrical response, and to make it behave as a piezoresistive and conductive material.

Kirigami-inspired gas sensors for strain-insensitive operation

Wearable electronics for the Internet of Things (IoT) have spurred interest in optimizing stretchable substrates, electrodes, and sensing materials. Specifically, wearable gas sensors are valuable for real-time monitoring of hazardous chemicals. For wearable gas sensors, a stable operation under mechanical deformation is required. Here, we introduce strain-insensitive Kirigami-structured gas sensors decorated with titanium dioxide (TiO2) functionalized carbon nanotubes (CNTs) for NO2 sensing. The Kirigami-shaped substrate is used to ensure mechanical stability when stretched. The developed device shows only a 1.3 % change in base resistance under 80 % strain. In addition, the impact of electro-thermal properties at various strain levels is analyzed to aid the understanding of the device's performance. The CNT-TiO2 composite induced alterations in p-n heterojunctions, improving the measurement sensitivity by approximately 250 % compared to a bare CNT sensor. Additionally, the sensors exhibited a 10-fold faster desorption rate due to the enhanced photocatalytic effect of TiO2 under UV exposure. Remarkably, the Kirigami-structured gas sensors maintained stable and repetitive sensing operation even under 80 % strain, which would be enough to be used in various wearable applications.

Ultraflexible Wireless Imager Integrated with Organic Circuits for Broadband Infrared Thermal Analysis.

Flexible imagers are currently under intensive development as versatile optical sensor arrays, designed to capture images of surfaces and internals, irrespective of their shape. A significant challenge in developing flexible imagers is extending their detection capabilities to encompass a broad spectrum of infrared light, particularly terahertz (THz) light at room temperature. This advancement is crucial for thermal and biochemical applications. In this study, a flexible infrared imager is designed using uncooled carbon nanotube (CNT) sensors and organic circuits. The CNT sensors, fabricated on ultrathin 2.4µm substrates, demonstrate enhanced sensitivity across a wide infrared range, spanning from near-infrared to THz wavelengths. Moreover, they retain their characteristics under bending and crumpling. The design incorporates light-shielded organic transistors and circuits, functioning reliably under light irradiation, and amplifies THz detection signals by a factor of 10. The integration of both CNT sensors and shielded organic transistors into an 8 × 8 active-sensor matrix within the imager enables sequential infrared imaging and nondestructive assessment for heat sources and in-liquid chemicals through wireless communication systems. The proposed imager, offering unique functionality, shows promise for applications in biochemical analysis and soft robotics.

Advancing accuracy in breath testing for lung cancer: strategies for improving diagnostic precision in imbalanced data

BackgroundBreath testing using an electronic nose has been recognized as a promising new technique for the early detection of lung cancer. Imbalanced data are commonly observed in electronic nose studies, but methods to address them are rarely reported.ObjectiveThe objectives of this study were to assess the accuracy of electronic nose screening for lung cancer with imbalanced learning and to select the best mechanical learning algorithm.MethodsWe conducted a case‒control study that included patients with lung cancer and healthy controls and analyzed metabolites in exhaled breath using a carbon nanotube sensor array. The study used five machine learning algorithms to build predictive models and a synthetic minority oversampling technique to address imbalanced data. The diagnostic accuracy of lung cancer was assessed using pathology reports as the gold standard.ResultsWe enrolled 190 subjects between 2020 and 2023. A total of 155 subjects were used in the final analysis, which included 111 lung cancer patients and 44 healthy controls. We randomly divided samples into one training set, one internal validation set, and one external validation set. In the external validation set, the summary sensitivity was 0.88 (95% CI 0.84–0.91), the summary specificity was 1.00 (95% CI 0.85–1.00), the AUC was 0.96 (95% CI 0.94–0.98), the pAUC was 0.92 (95% CI 0.89–0.96), and the DOR was 207.62 (95% CI 24.62–924.64).ConclusionElectronic nose screening for lung cancer is highly accurate. The support vector machine algorithm is more suitable for analyzing chemical sensor data from electronic noses.

Highpoints of carbon nanotube nanocomposite sensors—A review

One dimensional hollow cylindrical carbon nanotube nanostructure has played essential role in nanotechnology advancements, since its discovery. In technical fields, carbon nanotube has been applied in pristine as well as in nanocomposite form. Consequently, carbon nanotube has been composited with various conductive and non-conducting matrices as per desired end purposes. In sensing technology, significant breakthroughs have been observed regarding multifunctional carbon nanotube nanocomposites. Common matrices used in this concern include conjugated polymers like poly(3,4-ethylenedioxythiophene): polystyrene sulfonic acid, polyaniline, etc. along with some thermoplastics like polyamide, polyurethane, etc. In these matrices, carbon nanotube can form percolation network for electron or charge transportation and may also develop interfacial interactions for fine compatibility, stability, and robustness. Sensing features of the ensuing carbon nanotube nanocomposites depend upon their interactions with the analyte (gasses/ions, biomolecules, or motion). Consequently, nanocomposites have been used to develop efficient gas sensors, strain sensors, and biosensors. Performance of carbon nanotube sensors have been analyzed depending upon the sensitivity, selectivity, detection limit, reproducibility, and responses towards analytes.

Mechanical enhancement and high linearity health monitoring of composite materials based on CNTs/PSF/PI film sensor with ultra-low SWCNTs doping content.

A new type of embedded composite material health monitoring nano-sensor is designed to ensure that the unique material advantages of nanofillers can be maximized. The carbon nanotubes (CNTs)/polysulfone (PSF)/polyimide (PI) thin film sensor in this paper is obtained by the self-assembly of a PSF/PI asymmetric porous membrane which is prepared by a phase inversion method through vacuum filtration of SWCNTs. It is a new structure for a practical CNT sensor that can take into account both 'composite health monitoring and damage warning' and 'composite mechanical enhancement'. The new structure of the CNTs/PSF/PI film sensor is divided into two parts. The upper part consists of small-aperture finger-like holes filled with SWCNTs (the SWCNT content is 0.0127 mg cm-2). The lower part consists of large-aperture cavities conducive to resin infiltration, which enhance the interface bonding force between the sensor and the composite material. This unique structure allows the CNTs/PSF/PI film sensor to change the influence of the embedded sensor from 'introducing defects' to 'local enhancement', and the mechanical strength of the enhanced specimen can reach up to 1.68 times that of the original specimen, and the service interval can reach 2.01 times that of the original specimen. In addition, the CNTs/PSF/PI film sensor also has good sensitivity (GF = 2.54) and extremely high linearity (R2 = 0.9995), and has excellent follow-up and interface bonding ability. It can also maintain excellent fatigue resistance and stability over 46 500 vibration cycles, which provides new research ideas and research methods for the field of composite-life monitoring sensors.

A nIR fluorescent single walled carbon nanotube sensor for broad-spectrum diagnostics

In this review, we provide a comprehensive overview of the latest advancements in diagnostic sensor design using nIR fluorescent SWCNTs and suggest potential directions for technological developments for real-world applications.

Diagnosis and analysis of HIV-1 with different methods

Early detection and continuous monitoring of human immunodeficiency virus type 1 (HIV-1) infection are crucial for effective diagnosis and treatment. To ensure successful early ART application onto patients in early stages, methods of HIV-1 detection in premature HIV accumulation stages are important to prevent the accumulation of HIV-1 viral molecules after replication. At the same time, biomarkers such as CARD8 and TAT proteins are an important the early identification and monitoring mechanism of HIV-1 infection. These biomarkers are the building blocks of a successful biosensor and they can provide key insights into disease progression and treatment efficacy. This research provides an extensive review of HIV-1 biomarkers and potential carbon-based biosensing mediums such as carbon dot sensors and carbon nanotube sensors in order to detect HIV-1 viral detection after surface modification with a focus on their implications for early detection and monitoring.

Tailoring piezoresistive response of carbon nanotubes sensors by hybridization of cellulose nanocrystals for composite structures

Tailoring piezoresistive response of carbon nanotubes sensors by hybridization of cellulose nanocrystals for composite structures