Machine Learning Discrimination and Ultrasensitive Detection of Fentanyl Using Gold Nanoparticle-Decorated Carbon Nanotube-Based Field-Effect Transistor Sensors.

The opioid overdose crisis is a global health challenge. Fentanyl, an exceedingly potent synthetic opioid, has emerged as a leading contributor to the surge in opioid-related overdose deaths. The surge in overdose fatalities, particularly due to illicitly manufactured fentanyl and its contamination of street drugs, emphasizes the urgency for drug-testing technologies that can quickly and accurately identify fentanyl from other drugs and quantify trace amounts of fentanyl. In this paper, gold nanoparticle (AuNP)-decorated single-walled carbon nanotube (SWCNT)-based field-effect transistors (FETs) are utilized for machine learning-assisted identification of fentanyl from codeine, hydrocodone, and morphine. The unique sensing performance of fentanyl led to use machine learning approaches for accurate identification of fentanyl. Employing linear discriminant analysis (LDA) with a leave-one-out cross-validation approach, a validation accuracy of 91.2% is achieved. Meanwhile, density functional theory (DFT) calculations reveal the factors that contributed to the enhanced sensitivity of the Au-SWCNT FET sensor toward fentanyl as well as the underlying sensing mechanism. Finally, fentanyl antibodies are introduced to the Au-SWCNT FET sensor as specific receptors, expanding the linear range of the sensor in the lower concentration range, and enabling ultrasensitive detection of fentanyl with a limit of detection at 10.8 fg mL-1.

Diagnostics of Tuberculosis with Single-Walled Carbon Nanotube-Based Field-Effect Transistors.

Tuberculosis (TB) is still threatening millions of people's lives, especially in developing countries. One of the major factors contributing to the ongoing epidemic of TB is the lack of a fast, efficient, and inexpensive diagnostic strategy. In this work, we developed a semiconducting single-walled carbon nanotube (SWCNT)-based field-effect transistor (FET) device functionalized with anti-Mycobacterium tuberculosis antigen 85B antibody (Ab85B) to detect the major M. tuberculosis-secreted antigen 85B (Ag85B). Through optimizing the device fabrication process by evaluating the mass of the antibody and the concentration of the gating electrolyte, our Ab85B-SWCNT FET devices achieved the detection of the Ag85B spiked in phosphate-buffered saline (calibration samples) with a limit of detection (LOD) of 0.05 fg/mL. This SWCNT FET biosensor also showed good sensing performance in biological matrices including artificial sputum and can identify Ag85B in serum after introducing bovine serum albumin (BSA) into the blocking layer. Furthermore, our BSA-blocked Ab85B-SWCNT FET devices can distinguish between TB-positive and -negative clinical samples, promising the application of SWCNT FET devices in point-of-care TB diagnostics. Moreover, the robustness of this SWCNT-based biosensor to the TB diagnosis in blood serum was enhanced by blocking SWCNT devices directly with a glutaraldehyde cross-linked BSA layer, enabling future applications of these SWCNT-based biosensors in clinical testing.

Size-Based Norfentanyl Detection with SWCNT@UiO-MOF Composites.

Single-walled carbon nanotube (SWCNT)@metal-organic framework (MOF) field-effect transistor (FET) sensors generate a signal through analytes restricting ion diffusion around the SWCNT surface. Four composites made up of SWCNTs and UiO-66, UiO-66-NH2, UiO-67, and UiO-67-CH3 were synthesized to explore the detection of norfentanyl (NF) using SWCNT@MOF FET sensors with different pore sizes. Liquid-gated FET devices of SWCNT@UiO-67 showed the highest sensing response toward NF, whereas SWCNT@UiO-66 and SWCNT@UiO-66-NH2 devices showed no sensitivity improvement compared to bare SWCNT. Comparing SWCNT@UiO-67 and SWCNT@UiO-67-CH3 indicated that the sensing response is modulated by not only the size-matching between NF and MOF channel but also NF diffusion within the MOF channel. Additionally, other drug metabolites, including norhydrocodone (NH), benzoylecgonine (BZ), and normorphine (NM) were tested with the SWCNT@UiO-67 sensor. The sensor was not responding toward NH and or BZ but a similar sensing result toward NM because NM has a similar size to NF. The SWCNT@MOF FET sensor can avoid interference from bigger molecules but sensor arrays with different pore sizes and chemistries are needed to improve the specificity.

An Ultrasensitive Norfentanyl Sensor Based on a Carbon Nanotube-Based Field-Effect Transistor for the Detection of Fentanyl Exposure.

The opioid crisis is a worldwide public health crisis that has affected millions of people. In recent years, synthetic opioids, primarily illicit fentanyl, have become the primary driver of overdose deaths. There is a great need for a highly sensitive, portable, and inexpensive analytical tool that can quickly indicate the presence and relative threat of fentanyl. In this work, we develop a semiconductor enriched (sc-) single-walled carbon nanotube (SWCNT)-based field-effect transistor (FET) biosensor functionalized with norfentanyl antibodies for the sensitive detection of norfentanyl, the primary inactive metabolite of fentanyl, in urine samples. Different sensor configurations were explored in order to obtain the most optimized sensing results. Moreover, by employing the "reduced" antibody, we achieved orientated immobilization of the norfentanyl antibody and thus brought the antigen-antibody interaction closer to the sensor surface, further improving the sensitivity. The reported norfentanyl biosensors have a limit of detection in the fg/mL region in both calibration samples and synthetic urine samples, showing ultrasensitivity and high reliability.

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.

Bacterial Vaginosis Monitoring with Carbon Nanotube Field-Effect Transistors.

The ability to rapidly and reliably screen for bacterial vaginosis (BV) during pregnancy is of great significance for maternal health and pregnancy outcomes. In this proof-of-concept study, we demonstrated the potential of carbon nanotube field-effect transistors (NTFET) in the rapid diagnostics of BV with the sensing of BV-related factors such as pH and biogenic amines. The fabricated sensors showed good linearity to pH changes with a linear correlation coefficient of 0.99. The pH sensing performance was stable after more than one month of sensor storage. In addition, the sensor was able to classify BV-related biogenic amine-negative/positive samples with machine learning, utilizing different test strategies and algorithms, including linear discriminant analysis (LDA), support vector machine (SVM), and principal component analysis (PCA). The biogenic amine sample status could be well classified using a soft-margin SVM model with a validation accuracy of 87.5%. The accuracy could be further improved using a gold gate electrode for measurement, with accuracy higher than 90% in both LDA and SVM models. We also explored the sensing mechanisms and found that the change in NTFET off current was crucial for classification. The fabricated sensors successfully detect BV-related factors, demonstrating the competitive advantage of NTFET for point-of-care diagnostics of BV.

Cerebrospinal Fluid Leak Detection with a Carbon Nanotube-Based Field-Effect Transistor Biosensing Platform.

Cerebrospinal fluid (CSF) leakage may lead to life-threatening complications if not detected promptly. However, gel electrophoresis, the gold-standard test for confirming CSF leakage by detecting beta2-transferrin (ß2-Tf), requires 3-6 h and is labor-intensive. We developed a new ß2-Tf detection platform for rapid identification of CSF leakage. The three-step design, which includes two steps of affinity chromatography and a rapid sensing step using a semiconductor-enriched single-walled carbon nanotube field-effect transistor (FET) sensor, circumvented the lack of selectivity that antitransferrin antibody exhibits for transferrin isoforms and markedly shortened the detection time. Furthermore, three different sensing configurations for the FET sensor were investigated for obtaining the optimal ß2-Tf sensing results. Finally, body fluid (CSF and serum) tests employing our three-step strategy demonstrated high sensitivity, suggesting its potential to be used as a rapid diagnostic tool for CSF leakage.

Nitrogen-Doped Carbon Nanotube Cups for Cancer Therapy.

Carbon nanomaterials have attracted significant attention for a variety of biomedical applications including sensing and detection, photothermal therapy, and delivery of therapeutic cargo. The ease of chemical functionalization, tunable length scales and morphologies, and ability to undergo complete enzymatic degradation make carbon nanomaterials an ideal drug delivery system. Much work has been done to synthesize carbon nanomaterials ranging from carbon dots, graphene, and carbon nanotubes to carbon nanocapsules, specifically carbon nanohorns or nitrogen-doped carbon nanocups. Here, we analyze specific properties of nitrogen-doped carbon nanotube cups which have been designed and utilized as drug delivery systems with the focus on the loading of these nanocapsules with specific therapeutic cargo and the targeted delivery for cancer therapy. We also summarize our targeted synthesis of gold nanoparticles on the open edge of nitrogen-doped carbon nanotube cups to create loaded and sealed nanocarriers for the delivery of chemotherapeutic agents to myeloid regulatory cells responsible for the immunosuppressive properties of the tumor microenvironment and thus tumor immune escape.

Size Discrimination of Carbohydrates via Conductive Carbon Nanotube@Metal Organic Framework Composites.

Traditional chemical sensing methodologies have typically relied on the specific chemistry of the analyte for detection. Modifications to the local environment surrounding the sensor represent an alternative pathway to impart selective differentiation. Here, we present the hybridization of a 2-D metal organic framework (Cu3(HHTP)2) with single-walled carbon nanotubes (SWCNTs) as a methodology for size discrimination of carbohydrates. Synthesis and the resulting conductive performance are modulated by both mass loading of SWCNTs and their relative oxidation. Liquid gated field-effect transistor (FET) devices demonstrate improved on/off characteristics and differentiation of carbohydrates based on molecular size. Glucose molecule detection is limited to the single micromolar concentration range. Molecular Dynamics (MD) calculations on model systems revealed decreases in ion diffusivity in the presence of different sugars as well as packing differences based on the size of a given carbohydrate molecule. The proposed sensing mechanism is a reduction in gate capacitance initiated by the filling of the pores with carbohydrate molecules. Restricting diffusion around a sensor in combination with FET measurements represents a new type of sensing mechanism for chemically similar analytes.

Heterogeneous Growth of UiO-66-NH2 on Oxidized Single-Walled Carbon Nanotubes to Form "Beads-on-a-String" Composites.

In this work, we demonstrate a facile synthesis of UiO-66-NH2 metal-organic framework (MOF)/oxidized single-walled carbon nanotubes (ox-SWCNTs) composite at room temperature. Acetic acid (HAc) was used as a modulator to manipulate the morphology of the MOF in these composites. With a zirconium oxide cluster (Zr) to 2-aminoteraphthalate linker (ATA) 1:1.42 ratio and acetic acid modulator, we achieved predominately heterogeneous MOF growth on the sidewalls of CNTs. Understanding the growth mechanism of these composites was facilitated by conducting DFT calculations to investigate the interactions between ox-SWCNTs and the MOF precursors. The synthesized composites combine both microporosity of the MOF and electrical conductivity of the SWCNTs. Gas sensing tests demonstrated higher response for UiO-66-NH2/ox-SWCNT hybrid toward dry air saturated with dimethyl methylphosphonate (DMMP) vapor compared to oxidized single-walled carbon nanotubes (ox-SWCNTs) alone.

[2π + 2π] Photocycloaddition of Enones to Single-Walled Carbon Nanotubes Creates Fluorescent Quantum Defects.

Single-walled carbon nanotubes (SWCNTs) have been widely applied in biomedical fields such as drug delivery, biosensing, bioimaging, and tissue engineering. Understanding their reactivity with biomolecules is important for these applications. We describe here a photoinduced cycloaddition reaction between enones and SWCNTs. By creating covalent and tunable sp3 defects in the sp2 carbon lattice of SWCNTs through [2π + 2π] photocycloaddition, a bright red-shifted photoluminescence was gradually generated. The photocycloaddition functionalization was demonstrated with various organic molecules bearing an enone functional group, including biologically important oxygenated lipid metabolites. The mechanism of this reaction was studied empirically and using computational methods. Density functional theory calculations were employed to elucidate the identity of the reaction product and understand the origin of different substrate reactivities. The results of this study can enable engineering of the optical and electronic properties of semiconducting SWCNTs and provide understanding into their interactions with the lipid biocorona.

Breath Acetone Sensing Based on Single-Walled Carbon Nanotube-Titanium Dioxide Hybrids Enabled by a Custom-Built Dehumidifier.

Acetone is a metabolic byproduct found in the exhaled breath and can be measured to monitor the metabolic degree of ketosis. In this state, the body uses free fatty acids as its main source of fuel because there is limited access to glucose. Monitoring ketosis is important for type I diabetes patients to prevent ketoacidosis, a potentially fatal condition, and individuals adjusting to a low-carbohydrate diet. Here, we demonstrate that a chemiresistor fabricated from oxidized single-walled carbon nanotubes functionalized with titanium dioxide (SWCNT@TiO2) can be used to detect acetone in dried breath samples. Initially, due to the high cross sensitivity of the acetone sensor to water vapor, the acetone sensor was unable to detect acetone in humid gas samples. To resolve this cross-sensitivity issue, a dehumidifier was designed and fabricated to dehydrate the breath samples. Sensor response to the acetone in dried breath samples from three volunteers was shown to be linearly correlated with the two other ketone bodies, acetoacetic acid in urine and ß-hydroxybutyric acid in the blood. The breath sampling and analysis methodology had a calculated acetone detection limit of 1.6 ppm and capable of detecting up to at least 100 ppm of acetone, which is the dynamic range of breath acetone for someone with ketosis. Finally, the application of the sensor as a breath acetone detector was studied by incorporating the sensor into a handheld prototype breathalyzer.

Machine learning-assisted calibration of Hg2+ sensors based on carbon nanotube field-effect transistors.

Nanomaterial-based electronic sensors have demonstrated ultra-low detection limits, down to parts-per-billion (ppb) or parts-per-trillion (ppt) concentrations. However, these extreme sensitivities also make them susceptible to signal saturation at higher concentrations and restrict their usage primarily to low concentrations. Here, we report machine learning techniques to create a calibration method for carbon nanotube-based field-effect transistor (FET) devices. We started with linear regression, followed by regression splines to capture the non-linearity in the data. Further improvements in model performance were obtained with regression trees. Finally we lowered the model variance and further boosted the model performance by introducing random forest. The resulting performance as measured by R2 was estimated to be 0.8260 using out-of-bag error. The methodology avoids saturation and extends the dynamic range of the nanosensors up to 12 orders of magnitude in analyte concentrations. Further investigations of the sensing mechanism include analysis of feature importance in each of the model we tested. Functionalized nanosensors demonstrate selective detection of Hg2+ ions with detection limits 10-14.36±0.78 M, and maintain calibration to concentrations as high as 1 mM. Application of machine learning techniques to investigate which features in the FET signal maximally correlate with concentration changes provide valuable insight into the carbon nanotube sensing mechanism and assist in the rational design of future nanosensors.

Rapid Detection of SARS-CoV-2 Antigens Using High-Purity Semiconducting Single-Walled Carbon Nanotube-Based Field-Effect Transistors.

Early diagnosis of SARS-CoV-2 infection is critical for facilitating proper containment procedures, and a rapid, sensitive antigen assay is a critical step in curbing the pandemic. In this work, we report the use of a high-purity semiconducting (sc) single-walled carbon nanotube (SWCNT)-based field-effect transistor (FET) decorated with specific binding chemistry to assess the presence of SARS-CoV-2 antigens in clinical nasopharyngeal samples. Our SWCNT FET sensors, with functionalization of the anti-SARS-CoV-2 spike protein antibody (SAb) and anti-nucleocapsid protein antibody, detected the S antigen (SAg) and N antigen (NAg), reaching a limit of detection of 0.55 fg/mL for SAg and 0.016 fg/mL for NAg in calibration samples. SAb-functionalized FET sensors also exhibited good sensing performance in discriminating positive and negative clinical samples, indicating a proof of principle for use as a rapid COVID-19 antigen diagnostic tool with high analytical sensitivity and specificity at low cost.

Photoluminescence Response in Carbon Nanomaterials to Enzymatic Degradation.

Myeloperoxidase (MPO), a key enzyme released by neutrophils during inflammation, has been shown to catalyze the biodegradation of carbon nanomaterials. In this work, we perform photoluminescence studies on the MPO-catalyzed oxidation of graphene oxide (GO) and surfactant-coated pristine (6,5) single-walled carbon nanotubes (SWCNTs). The enzymatic degradation mechanism involves the introduction of defects, which promotes further degradation. Interestingly, the photoluminescence responses of GO and SWCNTs to enzymatic degradation are counterposed. Although the near-infrared (NIR) fluorescence intensity of SWCNTs at 998 nm is either unchanged or decreases depending on the surfactant identity, the blue fluorescence intensity of GO at 440 nm increases with the progression of oxidation by MPO/H2O2/Cl- due to the formation of graphene quantum dots (GQDs). Turn-on GO fluorescence is also observed with neutrophil-like HL-60 cells, indicative of potential applications of GO for imaging MPO activity in live cells. Based on these results, we further construct two ratiometric sensors using SWCNT/GO nanoscrolls by incorporating surfactant-wrapped pristine SWCNTs as the internal either turn-off (with sodium cholate (SC)) or reference (with carboxymethylcellulose (CMC)) sensor. The ratiometric approach enables the sensors to be more stable to external noise by providing response invariant to the absolute intensity emitted from the sensors. Our sensors show linear response to MPO oxidative machinery and hold the promise to be used as self-calibrating carbon nanomaterial-based MPO activity indicators.

Synthesis of Holey Graphene Nanoparticle Compounds.

Bulk-scale syntheses of sp2 nanocarbon have typically been generated by extensive chemical oxidation to yield graphite oxide from graphite, followed by a reductive step. Materials generated via harsh random processes lose desirable physical characteristics. Loss of sp2 conjugation inhibits long-range electronic transport and the potential for electronic band manipulation. Here, we present a nanopatterned holey graphene material electronically hybridized with metal-containing nanoparticles. Oxidative plasma etching of highly ordered pyrolytic graphite via previously developed covalent organic framework (COF)-5-templated patterning yields bulk-scale materials for electrocatalytic applications and fundamental investigations into band structure engineering of nanocomposites. We establish a broad ability (Ag, Au, Cu, and Ni) to grow metal-containing nanoparticles in patterned holes in a metal precursor-dependent manner without a reducing agent. Graphene nanoparticle compounds (GNCs) show metal-contingent changes in the valence band structure. Density functional theory investigations reveal preferences for uncharged metal states, metal contributions to the valence band, and embedding of nanoparticles over surface incorporation. Ni-GNCs show activity for oxygen evolution reaction in alkaline media (1 M KOH). Electrocatalytic activity exceeds 10,000 mA/mg of Ni, shows stability for 2 h of continuous operation, and is kinetically consistent via a Tafel slope with Ni(OH)2-based catalysis.

Luminescence "Turn-On" Detection of Gossypol Using Ln3+-Based Metal-Organic Frameworks and Ln3+ Salts.

Gossypol (Gsp), a natural toxin concentrated in cottonseeds, poses great risks to the safe consumption of cottonseed products, which are used extensively throughout the food industry. In this work, we report the first luminescence "turn-on" sensors for Gsp using near-infrared emitting lanthanide (Ln3+) materials, including Ln3+ MOFs and Ln3+ salts. We first demonstrate that the Yb3+ photoluminescence of a Yb3+ MOF, Yb-NH2-TPDC, can be employed to selectively detect Gsp with a limit of detection of 25 µg/mL via a "turn-on" response from a completely nonemissive state in the absence of Gsp. The recyclability and stability of Yb-NH2-TPDC in the presence of Gsp was demonstrated by fluorescence spectroscopy and PXRD analysis, respectively. A variety of background substances present in practical samples that would require Gsp sensing, such as refined cottonseed oil, palmitic acid, linoleic acid, and α-tocopherol, did not interfere with the Yb3+ photoluminescence signal. We further identified that the "turn-on" of Yb-NH2-TPDC photoluminescence was due to the "antenna effect" of Gsp, as evidenced by spectroscopic studies and supported by computational analysis. This is the first report that Gsp can effectively sensitize Yb3+ photoluminescence. Leveraging this sensing mechanism, we demonstrate facile, highly sensitive, fast-response detection of Gsp using YbCl3·6H2O and NdCl3·6H2O solutions. Overall, we show for the first time that Ln3+-based materials are promising luminescent sensors for Gsp detection. We envision that the reported sensing approach will be applicable to the detection of a wide variety of aromatic molecules using Ln3+ compounds including MOFs, complexes, and salts.

Modification of Carbon Nitride/Reduced Graphene Oxide van der Waals Heterostructure with Copper Nanoparticles To Improve CO2 Sensitivity.

Carbon nitride/reduced graphene oxide (rGO) van der Waals heterostructures (vdWH) have previously shown exceptional oxygen sensitivity via a photoredox mechanism, making it a potential material candidate for various applications such as oxygen reduction reaction catalysis and oxygen sensing. In this work, the electronic structure of a carbon nitride/rGO composite is modified through the introduction of copper nanoparticles (NPs). When incorporated into a chemiresistor device, this vdWH displayed a newfound CO2 sensitivity. The effects of humidity and light were investigated and found to be crucial components for the CO2 sensitivity. Density functional theory calculations performed on a carbon nitride/copper NP@rGO model system found an enhanced stabilization of CO2 caused by H-bonds between the carbon nitride layer and chemisorbed CO2 on copper, pointing to the important role played by humidity. The synergetic effect between the carbon nitride layer interfaced with CuNP@rGO, in combination with humidity and light (395 nm) irradiation, is found to be responsible for the newfound sensitivity toward CO2.

Probing Ca2+-induced conformational change of calmodulin with gold nanoparticle-decorated single-walled carbon nanotube field-effect transistors.

Nanomaterials are ideal for electrochemical biosensors, with their nanoscale dimensions enabling the sensitive probing of biomolecular interactions. In this study, we compare field-effect transistors (FET) comprised of unsorted (un-) and semiconducting-enriched (sc-) single-walled carbon nanotubes (SWCNTs). un-SWCNTs have both metallic and semiconducting SWCNTs in the ensemble, while sc-SWCNTs have a >99.9% purity of semiconducting nanotubes. Both SWCNT FET devices were decorated with gold nanoparticles (AuNPs) and were then employed in investigating the Ca2+-induced conformational change of calmodulin (CaM) - a vital process in calcium signal transduction in the human body. Different biosensing behavior was observed from FET characteristics of the two types of SWCNTs, with sc-SWCNT FET devices displaying better sensing performance with a dynamic range from 10-15 M to 10-13 M Ca2+, and a lower limit of detection at 10-15 M Ca2+.