Pushing Down the Limit of NH3 Detection of Graphene-Based Chemiresistive Sensors through Functionalization by Thermally Activated Tetrazoles Dimerization

Unveiling the drug delivery mechanism of graphene oxide dots at the atomic scale

Graphene oxide (GO) is an amphiphilic and versatile graphene-based nanomaterial that is extremely promising for targeted drug delivery, which aims to administer drugs in a spatially and temporally controlled manner. A typical GO nanocarrier features a polyethylene glycol coating and conjugation to an active targeting ligand. However, it is challenging to accurately model GO dots, because of their intrinsically complex and not unique structure. Here, realistic atomistic GO models are designed as homogeneously/inhomogeneously oxidized flakes and then coated with stealth polymeric chains conjugated to an active targeting ligand (PEG-cRGD). Doxorubicin (DOX) adsorption is investigated by metadynamics simulations for accelerated loading/release events. The presence of PEG and cRGD are found not to affect the DOX adsorption, whereas the homogeneity of oxidation plays a crucial role. We also proved that a change in pH towards acidic conditions causes a reduction in the GO/DOX affinity in line with a pH-triggered release mechanism. Based on this study, the ideal graphene-based DOX carrier is identified as a homogeneously highly oxidized GO where graphitic regions with strong DOX π-π stacking are limited. Such interactions excessively stabilize DOX and are not weakened by a pH-change. On the contrary, DOX interactions with surface oxidized groups are H-bonding and electrostatic, which can effectively be modified by a pH reduction. Our findings are useful to the experimental community to further develop successful drug delivery systems.

Customizing Wettability of Defect-Rich CeO2/TiO2 Nanotube Arrays for Humidity-Resistant, Ultrafast, and Sensitive Ammonia Response

In all their applications, gas sensors should satisfy several requirements, including low cost, reduced energy consumption, fast response/recovery, high sensitivity, and reliability in a broad humidity range. Unfortunately, the fast response/recovery and sensing reliability under high humidity conditions are often still missing, especially those working at room temperature. In this study, a humidity-resistant gas sensor with an ultrafast response/recovery rate was designed by integrating a defect-rich semiconducting sensing interface and a self-assembled monolayer (SAM) with controllable wettability. As a proof-of-concept application, ammonia (NH3), one of the atmospheric and indoor pollutants, was selected as the target gas. The decoration of interconnected defective CeO2 nanowires on spaced TiO2 nanotube arrays (NTAs) provided superior NH3 sensing performances. Moreover, we showed that manipulating the functional end group of SAMs is an efficient and simple method to adjust the wettability, by which 86% sensitivity retention with an ultrafast response (within 5 s) and a low limit of detection (45 ppb) were achieved even at 75% relative humidity and room temperature. This work provides a new route toward the comprehensive design and application of metal oxide semiconductors for trace gas monitoring under harsh conditions, such as those of agricultural, environmental, and industrial fields.

Machine-Learning-Aided NO2 Discrimination with an Array of Graphene Chemiresistors Covalently Functionalized by Diazonium Chemistry

Boosted by the emerging need for highly integrated gas sensors in the internet of things (IoT) ecosystems, electronic noses (e-noses) are gaining interest for the detection of specific molecules over a background of interfering gases. The sensing of nitrogen dioxide is particularly relevant for applications in environmental monitoring and precision medicine. Here we present an easy and efficient functionalization procedure to covalently modify graphene layers, taking advantage of diazonium chemistry. Separate graphene layers were functionalized with one of three different aryl rings: 4-nitrophenyl, 4-carboxyphenyl and 4-bromophenyl. The distinct modified graphene layers were assembled with a pristine layer into an e-nose for NO2 discrimination. A remarkable sensitivity to NO2 was demonstrated through exposure to gaseous solutions with NO2 concentrations in the 1-10 ppm range at room temperature. Then, the discrimination capability of the sensor array was tested by carrying out exposure to several interfering gases and analyzing the data through multivariate statistical analysis. This analysis showed that the e-nose can discriminate NO2 among all the interfering gases in a two-dimensional principal component analysis space. Finally, the e-nose was trained to accurately recognize NO2 contributions with a linear discriminant analysis approach, thus providing a metric for discrimination assessment with a prediction accuracy above 95 %.

A Chemiresistor Sensor Array Based on Graphene Nanostructures: From the Detection of Ammonia and Possible Interfering VOCs to Chemometric Analysis

Sensor arrays are currently attracting the interest of researchers due to their potential of overcoming the limitations of single sensors regarding selectivity, required by specific applications. Among the materials used to develop sensor arrays, graphene has not been so far extensively exploited, despite its remarkable sensing capability. Here we present the development of a graphene-based sensor array prepared by dropcasting nanostructure and nanocomposite graphene solution on interdigitated substrates, with the aim to investigate the capability of the array to discriminate several gases related to specific applications, including environmental monitoring, food quality tracking, and breathomics. This goal is achieved in two steps: at first the sensing properties of the array have been assessed through ammonia exposures, drawing the calibration curves, estimating the limit of detection, which has been found in the ppb range for all sensors, and investigating stability and sensitivity; then, after performing exposures to acetone, ethanol, 2-propanol, sodium hypochlorite, and water vapour, chemometric tools have been exploited to investigate the discrimination capability of the array, including principal component analysis (PCA), linear discriminant analysis (LDA), and Mahalanobis distance. PCA shows that the array was able to discriminate all the tested gases with an explained variance around 95%, while with an LDA approach the array can be trained to accurately recognize unknown gas contribution, with an accuracy higher than 94%.

Imine Bond-Based Fluorescent Nanofilms toward High-Performance Detection and Efficient Removal of HCl and NH3

A new kind of imine bond-based fluorescent nanofilm was developed as multifunctional materials for high-performance detection and efficient removal of hydrogen chloride (HCl) and ammonia (NH3). The flexible, uniform, and photochemically stable nanofilms as prepared showed fast (<1 and <0.5 s), sensitive (<150 ppb and <1.5 ppm), and selective response to HCl and NH3, respectively, and the removal efficiencies to HCl and NH3 are 187.5 and 37.5% (w/w), respectively. A reversible earthy-red to green fluorescence color change upon adsorption of NH3 or HCl enabled visualized monitoring of the two gases in the air. Mechanism studies revealed that the adsorption of HCl is a result of hydrogen bond formation between the analyte and the imine groups. Adsorption of NH3, however, is a result of chemical reaction with the pre-adsorbed HCl. The applicability of the detection and removal strategies as developed was further verified by conducting the tests on real-life or simulated scenarios.

Targeting biomarkers in the gas phase through a chemoresistive electronic nose based on graphene functionalized with metal phthalocyanines

Electronic noses (e-noses) have received considerable interest in the past decade as they can match the emerging needs of modern society such as environmental monitoring, health screening, and food quality tracking. For practical applications of e-noses, it is necessary to collect large amounts of data from an array of sensing devices that can detect interactions with molecules reliably and analyze them via pattern recognition. The use of graphene (Gr)-based arrays of chemiresistors in e-noses is still virtually missing, though recent reports on Gr-based chemiresistors have disclosed high sensing performances upon functionalization of the pristine layer, opening up the possibility of being implemented into e-noses. In this work, with the aim of creating a robust and chemically stable interface that combines the chemical properties of metal phthalocyanines (M-Pc, M = Fe, Co, Ni, Zn) with the superior transport properties of Gr, an array of Gr-based chemiresistor sensors functionalized with drop-cast M-Pc thin layers has been developed. The sensing capability of the array was tested towards biomarkers for breathomics application, with a focus on ammonia (NH₃). Exposure to NH₃ has been carried out drawing the calibration curve and estimating the detection limit for all the sensors. The discrimination capability of the array has then been tested, carrying out exposure to several gases (hydrogen sulfide, acetone, ethanol, 2-propanol, water vapour and benzene) and analysing the data through principal component analysis (PCA). The PCA pattern recognition results show that the developed e-nose is able to discriminate all the tested gases through the synergic contribution of all sensors.