Coherent Vibrations Promote Charge-Transfer across a Graphene-Based Interface.

Discerning the impact of the coherent motion of the nuclei on the timing and efficiency of charge transfer at the donor-acceptor interface is essential for designing performance-enhanced optoelectronic devices. Here, we employ an experimental approach using photocurrent detection in coherent multidimensional spectroscopy to excite a donor aromatic macrocycle and collect the charge transferred to a 2D acceptor layer. For this purpose, we prepared a cobalt phthalocyanine-graphene (CoPc-Gr) interface. Unlike blends, the well-ordered architecture achieved through the physical separation of the two layers allows us to unambiguously collect the electrical signal from graphene alone and associate it with a microscopic understanding of the whole process. The CoPc-Gr interface exhibits an ultrafast electron-transfer signal, stemming from an interlayer mechanism. Remarkably, the signal presents an oscillating time evolution modulated by coherent vibrations originating from the laser-excited CoPc states. By performing Fourier analysis on the beatings and correlating it with the Raman features, along with a comprehensive first-principles characterization of the vibrational coupling in the CoPc excited states, we successfully identify both the orbitals and molecular vibrations that promote the charge transfer at the interface.

Disclosing Fast Detection Opportunities with Nanostructured Chemiresistor Gas Sensors Based on Metal Oxides, Carbon, and Transition Metal Dichalcogenides.

With the emergence of novel sensing materials and the increasing opportunities to address safety and life quality priorities of our society, gas sensing is experiencing an outstanding growth. Among the characteristics required to assess performances, the overall speed of response and recovery is adding to the well-established stability, selectivity, and sensitivity features. In this review, we focus on fast detection with chemiresistor gas sensors, focusing on both response time and recovery time that characterize their dynamical response. We consider three classes of sensing materials operating in a chemiresistor architecture, exposed to the most investigated pollutants, such as NH3, NO2, H2S, H2, ethanol, and acetone. Among sensing materials, we first selected nanostructured metal oxides, which are by far the most used chemiresistors and can provide a solid ground for performance improvement. Then, we selected nanostructured carbon sensing layers (carbon nanotubes, graphene, and reduced graphene), which represent a promising class of materials that can operate at room temperature and offer many possibilities to increase their sensitivities via functionalization, decoration, or blending with other nanostructured materials. Finally, transition metal dichalcogenides are presented as an emerging class of chemiresistive layers that bring what has been learned from graphene into a quite large portfolio of chemo-sensing platforms. For each class, studies since 2019 reporting on chemiresistors that display less than 10 s either in the response or in the recovery time are listed. We show that for many sensing layers, the sum of both response and recovery times is already below 10 s, making them promising devices for fast measurements to detect, e.g., sudden bursts of dangerous emissions in the environment, or to track the integrity of packaging during food processing on conveyor belts at pace with industrial production timescales.

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%.

Self-assembled monolayer functionalized NiO nanowires: strategy to enhance the sensing performance of p-type metal oxide.

A novel strategy for the improvement in the sensing performance of p-type NiO is developed by employing the unique functional properties of self-assembled monolayers. Specifically, hole concentration near the surface of NiO nanowires (NWs) is modulated by terminal epoxy groups of the organosilane. This modulation leads to the increase in electron transfer from reducing gases to NWs surface. As a result, SAM-functionalized sensors showed 9-times higher response at low-temperature as compared to bare NiO NWs.

Trends in the Development of Electronic Noses Based on Carbon Nanotubes Chemiresistors for Breathomics.

The remarkable potential of breath analysis in medical care and diagnosis, and the consequent development of electronic noses, is currently attracting the interest of the research community. This is mainly due to the possibility of applying the technique for early diagnosis, screening campaigns, or tracking the effectiveness of treatment. Carbon nanotubes (CNTs) are known to be good candidates for gas sensing, and they have been recently considered for the development of electronic noses. The present work has the aim of reviewing the available literature on the development of CNTs-based electronic noses for breath analysis applications, detailing the functionalization procedure used to prepare the sensors, the breath sampling techniques, the statistical analysis methods, the diseases under investigation, and the population studied. The review is divided in two main sections: one focusing on the e-noses completely based on CNTs and one reporting on the e-noses that feature sensors based on CNTs, along with sensors based on other materials. Finally, a classification is presented among studies that report on the e-nose capability to discriminate biomarkers, simulated breath, and animal or human breath.

π-Orbital mediated charge transfer channels in a monolayer Gr-NiPc heterointerface unveiled by soft X-ray electron spectroscopies and DFT calculations.

With the aim to identify charge transfer channels underlying device development and operation, X-Ray Photoelectron Spectroscopy (XPS), Near-Edge X-Ray Absorption Fine Structure (NEXAFS), and Resonant Photoelectron Spectroscopy (ResPES) have been employed to characterize a novel heterointerface obtained by the controlled evaporation of a Nickel Phthalocyanine (NiPc) monolayer on a single layer of Graphene (Gr) on SiC substrate. Indeed, the Gr-NiPc interface could be a promising candidate for different applications in the field of photonics, optoelectronics, and sensing, provided that clear information on the charge transfer mechanisms at the Gr-NiPc interface can be obtained. The analysis of the spectroscopic data has shown the effective functionalization and the horizontally-flat disposition of the NiPc complexes over the Gr layer. With this geometry, the main intermolecular interaction experienced by the NiPc species is the coupling with the Gr substrate, through π-symmetry orbitals, as revealed by the different behaviour of the valence band photoemission at resonance with the N K-edge and Ni L3-edge. These results have been supported by the analysis of density functional theory (DFT) calculations, that allowed for a rationalization of the experimental data, showing that charge transfer at the interface occurs from the doubly degenerate eg LUMO orbital, involving mainly N and C (pyrrole ring) pz states, to the holes in the p-doped graphene layer.

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

An easy and cost-effective method is presented to functionalize graphene through thermally activated dimerization of 2,5-diaryltetrazoles. Consistently with the experimental spectroscopic results, theoretical calculations demonstrate that during the thermal treatment a dimerization process to tetrazine is energetically more favorable than covalent grafting. Since both the functionalization method by thermal activation and the use of tetrazoles have never been considered before to prepare graphene-based chemiresistors, this represents a promising approach to develop graphene-related sensing platforms. Five different 2,5-diaryltetrazoles have been tested here for the effective functionalization of low-defect graphene layers on silicon nitride. Based on these layers, an array of sensors has been prepared for testing upon ammonia exposure. The tests on the sensing performances clearly show sensitivity to ammonia, extending the current range of ammonia detection with a graphene-based chemiresistor down to the sub-ppm range, as results from a benchmarking with data available in the literature. Furthermore, all sensors perform better than bare graphene. Density functional theory (DFT) calculations, carried out on a model of the best performing layer of the array, provided the theoretical framework to rationalize the sensing mechanism and disclose a dual role played by the tetrazine molecules, (i) acting as ammonia concentrators and (ii) mediating the electron transfer between ammonia and graphene.

Chemical Defect-Driven Response on Graphene-Based Chemiresistors for Sub-ppm Ammonia Detection.

Gas sensors are essential in several fields and, in general, features such as high sensitivity, quick response, and fast recovery are required, along with low power consumption and low cost. Graphene is considered a promising material for gas sensing applications, its functionalization often being a requisite. In the present study, we developed competitive and promising gas sensors for ammonia detection. Interestingly, we present an easy and efficient method to functionalize graphene by using diazonium chemistry with different functional groups. Moreover, we prove the superior sensing capability of our covalently modified graphene layers. These experimental data have been consistently interpreted by theoretical calculations, which reveal a defect-driven sensor's response to ammonia. These results open the possibility of a comprehensive design and use of these graphene-based sensors in real applications.

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.

Exploring the performance of a functionalized CNT-based sensor array for breathomics through clustering and classification algorithms: from gas sensing of selective biomarkers to discrimination of chronic obstructive pulmonary disease.

An array of carbon nanotube (CNT)-based sensors was produced for sensing selective biomarkers and evaluating breathomics applications with the aid of clustering and classification algorithms. We assessed the sensor array performance in identifying target volatiles and we explored the combination of various classification algorithms to analyse the results obtained from a limited dataset of exhaled breath samples. The sensor array was exposed to ammonia (NH3), nitrogen dioxide (NO2), hydrogen sulphide (H2S), and benzene (C6H6). Among them, ammonia (NH3) and nitrogen dioxide (NO2) are known biomarkers of chronic obstructive pulmonary disease (COPD). Calibration curves for individual sensors in the array were obtained following exposure to the four target molecules. A remarkable response to ammonia (NH3) and nitrogen dioxide (NO2), according to benchmarking with available data in the literature, was observed. Sensor array responses were analyzed through principal component analysis (PCA), thus assessing the array selectivity and its capability to discriminate the four different target volatile molecules. The sensor array was then exposed to exhaled breath samples from patients affected by COPD and healthy control volunteers. A combination of PCA, supported vector machine (SVM), and linear discrimination analysis (LDA) shows that the sensor array can be trained to accurately discriminate healthy from COPD subjects, in spite of the limited dataset.

Gas Sensing with Solar Cells: The Case of NH3 Detection through Nanocarbon/Silicon Hybrid Heterojunctions.

Photovoltaic (PV) cells based on single-walled carbon nanotube (SWCNT)/silicon (Si) and multiwalled carbon nanotube (MWCNT)/Si junctions were tested under exposure to NH3 in the 0-21 ppm concentration range. The PV cell parameters remarkably changed upon NH3 exposure, suggesting that these junctions, while being operated as PV cells, can react to changes in the environment, thereby acting as NH3 gas sensors. Indeed, by choosing the open-circuit voltage, VOC, parameter as read-out, it was found that these cells behaved as gas sensors, operating at room temperature with a response higher than chemiresistors developed on the same layers. The sensitivity was further increased when the whole current-voltage (I-V) curve was collected and the maximum power values were tracked upon NH3 exposure.

Development of a Sensing Array for Human Breath Analysis Based on SWCNT Layers Functionalized with Semiconductor Organic Molecules.

A sensor array based on heterojunctions between semiconducting organic layers and single walled carbon nanotube (SWCNT) films is produced to explore applications in breathomics, the molecular analysis of exhaled breath. The array is exposed to gas/volatiles relevant to specific diseases (ammonia, ethanol, acetone, 2-propanol, sodium hypochlorite, benzene, hydrogen sulfide, and nitrogen dioxide). Then, to evaluate its capability to operate with real relevant biological samples the array is exposed to human breath exhaled from healthy subjects. Finally, to provide a proof of concept of its diagnostic potential, the array is exposed to exhaled breath samples collected from subjects with chronic obstructive pulmonary disease (COPD), an airway chronic inflammatory disease not yet investigated with CNT-based sensor arrays, and breathprints are compared with those obtained from of healthy subjects. Principal component analysis shows that the sensor array is able to detect various target gas/volatiles with a clear fingerprint on a 2D subspace, is suitable for breath profiling in exhaled human breath, and is able to distinguish subjects with COPD from healthy subjects based on their breathprints. This classification ability is further improved by selecting the most responsive sensors to nitrogen dioxide, a potential biomarker of COPD.

Interface Chemistry of Graphene/Cu Grafted By 3,4,5-Tri-Methoxyphenyl.

Chemical reaction with diazonium molecules has revealed to be a powerful method for the surface chemical modification of graphite, carbon nanotubes and recently also of graphene. Graphene electronic structure modification using diazonium molecules is strongly influenced by graphene growth and by the supporting materials. Here, carrying on a detailed study of core levels and valence band photoemission measurements, we are able to reconstruct the interface chemistry of trimethoxybenzenediazonium-based molecules electrochemically grafted on graphene on copper. The band energy alignment at the molecule-graphene interface has been traced revealing the energy position of the HOMO band with respect to the Fermi level.

Dramatic efficiency boost of single-walled carbon nanotube-silicon hybrid solar cells through exposure to ppm nitrogen dioxide in air: An ab-initio assessment of the measured device performances.

We observed a 73% enhancement of the power conversion efficiency (PCE) of a photovoltaic cell based on a single wall carbon nanotube/Si hybrid junction after exposing the device to a limited amount (10 ppm) of NO2 diluted in dry air. On the basis of a computational modeling of the junction, this enhancement is discussed in terms of both carbon nanotube (CNT) p-doping, induced by the interaction with the oxidizing molecules, and work function changes across the junction. Unlike studies so far reported, where the PCE enhancement was correlated only qualitatively to CNT doping, our study (i) provides a novel and reversible path to tune and considerably enhance the cell efficiency by a few ppm gas exposure, and (ii) shows computational results that quantitatively relate the observed effects to the electrostatics of the cell through a systematic calculation of the work function. These effects have been cross-checked by exposing the cell to reducing molecules (i.e·NH3) that resulted to be detrimental to the cell efficiency, consistently with the theoretical ab-initio calculations.

Enhanced selectivity of target gas molecules through a minimal array of gas sensors based on nanoparticle-decorated SWCNTs.

An array of five sensors, based on carbon nanotubes (CNT) functionalized with nanoparticles of Au, TiO2, ITO, and Si has been fabricated and exposed to a selected series of target gas molecules (NH3, NO2, H2S, H2O, benzene, ethanol, acetone, 2-propanol, sodium hypochlorite, and several combinations of two gases). The results of principal component analysis (PCA) of the experimental data show that this array of sensors is able to detect different target gas and to discriminate each molecule in the 2D PCA parameters space. In particular, the possibility to include in the array a humidity sensor significantly increases the capability to discriminate the response to volatile organic compounds (VOCs), even though VOCs usually react with CNTs less than NO2 or NH3. This leads to an improvement in selectivity that could meet the requirements for gas detection applications in the field of environmental monitoring and breathomics, where sensors are exposed to a variety of different molecules and where the humidity can severely affect the overall response of the sensor. Finally, we demonstrate that the ability to test multiple sensors simultaneously can reveal a specific sensor sensitivity, addressing the best functionalization choice to improve the response of new sensors based on decorated CNT layers. In particular, our study shows the better capability of the ITO-decorated sensor to detect H2S and benzene.

Rationalization of hydrogen production by bulk g-C3N4: an in-depth correlation between physico-chemical parameters and solar light photocatalysis.

The aim of this work is the systematic study of the photocatalytic activity of bulk graphitic carbon nitride (g-C3N4) in relation with the physical-chemical, structural and optical properties of the semiconductor. Fourteen g-C3N4 samples have been prepared by thermal condensation starting from three different precursor (melamine, dicyandiamide and urea) and exploring various temperatures (in the range 500-700 °C). The materials obtained have been deeply characterized by high resolution scanning electron microscopy, thermogravimetric analysis, X-ray diffraction, nitrogen adsorption measurements (BET method), X-ray photoelectron spectroscopy and diffuse reflectance spectroscopy. Each semiconductor, coupled with Pt co-catalyst, was tested for hydrogen gas production from aqueous triethanolamine as model sacrificial agent, under simulated solar light. The hydrogen evolution profiles turned out to be strictly dependent on precursor type and synthesis temperature, with the highest evolution rate observed for the samples series produced from urea (up to ca. 4400 µmol g-1 h-1). The results, corroborated by the excellent inter-day precision of irradiation tests (RSD < 5%, n = 3) together with the good batch-to-batch reproducibility (RSD < 11%, n = 3), were critically discussed. Apart from the appealing production values obtained using the as-prepared materials, it was importantly pointed out that, besides crystallinity and visible light absorption, the photocatalytic behavior is definitely correlated to the surface area, which is dependent on the synthesis conditions, that is polymerization temperature and nature of g-C3N4 precursor. Overall, this systematic investigation demonstrated that, contrary to the polymerization degree (sp2/sp3 carbon ratio), surface area is the real determinant parameter for g-C3N4 hydrogen evolution activity.

Hybridized C-O-Si Interface States at the Origin of Efficiency Improvement in CNT/Si Solar Cells.

Despite the astonishing values of the power conversion efficiency reached, in just less than a decade, by the carbon nanotube/silicon (CNT/Si) solar cells, many doubts remain on the underlying transport mechanisms across the CNT/Si heterojunction. Here, by combining transient optical spectroscopy in the femtosecond timescale, X-ray photoemission, and a systematic tracking of I-V curves across all phases of the interlayer SiOx growth at the interface, we grasp the mechanism that adequately preserves charge separation at the junction, hindering the photoexcited carrier recombination. Moreover, supported by ab initio calculations aimed to model the complex CNT-Si heterointerface, we show that oxygen-related states at the interface act as entrapping centers for the photoexcited electrons, thus preventing recombination with holes that can flow from Si to CNT across the SiOx layer.

Growth of hybrid carbon nanostructures on iron-decorated ZnO nanorods.

A novel carbon-based nanostructured material, which includes carbon nanotubes (CNTs), porous carbon, nanostructured ZnO and Fe nanoparticles, has been synthetized using catalytic chemical vapour deposition (CVD) of acetylene on vertically aligned ZnO nanorods (NRs). The deposition of Fe before the CVD process induces the presence of dense CNTs in addition to the variety of nanostructures already observed on the process done on the bare NRs, which range from amorphous graphitic carbon up to nanostructured dendritic carbon films, where the NRs are partially or completely etched. The combination of scanning electron microscopy and in situ photoemission spectroscopy indicate that Fe enhances the ZnO etching, and that the CNT synthesis is favoured by the reduced Fe mobility due to the strong interaction between Fe and the NRs, and to the presence of many defects, formed during the CVD process. Our results demonstrate that the resulting new hybrid shows a higher sensitivity to ammonia gas at ambient conditions (∼60 ppb) than the carbon nanostructures obtained without the aid of Fe, the bare ZnO NRs, or other one-dimensional carbon nanostructures, making this system of potential interest for environmental ammonia monitoring. Finally, in view of the possible application in nanoscale optoelectronics, the photoexcited carrier behaviour in these hybrid systems has been characterized by time-resolved reflectivity measurements.

Correlation between Deposition Parameters and Hydrogen Production in CuO Nanostructured Thin Films.

In this article, we report a systematic investigation of the role of (i) substrate temperature, (ii) oxygen partial pressure, and (iii) radio frequency (rf) power on the crystal structure and morphology of CuO nanostructured thin films prepared by means of rf-magnetron sputtering starting from a Cu metal target. On selected films, photocatalytic tests have been carried out in order to correlate the structural and morphological properties of the thin films prepared under different conditions with the photocatalytic properties and to find out the key parameters to optimize the CuO nanostructured films. All of the synthesized films were single-phase CuO nanorods of variable diameter between 80 and 200 nm. Better-aligned rods were obtained at relatively low substrate temperatures and from low to intermediate oxygen partial pressures, resulting in more efficient photocatalytic activities. Our investigation suggests a relevant role of the crystallographic orientation of the CuO tenorite film on the photocatalytic activity, as demonstrated by the significant improvement in H2 evolution for highly oriented films.