1,720,984 research outputs found
DEVELOPMENT OF NANOSTRUCTURED CARBON-BASED PLATFORMS FOR ADVANCED GAS SENSING
No full textTra le applicazioni all'avanguardia di materiali a base di carbonio nanostrutturato, come grafene e nanotubi di carbonio (CNTs), l'analisi del respiro (i.e. breathomics), il monitoraggio ambientale e l'industria alimentare stanno oggigiorno sfidando la fisica, la chimica e l’ingegneria dei materiali a sviluppare piattaforme di sensori estremamente sensibili, affidabili e stabili, che siano in grado di rilevare piccolissime quantità (ordine dei ppb) di molecole di gas nell’ambiente che le circonda. In questa tesi, verrà presentato lo sviluppo di 6 piattaforme di sensori di gas. Queste piattaforme saranno sviluppate con carbonio nanostrutturato e avranno come scopo principale quello di discriminare potenziali patologie attraverso il riconoscimento di pattern molecolari presenti nel respiro esalato, nonché la loro possibile applicazione nel monitoraggio ambientale degli inquinanti e nell’industria alimentare.
Questo obbiettivo verrà realizzato sviluppando dapprima piattaforme a base di CNTs su un substrato di plastica o su silicio/ossido di silicio e successivamente a base di grafene su nitruro di silicio.
Verranno esplorati diversi metodi di funzionalizzazione sia per i CNTs che per il grafene, per aumentarne la sensitività, e verranno utilizzati diversi materiali per la funzionalizzazione, incluse nanoparticelle, molecole organiche o sali di diazonio.
Tecniche di spettroscopie Raman ed elettroniche unitamente a microscopia a forza atomica verranno utilizzare per caratterizzare i campioni, mentre le esposizioni di gas verranno effettuate in aria, condizione più simile a quella delle applicazioni finali dei sensori, cercando di indagare concentrazioni dei gas selezionati nel sub-ppm o di poche decine di ppm. L’analisi delle componenti principali (PCA) verrà utilizzata per testare le capacità di discriminazione dei gas delle piattaforme sviluppate.
Infine, uno dei nasi elettronici sviluppati verrà testato con il respiro esalato di soggetti sani o affetti da broncopneumopatie cronico ostruttive (COPD), dimostrando un’ottima capacità di discriminare e riconoscere le due classi di pazienti.Among forefront applications of nanostructured carbon materials such as graphene and nanotubes, breathomics, environmental monitoring and food industry are challenging physics, chemistry and device engineering to develop extremely sensitive, selective, and stable platform to recognize ppb amount of target molecules in the environment.
In this thesis, the development of 6 platforms will be presented. The platforms are based on nanostructured carbon aimed mostly to discriminate potential pathologies through pattern recognition in molecular fingerprint of breath samples, but also for environmental monitoring or food industry applications. This objective will be realized through properly developed devices based first on CNTs on a plastic substrate or on silicon/silicon oxide substrate and then on graphene on silicon nitride. Different kinds of functionalization techniques of graphene and CNTs will be explored to enhance the sensitivity of the pristine layers, as well as different functionalization materials, going from nanoparticles to organic molecules or diazonium salt precursors.
The characterization of the materials involves electron and Raman spectroscopies, as well as atomic force microscopy, while gas exposures are carried out in the lab environment, which is much closer to the destination of the developed sensors, trying to investigate a low-ppm range or sub-ppm range of the considered gases. The gas discrimination is assessed through principal component analysis (PCA).
Finally, one of the developed devices is exposed to the exhaled breath of healthy subjects or patients affected by chronic obstructive pulmonary diseases (COPD), demonstrating a remarkable capability to discriminate between healthy and sick patients
Physical Virtualization of a GFET for a Versatile, High‐Throughput, and Highly Discriminating Detection of Target Gas Molecules at Room Temperature
Full text linkAn e-nose has been built on a single graphene field effect transistor (GFET), based on a graphene/Si3N4/Si stack of layers. Multichannel data acquisition, enabling to mimic the architecture of a sensor array, was achieved by steering the gate potential, thus yielding a virtual array of 2D chemiresistors on a single sensing layer. This setting allowed for the detection of volatile compounds with a remarkable discrimination capability, boosted by intensive machine learning analysis. Sensing of gas phase NH3 was tested, along with a set of possible interferents, and discrimination of NH3+NO2 mixtures was successfully probed. High throughput in terms of sensitivity was achieved by tracking the shift of the minimum of the GFET transfer curve vs. NH3 concentration. With this readout scheme, a 20-fold sensitivity increase over a 5-50 ppm range was registered with respect to the same layer used as a chemiresistor. High discrimination capability was probed by leveraging on machine learning algorithms, from PCA to u-MAP and, finally, to a deep NN where input neurons are the virtual sensors created by the gate voltage driving. For the tested case, the DNN maximum accuracy was achieved with 21 virtual sensors
Machine‐Learning‐Aided NO2 Discrimination with an Array of Graphene Chemiresistors Covalently Functionalized by Diazonium Chemistry
No full textBoosted 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 %
Disclosing Fast Detection Opportunities with Nanostructured Chemiresistor Gas Sensors Based on Metal Oxides, Carbon, and Transition Metal Dichalcogenides
Full text linkWith 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
, H2
S, 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
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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