Conductive inks of graphitic nanoparticles from a sustainable carbon feedstock

Microwave plasma splitting of biogas to solid carbon forms is a promising technique to produce large quantities of sustainable carbon based nano materials. Well defined graphitic nano carbons have been produced exhibiting graphene multilayers in turbostratic packing. After heat treatment, the purified material has been used to formulate stable, aqueous dispersions. These dispersions are used directly as inks, allowing the preparation of conductive membranes with remarkable resistivity. Nano carbons derived by plasma processes constitute a promising alternative to carbon black because they can be prepared from renewable sources of methane or natural gas, are calibrated in size, exhibit high conductivity, and have promising perspectives for chemical and material science purposes

Mediterranean raisins/currants as traditional superfoods: processing, health benefits, food applications and future trends within the bio-economy era

This review elaborates on the significance of Mediterranean raisins, focusing particularly on indigenous Greek varieties (e.g., Zante currants) as a previously overlooked traditional food, currently brought on the spotlight, resulting from the increased consumers’ awareness to improve wellness through diet modification. Recent studies on the effect of processing steps on final quality, along with findings on the potential health benefits raisins and currants elicit, are also presented. The development of novel functional food products to further exploit the nutritional value and the bioactive compounds of raisins is evidenced in view of indicating potential food industry applications. Moreover, valorization options of waste and by-product streams obtained from processing facilities are also proposed. Conclusively, raisins and currants should be further enhanced and incorporated in a balanced diet regime through the inclusion in novel foods formulation. Evidently, both the processing of the onset material and side-streams management, are essential to ensure sustainability. Hence, the article also highlights integrated biorefinery approaches, targeting the production of high-value added products that could be re-introduced in the food supply chain and conform with the pillars of bio-economy

Nanocarbon from food waste : dispersions and applications

Cette thèse se concentre sur la caractérisation, la dispersion, ainsi que les différentes applications d'un nouveau type de matériaux dérivé de la dégradation de biométhane dans le cadre d'un projet Européen, le projet PlasCarb. Nous appelons ces matériaux les nanopalets de carbone (CNP). Notre étude commence avec la caractérisation des CNP, puis nous poursuivons avec l'obtention de dispersions aqueuses bien définies et hautement concentrées de CNP. Ces dispersions ont été utilisées pour la préparation de films conducteurs et de composites conducteurs avec du caoutchouc naturel. Enfin, la photoluminescence des CNP dispersés et solubilisés dans un milieu liquide a été évaluée. Des tests préliminaires montrent une photoluminescence dans le bleu très prometteuse.This PhD thesis is focused on the characterization, dispersion and applications of graphitic material (in this manuscript referred as carbon nanopuck (CNP)) that derives from the splitting of biogas and obtained within the framework of the European project “PlasCarb”. This study starts with CNP characterization. Afterwards, well-defined, high concentrated CNP dispersions in water, calibrated insize have been obtained. These dispersions have been used to prepare conductive films and as components of conductive composites with natural rubber. Ultimately, the photoluminescence of CNP dispersed and dissolved in liquid media has been tested. Preliminary tests of these systems exhibit promising blue PL

Nanocarbone à partir de déchets alimentaires : dispersions et applications

This PhD thesis is focused on the characterization, dispersion and applications of graphitic material (in this manuscript referred as carbon nanopuck (CNP)) that derives from the splitting of biogas and obtained within the framework of the European project “PlasCarb”. This study starts with CNP characterization. Afterwards, well-defined, high concentrated CNP dispersions in water, calibrated insize have been obtained. These dispersions have been used to prepare conductive films and as components of conductive composites with natural rubber. Ultimately, the photoluminescence of CNP dispersed and dissolved in liquid media has been tested. Preliminary tests of these systems exhibit promising blue PL.Cette thèse se concentre sur la caractérisation, la dispersion, ainsi que les différentes applications d'un nouveau type de matériaux dérivé de la dégradation de biométhane dans le cadre d'un projet Européen, le projet PlasCarb. Nous appelons ces matériaux les nanopalets de carbone (CNP). Notre étude commence avec la caractérisation des CNP, puis nous poursuivons avec l'obtention de dispersions aqueuses bien définies et hautement concentrées de CNP. Ces dispersions ont été utilisées pour la préparation de films conducteurs et de composites conducteurs avec du caoutchouc naturel. Enfin, la photoluminescence des CNP dispersés et solubilisés dans un milieu liquide a été évaluée. Des tests préliminaires montrent une photoluminescence dans le bleu très prometteuse

Nanocarbon from food waste : dispersions and applications

Cette thèse se concentre sur la caractérisation, la dispersion, ainsi que les différentes applications d'un nouveau type de matériaux dérivé de la dégradation de biométhane dans le cadre d'un projet Européen, le projet PlasCarb. Nous appelons ces matériaux les nanopalets de carbone (CNP). Notre étude commence avec la caractérisation des CNP, puis nous poursuivons avec l'obtention de dispersions aqueuses bien définies et hautement concentrées de CNP. Ces dispersions ont été utilisées pour la préparation de films conducteurs et de composites conducteurs avec du caoutchouc naturel. Enfin, la photoluminescence des CNP dispersés et solubilisés dans un milieu liquide a été évaluée. Des tests préliminaires montrent une photoluminescence dans le bleu très prometteuse.This PhD thesis is focused on the characterization, dispersion and applications of graphitic material (in this manuscript referred as carbon nanopuck (CNP)) that derives from the splitting of biogas and obtained within the framework of the European project “PlasCarb”. This study starts with CNP characterization. Afterwards, well-defined, high concentrated CNP dispersions in water, calibrated insize have been obtained. These dispersions have been used to prepare conductive films and as components of conductive composites with natural rubber. Ultimately, the photoluminescence of CNP dispersed and dissolved in liquid media has been tested. Preliminary tests of these systems exhibit promising blue PL

Γεωμετρική προσέγγιση κατανεμημένης κατηγοριοποίησης με χρήση μηχανών υποστηρικτικών διανυσμάτων

Summarization: We live in the information age, and with every passing year, our environment becomes more and more heavily defined by data, leading to a major need for better decision-making models. The breakthroughs in data analytics have already seen through machine learning. Support vector machines (SVM) are a popular, adaptive, multipurpose machine learning algorithm with the ability to capture complex relationships between data points without having to perform difficult transformations. We study the problem of prohibitive communication costs that a centralized architecture implies if most of the data is generated or received on different remote machines. The past few years notable efforts have been made to achieve parallelism on the training procedure of machine learning models. We propose the use of Functional Geometric Monitoring (FGM) communication protocol which is used to monitor high-volume, rapid distributed streams to decrease the communication cost on a distributed SVM architecture. Our main goal is both to achieve centralized-like prediction loss and to minimize communication costs. In our proposal, the sklearn library, for centralized machine learning, is used in a distributed manner, with the use of Dask library, resulting in a notable speedup for the training procedure.Περίληψη: Ζούμε σε ένα περιβάλλον όπου οι πληροφορίες ρέουν ακατάπαυστα και με το πέρασμα των χρόνων το περιβάλλον μας διέπεται ολοένα και περισσότερο από δεδομένα, δημιουργώντας έτσι την ανάγκη για την κατασκευή καλύτερων μοντέλων για την διαχείριση τους. Η επανάσταση στον τομέα της ανάλυσης δεδομένων έχει ήδη ξεκινήσει με την χρήση machine learning αλγορίθμων. Οι Support Vector Machine (SVM) αλγόριθμοι είναι μια κατηγορία δημοφιλών machine learning αλγορίθμων, με μεγάλη προσαρμοστικότητα και πολλαπλές περιπτώσεις χρήσης καθώς έχουν την ικανότητα να εντοπίζουν πολύπλοκες συσχετίσεις μεταξύ δεδομένων χωρίς υψηλή υπολογιστική πολυπλοκότητα. Σε αυτήν την εργασία μελετήθηκε το πρόβλημα του υψηλού κόστους επικοινωνίας που παρατηρείται στην περίπτωση που τα δεδομένα παράγονται σε απομακρυσμένες πηγές και συλλέγονται σε μια μόνο δομή για την επεξεργασία τους. Τα τελευταία χρόνια έχουν γίνει αξιόλογες προσπάθειες ώστε να επιτευχθεί παραλληλισμός στην διαδικασία εκπαίδευσης machine learning αλγορίθμων ώστε να αποφευχθεί η συγκέντρωση όλων των δεδομένων σε μια κεντρική δομή. Η εργασία αυτή προτείνει σαν ενδεχόμενη λύση την χρήση του Functional Geometric Monitoring (FGM) πρωτοκόλλου επικοινωνίας, που χρησιμοποιείται για την παρακολούθηση μεγάλου όγκου δεδομένων σε κατανεμημένο σύστημα, ώστε να μειωθεί το κόστος επικοινωνίας. Βασικός στόχος είναι να επιτύχουμε σφάλμα πρόβλεψης αντίστοιχο αυτού ενός κεντρικοποιημένου SVM αλγορίθμου αλλά σε κατανεμημένο σύστημα με ελαχιστοποιημένη επικοινωνία μεταξύ κόμβων. Ταυτόχρονα αποδείχθηκε ότι η sklearn βιβλιοθήκη της python που χρησιμοποιείται για κεντρικοποιημένη υλοποίηση machine learning αλγορίθμου μπορεί να αποδώσει εξίσου καλά σε μια κατανεμημένη δομή με χρήση της βιβλιοθήκης Dask και να επιτευχθεί σημαντική επιτάχυνση στην διαδικασία εκπαίδευσης του αλγορίθμου

A Study on the Clustering of Extra Virgin Olive Oils Extracted from Cultivars Growing in Four Ionian Islands (Greece) by Multivariate Analysis of Their Phenolic Profile, Antioxidant Activity and Genetic Markers

Background: The phenolic fraction of extra virgin olive oil (EVOO) has disease preventive and health-promoting properties which are supported by numerous studies. As such, EVOO is defined as a functional food. The aim of the present study was to characterize the phenolic profile of olive oil from cultivars farmed in the Ionian Islands (Zakynthos, Kefalonia, Lefkada, and Kerkyra) and to investigate the association of phenols to antioxidant activity, which is central to its functionality. Furthermore, the study investigates whether multivariate analyses on the concentration of individual biophenolic compounds and genetic population diversity could classify the olive oil samples based on their geographic origin. Methods: Phenols were determined in 103 samples from different Ionian Island tree populations by 1H nuclear magnetic resonance (NMR), and sample antioxidant activity was measured by their capacity to reduce the free radical 2,2-diphenyl-1-picrylhydrazyl) (DPPH). Genetic diversity was measured by estimating Nei’s population genetic distance using 15 reproducible bands from random amplified polymorphic DNA (RAPD) genotyping. Results: Principal component analysis (PCA) of the secoiridoid concentrations clustered samples according to cultivar. Clustering based on genetic distances is not concordant with phenolic clustering. A cultivar effect was also demonstrated in the association between the concentration of individual phenols with DPPH reducing activity. Conclusions: Taken together, the study shows that the olive oil phenolic content defines “cultivar-specific phenolic profiles” and that environmental factors other than agronomic conditions contribute more to phenotype variance than genetics

A study on the clustering of extra virgin olive oils extracted from cultivars growing in four ionian islands (Greece) by multivariate analysis of their phenolic profile, antioxidant activity and genetic markers

Background: The phenolic fraction of extra virgin olive oil (EVOO) has disease preventive and health-promoting properties which are supported by numerous studies. As such, EVOO is defined as a functional food. The aim of the present study was to characterize the phenolic profile of olive oil from cultivars farmed in the Ionian Islands (Zakynthos, Kefalonia, Lefkada, and Kerkyra) and to investigate the association of phenols to antioxidant activity, which is central to its functionality. Furthermore, the study investigates whether multivariate analyses on the concentration of individual biophenolic compounds and genetic population diversity could classify the olive oil samples based on their geographic origin. Methods: Phenols were determined in 103 samples from different Ionian Island tree populations by1H nuclear magnetic resonance (NMR), and sample antioxidant activity was measured by their capacity to reduce the free radical 2,2-diphenyl-1-picrylhydrazyl) (DPPH). Genetic diversity was measured by estimating Nei’s population genetic distance using 15 reproducible bands from random amplified polymorphic DNA (RAPD) genotyping. Results: Principal component analysis (PCA) of the secoiridoid concentrations clustered samples according to cultivar. Clustering based on genetic distances is not concordant with phenolic clustering. A cultivar effect was also demonstrated in the association between the concentration of individual phenols with DPPH reducing activity. Conclusions: Taken together, the study shows that the olive oil phenolic content defines “cultivar-specific phenolic profiles” and that environmental factors other than agronomic conditions contribute more to phenotype variance than genetics. © 2021 by the authors. Licensee MDPI, Basel, Switzerland