56 research outputs found

    Halloysite Nanotubes Noncovalently Functionalised with SDS Anionic Surfactant and PS-b-P4VP Block Copolymer for Their Effective Dispersion in Polystyrene as UV-Blocking Nanocomposite Films

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    A simple and versatile method is reported for the noncovalent functionalisation of natural and “green” halloysite nanotubes (HNTs) allowing their effective dispersion in a polystyrene (PS) thermoplastic matrix via solvent mixing. Initially, HNTs (pristine HNTs) were modified with physically adsorbed surfactant molecules of sodium dodecyl sulphate (SDS) and PS-b-P4VP [P4VP: poly(4-vinylpyridine)] block copolymer (BCP). Hereafter, SDS and BCP modified HNTs will be indicated as SDS-m-HNT and BCP-m-HNT. Nanocomposite films with 1, 2, and 5 wt.% HNT loadings were prepared, abbreviated as PS-SDS-m-HNT1, PS-SDS-m-HNT2, and PS-SDS-m-HNT5 and PS-BCP-m-HNT1, PS-BCP-m-HNT2, and PS-BCP-m-HNT5 (where 1, 2, and 5 correspond to the wt.% of HNTs). All nanocomposites depicted improved thermal degradation compared to the neat PS as revealed by thermogravimetric analysis (TGA). Transmission electron microscopy (TEM) confirmed the good dispersion state of HNTs and the importance of modification by SDS and BCP. X-ray diffraction (XRD) studies showed the characteristic interlayer spacing between the two silicate layers of pristine and modified HNTs. The PS/HNT nanocomposite films exhibited excellent ultraviolent-visible (UV-vis) absorbance properties and their potential application as UV-filters could be envisaged

    Theoretical Investigation of the Deactivation of Ni Supported Catalysts for the Catalytic Deoxygenation of Palm Oil for Green Diesel Production

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    For the first time, a fully comprehensive heterogeneous computational fluid dynamic (CFD) model has been developed to predict the selective catalytic deoxygenation of palm oil to produce green diesel over an Ni/ZrO2 catalyst. The modelling results were compared to experimental data, and a very good validation was obtained. It was found that for the Ni/ZrO2 catalyst, the paraffin conversion increased with temperature, reaching a maximum value (>95%) at 300 °C. However, temperatures greater than 300 °C resulted in a loss of conversion due to the fact of catalyst deactivation. In addition, at longer times, the model predicted that the catalyst activity would decline faster at temperatures higher than 250 °C. The CFD model was able to predict this deactivation by relating the catalytic activity with the reaction temperature

    Ni Catalysts Based on Attapulgite for Hydrogen Production through the Glycerol Steam Reforming Reaction

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    Attapulgite (ATP, a natural clay) was used as carrier to produce a nickel-based catalyst (Ni/ATP) for the work that is presented herein. Its catalytic performance was comparatively assessed with a standard Ni/Al2O3 sample for the glycerol steam reforming (GSR) reaction. It was shown that the ATP support led to lower mean Ni crystallite size, i.e., it increased the dispersion of the active phase, to the easier reduction of NiO and also increased the basicity of the catalytic material. It was also shown that it had a significant effect on the distribution of the gaseous products. Specifically, for the Ni/ATP catalyst, the production of liquid effluents was minimal and subsequently, conversion of glycerol into gaseous products was higher. Importantly, the Ni/ATP favored the conversion into H2 and CO2 to the detriment of CO and CH4. The stability experiments, which were undertaken at a low WGFR, showed that the activity of both catalysts was affected with time as a result of carbon deposition and/or metal particle sintering. An examination of the spent catalysts revealed that the coke deposits consisted of filamentous carbon, a type that is known to encapsulate the active phase with fatal consequences

    Biogas dry reforming over Ni/LnOx-type catalysts (Ln = La, Ce, Sm or Pr)

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    Ni/LnOx-type catalysts (Ln = La, Ce, Sm or Pr, denoted as LNO, CNO, SNO and PNO, respectively) were prepared via a citrate sol-gel method, characterized, and evaluated for the dry reforming of biogas. For the calcined catalysts, the formation of LaNiO3 perovskite crystallites with high purity was observed in the case of La, whereas NiO-LnOx mixed oxides were obtained for the other lanthanides. The reduction treatment led to the formation of medium-sized (∼15 nm) and highly dispersed Ni nanoparticles in LNO following the decomposition of the LaNiO3 perovskite, in contrast to the other catalysts, where bigger Ni crystallites were formed (∼30 nm). As a result, LNO was shown to possess a higher catalytic activity in comparison to the other materials. Regarding the catalytic stability, LNO displayed a considerable activity loss followed by a high pressure drop due to reactor blockage, meaning that the use of Sm (Ni/Sm2O3) can be considered as an alternative strategy to restrict catalyst deactivation. As evidenced by the characterization of the spent catalysts, the deactivation for the most part can be attributed to the extensive coke deposition over the catalysts. The coke deposited was found to be both in the form of more disordered/amorphous carbon, as well as in the form of highly crystalline and multi-walled carbon nanotubes.The authors gratefully acknowledge the Ministry of Science and Technology (MOST) of the People's Republic of China providing funds through the National Key Research and Development Program (project code:2017YFE013330). The authors also gratefully acknowledge that this research has been co-financed by the European Union and Greek national funds under the call “Greece – China Call for Proposals for Joint RT&D Projects” (Project code: T7DKI-00388). V.S. acknowledges the assistance of the Laboratorio de Microscopias Avanzadas-LMA-ICTS ELECMI, Universidad de Zaragoza, Spain. CIBER-BBN is an initiative funded by the VI National R&D&i Plan 2008–2011 financed by the Instituto de Salud Carlos III with the assistance of the European Regional Development Fund.Peer reviewe

    Ni-noble metal bimetallic catalysts for improved low temperature CO2 methanation

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    Bimetallic nickel-noble metal catalysts with a low noble metal loading (1 wt% of Ru, Pt, Rh, Pd, or Ir) supported on Pr-doped CeO2 were comparatively evaluated regarding their CO2 methanation catalytic performance. Ru was the sole noble metal phase that could dramatically promote the catalytic activity of the corresponding monometallic catalyst, whereas the incorporation of the other noble metals either retained (Pt and Ir) or worsened (Rh and Pd) the catalytic performance. The best–performing RuNi bimetallic catalyst maintained around 80 % CO2 conversion and 99.5 % CH4 selectivity at 325 °C during 50 h of operation. Ru was found to be well dispersed along the support (as single atoms or small clusters), while a small part of it was also dispersed atop the medium-sized Ni nanoparticles. Its promoting ability was attributed to the improved metal dispersion, catalyst reducibility, moderate basicity and provision of additional active sites for CO2 and H2 dissociation, while DFT analysis evidenced that a Ru single atom atop a Ni cluster/ small particle is the structure that is most favorable towards the initial CO2 adsorption and dissociation.NDC and MAG acknowledge support of this work by the project “Development of new innovative low carbon energy technologies to improve excellence in the Region of Western Macedonia” (MIS 5047197), which is implemented under the Action “Reinforcement of the Research and Innovation Infrastructure” funded by the Operational Program “Competitiveness, Entrepreneurship and Innovation” (NSRF 2014–2020) and co-financed by Greece and the European Union (European Regional Development Fund). AIT thanks the Hellenic Foundation for Research and Innovation (HFRI) for supporting this research work under the 3rd Call for HFRI PhD Fellowships (Fellowship Number: 6033). VS acknowledges the support of ELECMI-LMA and Nanbiosis ICTSs. KP and NS acknowledge the financial support from Khalifa University through the RC2-2018-024 and the computational resources and support from high performance computing facility Almesbar at Khalifa University of Science and Technology.Peer reviewe

    Selective catalytic deoxygenation of palm oil to produce green diesel over Ni catalysts supported on ZrO2 and CeO2–ZrO2: Experimental and process simulation modelling studies

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    The selective deoxygenation of palm oil to produce green diesel has been investigated over Ni catalysts supported on ZrO2 (Ni/Zr) and CeO2–ZrO2 (Ni/CeZr) supports. The modification of the support with CeO2 acted to improve the Ni dispersion and oxygen lability of the catalyst, while reducing the overall surface acidity. The Ni/CeZr catalyst exhibited higher triglyceride (TG) conversion and yield for the desirable C15–C18 hydrocarbons, as well as improved stability compared to the unmodified Ni/Zr catalyst, with TG conversion and C15–C18 yield remaining above 85% and 80% respectively during 20 h of continuous operation at 300 oC. The high C17 yields also revealed the dominance of the deCOx (decarbonylation/decarboxylation) pathway. A fully comprehensive process simulation model has been developed to validate the experimental findings in this study, and a very good validation with the experimental data has been demonstrated. The model was then further utilised to investigate the effects of temperature, H2 partial pressure, H2/oil feed ratio and LHSV. The model predicted that maximum triglyceride conversion was attainable at reaction conditions of 300 °C temperature, 30 bar H2 partial pressure, H2/oil of 1000 cm3/cm3 feed ratio and 1.2 h−1 LHSV.MAG and NDC gratefully acknowledge that this researched was co-financed by Greece and the European Union (European Social Fund-ESF) through the Operational Programme “Human Resources Development, Education and Lifelong Learning” (MIS-5050170). KP and SA acknowledge the financial support from the Abu Dhabi Department of Education and Knowledge through the grant AARE-2019-233 and the support from Khalifa University through the grant RC2-2018-024. VS acknowledges the ICTS ELECMI-LMA for offering access to their instruments and expertise.Peer reviewe

    Optimizing the oxide support composition in Pr-doped CeO2 towards highly active and selective Ni-based CO2 methanation catalysts

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    In this study, Ni catalysts supported on Pr-doped CeO2 are studied for the CO2 methanation reaction and the effect of Pr doping on the physicochemical properties and the catalytic performance is thoroughly evaluated. It is shown, that Pr3+ ions can substitute Ce4+ ones in the support lattice, thereby introducing a high population of oxygen vacancies, which act as active sites for CO2 chemisorption. Pr doping can also act to reduce the crystallite size of metallic Ni, thus promoting the active metal dispersion. Catalytic performance evaluation evidences the promoting effect of low Pr loadings (5 at% and 10 at%) towards a higher catalytic activity and lower CO2 activation energy. On the other hand, higher Pr contents negate the positive effects on the catalytic activity by decreasing the oxygen vacancy population, thereby creating a volcano-type trend towards an optimum amount of aliovalent substitution.AIΤ, NDC and MAG acknowledge support of this work by the project “Development of new innovative low carbon energy technologies to improve excellence in the Region of Western Macedonia” (MIS 5047197) which is implemented under the Action “Reinforcement of the Research and Innovation Infrastructure”, funded by the Operational Program “Competitiveness, Entrepreneurship and Innovation” (NSRF 2014-2020) and co-financed by Greece and the European Union (European Regional Development Fund).Peer reviewe

    Nickel Supported on AlCeO3 as a Highly Selective and Stable Catalyst for Hydrogen Production via the Glycerol Steam Reforming Reaction

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    In this study, a critical comparison between two low metal (Ni) loading catalysts is presented, namely Ni/Al2O3 and Ni/AlCeO3 for the glycerol steam reforming (GSR) reaction. The surface and bulk properties of the catalysts were evaluated using a plethora of techniques, such as N2 adsorption/desorption, Inductively Coupled Plasma Atomic Emission Spectroscopy (ICP–AES), X-ray Diffraction (XRD), X-ray Photoelectron Spectroscopy (XPS), Scanning Electron Microscopy / Energy Dispersive X-Ray Spectroscopy (SEM/EDX, Transmission Electron Microscopy (TEM), CO2 and NH3– Temperature Programmed Desorption (TPD), and Temperature Programmed Reduction (H2–TPR). Carbon deposited on the catalyst’s surfaces was probed using Temperature Programmed Oxidation (TPO), SEM, and TEM. It is demonstrated that Ce-modification of Al2O3 induces an increase of the surface basicity and Ni dispersion. These features lead to a higher conversion of glycerol to gaseous products (60% to 80%), particularly H2 and CO2, enhancement of WGS reaction, and a higher resistance to coke deposition. Allyl alcohol was found to be the main liquid product for the Ni/AlCeO3 catalyst, the production of which ceases over 700 °C. It is also highly significant that the Ni/AlCeO3 catalyst demonstrated stable values for H2 yield (2.9–2.3) and selectivity (89–81%), in addition to CO2 (75–67%) and CO (23–29%) selectivity during a (20 h) long time-on-stream study. Following the reaction, SEM/EDX and TEM analysis showed heavy coke deposition over the Ni/Al2O3 catalyst, whereas for the Ni/AlCeO3 catalyst TPO studies showed the formation of more defective coke, the latter being more easily oxidized

    Fault detection of air quality measurements using artificial intelligence

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    In this work we use Artificial Intelligence (AI) for the detection of faults in air quality measurements. This is crucial in large air quality monitoring networks in particular were fault detection can be a complex and time consuming process. The proposed methodology encompasses several essential steps in anomaly detection. Data preprocessing ensures the quality and relevance of the data by applying techniques like data cleaning, outlier removal, and feature selection. The Isolation Forest model is trained using the pre-processed data, and appropriate hyperparameters are determined through cross-validation. Anomaly detection is performed using the trained model, allowing the identification of abnormal events or instances. The visualization of anomalies provides a clear representation of abnormal patterns, facilitating the interpretation and understanding of air quality data. The proposed methodology can help environmental agencies, researchers, and policymakers in identifying abnormal air quality events, enhancing the accuracy of monitoring systems, and facilitating timely interventions. This methodology can be applied to other industries also, to improve operations and reduce risk
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