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Polymer Based Catalytic Systems for Different Organic Reactions

Thesis Info

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Author

Begum, Robina

Program

PhD

Institute

University of the Punjab

City

Lahore

Province

Punjab

Country

Pakistan

Thesis Completing Year

2019

Thesis Completion Status

Completed

Subject

Chemistry

Language

English

Link

http://prr.hec.gov.pk/jspui/bitstream/123456789/12822/1/Robina%20Begum.pdf

Added

2021-02-17 19:49:13

Modified

2024-03-24 20:25:49

ARI ID

1676726962600

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Acrylamide based nearly mono-disperse polymer microgels including poly(N-isopropylacrylamide-co-acrylamide) and Poly(N-isopropylacrylamide-acrylic acid-acrylamide) with different feed compositions were synthesized using precipitation polymerization in aqueous medium. These microgels were used as micro-reactors to fabricate silver nanoparticles by chemical reduction of silver ions inside the polymer network. The pure and hybrid microgels were characterized by using Fourier transform infra-red spectroscopy (FTIR), UV Visible spectroscopy (UV Vis), Dynamic light scattering (DLS), X-ray diffraction (XRD), Thermogravimetric analysis (TGA), Differential scanning calorimetry (DSC), Scanning electron microscopy (SEM), Energy Dispersive X-ray (EDX),Transmission electron microscopy (TEM) and Scanning transmission electron microscopy (STEM). Ag contents in the hybrid system were determined by ICP-OES. Results revealed that spherical silver nanoparticles having diameter of 10-20 nm were successfully fabricated within the microgels with hydrodynamic diameter of 250±50 nm. The uniformly loaded silver nanoparticles were found to be stable for long time due to donor-acceptor interaction between amide groups of polymer network and silver nanoparticles. Catalytic activity of the hybrid systems was initially tested by choosing catalytic reduction of 4-nitrophenol as a model reaction under various conditions of catalyst dose and concentration of NaBH4 at room temperature in aqueous medium to explore the insights of catalysis process. The progress of the reaction was monitored by UV Visible Spectrophotometry. The pseudo first order kinetic model was employed to evaluate the apparent rate constant of the reaction. It was found that the value of apparent constant increases with increase of catalyst dose due to increase of surface area as a result of increase of number of nanoparticles. The Ag- poly(N-isopropylacrylamide-co-acrylamide) hybrid microgels were found to be temperature sensitive and Ag-Poly(N-isopropylacrylamide-acrylic acid-acrylamide) hybrid microgels both temperature and pH sensitive in aqueous medium. Ag-Poly(N-isopropylacrylamide-acrylic acid-acrylamide) hybrid microgels have long term stability under various conditions of pH of the medium. The hybrid microgels were used as catalysts for simultaneous reduction of various nitro compounds in aqueous medium. Nitroarenes like o-nitroaniline (o-NA), p-nitroaniline (p-NA), p-nitrophenol (p-NP) and nitrobenzene (NB) were individually and simultaneously reduced to corresponding amino-aromatic compounds by sodium borohydride in the presence of Ag-Poly(N-isopropylacrylamide-acrylic acid-acrylamide) hybrid microgels catalyst. Catalytic activity of the hybrid microgels for individual and simultaneous reduction of nitroarenes was compared with each other. The retardation in catalytic reduction of each nitroarene in the presence of other nitroarenes was explained on the basis of simultaneous adsorption. Various factors affecting the catalytic reduction of p-nitroaniline (p-NA) like catalyst dose and pH of the medium were also investigated. Rate of reduction of p-nitroaniline was found to be increased with increase of catalyst dose and pH of the medium. Various nitroarenes were successfully converted into their respective aromatic amines with good to excellent yields (ranging from 75% to 97%) under mild reaction conditions in the presence of Ag-Poly(N-isopropylacrylamide-acrylic acid-acrylamide) and Pd-Poly(N-isopropylacrylamide-acrylic acid-acrylamide) hybrid microgels. The catalyst has ability to successfully convert substituted nitroarenes into desired products keeping many functionalities intact. Pd-Poly(N-isopropylacrylamide-acrylic acid-acrylamide) hybrid microgels were also found to active for a variety of Suzuki coupling reaction. The catalyst can be stored for long time without any sign of aggregation and can be used multiple times without any significant loss in its catalytic activity.
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جب تُو مجھ کو چھوڑگیا تھا
پتّے سارے سوکھ گئے تھے
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التفكير الاستراتيجي وعلاقته بالاداء الوظيفي في وزارة التربية والتعليم الفلسطينية

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Enhancing Qos in 5G Networks Using Self Optimization of Radio Resource Management Parameters

Enhancing QoS in 5G networks using Self Optimization of Radio Resource Management Parameters The demand for high data rate mobile traffic is increasing tremendously as the world transcends into High Definition (HD) quality applications, video calling, streaming traffic, social media etc. To match these sky-rocketing user demands, increasing traffic and volatile radio environment, mobile networks are continually evolving and becoming more and more sophisticated. While, the trend of mobile networks has been towards an all IP flat network, the network Quality of Service (QoS) metric has shifted from simple voice services to providing high volume data services. The increased network complexity puts a high burden on operation and maintenance costs making the traditional methods obsolete. In this backdrop, the concept of Self Organizing Networks (SONs) was introduced in the 4G mobile network standard by the 3rd Generation Partnership Project (3GPP) to enhance network performance and reduce operational costs. SON is also a significant component in the upcoming 5G mobile standard and thus has received much interest by the research community. SONs behave like an intelligent living organism and adapt to changing environment, resources and traffic loads. Two areas that have a notable impact on network performance are, interference mitigation and coverage adaptation for load balancing and these are the main focus of this PhD research work. We have worked on finding and comparing different self-optimisation techniques based on network Key Performance Indicators (KPIs), to reduce network interference and balance traffic load in the context of SON. In particular, we have applied simple machine learning techniques of Stochastic Cellular Learning Automata (SCLA), simple Q-Learning and Artificial Neural Networks (ANN) QLearning in a fully distributed SON 5G environment with a unique information sharing model among cells, its neighbours and the network. This model is unique in the sense that it depends on a simple distance separation criteria instead of Radio Frequency (RF) environment to identify and define neighbours for information sharing. Interference reduction was done for femtocells, and coverage adaptation for load balancing was done using active antenna tilt model. Test results from network-based simulators based on 3GPP guidelines show that simple SON technique like SCLA adapt quickly, as compared to advance techniques like Q-Learning but are limited in capturing complex network scenarios. The reason being, simple Q-Learning techniques fail to swiftly adjust to changing environment conditions as the number of state variables grow. This is due to increased training time required to build a meaningful Q matrix. ANN showed promising results concerning agility and adaptability to complex changing environments. ANN has the inherent capacity to accept a large number of inputs, reduce the input dimension and adapt to changes as time grows. It is thus concluded, that simple machine learning techniques like SCLA are best suited for enhancing QoS in 5G networks where optimisation input variables are unavailable or unknown like in standalone Femtocell case. However, in scenarios where the numbers of input variable are known and readily available from the network, i.e. cooperative distributed environment, ANN gives better results.