Polyolefins are one of the most widely used commodity polymers with applications in films, packaging and automotive industry. The modeling of polymerization processes producing polyolefins, including high-density polyethylene (HDPE), polypropylene (PP), and linear low-density polyethylene (LLDPE) using Ziegler-Natta catalysts with multiple active sites, is a complex and challenging task. In our study, we integrate process modeling and data analytics for improving and optimizing polyolefin manufacturing processes. Most of the current literature on polyolefin modeling does not consider all of the commercially important production targets when quantifying the relevant polymerization reactions and their kinetic parameters based on measurable plant data. We develop an effective methodology to estimate kinetic parameters that have the most significant impacts on specific production targets, and to develop the kinetics using all commercially important production targets validated over industrial polyolefin processes. We showcase the utility of dynamic models for efficient grade transition in polyolefin processes. We also use the dynamic models for inferential control of polymer processes. Thus, we showcase the methodology for making first-principle polyolefin process models which are scientifically consistent, but tend to be less accurate due to many modeling assumptions in a complex system. Data analytics and machine learning (ML) have been applied in the chemical process industry for accurate predictions for data-based soft sensors and process monitoring/control. Specifically, for polymer processes, they are very useful since the polymer quality measurements like polymer melt index, molecular weight etc. are usually less frequent compared to the continuous process variable measurements. We showcase the use of predictive machine learning models like neural networks for predicting polymer quality indicators and demonstrate the utility of causal models like partial least squares to study the causal effect of the process parameters on the polymer quality variables. ML models produce accurate results can over-fit the data and also produce scientifically inconsistent results beyond the operating data range. Thus, it is growingly important to develop hybrid models combining data-based ML models and first-principle models. We present a broad perspective of hybrid process modeling and optimization combining the scientific knowledge and data analytics in bioprocessing and chemical engineering with a science-guided machine learning (SGML) approach and not just the direct combinations of first-principle and ML models. We present a detailed review of scientific literature relating to the hybrid SGML approach, and propose a systematic classification of hybrid SGML models according to their methodology and objective. We identify the themes and methodologies which have not been explored much in chemical engineering applications, like the use of scientific knowledge to help improve the ML model architecture and learning process for more scientifically consistent solutions. We apply these hybrid SGML techniques to industrial polyolefin processes such as inverse modeling, science guided loss and many others which have not been applied previously to such polymer applications. / Doctor of Philosophy / Almost everything we see around us from furniture, electronics to bottles, cars, etc. are made fully or partially from plastic polymers. The two most popular polymers which comprise almost two-thirds of polymer production globally are polyethylene (PE) and polypropylene (PP), collectively known as polyolefins. Hence, the optimization of polyolefin manufacturing processes with the aid of simulation models is critical and profitable for chemical industry. Modeling of a chemical/polymer process is helpful for process-scale up, product quality estimation/monitoring and new process development. For making a good simulation model, we need to validate the predictions with actual industrial data. Polyolefin process has complex reaction kinetics with multiple parameters that need to be estimated to accurately match the industrial process. We have developed a novel strategy for estimating the kinetics for the model, including the reaction chemistry and the polymer quality information validating with industrial process. Thus, we have developed a science-based model which includes the knowledge of reaction kinetics, thermodynamics, heat and mass balance for the polyolefin process. The science-based model is scientifically consistent, but may not be very accurate due to many model assumptions. Therefore, for applications requiring very high accuracy predicting any polymer quality targets such as melt index (MI), density, data-based techniques might be more appropriate. Recently, we may have heard a lot about artificial intelligence (AI) and machine learning (ML) the basic principle behind these methods is to making the model learn from data for prediction. The process data that are measured in a chemical/polymer plant can be utilized for data analysis. We can build ML models to predict polymer targets like MI as a function of the input process variables. The ML model predictions are very accurate in the process operating range of the dataset on which the model is learned, but outside the prediction range, they may tend to give scientifically inconsistent results. Thus, there is a need to combine the data-based models and scientific models. In our research, we showcase novel approaches to integrate the science-based models and the data-based ML methodology which we term as the hybrid science-guided machine learning methods (SGML). The hybrid SGML methods applied to polyolefin processes yield not only accurate, but scientifically consistent predictions which can be used for polyolefin process optimization for applications like process development and quality monitoring.

Thesis (PhD)--Stellenbosch University, 2012. / ENGLISH ABSTRACT: An instrument, named solution crystallization analysis by laser light scattering (SCALLS), that measures the solution melting and crystallization of polymers in solution was developed further in this study. The instrument was tested in a theoretical study to evaluate the Flory-Huggins relationship of melting point depression in solution of copolymers. It was found that the solvent interaction parameter for propylene/higher 1-alkene copolymers, with low comonomer content is dependent on the comonomer type. It was also showed that the melting point depression is dependent on both the type and amount of comonomer included in the copolymer. The instrument was further developed to include a total of three lasers with different wavelengths. Initial problems with laser interference was rectified by the introduction of dichroic mirrors to direct the laser light to the relevant detectors and broad pass filters in front of the the detectors to ensure that only the relevant laser light passes through. For homogenous polypropylene samples it was found that even though a slower cooling rate increases the relative peak temperatures as well as the relative temperature differences between the peaks, detail in the peak profiles is the same for the faster cooling rate. The subsequent heating analysis does show that there is a definite dependence on the cooling rate. The ZNPP-4 sample shows that the appearance of a shoulder in the heating analysis becomes more defined as a peak if the preceding cooling analysis is slower. Complex impact-polypropylene samples, differing only in the amount of ethylene were analysed and even small differences between samples were detected. The possible application of the SCALLS instrument was investigated. It was proven that the instrument can be used as a screening method for prep-TREF to determine the fractionation temperatures. / AFRIKAANSE OPSOMMING: 'n Instrument, genoem oplossing kristallisasie-analise deur laser lig verstrooiing (SCALLS), wat die smeltpunt asook die kristallisasie temperatuur in oplossing kan meet is verder ontwikkel in hierdie studie. Die Flory-Huggins verhouding oor die smeltpunt depressie in oplossing van ko-polimere is ondersoek in ‘n teoretiese studie. Daar is bevind dat die oplossing interaksie parameter vir propileen/hoër 1-alkeen kopolimere, met lae ko-monomeer inhoud is afhanklik op die ko-monomeer tipe. Dit is ook getoon dat die smeltpunt depressie afhanklik is van beide die tipe en hoeveelheid ko-monomeer in die ko-polimeer. Die instrument is verder ontwikkel om 'n totaal van drie lasers met verskillende golflengtes in te sluit. Aanvanklike probleme met laser inmenging is reggestel deur die bekendstelling van dichromatiese spieëls wat die laser lig na die regte ooreenstemmende detektor rig en filters voor die detektors verseker dat net die relevante laser lig die detektor bereik. Vir homogene polipropileen monsters is dit bevind dat selfs al is die analises gedoen teen ‘n stadiger afkoelings tempo wat lei tot ‘n verhoging in die piek kristallisasie temperatuur asook die relatiewe temperatuur verskille tussen die lasers, bly die detail in die piek profiele dieselfde as wat gesien word met ‘n vinniger afkoelings tempo. Die daaropvolgende verhitting analise toon dat die analise definitief afhanklik is op die voorafgaande afkoelings analise. Die ZNPP-4 monster toon dat die voorkoms van 'n skouer in die verwarming-analise word meer gedefinieerd en ‘n piek word gevorm soos die voorafgaande afkoelings tempo verlaag. Komplekse impak-polipropileen monsters, wat net verskil in die hoeveelheid etileen inhoud is geanaliseer en verskille is bepaal. Moontlike toepassings van die SCALLS instrument is ondersoek. Dit is bewys dat die instrument gebruik kan word om die fraksionering temperature vooraf te bepaal vir prep-TREF.

The microstructure of polyolefins determines their macroscopic properties. Consequently, it is essential to predict how polymerization conditions will affect polyolefin microstructure. The most important microstructural distributions of ethylene/alfa-olefin copolymers made with coordination catalysts are their molecular weight (MWD), chemical composition (CCD), and comonomer sequence length (CSLD). Several mathematical models have been developed to predict these microstructural distributions; reliable techniques to estimate parameters for these models, however, are still poorly developed, especially for catalysts that have multiple site types, such as heterogeneous Ziegler-Natta complexes. Most commercial polyolefins are made with heterogeneous Ziegler-Natta catalysts, which make polyolefins with broad MWD, CCD, and CSLD. This behavior is attributed to the presence of several active site types, leading to a final product that can be seen as a blend of polymers made on the different catalyst site types. The main objective of this project is to develop a methodology to estimate the most important parameters needed to describe the microstructure of ethylene/alfa-olefin copolymers made with these multiple site-type catalysts. To accomplish this objective, we developed the Integrated Deconvolution Estimation Model (IDEM). IDEM estimates ethylene/alf-olefin reactivity ratios for each site type in two-steps. In the first step, the copolymer MWD, measured by high-temperature gel permeation chromatography, is deconvoluted into several Flory’s most probable distributions to determine the number of site types and the weight fractions of copolymer made on each of them. In the second estimation step, the model uses the MWD deconvolution information to fit the copolymer triad distributions measured by 13C NMR and estimate the reactivity ratios per site type. This is the first time that MWD and triad distribution information is integrated to estimate the reactivity ratio per site type of multiple site-type catalysts used to make ethylene/alfa-olefin copolymers. IDEM was applied to two sets of ethylene-co-1-butene copolymers made with a commercial Ziegler-Natta catalyst, covering a wide range of 1-butene fractions. In the first set of samples (EBH), hydrogen was used as a chain transfer agent, whereas it was absent in the second set (EB). Comparison of the reactivity ratio estimates for the sets of samples permitted the quantification of the hydrogen effect on the reactivity ratios of the different site types present in the Ziegler-Natta catalyst used in this thesis. Since 13C NMR it is an essential analytical step in IDEM, triad distributions for the EB and EBH copolymers were measured in two different laboratories (Department of Chemistry at the University of Waterloo, and Dow Chemical Research Center at Freeport, Texas). IDEM was applied to both set of triad measurements to find out the effect of interlaboratory 13C NMR analysis on reactivity ratio estimation.

Polypropylene (PP) and ethylene-co-octene copolymer (EOC) blends were prepared at various component ratios and reinforced with silica nanoparticles (SiO2). Strategies to improve filler dispersion involved the grafting of a silane coupling agent on the PP matrix, the addition of a maleated PP (PP-g-MA) as a compatibilizer and the use of hydrophobic silica nanoparticles. These approaches resulted in a fine dispersion of the nanoparticles within the PP phase and induced a reduction of the size of the EOC domains, due to a barrier effect. Tensile and flexural properties were significantly increased, whereas ductility and impact properties were not affected. These enhancements are attributed to the favourable microstructure of the blends, featuring a segregated microstructure, and to the improved interfacial adhesion between the functionalized polymer matrix and the surface of the nanoparticles. The microstructure and rheology of model melt compounded EOC-based nanocomposites were investigated. Functionalization of the polyolefin matrix was accomplished through silane grafting, or addition of a maleated EOC (EOC-g-MA) compatibilizer. Various grades of unmodified SiO2 having different specific surface areas (SSA), as well as a surface-modified grade were added to the EOC matrix at various loadings. The formation of covalent and hydrogen bonds between the silanol groups and the functionalized polymer generated strong polymer/filler (P/F) interactions, resulting in improved filler dispersion. Bound polymer characterization revealed that in the compatibilized materials, the amount of polymer physically attached to the nanoparticles was higher than in the non-compatibilized samples. In the absence of a compatibilizer, larger SiO2 aggregates formed upon increasing SSA because of increased probability of hydrogen bonding between the particles. The increased propensity for aggregation was revealed by time sweeps as well as by the increased strain sensitivity in stress sweeps. On the contrary, the compatibilized composites exhibited a stable response and a higher critical strain for the onset of non-linearity, indicative of stronger adhesion between the fillers and the matrix. Superposition of oscillatory and creep/recovery experiments revealed that the viscoelastic properties in the terminal region were influenced substantially by the state of dispersion of the nanoparticles. In the absence of a compatibilizer, substantial enhancements in the linear viscoelastic (LVE) functions were noted and an increasing SSA resulted in more significant deviations from terminal flow. On the contrary, the SSA of the particles had no effect on the viscoelastic and mechanical properties of the compatibilized composites. / Thesis (Ph.D, Chemical Engineering) -- Queen's University, 2011-04-18 15:17:52.471

The microstructure of polyolefins determines their macroscopic properties. Consequently, it is essential to predict how polymerization conditions will affect polyolefin microstructure. The most important microstructural distributions of ethylene/alfa-olefin copolymers made with coordination catalysts are their molecular weight (MWD), chemical composition (CCD), and comonomer sequence length (CSLD). Several mathematical models have been developed to predict these microstructural distributions; reliable techniques to estimate parameters for these models, however, are still poorly developed, especially for catalysts that have multiple site types, such as heterogeneous Ziegler-Natta complexes. Most commercial polyolefins are made with heterogeneous Ziegler-Natta catalysts, which make polyolefins with broad MWD, CCD, and CSLD. This behavior is attributed to the presence of several active site types, leading to a final product that can be seen as a blend of polymers made on the different catalyst site types. The main objective of this project is to develop a methodology to estimate the most important parameters needed to describe the microstructure of ethylene/alfa-olefin copolymers made with these multiple site-type catalysts. To accomplish this objective, we developed the Integrated Deconvolution Estimation Model (IDEM). IDEM estimates ethylene/alf-olefin reactivity ratios for each site type in two-steps. In the first step, the copolymer MWD, measured by high-temperature gel permeation chromatography, is deconvoluted into several Flory’s most probable distributions to determine the number of site types and the weight fractions of copolymer made on each of them. In the second estimation step, the model uses the MWD deconvolution information to fit the copolymer triad distributions measured by 13C NMR and estimate the reactivity ratios per site type. This is the first time that MWD and triad distribution information is integrated to estimate the reactivity ratio per site type of multiple site-type catalysts used to make ethylene/alfa-olefin copolymers. IDEM was applied to two sets of ethylene-co-1-butene copolymers made with a commercial Ziegler-Natta catalyst, covering a wide range of 1-butene fractions. In the first set of samples (EBH), hydrogen was used as a chain transfer agent, whereas it was absent in the second set (EB). Comparison of the reactivity ratio estimates for the sets of samples permitted the quantification of the hydrogen effect on the reactivity ratios of the different site types present in the Ziegler-Natta catalyst used in this thesis. Since 13C NMR it is an essential analytical step in IDEM, triad distributions for the EB and EBH copolymers were measured in two different laboratories (Department of Chemistry at the University of Waterloo, and Dow Chemical Research Center at Freeport, Texas). IDEM was applied to both set of triad measurements to find out the effect of interlaboratory 13C NMR analysis on reactivity ratio estimation.

Environmental stress cracking (ESC) is a significant problem that has plagued the plastics industry since its discovery nearly 70 years ago. The accelerated brittle failure brought about when a stressed polymer comes in contact with an aggressive environment can happen suddenly with destructive results. Many classes of polymers are susceptible to this type of slow crack growth; however special emphasis has typically been placed on polyolefins due to their wide range of working environments, market dominance and their seemingly chemical resistance. Much research has been focused on formulating environmentally resistant materials, while the evaluation techniques for gauging environmental stress cracking resistance (ESCR) seem to have been left behind. This research focuses on developing a reliable testing technique for evaluating the ESCR of polyethylene resins. Passive acoustic monitoring was adapted to an industrially accepted ESCR test in an attempt to hear polymer damage before it was visually apparent. It was discovered that the low energy released during the early stages of damage and excessive background noise masked passive signals, making this method of evaluation impractical. Alternatively, active ultrasonic monitoring through velocity and attenuation measurements was investigated to see if probing techniques could be used to detect structural damage. Active ultrasonic monitoring of static and tensile stressed samples were able to differentiate plasticization after ageing, however no indication of ESCR properties could be inferred. A novel forced based monitoring system was developed in response to the acoustic testing techniques. Force monitoring was able to provide useful information regarding the failure cycle of ESC and the acquired profiles could describe a failure onset time. Several ageing environments were also tested with force monitoring and a traditional ESCR test to reveal the stress cracking ability of biodiesel, an important finding. / Thesis / Master of Applied Science (MASc) / Accelerated failure of stressed plastics can occur upon exposure to fluids through a phenomenon known as environmental stress cracking (ESC). The following research outlines the development of a novel testing technique to gauge a material’s environmental stress cracking resistance (ESCR). Adaption of passive acoustics to an existing stress cracking test was unable to provide any indication of ESCR, however the use of active ultrasonics was able to show sample plasticization. A novel forced based measuring technique was found to uniquely map the failure progression of a sample undergoing ESC, providing valuable information for understanding the phenomenon. Additional testing was also completed on various environmental fluids to reveal biodiesel’s ability to provoke ESC, an important observation.

Group 3 and 4 complexes bearing linked cyclopentadienyl amido ligands, often referred to as constrained geometry complexes (CGCs), have experienced considerable interest due to their superior ability to copolymerise ethylene and higher alpha-olefins when activated with suitable co-catalyst.The work presented in this thesis aimed to replace the most commonly applied bridge in CGCs, which is silicon based, by one containing boron. The potential of the bridging element to have Lewis acidic character was expected to positively alter the catalytic activity of the activated species and possibly allowing for self-activation.Synthetic approaches to ligand precursors based on aminoboranes, diaminodiboranes(4) and ferrocenylboranes are described. Starting from the dihalo derivatives of these boranes, sequential substitution of the halides by one equivalent each of a cyclopentadienide derivative and an amide allowed the synthesis and isolation of a broad range of new CGC ligand precursors.Complexation of these ligand precursors to Group 4 metals was studied by utilising various protocols. The reaction with Group 4 tetraamides via amine elimination was the most successful yielding numerous new boron-bridged CGCs and related complexes in which the boron-bridged ligand binds in a non-chelating fashion.The newly synthesised compounds were fully characterised by multinuclear NMR spectroscopy, supplemented by X-ray diffraction studies where applicable.Studies on the reactivity of boron-bridged CGCs in the presence of alkylating agents indicated susceptibility of the boron atom to nucleophilic attack resulting in a decomposition of the linking moiety between the cyclopentadienyl and amido fragments. This is as well reflected in the data gathered from polymerisation experiments, in which methylaluminoxane activated boron-bridged CGCs displayed a low activity towards ethylene polymerisation, but a high activity towards styrene polymerisation. Such characteristics are comparable to unbridged compounds, e.g. [(eta5-C5H5)TiCl3], rather than silicon-bridged CGCs, thus suggesting degradation of the boron-bridged CGCs to unbridged complexes under polymerisation conditions.

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Submitted by Sandra Pereira (srpereira@ufrrj.br) on 2017-01-20T13:13:06Z No. of bitstreams: 1 2013 - Mauro Meliga Wysard Junior.pdf: 3560905 bytes, checksum: 2826a580c7e2ec9ebe3a9e07daacb4f7 (MD5) / Made available in DSpace on 2017-01-20T13:13:06Z (GMT). No. of bitstreams: 1 2013 - Mauro Meliga Wysard Junior.pdf: 3560905 bytes, checksum: 2826a580c7e2ec9ebe3a9e07daacb4f7 (MD5) Previous issue date: 2013-10-15 / Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior - CAPES / The need to reduce environmental impacts while maintaining economic efficiency of various processes has motivated research to develop cheaper and sustainable technologies, to replace those already employed in the industrial sectors. Thus, recycling and utilization of natural materials such as coconut fiber or marine animal shells, is envisioned as an alternative to reduce the environmental impact and at the same time the use of these components in industrial processes reduces operational costs. In this context the biosorbents are included, such as coconut fibers and chitosan, which have high applicability to processes for removing metal ions, and are widely available at low cost. In addition, the problem found in the recovery of these adsorbents and adsorbate after the adsorption process can be bypassed by setting biosorbents in polymeric matrixes, obtaining larger parts, which facilitates the separation steps. Thus, this work aims to develop porous composite adsorbent properties, from the physical mixture of maleic anhydride polyethylene (PE-g-MA), coconut fiber (FC), chitosan (Q), and sodium chloride (NaCl) used as porogen agent), and assess the capacity of these new porous composite in the removal of metallic chromium (III) Ion, since this is a residue present in large industrial activities such as electroplating. The porosity of this material was obtained by leaching of NaCl, present in the composition of composite material. For this assessment, we conducted a trial planning, where could be evaluate the influence of particle size of coconut fiber and the amount of chitosan on adsorption process efficiency, as well as the pH of an aqueous solution containing the chromium (III) adsorbate. With the results could be concluded that the model used in planning was valid for the evaluation of the significance of these variables, as well as the trend of better removal of chromium (III), which took place in the higher pH values (between 6 and 7) and in the presence of increased amounts of chitosan (7.5-8.6 g). The granulometric size range of coconut fiber that was more favorable was between 0.097-0.142 mm. Analyzing these porous composites by spectroscopy in the infrared (FTIR), X-ray diffraction (XRD), water absorption and scanning electron microscopy (SEM), you can see and confirm the strong interaction between the components of the mixture, possibly by interfering in the process efficiency of adsorption of chromium / A necessidade de reduzir impactos ambientais e ao mesmo tempo manter a efici?ncia econ?mica de diversos processos, vem motivando o meio acad?mico a realizar pesquisas voltadas para o desenvolvimento de novas tecnologias mais baratas e sustent?veis, que possam substituir as j? empregadas nos setores industriais. Desta forma, a reciclagem e a utiliza??o de mat?rias-primas naturais como a casca de coco e carapa?as de animais marinhos ? vislumbrada como uma alternativa para a redu??o do impacto ambiental, e ao mesmo tempo, pela utiliza??o desses componentes em processos industriais com a finalidade de reduzir custos operacionais. Neste contexto encontram-se os biossorventes naturais, como a fibra de coco e a quitosana, que apresentam alta aplicabilidade em processos de remo??o de ?ons met?licos, e uma grande disponibilidade a baixo custo. Al?m disso, o problema encontrado na recupera??o desses adsorventes e do adsorvato ap?s o processo de adsor??o pode ser contornado pela fixa??o dos biossorventes em matrizes polim?ricas, obtendo-se pe?as de maior volume, o que facilita as etapas de separa??o. Assim, este trabalho teve como objetivo desenvolver comp?sitos porosos com propriedades adsorventes, a partir da mistura f?sica de polietileno graftizado com anidrido maleico (PE-g-MA), fibra de coco (FC), quitosana (Q) e cloreto de s?dio (NaCl) utilizado como agente porog?nico), e avaliar a capacidade de adsor??o desses novos comp?sitos porosos na remo??o do ?on met?lico cromo (III), j? que este, ? um res?duo presente em grandes atividades industriais, como a galvanoplastia. Com esta finalidade, foi realizado um planejamento experimental, onde foi avaliada a influ?ncia do tamanho das part?culas de fibra de coco e da quantidade de quitosana na efici?ncia do processo de adsor??o, assim como o pH da solu??o aquosa contendo o adsorvato cromo (III). Com os resultados pode-se concluir que o modelo usado no planejamento experimental foi v?lido para a avalia??o da signific?ncia dessas vari?veis, como para as melhores condi??es de remo??o do cromo (III), as quais aconteceram nos valores mais elevados de pH (entre 6 e 7) e na presen?a de maiores quantidades de quitosana (7,5-8,6 g). A faixa granulom?trica da fibra de coco que se mostrou mais favor?vel foi de 0,097-0,142 mm. Analisando esses comp?sitos porosos por espectroscopia na regi?o do infravermelho (FTIR), difra??o de raios-X (DRX), absor??o de ?gua e microscopia eletr?nica de varredura (MEV), p?de-se constatar e confirmar a forte intera??o ocorrida entre os componentes da mistura, possivelmente, interferindo na efici?ncia do processo de adsor??o do cromo (III).

Made available in DSpace on 2014-10-09T12:35:51Z (GMT). No. of bitstreams: 0 / Made available in DSpace on 2014-10-09T14:03:39Z (GMT). No. of bitstreams: 0 / Dissertação (Mestrado) / IPEN/D / Instituto de Pesquisas Energeticas e Nucleares - IPEN-CNEN/SP