This dissertation work deals with the thermic and the mechanical behavior of plasticized bio-plastics and bio-composites for the 3D printing applications. The influence of plasticizer chemical structure on thermic and mechanical properties of plasticized polymeric blends from the poly-3-hydroxybutyrate and the poly lactic acid was investigated. Used plasticizers are based on derivative of citric acid. The influence of plasticizers on polymeric matrix and their compatibility was estimated by gear torque rate of melt mixer, respectively rate of plasticizer migration from the material during higher temperature. The plasticizer structure influence on the glass transition temperature and on the kinetics of crystallization of plasticized material was investigated by modulated differential scanning calorimetry. The behavior of material during 3D printing was also observed. Mechanical properties of printed samples, especially their elongation at break, were determined by tensile tests. The largest softening effect was observed using tributylcitrate plasticizer, where the glass temperature decreased by 35 °C and elongation at break increased by 150% compared to non-plasticized reference material. This plasticized polymeric blend showed also sufficient 3D printing properties and was used as the matrix for composites in the next part of this work. Composites were filled by kaolin, limestone, halloysit, fumed silica, talc, magnesium hydroxide and chopped flax fibers. Particle distribution in composites in dependence of used surface treatment of filler was observed by scanning electron microscopy. The influence of composite filler on rheological properties, crystallization kinetics and thermal stability of composites, was observed by viscometry and differential scanning calorimetry. Their mechanical properties and heat deflection temperature were observed on samples prepared by 3D print. Kaolin in composite material showed homogeneous particle distribution and insignificant nucleation effect and influence on thermic stability. Composite filled by kaolin also showed 18% smaller warping during 3D printing compared to non-filled reference. Consequently kaolin was evaluated as suitable inorganic filler for bioplastic composite intended for 3D print and this composite was used in the following part of this thesis. Method of mathematical prediction of Young's modulus was described for composite samples prepared by 3D print. Composites filled by one type of filler – kaolin, or limestone, resp. by combination of both fillers were investigated on the basis of the micromechanic Halpin-Tsai model modified by the semiempiric multiparametric Cerny's equation. Additive and combinational method of Young's modulus evaluation is used for composites with hybrid filling. Deflection of measured and theoretical Young's modulus value of composite filled with kaolin was decreased by established correction from 21% to 1% and for composites filled with limestone from 13% to 9%. In this manner it is possible to predict the Young's modulus of the samples prepared by 3D print.

Please read the abstract in the dissertation Copyright / Dissertation (MSc)--University of Pretoria, 2013. / Chemical Engineering / unrestricted

Made available in DSpace on 2014-12-17T14:58:19Z (GMT). No. of bitstreams: 1 EduardoCBC_DISSERT.pdf: 1858317 bytes, checksum: de7993f7a4a27b8a08342ddc43175aff (MD5) Previous issue date: 2012-12-14 / Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior / The aim of this study is to create an artificial neural network (ANN) capable of modeling the transverse elasticity modulus (E2) of unidirectional composites. To that end, we used a dataset divided into two parts, one for training and the other for ANN testing. Three types of architectures from different networks were developed, one with only two inputs, one with three inputs and the third with mixed architecture combining an ANN with a model developed by Halpin-Tsai. After algorithm training, the results demonstrate that the use of ANNs is quite promising, given that when they were compared with those of the Halp?n-Tsai mathematical model, higher correlation coefficient values and lower root mean square values were observed / Este trabalho tem como principal objetivo a cria??o de uma arquitetura de rede neural artificial (RNA) capaz de modelar o m?dulo de elasticidade transversal (E2) de comp?sitos unidirecionais. Para tanto, se fez necess?rio o uso de um conjunto de dados que foi dividido em duas partes, uma parte sendo utilizada para o treinamento e a outra para teste das RNA. Para este trabalho se desenvolveu tr?s tipos de arquiteturas de rede diferentes uma delas possuindo somente duas entradas, a outra tr?s entradas e a ?ltima foi uma arquitetura mista que combina uma RNA com um modelo desenvolvido por Halpin-Tsai. Ap?s o treinamento dos algoritmos, os resultados demonstram que o uso de RNAs se mostra bastante promissor, j? que quando esses resultados foram comparados com o modelo matem?tico de Halpin-Tsai, apresentaram maiores valores de coeficiente de correla??o e menores valores de erro m?dio quadr?tico

Diplomová práca sa zaoberá prípravou teromplastických kompzoitov s PMMA a PC matricou s potenciálnym využitím v automobilovom priemysle. Ako výstuž boli použité krátke sklenené, uhlíkové a PBO (poly(p-fenylén benzobisoxazol)) vlákna známe pod obchodným názvom Zylon®. Práve do PBO vlákien boli vkladané veľké nádeje vzhľadom na ich ohromujúce mechanické vlastnosti. Vplyv objemového zlomku vlákien na modulu pružnosti, pevnosť a ťažnosť kompozitov bol skúmaný. Experimentálne zistený modul pružností bol porovnaný so semi-empirickým Halpin-Tsai modelom. Prídavok sklenených a uhlíkových vlákien viedol k značnému zvýšeniu modulu pružnosti. Ukázalo sa, že po istej hodnote objemového zlomku dochádza k poklesu pevností kompozitov v dôsledku zvyšujúceho sa počtu defektov. Prídavok PBO vlákien preukázal len nepatrný vystužujúci efekt. Viskoelastické vlastností kompozitov boli skúmané pomocou dynamicko mechanickej analýzy (DMA). Termogravimetrická analýza (TGA), konfokálna laserová rastrovacia mikroskopia (CLSM) a rastrovacia elektrónová mikroskopia (SEM) boli využité k štúdiu štruktúry kompozitov.