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Full-Text Articles in Engineering
On Line Measurement Of Crystallinity Of Nylon 6 Nanocomposites By Laser Raman Spectroscopy And Neural Networks, Z. Ergungor, Celal Batur, Mukerrem Cakmak
On Line Measurement Of Crystallinity Of Nylon 6 Nanocomposites By Laser Raman Spectroscopy And Neural Networks, Z. Ergungor, Celal Batur, Mukerrem Cakmak
Dr. Celal Batur
A neural network is trained to estimate the unknown crystallinity and temperature of Nylon 6 and its nanocomposites while the material is undergoing cooling at a fixed rate. The innovation of the work is that the full spectrum captured by the laser Raman spectroscope is used to train a neural network for estimation of crystallinity and temperature. The small-angle light scattering (SALS) and differential scanning calorimetry (DSC) data were used to provide the training examples for the neural network. Results indicate that the neural network can provide reliable estimates of the crystallinity and temperature provided that there is a sufficient …
Effect Of Processing Conditions On The Development Of Morphology In Clay Nanoparticle Filled Nylon 6 Fibers, Zeynep Ergungor, Mukerrem Cakmak, Celal Batur
Effect Of Processing Conditions On The Development Of Morphology In Clay Nanoparticle Filled Nylon 6 Fibers, Zeynep Ergungor, Mukerrem Cakmak, Celal Batur
Dr. Celal Batur
The effect of melt temperature on the phase behavior and preferential orientation development in Nylon 6/montmorillonite nanocomposites were investigated at melt spinning temperatures ranging from 230° to 250°C. The fibers were found to exhibit mostly γ crystalline form that is typical of Nylon 6 filled with montmorillonite nanoparticles. At higher take-up speeds α-crystals begin to appear in the crystalline phase. The presence of nanoparticles was found to impart substantial chain orientation levels even at low to moderate take up speeds reaching a plateau at moderate take up speeds. This was attributed to the increased spin line stress in the presence …
Pressure Control System For Electrospinning Process, Charles Druesedow, Celal Batur, Mukerrem Cakmak, Baris Yalcin
Pressure Control System For Electrospinning Process, Charles Druesedow, Celal Batur, Mukerrem Cakmak, Baris Yalcin
Dr. Celal Batur
Electrospinning is used to produce micro- and nano-sized synthetic fibers through the use of electrostatic forces. Commercially, viable production of fibers requires high throughput of uniform fibers that are free of defects. To achieve greater control over the process variables that affect the fiber formation, a scalable closed loop control system that can maintain a constant pressure at the capillary tip was designed and tested. Two sensing technologies, infrared and ultrasonic, were used and compared for their ability to detect the height of polymer solution in the electrospinning fluid container. The air pressure above the solution was measured with a …
Molecular Origins Of Toughening Mechanism In Uniaxially Stretched Nylon 6 Films With Clay Nanoparticles, B. Yalcin, Z. Ergungor, Y. Konishi, Mukerrem Cakmak, Celal Batur
Molecular Origins Of Toughening Mechanism In Uniaxially Stretched Nylon 6 Films With Clay Nanoparticles, B. Yalcin, Z. Ergungor, Y. Konishi, Mukerrem Cakmak, Celal Batur
Dr. Celal Batur
Introduction of nanoplatelets into the nylon matrix preorients the polymer chains in the film plane during melt casting leading to uniplanar (001) texture in nylon 6 crystalline as well as clay phase. This behavior enhances the uniformity of films during cold deformation well above the glass transition temperature by suppressing the localized necking behavior. The clay platelets reduce the polymer interchain hydrogen bonding and entanglements leading to decrease of long range “connectivity”. As a result, a delay in strain hardening during deformation occurs allowing much larger deformations to be attained without fracture. This in turn leads to increase in toughness.
On-Line Crystallinity Measurement Using Laser Raman Spectrometer And Neural Network, Celal Batur, Mohamad Vhora, Mukerrem Cakmak, Toprak Serhatkulu
On-Line Crystallinity Measurement Using Laser Raman Spectrometer And Neural Network, Celal Batur, Mohamad Vhora, Mukerrem Cakmak, Toprak Serhatkulu
Dr. Celal Batur
A neural network is configured and trained to measure the polymer crytallinity in real time and non-intrusive manner. After the training, input to the neural network becomes the laser Raman spectrum at selected ferquencies and the output from the network is the current crystallinity of polymer. In order to train the neural network, a training data set is constructed where the crystallinities corresponding to a given set of Raman spectra are pre-determined by the small angle light scattering (SALS) methodology. The technique is applied to measure the crystallinity of low-density thin polyethylene (LDPE) film. A typical sampling period for the …