The Experts below are selected from a list of 2991 Experts worldwide ranked by ideXlab platform
Fang Yunxiang - One of the best experts on this subject based on the ideXlab platform.
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environment friendly halogen free flame retardant polyethylene glycol terephthalate Molded Plastic
2013Co-Authors: Fang YunxiangAbstract:The invention relates to environment-friendly halogen-free flame retardant polyethylene glycol terephthalate Molded Plastic, and belongs to the technical field of high molecular materials. The environment-friendly halogen-free flame retardant polyethylene glycol terephthalate Molded Plastic comprises the following raw materials in parts by weight: 63-75 parts of polyethylene glycol terephthalate, 7-13 parts of polyolefin, 15-23 parts of noncrystalline polyester resin, 6-14 parts of a flexibilizer, 12-22 parts of phosphate, 18-27 parts of filler, 0.7-1.2 parts of an antioxidant, 12-25 parts of nanofiber and 1.3-1.9 parts of carbon black. The environment-friendly halogen-free flame retardant polyethylene glycol terephthalate Molded Plastic provided by the invention through tests has the following performance indexes: the tensile strength is 116-132MPa, the bending strength is 205-226MPa, the notch impact strength is 58-78j/m, the fire resistance reaches V-0(UL-94-3.0mm) and the thermal distortion temperature is 220-240 DEG C. The waste Plastic does not damage the environment.
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preparation method of environment friendly halogen free flame retardant polyethylene glycol terephthalate Molded Plastic
2013Co-Authors: Fang YunxiangAbstract:The invention relates to a preparation method of environmental-friendly halogen-free flame-retardant polyethylene glycol terephthalate Molded Plastic, and belongs to the technical field of preparation of high molecular materials. The preparation method comprises the following steps: putting 63-75 parts of polyethylene glycol Terephthalate to a drying device to be dried to obtain a dried material which is put into a high speed mixer; then, putting 7-13 parts of polyolefin, 15-23 parts of amorphous polyester resin, 6-14 parts of a flexibilizer, 12-22 parts of phosphate, 18-27 parts of a filler, 0.7-1.2 parts of an antioxygen, 12-25 parts of a nanofiber and 1.3-1.9 parts of carbon black to the high speed mixer to be mixed with the dried material; and guiding the mixture in a twin-screw extruder to carry out melt extrusion, and cooling, granulating and drying to obtain a finished product, wherein the screw temperatures of zones I to X are controlled as follows: 210 DEG C, 215 DEG C, 225 DEG C, 235 DEG C, 245 DEG C, 255 DEG C, 265 DEG C, 265 DEG C, 265 DEG C and 265 DEG C. The tensile strength is 116-132 MPa, the bending strength is 205-226 MPa, the notch impact strength is 58-78 j/m, the fire resistance reaches V-0(UL-94-3.0mm), and the thermal distortion temperature is 220-240 DEG C. The wasted Molded Plastic does not damage the environment.
Qian Li - One of the best experts on this subject based on the ideXlab platform.
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optimization of injection molding process parameters using combination of artificial neural network and genetic algorithm method
Journal of Materials Processing Technology, 2007Co-Authors: Changyu Shen, Lixia Wang, Qian LiAbstract:Abstract Injection molding is the most widely used process in manufacturing Plastic products. Since the quality of injection Molded Plastic parts are mostly influenced by process conditions, how to determine the optimum process conditions becomes the key to improving the part quality. In this paper, a combining artificial neural network and genetic algorithm (ANN/GA) method is proposed to optimize the injection molding process. In this method, a BP neural network model is developed to map the complex non-linear relationship between process conditions and quality indexes of the injection Molded parts, and a GA is used in the process conditions optimization with the fitness function based on an ANN model. The combining ANN/GA method is used in the process optimization for an industrial part in order to improve the quality index of the volumetric shrinkage variation in the part. The results show that the combining ANN/GA method is an effective tool for the process optimization of injection molding.
Javad Seyfi - One of the best experts on this subject based on the ideXlab platform.
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warpage and shrinkage optimization of injection Molded Plastic spoon parts for biodegradable polymers using taguchi anova and artificial neural network methods
Journal of Materials Science & Technology, 2016Co-Authors: Erfan Oliaei, Behzad Shiroud Heidari, Seyed Mohammad Davachi, Mozhgan Bahrami, Saeed Davoodi, Iman Hejazi, Javad SeyfiAbstract:In this study, it is attempted to give an insight into the injection processability of three self-prepared polymers from A to Z. This work presents material analysis, injection molding simulation, design of experiments alongside considering all interaction effects of controlling parameters carefully for green biodegradable polymeric systems, including polylactic acid (PLA), polylactic acid-thermoPlastic polyurethane (PLA-TPU) and polylactic acid-thermoPlastic starch (PLA-TPS). The experiments were carried out using injection molding simulation software Autodesk Moldflow® in order to minimize warpage and volumetric shrinkage for each of the mentioned systems. The analysis was conducted by changing five significant processing parameters, including coolant temperature, packing time, packing pressure, mold temperature and melt temperature. Taguchi's L27 (35) orthogonal array was selected as an efficient method for design of simulations in order to consider the interaction effects of the parameters and reduce spurious simulations. Meanwhile, artificial neural network (ANN) was also used for pattern recognition and optimization through modifying the processing conditions. The Taguchi coupled analysis of variance (ANOVA) and ANN analysis resulted in definition of optimum levels for each factor by two completely different methods. According to the results, melting temperature, coolant temperature and packing time had significant influence on the shrinkage and warpage. The ANN optimal level selection for minimization of shrinkage and/or warpage is in good agreement with ANOVA optimal level selection results. This investigation indicates that PLA-TPU compound exhibits the highest resistance to warpage and shrinkage defects compared to the other studied compounds.
Changyu Shen - One of the best experts on this subject based on the ideXlab platform.
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optimization of injection molding process parameters using combination of artificial neural network and genetic algorithm method
Journal of Materials Processing Technology, 2007Co-Authors: Changyu Shen, Lixia Wang, Qian LiAbstract:Abstract Injection molding is the most widely used process in manufacturing Plastic products. Since the quality of injection Molded Plastic parts are mostly influenced by process conditions, how to determine the optimum process conditions becomes the key to improving the part quality. In this paper, a combining artificial neural network and genetic algorithm (ANN/GA) method is proposed to optimize the injection molding process. In this method, a BP neural network model is developed to map the complex non-linear relationship between process conditions and quality indexes of the injection Molded parts, and a GA is used in the process conditions optimization with the fitness function based on an ANN model. The combining ANN/GA method is used in the process optimization for an industrial part in order to improve the quality index of the volumetric shrinkage variation in the part. The results show that the combining ANN/GA method is an effective tool for the process optimization of injection molding.
H E Garrett - One of the best experts on this subject based on the ideXlab platform.
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Compact, Low-Crosstalk, WDM Filter Elements for Multimode Ribbon Fiber Data Links Compact, Low-Crosstalk, WDM Filter Elements for Multimode Ribbon Fiber Data Links
2020Co-Authors: R R Pate1, H E Garrett, M A Emanuel, M C Larson, M D Pocha, D M Krol, R J Deri, M E Lowry, R R PatelAbstract:Abstract We have been developing the optical components for a source-routed wavelength division multiplexed (WDM) computer interconnect fabric that uses multi-mode fiber ribbon cable as the transmission medium. We are developing wavelength selectable VCSEL transmitters, interference filters, and a compact broadcast element. Here we report on key results from our interference filter development activities. Our WDM filter approach is based upon post-market machining of the commercially available Molded Plastic "MT" fiber ribbon connector. We use III-IV semiconductors grown by MBE or MOCVD as the filter materials. The high indices of our thin film materials enable us to use multimode fiber and maintain narrow passbands without the need for micro-optics. We have fabricated both 2-port and 3-port devices based upon this approach. Our current work focuses on 2-port WDM filters suitable for a broadcast and select architecture. Our single-cavity FabryPerot (FP) filters have demonstrated insertion losses of < 2 dB for 4 nm passbands. The maximum crosstalk suppression for the single-cavity FP filters is 18dB To improve crosstalk suppression beyond that attainable with the Lorentzian lineshapes of the single-cavity FP we have investigated some multiple-cavity Fabry-Perot (MC-FP) designs which have a spectral response with a flatter top and sharper passband edges. Filter passband edge sharpness can be quantified by the ratio of the filter 3 dB bandwidth to 18 dB bandwidth This ratio is 0.48 for our multi-cavity filter, three times sharper than the single-cavity FP devices. This device provides a 5 nm tolerance window for component wavelength variations (at 1 dB excess loss) and is suitable for 10 nm channel spacing with 23 dB crosstalk suppression between adjacent channels. The average insertion loss for the MC-l? devices is 1.6 dB. (Average of insertion losses for the 12 fibers in a filter module.) Our current MC-FP filters have a 3-dB width of 7.6nm. Fiber to fiber center wavelength variations within a typical filter module are less than lnm. The MC-FP devices exhibit cross-talk suppression >30dB over a 100nm span