• Applied Microscopy
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• 제46권3호
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• pp.160-163
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• 2016

Effect of dealloying condition on the formation of nanoporous structure in melt-spun $Al_{60}Ge_{30}Mn_{10}$ alloy has been investigated in the present study. In as-melt-spun $Al_{60}Ge_{30}Mn_{10}$ alloy spinodal decomposition occurs in the undercooled liquid during cooling, leading to amorphous phase separation. By immersing the as-melt-spun $Al_{60}Ge_{30}Mn_{10}$ alloy in 5 wt% HCl solution, Al-rich amorphous region is leached out, resulting in an interconnected nano-porous $GeO_x$ with an amorphous structure. The dealloying temperature strongly affects the whole dealloying process. At higher dealloying temperature, dissolution kinetics and surface diffusion/agglomeration rate become higher, resulting in the accelerated dealloying kinetics, i.e., larger dealloying depth and coarser pore-ligament structure.

• 한국결정성장학회지
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• 제15권5호
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• pp.188-192
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• 2005

High $T_c(Y_{0.5}Nd_{0.25}Sm_{0.25})Ba_2Cu_3O_y[(YNS)-123]$ superconductors with/without $CeO_2$ additive were systematically investigated by the zone melt growth process in air. Cylindrical green rods of (YNS)-123 oxides were fabricated by cold isostatic pressing (CIP) method using rubber mould. A sample prepared by this method showed well-textured microstructure, and $(Y_{0.5}Nd_{0.25}Sm_{0.25})_2BaCuO_5[(YNS)211]$ nonsuperconducting inclusions were uniformly dispersed in large $(Y_{0.5}Nd_{0.25}Sm_{0.25})Ba_2Cu_3O_y$[(YNS)123] superconducting matrix. In this study, optimum melting temperature and growth rate were $1100^{\circ}C$ and 3 mm/hr, respectively. The directionally melt-textured (YNS)-123 sample with $CeO_2$ additive showed an onset critical temperature $(T_c)\;T_c{\geq}93K$ and sharp superconducting transition.

• Progress in Superconductivity
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• 제6권1호
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• pp.1-6
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• 2004

Melt-textured YBCO in high quantity and good quality is prepared in a batch process. A mean trapped field >1. IT at 77K is achieved in batch processed material. Studying the microstructure is a necessary tool to understand the growth mechanisms and thus to opimise the material. From the growth induced structures in the material the anisotropy in growth speed is 1.37. From batch processed material function elements for different cryomagnetic applications are constructed. Motors with an output power > 200 kW at 77 K and bearings that can lift more than 200 kg were equipped with melt-textured YBCO.

• 한국고분자학회:학술대회논문집
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• 한국고분자학회 2006년도 IUPAC International Symposium on Advanced Polymers for Emerging Technologies
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• pp.215-215
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• 2006

The cyclic butylene terephthalte oligomer was synthesized and the composition of butylenes terephthalate cyclic oligomers was 51.2 % of dimer, 28.1 % of trimer, 7.9 % of tetramer, 8 % of pentamer and 4.8% of hexamer. Polybuthylene terephthalate was polymerized using this cyclic oligomer in the condition of melt process and supercritical process. And PBT/clay nanocomposite were manu- factured from melt process and supercritical process. Chlorodifluoro- methane(HCFC-22) was used as a solvent which has critical point ($Tc=96.2^{\circ}C$, Pc=49.7bar). Also polymer nanocomposite were manufactured using rapid expansion of supercritical solution process.

• 한국정밀공학회지
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• 제19권12호
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• pp.33-37
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• 2002

A short shot is a molded part that is incomplete because insufficient material was injected into the mold. Remedial actions to control the process conditions can be taken by the injection molding experts based on their knowledge and experience. However, it is very difficult for the non-experts to avoid short shot by finding the proper process conditions such as mold temperature, melt temperature and filling time. In this paper, an intelligent generator of the optimal process conditions based upon fuzzy logic algorithm is proposed so that trial and error can be minimized and the non-experts as well as the experts can also find the optimal process conditions.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2001년도 춘계학술대회 논문집
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• pp.402-405
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• 2001

A short shot is a molded part that is incomplete because insufficient material was injected into the mold. Remedial actions to control the process conditions can be taken by the injection molding experts based on their knowledge and experience. However, it is very difficult for the non-experts to avoid short shot by finding the proper process conditions such as mold temperature, melt temperature and filling time. In this paper, an intelligent generator of the optimal process conditions based upon fuzzy logic algorithm is proposed so that trial and error can be minimized and the non-experts as well as the experts can also find the optimal process conditions.

• 열처리공학회지
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• 제27권4호
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• pp.180-184
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• 2014

In order to make clear relationship between high temperature tensile properties and fine microstructure of rapidly solidified cast-type Ni-base superalloys without heat treatment required for consolidation process, tensile test was carried out by changing strain rate from $5{\times}10^{-5}s^{-1}$ to $2{\times}10^{-2}s^{-1}$ and test temperature from $900^{\circ}C$ to $1050^{\circ}C$ using IN738LC and Rene'80 melt-spinning ribbons by twin roll process which were superior to ribbons by single roll process from the viewpoint of structure homogeneity. The dependence of tensile strength on strain rate and test temperature was studied and strain rate sensitivity, m, were estimated from tensile test results. From this study, it was found that tensile strength was influenced by ${\gamma}^{\prime}$ particle diameter, test temperature and strain rate, and m of ribbons exhibited above 0.3 over $950^{\circ}C$.

• 한국표면공학회지
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• 제56권5호
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• pp.309-319
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• 2023

Non-woven fabric is a textile product made by spinning thermoplastic polymers without manufacturing processes such as stretching, doubling, twisting, weaving, and knitting to form a sheet-shaped web in which fibers are tangled with each other, and then combining them by mechanical and physical methods. In addition, the non-woven fabric manufacturing process has various raw material choices, high productivity, so it is a textile manufacturing technology that can have various uses and increase added value. This study was conducted to control the shape and physical properties of products by improving the manufacturing method of melt-blown non-woven fabrics using process technology that easily changes the shape of non-woven fabrics and improves mechanical properties. In particular, it is considered that a non-woven fabric with a thin material shape and improved mechanical properties will be easily applied to a continuous secondary battery manufacturing industry such as roll to roll operation.

• 한국산업융합학회 논문집
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• 제23권5호
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• pp.773-787
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• 2020

In the injection molding process, the controlling stability of products quality is a very important factor in terms of productivity. Even when the optimum process conditions for the desired product quality are applied, uncontrollable external factors such as ambient temperature and humidity cause inevitable changes in the state of the melt resin, mold temperature. etc. Therefore, it is very difficult to maintain prodcut quality. In this study, a system that learns the correlation between process variables and product weight through artificial neural networks and predicts process conditions for the target weight was established. Then, when a disturbance occurs in the injection molding process and fluctuations in the weight of the product occur, the stability control of the product quality was performed by ANN predicting a new process condition for the change of weight. In order to artificially generate disturbance in the injection molding process, controllable factors were selected and changed among factors not learned in the ANN model. Initially, injection molding was performed with a polypropylene having a melt flow index of 10 g/10min, and then the resin was replaced with a polypropylene having a melt floiw index of 33 g/10min to apply disturbance. As a result, when the disturbance occurred, the deviation of the weight was -0.57 g, resulting in an error of -1.37%. Using the control method proposed in the study, through a total of 11 control processes, 41.57 g with an error of 0.00% in the range of 0.5% deviation of the target weight was measured, and the weight was stably maintained with 0.15±0.07% error afterwards.

• 한국분말재료학회지
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• 제29권6호
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• pp.459-467
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• 2022

Soft magnetic powder materials are used throughout industries such as motors and power converters. When manufacturing Fe-based soft magnetic composites, the size and shape of the soft magnetic powder and the microstructure in the powder are closely related to the magnetic properties. In this study, Fe-Si-Al-P alloy powders were manufactured using various manufacturing process parameter sets, and the process parameters of the vacuum induction melt gas atomization process were set as melt temperature, atomization gas pressure, and gas flow rate. Process variable data that records are converted into 6 types of data for each powder recovery section. Process variable data that recorded minute changes were converted into 6 types of data and used as input variables. As output variables, a total of 6 types were designated by measuring the particle size, flowability, apparent density, and sphericity of the manufactured powders according to the process variable conditions. The sensitivity of the input and output variables was analyzed through the Pearson correlation coefficient, and a total of 6 powder characteristics were analyzed by artificial neural network model. The prediction results were compared with the results through linear regression analysis and response surface methodology, respectively.