• 한국재료학회지
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• 제15권6호
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• pp.426-430
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• 2005

Chemical mechanical polishing (CMP) is an essential process in the production of integrated circuits containing copper interconnects. The effect of alanine in reactive slurries representative of those that might be used in copper CMP was studied with the aim of improving selectivity between copper(Cu) film and tantalum-nitride(TaN) film. We investigated the pH effect of nano-colloidal silica slurry containing alanine through the chemical mechanical polishing test for the 8(inch) blanket wafers as deposited Cu and TaN film, respectively. The copper and tantalum-nitride removal rate decreased with the increase of pH and reaches the neutral at pH 7, then, with the further increase of pH to alkaline, the removal rate rise to increase soddenly. It was found that alkaline slurry has a higher removal rate than acidic and neutral slurries for copper film, but the removal rate of tantalum-nitride does not change much. These tests indicated that alanine may improve the CMP process by controlling the selectivity between Cu and TaN film.

• 한국세라믹학회지
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• 제43권9호
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• pp.564-568
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• 2006

AlO(OH) nano gel is used in precursor of ceramic material, coating material and catalyst. For use of these, not only physiochemical control for particle morphology, pore characteristic and peptization but also studies of synthetic method for preparation of advanced application products were required. In this study, AlO(OH) nano gel was prepared through the aging and drying process of aluminum hydroxides gel precipitated by the hydrolysis reaction of dilute NaOH solution and aluminum sulfate solution. In this process, optimum synthetic condition of AlO(OH) nano gel having excellent pore volume as studying the effect of water and aluminum sulfate mole ratio on gel precipitates has been studied. Water and aluminum sulfate mole ratio brought about numerous changes on crystal morphology, surface area, pore volume and pore size. Physiochemical properties were investigated as using XRD, TEM, TG/DTA, FT-IR, and $N_2$ BET method.

• 한국기계가공학회지
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• 제17권5호
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• pp.8-15
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• 2018

Films with special properties (e.g., water-repellent films, optical films, anti-reflection films, and flexible films) are referred to as functional films. Recently, there has been interest in fine patterning methods for film fabrication. In particular there have been many studies that use a UV nanoimprint process involving a UV curing method. In this paper, a polymer film was fabricated by the UV nanoimprint process with a micro-pattern, and its durability was evaluated by a wear test and a nano-indentation test. The film mechanical properties (such as coefficient of friction, hardness, and modulus of elasticity) were measured. Moreover, the choice of PUA type resin used in the UV nanoimprint process was confirmed to impact the durability of the thin film. Despite making the polymer film samples using the same method and PUA type resin, different coefficient of friction, hardness, and modulus of elasticity values were obtained. PUA 4 resin had the most favorable coefficient of friction, hardness, and modulus of elasticity. This material is predicted to produce a high durability functional film.

• Advances in nano research
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• 제12권4호
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• pp.375-386
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• 2022

Synthesis of acrylate-based dispersion resins involves many parameters including temperature, ingredients concentrations, and rate of adding ingredients. Proper controlling of these parameters results in a uniform nano-size chain of polymer on one side and elimination of hazardous residual monomer on the other side. In this study, we aim to screen the process parameters via Internet of Things (IoT) to ensure that, first, the nano-size polymeric chains are in an acceptable range to acquire high adhesion property and second, the remaining hazardous substance concentration is under the minimum value for safety of public and personnel health. In this regard, a set of experiments is conducted to observe the influences of the process parameters on the size and dispersity of polymer chain and residual monomer concentration. The obtained dataset is further used to train an Adaptive Neural network Fuzzy Inference System (ANFIS) to achieve a model that predicts these two output parameters based on the input parameters. Finally, the ANFIS will return values to the automation system for further decisions on parameter adjustment or halting the process to preserve the health of the personnel and final product consumers as well.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2007년도 춘계학술대회A
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• pp.37-42
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• 2007

We present a powder injection molding technique of fabricating cemented tungsten carbide(WC) balls for milling and dispersing nano-powder in this paper. The conventional powder metallurgy approach is investigated to reveal its drawbacks of density non-homogeneity. New procedures of powder injection molding for the homogeneous high-precision WC balls, involving the binding process, powder injection molding process and sintering process, are presented in detail. Each process is investigated empirically and numerically to obtain its engineering information, which can used for process optimization.

• 한국소성가공학회:학술대회논문집
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• 한국소성가공학회 2007년도 춘계학술대회 논문집
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• pp.371-374
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• 2007

A method for metal nano powder imprinting is proposed as a patterning process for conductive tracks that is inexpensive and scalable down to the nanoscale. Conductive tracks with line widths of $0.5{\sim}20{\mu}m$ were fabricated using this method. The processing conditions were optimized to avoid various types of defects, and to increase the degree of sintering and electric conductivity of the imprinted conductive tracks. The mean electric resistivity of the conductive tracks imprinted under optimum conditions was $8.95{\mu}{\Omega}{\cdot}cm$, which is in the range required for practical applications.

• 한국분말재료학회지
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• 제14권2호
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• pp.116-122
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• 2007

It is well known that thermal plasma process has lots of advantages such as high temperature and good quality for synthesis of nano particles. In this research, we attempt the synthesis of nano unitary and composite powder (Ag, Mg-Al, Zr-V-Fe) using transferred thermal plasma. Nano particles of metal alloy, ranging from 20 nm to 150 nm, have been synthesized by this process.

• 한국입자에어로졸학회지
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• 제6권1호
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• pp.37-46
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• 2010

Cu nano-colloid was prepared by wire electric explosion process under de-mineralized water and anhydrous ethanol. To control the properties of Cu nano-colloid, experimental conditions such as diameter of Cu wire and applied voltage were changed. The optimal Cu nano-colloid was prepared when the 0.1mm diameter of Cu wire with the applied voltage of 2000 V was used. The shape of Cu particles in colloid was spherical and the XRD result revealed that the phase of Cu particles was cubic phase. About 20nm Cu nanoparticles with high crystallinity were successfully prepared using wire explosion process under anhydrous ethanol and they showed more than 100 hours dispersion stability.

• 대한금속재료학회지
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• 제50권2호
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• pp.93-99
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• 2012

The mechanical properties of nano composites were evaluated for structural performance in order to enhance their applicability to the car and machine industrial fields. Carbon fiber reinforced plastics (CFRP) and GFRP were manufactured by vacuum-assisted resin transfer molding (VARTM) process with good mechanical properties. Tensile test was conducted to obtain the process factor of each composite. Also, carbon nano fiber (CNF) was dispersed in the composites and the relationship between the mechanical property and the CNF fraction was compared. The tensile strength and stiffness of 0/90 laminated CFRP were the best. CFRP/CNF (0.5 wt.%) was confirmed to be an excellent material for its elasticity and tensile strength.

• Computers and Concrete
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• 제30권1호
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• pp.33-42
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• 2022

Experimentally predicting the compressive strength (CS) of concrete (for a mix design) is a time-consuming and laborious process. The present study aims to propose surrogate models based on Support Vector Machine (SVM) and Gaussian Process Regression (GPR) machine learning techniques, which can predict the CS of concrete containing nano-silica. Content of cement, aggregates, nano-silica and its fineness, water-binder ratio, and the days at which strength has to be predicted are the input variables. The efficiency of the models is compared in terms of Correlation Coefficient (CC), Root Mean Square Error (RMSE), Variance Account For (VAF), Nash-Sutcliffe Efficiency (NSE), and RMSE to observation's standard deviation ratio (RSR). It has been observed that the SVM outperforms GPR in predicting the CS of the concrete containing nano-silica.