Applied Chemistry for Engineering, Vol.31, No.4, 377-382, August, 2020
아세틸렌 흡착공정용 MOF-235 합성 최적화를 위한 실험 계획법 적용
An Application of Design of Experiments for Optimization of MOF-235 Synthesis for Acetylene Adsorption Process
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초록
아세틸렌 흡착 공정을 위한 MOF-235 합성의 최적화를 위해 순차적인 실험 계획법을 사용하였다. 이를 위하여 두 가지 실험 계획법이 적용되었는데, screening을 위한 2단계 요인 설계와 반응표면 분석법 중에 하나인 중심합성 계획이다. 본 연구에서는 23 요인 설계법을 이용하여 MOF-235의 결정도에 대한 합성 온도, 합성 시간 및 혼합 속도의 영향을 평가하였다. MINITAB 19 소프트웨어에 따라 설계된 16번의 MOF-235 합성 실험을 수행하였다. XRD 분석을 바탕으로 Half-Normal, Pareto, Residual, Main 및 Interaction 효과를 구하였다. 시험 결과의 분산 분석(ANOVA)을 통해 합성 온도 및 시간이 MOF-235의 결정도에 중요한 영향을 미친다는 것을 분석하였다. 이후, 중심합성 계획법을 이용하여 아세틸렌 흡착성능 최적화를 MOF-235의 선정된 합성 조건을 바탕으로 수행하였다. 설계된 9번의 흡착실험을 통해 도출된 결과를 2차 모델 방정식을 이용하여 계산하였다. 아세틸렌의 최대 흡착 용량(18.7 mmol/g)은 86.3 ℃ 및 28.7 h의 최적의 조건에서 합성된 MOF-235에서 얻을 수 있다고 예측하였다.
A sequential design of experiments was employed to optimize MOF-235 synthesis for acetylene adsorption process. Two experimental designs were applied: a two-level factorial design for screening and a central composite design, one of response surface methodologies (RSM). In this study, 23 factorial design of experiment was used to evaluate the effect of parameters of synthesis temperature and time, and also mixing speed on crystallinity of MOF-235. Experiments were conducted 16 times follwing MINITAB 19 design software for MOF-235 synthesis. Half-normal, pareto, residual, main and interaction effects were drawn based on the XRD results. The analysis of variance (ANOVA) of test results depicts that the synthesis temperature and time have significant effects on the crystallinity of MOF-235 (response variable). After screening, a central composite design was performed to optimize the acetylene adsorption capacity of MOF-235 based on synthesis conditions. From nine runs designed by MINITAB 19, the result was calculated using the second order model equation. It was estimated that the maximum adsorption capacity (18.7 mmol/g) was observed for MOF-235 synthesized at optimum conditions of 86.3 ℃ and 28.7 h.
- Fisher RA, The Design of Experiments, 8-58, 8th ed., Hafner Publishing Company, New York, USA (1966).
- Fisher RA, Yates F, Statistical Tables for Biological, Agricultural, and Medical Research, 10-30, 4th ed., Oliver and Boyd, Edinburgh, UK (1953).
- Box GEP, Wilson KG, J. R. Stat. Soc., 13, 1 (1951)
- Taguchi G, Wu Y, Introduction to Off-Line Quality Control, 5-50, Central Japan Quality Control Association, Nagoya, Japan (1985).
- Kackar RN, J. Quality Tech., 17, 176 (1985)
- Taguchi G, System of Experimental Design, 5-50, 1st ed., UNIPUB, White Plains, New York, USA (1987).
- Papadopoulou K, Dimitropoulos V, Rigas F, Environ. Prog. Sustain. Energy, 34, 1705 (2015)
- Ranganathan S, Tebbe J, Wiemann L, Sieber V, Process Biochem., 51(10), 1479 (2016)
- Fissore D, Pisano R, Barresi AA, Dry. Technol., 36, 1839 (2008)
- Simon LL, Simone E, Oucherif KA, Comput. Aided Chem. Eng., 41, 215 (2018)
- Anbia M, Hoseini V, Sheykhi S, J. Ind. Eng. Chem., 18(3), 1149 (2012)
- Haque E, Jun JW, Jhung SH, J. Hazard. Mater., 185, 507 (2011)
- Tran NT, Kim D, Yoo KS, Kim J, Bull. Korean Chem. Soc., 40, 112 (2019)
- Tao X, Sun C, Han Y, Huang L, Xu D, Cryst. Eng. Comm., 21, 2541 (2019)
- Chung MG, Yoo KS, Appl. Chem. Eng., 30(5), 615 (2019)
- Nair VN, Pregibon D, Technometrics, 30, 247 (1988)
- Lenth RV, Technometrics, 31, 469 (1989)
- Pan G, Technometrics, 41, 313 (1999)
- Plackett RL, Burman JP, Biometrika, 34, 255 (1946)
- Khajeh M, Food Chem., 129, 1832 (2011)
- Rostamian H, Lotfollahi MN, Period. Polytech. Chem., 60, 93 (2016)
- LotfizadehDehkordi B, Ghadimi A, Metselaar HSC, J. Nanopart. Res., 15, 1 (2013)