Optimization of Fluoride Adsorption on Bone Char with Response Surface Methodology (RSM)

반응표면분석법(RSM)을 이용한 골탄의 불소 흡착 조건 최적화

  • Hwang, Jiyun (Department of Environmental Engineering, Chungnam National University) ;
  • Rachana, Chhuon (Department of Environmental Engineering, Chungnam National University) ;
  • Dsane, Victory FiiFi (Department of Environmental Engineering, Chungnam National University) ;
  • Kim, Junyoung (Department of Environmental Engineering, Chungnam National University) ;
  • Choi, Younggyun (Department of Environmental Engineering, Chungnam National University) ;
  • Shin, Gwyam (Department of Environmental and safety Engineering, Ajou University)
  • Received : 2019.08.01
  • Accepted : 2019.11.01
  • Published : 2019.11.20

Abstract

The Box-Benhken Design (BBD) model of response surface methodology (RSM) was used to optimize fluoride adsorption conditions in water using a 350℃ thermally treated cow bone. Water temperature, pH, contact time, and initial fluoride concentration were selected as variables to be optimized. A second order reaction equation was obtained from a Box-Behnken Design DoE experimental matrix of 29 runs. R2 and p-value of the model were 0.9242 and <0.0001, respectively, indicating that the selected variables had a very substantial effect on the adsorption results. The optimized adsorption capacity of the thermally synthesized bone char was estimated to be 6.46 mgF/g at the water temperature of 39.68℃, pH 6.25, contact time of 88.81 minutes and an initial fluorine concentration of 14.64 mgF/L.

반응표면분석법(Response surface methodology, RSM)의 Box-Benhken Design (BBD) 모델을 사용하여, 350℃로 가열한 골탄의 수중 불소 흡착 조건을 최적화하였다. 최적화 변수로 수온, pH, 접촉시간, 초기불소농도를 선택하였고, Box-Behnken Design에 의한 29회의 매트릭스 실험값으로부터 2차 반응 표면식을 얻었다. 이 반응 모델식의 결정계수(R2)는 0.9249였고 모델의 p-value는 <0.0001로 나타나 실험 변수들이 흡착결과에 매우 유의미한 영향을 미친다는 것을 알 수 있었다. 반응 표면식에 의해 예측된 골탄의 불소 흡착 최적 조건은 수온 39.68℃, pH 6.25, 접촉시간 88.81 min, 초기불소농도 14.64 mgF/L이었으며 이때의 불소 흡착용량(adsorption capacity)은 6.46 mgF/g인 것으로 분석되었다.

Keywords

Acknowledgement

본 연구는 한국연구재단(과제번호: 2017K1A3A9A04013880)과 충남대학교 연구 우수 장학금의 지원을 받아 연구 되었습니다.