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학술발표회초록보기

초록문의 abstract@kcsnet.or.kr

결제문의 member@kcsnet.or.kr

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제114회 대한화학회 학술발표회, 총회 및 기기전시회 안내 In silico Prediction of critical micelle concentrations for gemini surfactants

등록일
2014년 8월 28일 16시 00분 21초
접수번호
1179
발표코드
MAT.P-1132 이곳을 클릭하시면 발표코드에 대한 설명을 보실 수 있습니다.
발표시간
10월 15일 (수요일) 16:00~19:00
발표형식
포스터
발표분야
재료화학
저자 및
공동저자
이민지, 진은실, 이성광*
한남대학교 화학과, Korea
Gemini surfactants are composed of two monomeric surfactant molecules linked by a spacer chain. gemini surfactants can self-assemble at concentrations almost a hundred-fold lower than that of corresponding conventional surfactants. Also, unlike conventional surfactants, gemini surfactants have unique properties because of the high surface tension lowering ability, good solubility for water. This study aimed to predict critical micelle concentration(CMC) of gemini surfactant by using a quantitative structure-property relationship(QSPR) method. The CMC dataset were collected from a series of 130 gemini surfactants. We tried to calculate each molecular descriptor using PreADMET program from gemini surfactants substructure which subdivided in a various of ways. The forward selection and bootstrap sampling method were applied to determine the optimum descriptor of the multiple linear regression(MLR). It was possible to know the applicable range of the prediction model by applicability domain(AD) of the results of each model. Y-scrambling was performed to confirm chance correlation of the model.

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