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A nonlinear regression model applied to kinetic multi‐component analysis of esters with a SAW‐impedance sensor
Author(s) -
QingYun Cai,
Li Peng,
RongHui Wang,
LiHua Nie,
ShouZhuo Yao
Publication year - 1996
Publication title -
chinese journal of chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.28
H-Index - 41
eISSN - 1614-7065
pISSN - 1001-604X
DOI - 10.1002/cjoc.19960140607
Subject(s) - chemistry , kinetic energy , nonlinear regression , electrical impedance , conductance , hydrolysis , alkaline hydrolysis , methyl acetate , component (thermodynamics) , detection limit , nonlinear system , analytical chemistry (journal) , linear regression , chromatography , regression analysis , organic chemistry , thermodynamics , catalysis , statistics , physics , mathematics , quantum mechanics , combinatorics , electrical engineering , engineering
A kinetic nonlinear regression model for multi‐component assay of esters was proposed based on their different alkaline‐catalysed hydrolysis rate. The reaction rate was determined by monitoring the conductance change in solution with a liquid‐purpose surface acoustic wave impedance sensor(SAW). The model was tested theoretically and experimentally with the mixture of methyl acetate and n ‐propyl acetate. The experimental detection limit of methyl acetate and n ‐propyl acetate (within 10 min) was 0.5 μmol/L and 1.0 μmol/L respectively and the recovery of the sensor system ranged from 93% to 106% ( n =6).