Analytical Figures of Merit: From Univariate to Multiway Calibration

被引:275
|
作者
Olivieri, Alejandro C. [1 ]
机构
[1] Univ Nacl Rosario, Fac Ciencias Bioquim & Farmaceut, Dept Quim Analit, Inst Quim Rosario IQUIR CONICET, RA-2000 Rosario, Santa Fe, Argentina
关键词
POTENTIOMETRIC SELECTIVITY COEFFICIENTS; PARALLEL FACTOR-ANALYSIS; PARTIAL LEAST-SQUARES; TRILINEAR DECOMPOSITION ALGORITHM; POLYCYCLIC AROMATIC-HYDROCARBONS; EMISSION MATRIX FLUORESCENCE; INTERFERENCE-FREE ANALYSIS; MULTIVARIATE SELECTIVITY; 2ND-ORDER CALIBRATION; ANALYTICAL-CHEMISTRY;
D O I
10.1021/cr400455s
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
The search for new ways to improve analytical figures of merit is an important driving force in modern analytical chemistry research, with the sensitivity occupying one of the prominent places among these figures. Whether the purpose is the comparison of the performance of different experimental procedures or the optimization of a given methodology under various experimental conditions, a consistent numerical sensitivity parameter is required in order to judge about the real improvement obtained from various experimental strategies. Analytical figures of merit are an integral part of official protocols of analysis, as documented in international standards. The International Union of Pure and Applied Chemistry (IUPAC) has set sensitivity definitions for various calibration scenarios. What is even more worrying, the plainly extrapolated expressions to data arrays with higher number of modes appeared to lead to a serious underestimation of true sensitivities.
引用
收藏
页码:5358 / 5378
页数:21
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