title: [Application of three-way data analysis (second-order tensor decomposition) algorithms in analysis of liquid chromatography].
abstract: Using dropline separation, tangent skimming, and triangulation to estimate the area of an overlapping chromatographic peak might contribute to a large deviation. It is easy, however, to eliminate these errors caused by geometric segmentation using three-way data analysis (second-order tensor decomposition) algorithms. This method of chromatographic analysis has many advantages: automation, anti-interference, high accuracy in the resolution of overlapping chrom- atographic peaks. It even makes the final goal of analytical chemistry achievable without the aid of complicated separation procedures. The core of this method is the process of utilizing useful information and building models through chemometric algorithms. Three-way chromatographic data set can be divided into trilinear dataset and nontrilinear dataset, correspondingly, three-way data analysis (second-order tensor decomposition) algorithms can be divided into trilinear algorithms and nontrilinear algorithms. In this paper, three-way calibration used in liquid chromatography for complex chemical systems in the last decade is reviewed, and focused on sample pretreatment, auxiliary algorithms, the combination and comparison of correction algorithms.
authors.forename: Jin
authors.initials: J
authors.lastname: Zhang
authors.forename: Qianrong
authors.initials: Q
authors.lastname: Peng
authors.forename: Longquan
authors.initials: L
authors.lastname: Xu
authors.forename: Min
authors.initials: M
authors.lastname: Yang
authors.forename: Aijing
authors.initials: A
authors.lastname: Wu
authors.forename: Shizhu
authors.initials: S
authors.lastname: Ye