Use of CuO Particles as an Interface in LC-FTIR Analysis

Yan, Li; Guo, Ruyan; Liu, Shengnan; He, Aiyong; Bao, Yongping; Weng, Shifu; Huang, Yan‐Hua; Xu, Yizhuang; Ozaki, Yukihiro; Noda, Isao; Wu, Jinguang

doi:10.2116/analsci.33.105

Cited by 4 publications

(1 citation statement)

References 25 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Parallel factor analysis (PARAFAC) 61,62 of dimensionality reduction for multi-dimensional array data is included in the scikit-tensor-py3 (sktensor) 63 library. Such multi-dimensional array data are obtained in many different types of instrumental analyses through hyphenated techniques, e.g., GC-MS, [64][65][66] LC-MS, [67][68][69] LC-Vis, 37,70 LC-IR, 71,72 TG-IR, 73,74 etc., as well as fluorescence excitation-emission matrix (EEM) spectroscopy, 75,76 hyperspectral imaging, 77,78 microscopic spectroscopy, 36,79,80 etc.…”

Section: Dimensionality Reductionmentioning

confidence: 99%

Chemometrics and Related Fields in Python

Morita

2019

ANAL. SCI.

View full text Add to dashboard Cite

The Python programing language is becoming a promising tool for data analysis in various fields. However, little attention has been paid to using Python in the field of analytical chemistry, though recent advances in instrumental analysis require robust and reliable data analysis. In order to overcome the difficulty in accurate analysis, multivariate analysis, or chemometrics, has been widely applied to various kinds of data obtained by instrumental analysis. In the present work, the potential usefulness of Python for chemometrics and related fields in chemistry is reviewed. Many practical tools for chemometrics, e.g., principal component analysis (PCA), partial least squares (PLS), support vector machine (SVM), etc., are included in the scikit-learn machine learning (ML) library for Python. Other useful libraries such as pyMCR for multivariate curve resolution (MCR), 2Dpy for two-dimensional correlation spectroscopy (2D-COS), etc. can be obtained from GitHub. For these reasons, a computational environment for chemometrics is easily constructed in Python.

show abstract