Journal of Chemometrics

Aims & Scope✦ Inferred from recent articles

The Journal of Chemometrics focuses on the development and application of mathematical and statistical methods for the analysis of chemical data. Recent articles highlight the use of techniques such as principal component analysis (PCA), partial least squares (PLS) regression, and machine learning (including deep learning and graph neural networks) for tasks like spectral unmixing, multivariate calibration, classification, and molecular property prediction. Applications span diverse fields including spectroscopy (hyperspectral, FTIR, NIR, Raman), electrochemistry, and environmental monitoring, with an emphasis on improving robustness, interpretability, and prediction accuracy in complex datasets.

AI-summarised from recent articles · verify on publisher page →

Based on the Think.Check.Submit framework by DOAJ, COPE & OASPA. All data from verified open sources.

Source: OpenAlex · Each year’s green bar = citations earned by that year’s papers, counted to date — so recent years look lower simply because their papers haven’t had time to be cited yet.

SJR Quartile by Discipline

Scimago ranks this journal separately in each subject category — its quartile can differ by discipline.

Subject Classification