Chemometrics and Intelligent Laboratory Systems

Aims & Scope

Chemometrics and Intelligent Laboratory Systems publishes original research papers, short communications, reviews, tutorials and Original Software Publications reporting on development of novel statistical, mathematical, or computer techniques in Chemistry and related disciplines.

Chemometrics is the chemical discipline that uses mathematical and statistical methods to design or select optimal procedures and experiments, and to provide maximum chemical information by analysing chemical data.

The journal deals with the following topics: 1) Development of new statistical, mathematical and chemometrical methods for Chemistry and related fields (Environmental Chemistry, Biochemistry, Toxicology, System Biology, -Omics, etc.) 2) Novel applications of chemometrics to all branches of Chemistry and related fields (typical domains of interest are: process data analysis, experimental design, data mining, signal processing, supervised modelling, decision making, robust statistics, mixture analysis, multivariate calibration etc.) Routine applications of established chemometrical techniques will not be considered. 3) Development of new software that provides novel tools or truly advances the use of chemometrical methods. 4) Well characterized data sets to test performance for the new methods and software.

The journal complies with International Committee of Medical Journal Editors' Uniform requirements for manuscripts.

View Aims & Scope

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Metrics & Ranking

Impact Factor

Year	Value
2025	3.8
2024	3.70

Journal Rank

Year	Value
2024	8779

Journal Citation Indicator

Year	Value
2024	2385

SJR (SCImago Journal Rank)

Year	Value
2024	0.654

Quartile

Year	Value
2024	Q2

h-index

Year	Value
2024	150

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Abstracting & Indexing

Journal is indexed in leading academic databases, ensuring global visibility and accessibility of our peer-reviewed research.

• Scopus
• Google Scholar
• Web of Science
• Embase

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Subjects & Keywords

Journal’s research areas, covering key disciplines and specialized sub-topics in Chemical Engineering, Chemistry and Computer Science, designed to support cutting-edge academic discovery.

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Most Cited Articles

The Most Cited Articles section features the journal's most impactful research, based on citation counts. These articles have been referenced frequently by other researchers, indicating their significant contribution to their respective fields.

• Principal component analysis

  Citation: 9355

  Authors: Svante, Kim, Paul

• PLS-regression: a basic tool of chemometrics

  Citation: 7841

  Authors: Svante, Michael, Lennart

• PARAFAC. Tutorial and applications

  Citation: 2403

  Authors: Rasmus

• The Mahalanobis distance

  Citation: 1864

  Authors: R., D., D.L.

• Performance of some variable selection methods when multicollinearity is present

  Citation: 1697

  Authors: Il-Gyo, Chi-Hyuck

• Least squares formulation of robust non-negative factor analysis

  Citation: 1593

  Authors: Pentti

• SIMPLS: An alternative approach to partial least squares regression

  Citation: 1532

  Authors: Sijmen

• Particle swarm optimization (PSO). A tutorial

  Citation: 1424

  Authors: Federico, Beata

• A review of variable selection methods in Partial Least Squares Regression

  Citation: 1353

  Authors: Tahir, Kristian Hovde, Lars, Solve

• Disturbance detection and isolation by dynamic principal component analysis

  Citation: 1273

  Authors: Wenfu, Robert H., Christos

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