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Cited by 600

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Structure, Energy, Synergy, Time—The Fundamentals of Process Intensification

Van Gerven, Tom, Stankiewicz, Andrzej·2009·Industrial & Engineering Chemistry Research

Abstract

Process intensification (PI) is commonly seen as one of the most promising development paths for the chemical process industry and one of the most important progress areas for modern chemical engineering. Often illustrated with spectacular examples, process intensification struggles, however, with its definition and interpretation. Instead of narrowing the scientific discussion down to finding a commonly accepted definition of PI, it is more important to determine its position within chemical engineering and to identify its fundamentals. Accordingly, the paper presents a fundamental vision on process intensification. The vision encompasses four approaches in spatial, thermodynamic, functional, and temporal domains, which are used to realize four generic principles of PI. The approaches refer to all scales existing in chemical processes, from molecular to meso- and macroscale, and are illustrated with relevant examples with special attention given to the molecular scale.

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Metadata

Authors
Van Gerven, T., & Stankiewicz, A.
Venue
Industrial & Engineering Chemistry Research
Published
2009-02-09
Volume
48
Issue
5
Pages
2465-2474
ISSN
  • 0888-5885 (ISSN-L)
  • 1520-5045
OpenAlex
W2041938303
Cited by
600
References
0
FWCI
44.58
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Structure, Energy, Synergy, Time—The Fundamentals of Process Intensification. https://app.cochat.ai/papers/10.1021/ie801501y
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Van Gerven, T., & Stankiewicz, A. (2009). Structure, Energy, Synergy, Time—The Fundamentals of Process Intensification. Industrial & Engineering Chemistry Research. https://doi.org/10.1021/ie801501y

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.