KiMoPack : A python Package for Kinetic Modeling of the Chemical Mechanism
(2022) In Journal of Physical Chemistry A 126(25). p.4087-4099- Abstract
Herein, we present KiMoPack, an analysis tool for the kinetic modeling of transient spectroscopic data. KiMoPack enables a state-of-the-art analysis routine including data preprocessing and standard fitting (global analysis), as well as fitting of complex (target) kinetic models, interactive viewing of (fit) results, and multiexperiment analysis via user accessible functions and a graphical user interface (GUI) enhanced interface. To facilitate its use, this paper guides the user through typical operations covering a wide range of analysis tasks, establishes a typical workflow and is bridging the gap between ease of use for less experienced users and introducing the advanced interfaces for experienced users. KiMoPack is open source and... (More)
Herein, we present KiMoPack, an analysis tool for the kinetic modeling of transient spectroscopic data. KiMoPack enables a state-of-the-art analysis routine including data preprocessing and standard fitting (global analysis), as well as fitting of complex (target) kinetic models, interactive viewing of (fit) results, and multiexperiment analysis via user accessible functions and a graphical user interface (GUI) enhanced interface. To facilitate its use, this paper guides the user through typical operations covering a wide range of analysis tasks, establishes a typical workflow and is bridging the gap between ease of use for less experienced users and introducing the advanced interfaces for experienced users. KiMoPack is open source and provides a comprehensive front-end for preprocessing, fitting and plotting of 2-dimensional data that simplifies the access to a powerful python-based data-processing system and forms the foundation for a well documented, reliable, and reproducible data analysis.
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- author
- Müller, Carolin ; Pascher, Torbjörn LU ; Eriksson, Axl LU ; Chabera, Pavel LU and Uhlig, Jens LU
- organization
- publishing date
- 2022-06-30
- type
- Contribution to journal
- publication status
- published
- subject
- in
- Journal of Physical Chemistry A
- volume
- 126
- issue
- 25
- pages
- 13 pages
- publisher
- The American Chemical Society (ACS)
- external identifiers
-
- scopus:85133148607
- pmid:35700393
- ISSN
- 1089-5639
- DOI
- 10.1021/acs.jpca.2c00907
- language
- English
- LU publication?
- yes
- id
- 4307369b-e083-4106-bf97-8cde9249c5c6
- date added to LUP
- 2022-09-13 15:12:03
- date last changed
- 2024-06-13 19:23:46
@article{4307369b-e083-4106-bf97-8cde9249c5c6, abstract = {{<p>Herein, we present KiMoPack, an analysis tool for the kinetic modeling of transient spectroscopic data. KiMoPack enables a state-of-the-art analysis routine including data preprocessing and standard fitting (global analysis), as well as fitting of complex (target) kinetic models, interactive viewing of (fit) results, and multiexperiment analysis via user accessible functions and a graphical user interface (GUI) enhanced interface. To facilitate its use, this paper guides the user through typical operations covering a wide range of analysis tasks, establishes a typical workflow and is bridging the gap between ease of use for less experienced users and introducing the advanced interfaces for experienced users. KiMoPack is open source and provides a comprehensive front-end for preprocessing, fitting and plotting of 2-dimensional data that simplifies the access to a powerful python-based data-processing system and forms the foundation for a well documented, reliable, and reproducible data analysis.</p>}}, author = {{Müller, Carolin and Pascher, Torbjörn and Eriksson, Axl and Chabera, Pavel and Uhlig, Jens}}, issn = {{1089-5639}}, language = {{eng}}, month = {{06}}, number = {{25}}, pages = {{4087--4099}}, publisher = {{The American Chemical Society (ACS)}}, series = {{Journal of Physical Chemistry A}}, title = {{KiMoPack : A python Package for Kinetic Modeling of the Chemical Mechanism}}, url = {{http://dx.doi.org/10.1021/acs.jpca.2c00907}}, doi = {{10.1021/acs.jpca.2c00907}}, volume = {{126}}, year = {{2022}}, }