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Pressure-Dependent Rate Constant Predictions Utilizing the Inverse Laplace Transform: A Victim of Deficient Input Data
[Image: see text] k(E) can be calculated either from the Rice–Ramsperger–Kassel–Marcus theory or by inverting macroscopic rate constants k(T). Here, we elaborate the inverse Laplace transform approach for k(E) reconstruction by examining the impact of k(T) data fitting accuracy. For this approach, a...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Chemical Society
2018
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6644344/ https://www.ncbi.nlm.nih.gov/pubmed/31458958 http://dx.doi.org/10.1021/acsomega.8b00311 |
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author | Firaha, Dzmitry S. Döntgen, Malte Berkels, Benjamin Leonhard, Kai |
author_facet | Firaha, Dzmitry S. Döntgen, Malte Berkels, Benjamin Leonhard, Kai |
author_sort | Firaha, Dzmitry S. |
collection | PubMed |
description | [Image: see text] k(E) can be calculated either from the Rice–Ramsperger–Kassel–Marcus theory or by inverting macroscopic rate constants k(T). Here, we elaborate the inverse Laplace transform approach for k(E) reconstruction by examining the impact of k(T) data fitting accuracy. For this approach, any inaccuracy in the reconstructed k(E) results from inaccurate/incomplete k(T) description. Therefore, we demonstrate how an improved mathematical description of k(T) data leads to accurate k(E) data. Refitting inaccurate/incomplete k(T), hence, allows for recapturing k(T) information that yields more accurate k(E) reconstructions. The present work suggests that accurate representation of experimental and theoretical k(T) data in a broad temperature range could be used to obtain k(T,p). Thus, purely temperature-dependent kinetic models could be converted into fully temperature- and pressure-dependent kinetic models. |
format | Online Article Text |
id | pubmed-6644344 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | American Chemical Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-66443442019-08-27 Pressure-Dependent Rate Constant Predictions Utilizing the Inverse Laplace Transform: A Victim of Deficient Input Data Firaha, Dzmitry S. Döntgen, Malte Berkels, Benjamin Leonhard, Kai ACS Omega [Image: see text] k(E) can be calculated either from the Rice–Ramsperger–Kassel–Marcus theory or by inverting macroscopic rate constants k(T). Here, we elaborate the inverse Laplace transform approach for k(E) reconstruction by examining the impact of k(T) data fitting accuracy. For this approach, any inaccuracy in the reconstructed k(E) results from inaccurate/incomplete k(T) description. Therefore, we demonstrate how an improved mathematical description of k(T) data leads to accurate k(E) data. Refitting inaccurate/incomplete k(T), hence, allows for recapturing k(T) information that yields more accurate k(E) reconstructions. The present work suggests that accurate representation of experimental and theoretical k(T) data in a broad temperature range could be used to obtain k(T,p). Thus, purely temperature-dependent kinetic models could be converted into fully temperature- and pressure-dependent kinetic models. American Chemical Society 2018-07-24 /pmc/articles/PMC6644344/ /pubmed/31458958 http://dx.doi.org/10.1021/acsomega.8b00311 Text en Copyright © 2018 American Chemical Society This is an open access article published under an ACS AuthorChoice License (http://pubs.acs.org/page/policy/authorchoice_termsofuse.html) , which permits copying and redistribution of the article or any adaptations for non-commercial purposes. |
spellingShingle | Firaha, Dzmitry S. Döntgen, Malte Berkels, Benjamin Leonhard, Kai Pressure-Dependent Rate Constant Predictions Utilizing the Inverse Laplace Transform: A Victim of Deficient Input Data |
title | Pressure-Dependent Rate Constant Predictions Utilizing
the Inverse Laplace Transform: A Victim of Deficient Input Data |
title_full | Pressure-Dependent Rate Constant Predictions Utilizing
the Inverse Laplace Transform: A Victim of Deficient Input Data |
title_fullStr | Pressure-Dependent Rate Constant Predictions Utilizing
the Inverse Laplace Transform: A Victim of Deficient Input Data |
title_full_unstemmed | Pressure-Dependent Rate Constant Predictions Utilizing
the Inverse Laplace Transform: A Victim of Deficient Input Data |
title_short | Pressure-Dependent Rate Constant Predictions Utilizing
the Inverse Laplace Transform: A Victim of Deficient Input Data |
title_sort | pressure-dependent rate constant predictions utilizing
the inverse laplace transform: a victim of deficient input data |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6644344/ https://www.ncbi.nlm.nih.gov/pubmed/31458958 http://dx.doi.org/10.1021/acsomega.8b00311 |
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