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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...

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Detalles Bibliográficos
Autores principales: Firaha, Dzmitry S., Döntgen, Malte, Berkels, Benjamin, Leonhard, Kai
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2018
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
Descripción
Sumario:[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.