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3-Newcomer
Apr 3, 2023 1:45 AM UTC
Solved

Mathcad-how to fit and optimize two objective functions

Hi guys, I`m a student major in chemistry. Recently, i`m confused this this interpretation, The equation"The method proposed here for determining the kinetic parameters is a multistage procedure. First, the Pearsons linear correlation coefficient between the left-hand side of eq 15 and the reciprocal of temperature is used as the objective functionfor optimization, where n and m are the variable parameters to maximize the objective function. Here, optimization has been performed by means of the maximize function of Mathcad software (Mathsoft inc.). By this optimization procedure, the n  and m parameters that yield the best linear correlation for the plot of the left-hand side of eq 15 versus the reciprocal of temperature are obtained".  The equation is shown below. So I was wondering how can I implement this derivation through Mathcad.

equation.png

 

 

 

24-Ruby IV
Apr 7, 2023 3:58 PM UTC

5 replies

terryhendicott
21-Topaz II
Apr 3, 2023 3:17 AM UTC

Hi,

Need some data to work with.

Can you tell us the paper that the quotes come from?

Cheers

Terry

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3-Newcomer
Apr 3, 2023 3:29 AM UTC

Thanks for you reply, the paper was titled Combined Kinetic Analysis of Solid-State Reactions: A Powerful Tool for the Simultaneous

Determination of Kinetic Parameters and the Kinetic Model without Previous Assumptions on the Reaction Mechanism from https://pubs.acs.org/doi/10.1021/jp064792g#

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terryhendicott
21-Topaz II
Apr 3, 2023 4:50 PM UTC

Hi,

Downloaded the paper thank you.

Proposing an alternative strategy to multiphase process of optimizing for maximum Pearson's linear correlation coefficient used in the paper.

Prime has a general purpose curve fitting function called genfit() that can fit any function with any number of parameters to x and y data modelled or experimental.

Function genfit() easily produces the model equations parameter c, n, & m values from Table 1 of the paper

Cheers

Terry 

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24-Ruby IV
Apr 7, 2023 3:58 PM UTC