AI Article Synopsis
- We introduce a new method that guarantees finding the best least-squares fit for experimental data using a nonlinear kinetic model.
- This method addresses the limitations of locally optimum fits, providing certainty when data and models seem inconsistent.
- The approach allows for rigorous evaluation of complex kinetic models, aiding in determining their validity against experimental measurements.
Article Abstract
We present the first method guaranteed to find the best possible least-squares (chi2) fit of experimental data by a nonlinear kinetic model. Several important advantages of knowing with certainty the best possible fit rather than a locally optimum fit are discussed and demonstrated using data from the recent literature. This is particularly important when the model and the data appear to be inconsistent. With the new method, one can rigorously demonstrate that a nonlinear kinetic model with several adjustable rate parameters is inconsistent with measured experimental data. The numerical method presented is a valuable tool in evaluating the validity of a complex kinetics model.
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| http://dx.doi.org/10.1021/jp0548873 | DOI Listing |
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