Bayes Rule and Its Probability-Theoretic Applications in Electrocatalytic Reaction Engineering

ABSTRACT

From the notion of connecting prior probability and conditional probability to posterior probability via Bayes rule, Bayesian approaches emerge. The chance of obtaining empirical evidence if the underlying assumptions are correct is used to update the prior probability of an occurrence, which is what the posterior probability is based on. Bayesian approaches have been proven to be more effective than distribution-based strategies where there is no available frequency distribution for the prior probability. Utilizing four numerical examples - a catalytic oxygen cathode, hydrogen evolution on a synthetic metal, the dependability of a device testing the quality of an electrocatalyst, and the spectrum of Tafel slopes exhibited by an electrocatalyst-the paper demonstrates the value of Bayes rule in the analysis of electrocatalytic reactor performance.

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