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Estimation of the order of a chemical reaction is often at least as important as estimation of the rate of the reaction. Locally optimum experimental designs are found for the order and the rate, separately and together. Compound D-optimum designs provide a method for designing experiments with specified efficiency for rate or order determination. A relationship between the compound designs and D-optimum designs for both rate and order aids interpretation of the plots of design efficiencies. Bayesian designs incorporating prior uncertainty are exemplified. Monte Carlo sampling of the prior is used to design an experiment for the esterification of acetic anhydride.
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