Journal
CRYSTAL GROWTH & DESIGN
Volume -, Issue -, Pages -Publisher
AMER CHEMICAL SOC
DOI: 10.1021/acs.cgd.2c01133
Keywords
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Funding
- European Research Council (ERC) under the European Unions Horizon 2020 Research and Innovation Program [788607]
- Janssen Pharmaceutical Companies of Johnson Johnson
- European Research Council (ERC) [788607] Funding Source: European Research Council (ERC)
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This work presents a generalized framework to assess the accuracy of methods for estimating primary and secondary nucleation rates. Simulation of the crystallization process was conducted using a novel stochastic modeling methodology. It was found that deterministic methods tend to overpredict rates in the presence of secondary nucleation, while stochastic methods were accurate irrespective of secondary nucleation. A criterion was proposed to evaluate the accuracy of stochastic methods. Additionally, the study showed how deterministic and stochastic considerations can be combined to infer both primary and secondary nucleation rates.
This work presents a generalized framework to assess the accuracy of methods to estimate primary and secondary nucleation rates from experimental data. The crystallization process of a well-studied model compound was simulated by means of a novel stochastic modeling methodology. Nucleation rates were estimated from the simulated data through multiple methods and were compared with the true values. For primary nucleation, no method considered in this work was able to estimate the rates accurately under general conditions. Two deterministic methods that are widely used in the literature were shown to overpredict rates in the presence of secondary nucleation. This behavior is shared by all methods that extract rates from deterministic process attributes, as they are insensitive to primary nucleation if secondary nucleation is sufficiently fast. Two stochastic methods were found to be accurate independent of whether secondary nucleation is present, but they underestimated rates in the case where a large number of primary nuclei are formed. We hence proposed a criterion to probe the accuracy of stochastic methods for arbitrary data sets, thus providing the theoretical foundations required for their rational use. Finally, we showed how both primary and secondary nucleation rates can be inferred from the same set of detection time data by combining deterministic and stochastic considerations.
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