Factor analysis of error in oxidation potential calculation: A machine learning study.

The conductor-like polarizable continuum model (C-PCM), which is a low-cost solvation model, cannot treat characteristic interactions between the solvent and substructure(s) of the solute. Moreover, the error in a charged system is significant. Using machine learning, we clarified that the systematic error of the oxidation potential calculated by the G3B3/C-PCM was correlated with the molecular size of a solute. The G3B3/C-PCM overestimated the Gibbs oxidation energy by averaging 6.94 kcal/mol. According to the performance of related methods reported in previous studies, this error is mainly due to the solvation energy of the charged solute. Additionally, we succeeded in reducing the error to 2.27 kcal/mol (32%)-3.2 kcal/mol (40%) by correction based on the substructure information of the solute. To modify the C-PCM, effects that correlate with the molecular size of the solute in the charged system should be incorporated.

Magnetic probe array with high sensitivity for fluctuating field.

A magnetic probe array is constructed to measure precisely the spatial structure of a small fluctuating field included in a strong confinement field that varies with time. To exclude the effect of the confinement field, the magnetic probes consisting of figure-eight-wound coils are prepared. The spatial structure of the fluctuating field is obtained from a Fourier analysis of the probe signal. It is found that the probe array is more sensitive to the fluctuating field with a high mode number than that with a low mode number. An experimental demonstration of the present method is attempted using a field-reversed configuration plasma, where the fluctuating field with 0.1% of the confinement field is successfully detected.