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• W4213431027 abstract "The Poisson-Boltzmann equation offers an efficient way to study electrostatics in molecular settings. Its numerical solution with the boundary element method is widely used, as the complicated molecular surface is accurately represented by the mesh, and the point charges are accounted for explicitly. In fact, there are several well-known boundary integral formulations available in the literature. This work presents a generalized expression of the boundary integral representation of the implicit solvent model, giving rise to new forms to compute the electrostatic potential. Moreover, it proposes a strategy to build efficient preconditioners for any of the resulting systems, improving the convergence of the linear solver. We perform systematic benchmarking of a set of formulations and preconditioners, focusing on the time to solution, matrix conditioning, and eigenvalue spectrum. We see that the eigenvalue clustering is a good indicator of the matrix conditioning, and show that they can be easily manipulated by scaling the preconditioner. Our results suggest that the optimal choice is problem-size dependent, where a simpler direct formulation is the fastest for small molecules, but more involved second-kind equations are better for larger problems. We also present a fast Calderón preconditioner for first-kind formulations, which shows promising behavior for future analysis. This work sets the basis towards choosing the most convenient boundary integral formulation of the Poisson-Boltzmann equation for a given problem." @default.
• W4213431027 created "2022-02-25" @default.
• W4213431027 creator A5012516851 @default.
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• W4213431027 date "2022-02-24" @default.
• W4213431027 modified "2023-10-18" @default.
• W4213431027 title "Towards optimal boundary integral formulations of the <scp>Poisson–Boltzmann</scp> equation for molecular electrostatics" @default.
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• W4213431027 doi "https://doi.org/10.1002/jcc.26825" @default.
• W4213431027 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/35201634" @default.
• W4213431027 hasPublicationYear "2022" @default.
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