Statistical Inference for Ergodic Algorithmic Model (EAM), Applied to Hydrophobic Hydration Processes

Statistical Inference for Ergodic Algorithmic Model (EAM), Applied to Hydrophobic Hydration Processes

The thermodynamic properties of hydrophobic hydration processes can be represented in probability space by a Dual-Structure Partition Function {<i>DS-PF</i>} = {M<i>-PF</i>} · {<i>T-PF</i>}, which is the product of a Motive Partition Function {M<i>-PF</i&...

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Bibliographic Details
Main Authors: Emilia Fisicaro, Carlotta Compari, Antonio Braibanti
Format: Article
Language:English
Published: MDPI AG 2021-06-01
Series:Entropy
Subjects:
hydrophobic hydration process
ergodic algorithmic model (EAM)
thermal equivalent dilution (TED)
binding potential functions
intensity entropy
density entropy
Online Access:https://www.mdpi.com/1099-4300/23/6/700

Internet

https://www.mdpi.com/1099-4300/23/6/700

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