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Continuous Charge Distributions

Continuous Charge Distributions

Imagine a bucket of water. It contains many molecules, of the order of 1026 molecules. Thus, although it contains discrete elements (molecules) at the microscopic level, macroscopically, it can be considered continuous. Small volume elements of water, infinitesimal compared to the bulk of the bucket's volume, still contain many molecules. Under this framework, quantized matter is approximated as continuous for practical purposes.
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Related Experiment Video

Updated: Aug 6, 2025

Finite Element Modelling of a Cellular Electric Microenvironment

Finite Element Modelling of a Cellular Electric Microenvironment

Published on: May 18, 2021

Profiling charge transport: A new computational approach.

Ibrahim Maqboul¹

¹Computer Chemistry Center (CCC), Department of Chemistry and Pharmacy, Faculty of Sciences, Friedrich-Alexander-University, Nägelsbachstraße 25, 91052 Erlangen, Germany..

International Journal of Biological Macromolecules

|March 22, 2023

Summary

Efficient charge transfer is vital for life. This study presents a novel computational method to accurately predict electron and hole transport pathways and energies in biological systems.

Keywords:

Androstane Azurin Cytochrome C peroxidase Dijkstra algorithm Electron transport Hole-hopping Ionization Metropolis Monte-Carlo

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Finite Element Modelling of a Cellular Electric Microenvironment

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Characterizing Electron Transport through Living Biofilms

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Scanning-probe Single-electron Capacitance Spectroscopy

Scanning-probe Single-electron Capacitance Spectroscopy

Published on: July 30, 2013

Area of Science:

Biophysics
Computational Chemistry
Biochemistry

Background:

Efficient charge transfer is essential for biological processes.
Existing methods struggle to accurately predict charge transport pathways and energetics.

Purpose of the Study:

To develop and validate a computational approach for calculating charge transport pathways and free-energy profiles.
To accurately determine electronic coupling and charge transport rates in biological molecules.

Main Methods:

Utilized local ionization and affinity energies to compute electron and hole transport pathways.
Employed Monte Carlo simulations to identify charge transport terminals when the acceptor is unknown.
Applied Marcus theory and configuration interaction for rate and electronic coupling calculations.

Main Results:

The model accurately predicts charge transport pathways and free-energy profiles within 0.1 eV of experimental measurements.
Electronic coupling was calculated with high precision, within 3 meV.
Demonstrated the method's efficacy on androstane, azurin protein, and cytochrome c peroxidase.

Conclusions:

The developed computational model provides an effective and accurate means to study charge transport in biological systems.
This approach enhances our understanding of electron and hole migration crucial for life's processes.