Predictive Molecular Models for Charged Materials Systems: From Energy Materials to Biomacromolecules

Area of Science:

• Materials Science
• Computational Chemistry
• Biophysics

Background:

• Electrostatic interactions are crucial in charged materials systems.
• Interfaces in charged systems (e.g., electrode-electrolyte, biological membranes) add complexity to understanding structure-property relationships.
• Rational design of advanced materials requires deep understanding of these systems.

Purpose of the Study:

• To provide an overview of recent advances in understanding charged interfacial systems using predictive molecular simulations.
• To highlight how molecular models characterize interfacial properties in energy materials and biomacromolecules.
• To foster interdisciplinary research between energy materials and biological science.

Main Methods:

• Utilizing predictive molecular simulations founded in fundamental physics.
• Optimizing simulations for charged interfacial systems.
• Analyzing ion structure, charge transport, morphology, and molecular binding thermodynamics/kinetics at interfaces.

Main Results:

• Molecular simulations provide molecular-level understanding of physicochemical properties and functional mechanisms.
• Characterization of ion behavior, charge dynamics, and environmental influences at interfaces.
• Detailed analysis of molecular binding at interfaces in energy and biological contexts.

Conclusions:

• Predictive molecular simulations are valuable tools for studying complex charged interfacial systems.
• Recent advances enable a deeper understanding of materials relevant to both energy and biological applications.
• Bridging the fields of energy materials and biological science through a common simulation perspective is encouraged.