Bulletin of the American Physical Society
2024 APS March Meeting
Monday–Friday, March 4–8, 2024; Minneapolis & Virtual
Session HH01: V: Statistical and Nonlinear Physics III
11:30 AM–1:06 PM,
Wednesday, March 6, 2024
Room: Virtual Room 01
Sponsoring
Unit:
GSNP
Chair: Joshua Socolar, Duke University
Abstract: HH01.00005 : Investigating Self-Organization in Open, Non-Equilibrium Thermodynamic Systems*
12:18 PM–12:30 PM
Presenter:
Georgi Georgiev
(Assumption University)
Authors:
Georgi Georgiev
(Assumption University)
Matthew Brouillet
(Assumption University)
Central to this investigation is the principle of Maximum Entropy Production (MEP). This principle suggests that such systems evolve toward states that optimize entropy production, leading to the formation of structured environments. It is hypothesized that guided by the least action principle, open thermodynamic systems identify and follow the shortest paths to transmit energy and matter, resulting in maximal entropy production, internal structure formation, and a decrease in internal entropy. Concurrently, it is predicted that there will be an increase in system information as more information is required to describe the developing structure. Of all entropy formulations, it appears that Tsallis Entropy may be one of the most suitable for the investigation of self-organization in open, non-equilibrium thermodynamic systems.
This study provides a novel perspective on the exploration of self-organization in thermodynamic systems, establishing a correlation between internal entropy decrease rate and external entropy production rate. Moreover, it presents a flexible framework for assessing the impact of external factors like changes in world size, path obstacles, and friction.
Overall, this research offers a robust, replicable model for studying self-organization processes in any open thermodynamic system. As such, it provides a foundation for further in-depth exploration of the complex behaviors of these systems and contributes to the development of more efficient self-organizing systems across various scientific fields.
*Assumption University
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