Dissipation + Utilization = Self-Organization (A Summary)
Has anyone not looked around in awe of nature’s creations? The biosphere displays incredible complexity, and it continues to adapt and evolve. The biosphere’s state is highly organized and far from equilibrium, and this makes it thermodynamically unstable. The biosphere’s stability clearly does not arise from its state, which is unstable. Its stability arises instead from its process of utilizing the sun’s energy.
The sun’s energy has enabled the biosphere to self-organize itself into enormously complex structures at multiple scales. Biological self-organization ranges from cells, with their networks of chemical transitions, to ecosystems, with their networks of interacting species. Plants provide the base for the solar powered biosphere. The biosphere also has herbivores, predators, scavengers, and degraders. Each plays an essential role in an ecosystem’s function. Without a source of energy and without a stable process of utilizing it, a complex system’s state would have nothing to sustain it, and it would fade into the ambient background. The stability of a dissipative system, such as the biosphere, is sustained by deferring dissipation and by utilizing energy to maintain the system’s function.
A dissipative system’s state may be far from equilibrium and unstable, but inspection of a system’s stabilizing process reveals its tendency to spread energy transitions out over many steps. Inspection further reveals that each step of an overall process approaches thermodynamic balance, minimum dissipation, and maximum efficiency. I refer to this tendency toward maximum efficiency as MaxEff, and in my published article [1], I propose it as a general principle of nature. However, it is one thing to recognize nature’s efficiency; it is quite another to define it.
The challenge with defining efficiency and the stability of processes is that physics and thermodynamics are focused on states. Physics and thermodynamics are the most fundamental descriptions of nature. They underlie all of the natural sciences and much of the social sciences, and they ignore what is really important — the role of processes in stabilizing far-from-equilibrium dissipative systems (living or non-living).
Physics — classical, quantum, and relativistic — all fail to recognize the dissipation of energy or the efficiency of its utilization. It reduces thermodynamics to statistical mechanics. Statistical mechanics can describe the steps in forming a complex molecule or the transition of a heated liquid from conduction to organized convective heat flow. Physics and thermodynamics cannot, however, explain in general terms or principles why convection or macromolecules form. Physics has no concept of irreversible process; thermodynamics recognizes irreversible process, but it has no concept of its stabilizing role.
Defining efficiency requires an infrastructure and conceptual framework in which the dissipation and utilization of energy can be defined. In an earlier article I proposed the thermocontextual interpretation (TCI) [2,3] as an axiom-based conceptual framework. It allows formal definitions of dissipative systems and their evolution.
The TCI has two key innovations that set it apart from physics as we know it. The first innovation is defining a state thermocontextually. This means defining the state with respect to a reference state that is in equilibrium with the system’s actual surroundings at a positive ambient temperature. The addition of the surroundings’ ambient temperature as a thermocontextual property changes everything.
A positive ambient reference temperature resolves a system’s energy into exergy (potential work on the ambient surroundings) and entropic energy (ambient heat), having zero work potential. The TCI introduces values to physics by defining energy both by its quantity and by its quality (exergy).
This innovation allows TCI to integrate the mechanical and thermodynamic descriptions of states into a more generalized thermocontextual framework. A positive ambient temperature of the surroundings also means that perfect measurements of energy and space have finite resolution.
TCI’s second innovation is the explicit rejection of hidden variables. “No unobservable properties of state” means, ipso facto, that the state is completely defined by perfect measurement from the ambient surroundings. “No hidden variables” means that the finite resolution of perfect measurement applies not just to the measurements, but to the physical system itself, which is therefore quantized.
The no-hidden-variables postulate also applies to processes. The TCI resolves a dissipative process into elementary transitions, which cannot be resolved into smaller transitions. The TCI describes a dissipative process as a network of elementary transition nodes and links. It defines utilization as the sum of measurable work and exergy transfers between the network’s nodes. The TCI defines efficiency by the ratio of utilization and exergy input. The MaxEff principle states that a dissipative system evolves by preferentially selecting dissipative processes with higher efficiency. With feedback loops and recycling of exergy, a dissipative network’s efficiency can exceed one hundred percent, with no theoretical limit.
Exergy is a measure of energy’s usefulness and a measure of its value. The efficiency of a dissipative system’s process is a measure of its value. Nature values high-exergy energy sources and it values efficient utilization of exergy. A dissipative system can increase its exergy resource base through competition and growth. It can increase its functional complexity through coordination of the networked dissipators to increase recycling and efficiency. Efficiency is a measurable and well-defined property of process, and it is a measure of functional complexity.
The TCI introduces irreversible dissipation and values as thermocontextual properties. These are essential to get beyond the mere description of complex systems, to an explanation of their evolution in terms of general principles. Given a stable environment, MaxEff drives a dissipative system to spontaneously expand to the carrying capacity of its environment, and to spontaneously evolve toward higher functional complexity, with no theoretical limit. MaxEff is a general principle of nature, and it can be applied to any non-equilibrium system, physical, chemical, biological, social, neural-network, or economic.
[1] Dissipation + Utilization = Self-Organization https://www.mdpi.com/1099-4300/25/2/229
[2] Time and Causality: A Thermocontextual Perspective https://www.mdpi.com/1099-4300/23/12/1705
[3] A Thermocontextual Perspective — Reimagining Physics Part 3 https://harrison-69935.medium.com/d95313ccd709
