detailed balance principle
E267413
The detailed balance principle is a thermodynamic concept stating that, at equilibrium, every microscopic process is exactly balanced by its reverse process, ensuring no net change in the system’s macroscopic state.
All labels observed (1)
| Label | Occurrences |
|---|---|
| detailed balance principle canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T2443015 — resolving that mention is where its identity was fixed. The disambiguator weighed these candidate entities and picked the highlighted one (or “None”, minting a new entity). This is how homonymy is resolved: the same surface form can point to different entities.
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: detailed balance principle Context triple: [Shockley–Queisser limit, isBasedOn, detailed balance principle]
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A.
d’Alembert’s principle
d’Alembert’s principle is a fundamental concept in classical mechanics that reformulates Newton’s laws to analyze the motion of systems by introducing inertial forces so they can be treated as if in static equilibrium.
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B.
Onsager reciprocal relations
Onsager reciprocal relations are fundamental symmetry relations in nonequilibrium thermodynamics that link pairs of coupled fluxes and forces, showing that certain transport coefficients are equal.
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C.
The Principles of Statistical Mechanics
The Principles of Statistical Mechanics is a classic 1938 textbook by Richard C. Tolman that systematically develops the foundations of statistical mechanics and its applications to thermodynamics and physical chemistry.
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D.
fluctuation–dissipation theorem
The fluctuation–dissipation theorem is a fundamental principle in statistical physics that links the random microscopic fluctuations in a system at thermal equilibrium to its macroscopic response to external perturbations.
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E.
Boltzmann–Gibbs entropy in statistical mechanics
Boltzmann–Gibbs entropy in statistical mechanics is the standard measure of disorder or uncertainty in a system, quantifying how many microscopic configurations correspond to a given macroscopic state and forming the basis of classical equilibrium statistical mechanics.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: detailed balance principle Target entity description: The detailed balance principle is a thermodynamic concept stating that, at equilibrium, every microscopic process is exactly balanced by its reverse process, ensuring no net change in the system’s macroscopic state.
-
A.
d’Alembert’s principle
d’Alembert’s principle is a fundamental concept in classical mechanics that reformulates Newton’s laws to analyze the motion of systems by introducing inertial forces so they can be treated as if in static equilibrium.
-
B.
Onsager reciprocal relations
Onsager reciprocal relations are fundamental symmetry relations in nonequilibrium thermodynamics that link pairs of coupled fluxes and forces, showing that certain transport coefficients are equal.
-
C.
The Principles of Statistical Mechanics
The Principles of Statistical Mechanics is a classic 1938 textbook by Richard C. Tolman that systematically develops the foundations of statistical mechanics and its applications to thermodynamics and physical chemistry.
-
D.
fluctuation–dissipation theorem
The fluctuation–dissipation theorem is a fundamental principle in statistical physics that links the random microscopic fluctuations in a system at thermal equilibrium to its macroscopic response to external perturbations.
-
E.
Boltzmann–Gibbs entropy in statistical mechanics
Boltzmann–Gibbs entropy in statistical mechanics is the standard measure of disorder or uncertainty in a system, quantifying how many microscopic configurations correspond to a given macroscopic state and forming the basis of classical equilibrium statistical mechanics.
- F. None of above. chosen
Statements (46)
| Predicate | Object |
|---|---|
| instanceOf |
concept in statistical mechanics
ⓘ
thermodynamic principle ⓘ |
| appliesTo |
microscopic processes
ⓘ
reversible Markov chains ⓘ systems in thermodynamic equilibrium ⓘ |
| assumes |
existence of equilibrium state
ⓘ
reversibility of microscopic dynamics ⓘ |
| category |
physical law
ⓘ
probabilistic constraint on dynamics ⓘ |
| conditionType | microscopic reversibility condition ⓘ |
| contrastsWith | global balance condition ⓘ |
| coreIdea | each microscopic process is balanced by its reverse at equilibrium ⓘ |
| describes | balance of microscopic transition probabilities at equilibrium ⓘ |
| ensures |
no net macroscopic change in equilibrium state
ⓘ
no net probability current between microstates at equilibrium ⓘ time-reversal symmetry at equilibrium for many systems ⓘ |
| field |
Markov processes
ⓘ
chemical kinetics ⓘ statistical mechanics ⓘ thermodynamics ⓘ |
| goalInMCMC | to make target distribution invariant under Markov chain transitions ⓘ |
| historicalOrigin | early 20th century development of kinetic theory and statistical mechanics ⓘ |
| holdsWhen | system is closed and isolated long enough to reach equilibrium ⓘ |
| implies |
Boltzmann distribution for systems in canonical ensemble
ⓘ
stationary distribution of microstates ⓘ |
| mathematicalForm | π(i) P(i→j) = π(j) P(j→i) for all states i,j at equilibrium ⓘ |
| mayFailWhen |
in presence of external fields driving steady currents
ⓘ
system is driven far from equilibrium ⓘ time-reversal symmetry is broken ⓘ |
| relatedConcept |
Boltzmann distribution
ⓘ
Markov chain reversibility ⓘ Onsager reciprocal relations ⓘ equilibrium statistical mechanics ⓘ microscopic reversibility ⓘ |
| relates | forward transition rates and reverse transition rates ⓘ |
| usedIn |
Gibbs sampling
ⓘ
Metropolis–Hastings algorithm ⓘ
linked to:
Metropolis algorithm
construction of Markov Chain Monte Carlo algorithms ⓘ derivation of Boltzmann equation ⓘ derivation of rate equations in chemical kinetics ⓘ kinetic theory of gases ⓘ radiative transfer theory ⓘ reaction network theory ⓘ semiconductor physics ⓘ |
| usedToDerive |
Einstein relations in some transport processes
ⓘ
equilibrium relations between reaction rate constants ⓘ |
How these facts were elicited
The pipeline generated the facts above by prompting gpt-5.1 with this entity's name + description and the instruction below.
Instruction
You are a knowledge base construction expert. Given a subject entity and a description of it, return factual statements that you know for the subject as a JSON list of dictionaries(triples), where keys must be "subject", "predicate" and "object". The number of facts may be very high, between 25 to 50 or more, for very popular subjects. For less popular subjects, the number of facts can be very low, like 5 or 10. # Requirements - If you don't know the subject at all, return an empty list. - If the subject is not a named entity, return an empty list. - Include at least one triple where predicate is "instanceOf". - Do not get too wordy. - Separate several objects into multiple triples with one object.
Input
Subject: detailed balance principle Description of subject: The detailed balance principle is a thermodynamic concept stating that, at equilibrium, every microscopic process is exactly balanced by its reverse process, ensuring no net change in the system’s macroscopic state.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.