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  1. 13 Μαΐ 2023 · Changes in entropy (ΔS Δ S), together with changes in enthalpy (ΔH Δ H), enable us to predict in which direction a chemical or physical change will occur spontaneously. Before discussing how to do so, however, we must understand the difference between a reversible process and an irreversible one.

  2. 28 Απρ 2023 · We introduce heuristic arguments to infer that \(\Delta S=0\) is not possible for a spontaneous process in an isolated system. From this, we show that \(\Delta S_{universe}>0\) for any spontaneous process and hence that \(\Delta S_{universe}=0\) is not possible for any spontaneous process.

  3. For reversible processes (the most efficient processes possible), the net change in entropy in the universe (system + surroundings) is zero. Phenomena that introduce irreversibility and inefficiency are: friction, heat transfer across finite temperature differences, free expansion, ...

  4. 9 Δεκ 2022 · In this paper, we compute the entropy production of diffusion processes at non-equilibrium steady-state under the condition that the time-reversal of the diffusion remains a diffusion. We start by characterising the entropy production of both discrete and continuous-time Markov processes.

  5. Entropy Changes in Reversible Processes. Suppose that the heat absorbed by the system and heat lost by the surrounding are under completely reversible conditions. In other words, qrev is the heat absorbed and lost by the surrounding at temperature T, then we can say that the entropy change in the system will be given by the following relation. (26)

  6. 15 Ιαν 2021 · We introduce a measure of irreversibility we term the entropy production factor to quantify how time reversal symmetry is broken in field theories across scales. We use this scalar, dimensionless...

  7. 15 Απρ 2021 · Time reversal of diffusion processes under a finite entropy condition. Motivated by entropic optimal transport, time reversal of diffusion processes is revisited. An integration by parts formula is derived for the carré du champ of a Markov process in an abstract space.

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