Evidence map›Paper›PMID 34441208›Full record

ArticleEntropy (Basel, Switzerland)2021

Dissipation-Driven Selection under Finite Diffusion: Hints from Equilibrium and Separation of Time Scales.

Shiling Liang, Paolo De Los Rios, Daniel Maria Busiello

Abstract read
In one paragraph

Article in Entropy (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Shiling LiangInstitute of Physics, School of Basic Sciences, École Polytechnique Fédérale de Lausanne-EPFL, 1015 Lausanne, Switzerland.ORCID 0000-0001-8968-8443
Paolo De Los RiosInstitute of Physics, School of Basic Sciences, École Polytechnique Fédérale de Lausanne-EPFL, 1015 Lausanne, Switzerland.
Daniel Maria BusielloInstitute of Physics, School of Basic Sciences, École Polytechnique Fédérale de Lausanne-EPFL, 1015 Lausanne, Switzerland.ORCID 0000-0002-6754-5019

Funding

Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung 200020_178763
6 · The paper itself

Abstract

When exposed to a thermal gradient, reaction networks can convert thermal energy into the chemical selection of states that would be unfavourable at equilibrium. The kinetics of reaction paths, and thus how fast they dissipate available energy, might be dominant in dictating the stationary populations of all chemical states out of equilibrium. This phenomenology has been theoretically explored mainly in the infinite diffusion limit. Here, we show that the regime in which the diffusion rate is finite, and also slower than some chemical reactions, might bring about interesting features, such as the maximisation of selection or the switch of the selected state at stationarity. We introduce a framework, rooted in a time-scale separation analysis, which is able to capture leading non-equilibrium features using only equilibrium arguments under well-defined conditions. In particular, it is possible to identify fast-dissipation sub-networks of reactions whose Boltzmann equilibrium dominates the steady-state of the entire system as a whole. Finally, we also show that the dissipated heat (and so the entropy production) can be estimated, under some approximations, through the heat capacity of fast-dissipation sub-networks. This work provides a tool to develop an intuitive equilibrium-based grasp on complex non-isothermal reaction networks, which are important paradigms to understand the emergence of complex structures from basic building blocks.

Indexed as

diffusionnon-equilibrium systemsreaction networks

Identifiers

PMID34441208
PMCPMC8394842

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.