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Entropy01:18

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The first law of thermodynamics is quantitatively formulated via an equation relating the internal energy of a system, the heat exchanged by it, and the work done on it. A quantitative formulation of the second law of thermodynamics leads to defining a state function, the entropy.
When an ideal gas expands isothermally, the disorder in the gas increases. From the molecular perspective, the gas molecules have more volume to move around in.
Consider an infinitesimal step in the expansion, which...
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Entropy and the Second Law of Thermodynamics01:20

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The second law of thermodynamics can be stated quantitatively using the concept of entropy. Entropy is the measure of disorder of the system.
The relation  between entropy and disorder can be illustrated with the example of the phase change of ice to water. In ice, the molecules are located at specific sites giving a solid state, whereas, in a liquid form, these molecules are much freer to move. The molecular arrangement has therefore become more randomized. Although the change in average...
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Variance01:15

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 The deviations show how spread out the data are about the mean. A positive deviation occurs when the data value exceeds the mean, whereas a negative deviation occurs when the data value is less than the mean. If the deviations are added, the sum is always zero. So one cannot simply add the deviations to get the data spread. By squaring the deviations, the numbers are made positive; thus, their sum will also be positive.
The standard deviation measures the spread in the same units as the...
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The Second Law of Thermodynamics01:14

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In the quest to identify a property that may reliably predict the spontaneity of a process, a promising candidate has been identified: entropy. Scientists refer to the measure of randomness or disorder within a system as entropy. High entropy means high disorder and low energy. To better understand entropy, think of a student’s bedroom. If no energy or work were put into it, the room would quickly become messy. It would exist in a very disordered state, one of high entropy. Energy must be...
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Second Law of Thermodynamics02:49

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In the quest to identify a property that may reliably predict the spontaneity of a process, a promising candidate has been identified: entropy. Processes that involve an increase in entropy of the system (ΔS > 0) are very often spontaneous; however, examples to the contrary are plentiful. By expanding consideration of entropy changes to include the surroundings, a significant conclusion regarding the relation between this property and spontaneity may be reached. In thermodynamic...
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Entropy Change in Reversible Processes01:10

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In the Carnot engine, which achieves the maximum efficiency between two reservoirs of fixed temperatures, the total change in entropy is zero. The observation can be generalized by considering any reversible cyclic process consisting of many Carnot cycles. Thus, it can be stated that the total entropy change of any ideal reversible cycle is zero.
The statement can be further generalized to prove that entropy is a state function. Take a cyclic process between any two points on a p-V diagram.
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Applications of EEG Neuroimaging Data: Event-related Potentials, Spectral Power, and Multiscale Entropy
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Regla de la suma de la varianza para la producción de entropía

I Di Terlizzi1,2, M Gironella3,4, D Herraez-Aguilar5

  • 1Max Planck Institute for the Physics of Complex Systems, Nöthnitzer Straße 38, 01187 Dresden, Germany.

Science (New York, N.Y.)
|February 29, 2024
PubMed
Resumen
Este resumen es generado por máquina.

Los investigadores desarrollaron un nuevo método para medir la producción de entropía a nanoescala utilizando una regla de suma de varianza. Esta técnica cuantifica la irreversibilidad y la disipación de energía en sistemas no equilibrados, aplicables a la materia activa y las células biológicas.

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Área de la Ciencia:

  • Física de no equilibrio
  • Mecánica estadística
  • Física de la materia blanda
  • La biofísica

Sus antecedentes:

  • La producción de entropía cuantifica la irreversibilidad y la disipación en física, crucial para comprender la transducción de energía.
  • La medición de la producción de entropía a nanoescala es un desafío significativo en los sistemas de no equilibrio.
  • Los métodos existentes a menudo carecen de precisión o aplicabilidad para fenómenos complejos a nanoescala.

Objetivo del estudio:

  • Introducir una nueva regla de suma de variación (VSR) para medir la tasa de producción de entropía (σ) en estados estacionarios de no equilibrio.
  • Demostrar la aplicabilidad del VSR a sistemas con fuerzas directamente mensurables y sistemas biológicos complejos.
  • Proporcionar una nueva herramienta para cuantificar la irreversibilidad y la disipación a nanoescala.

Principales métodos:

  • Desarrollo de una regla de suma de variación (RSV) relacionada con el desplazamiento y las variaciones de fuerza.
  • Aplicación de VSR a una partícula browniana activa en una trampa óptica.
  • Validación experimental mediante mediciones de parpadeo en glóbulos rojos humanos.

Principales resultados:

  • El VSR mide con éxito la tasa de producción de entropía (σ) en estados estacionarios de no equilibrio.
  • Se observó una producción de entropía espacialmente heterogénea con una longitud de correlación finita en los glóbulos rojos.
  • Los valores medios de producción de entropía obtenidos mediante VSR concuerdan con las mediciones de calorimetría independientes.

Conclusiones:

  • La regla de la suma de variación (VSR) ofrece un método práctico para medir la producción de entropía a nanoescala.
  • El VSR es aplicable a diversos sistemas, incluidos la materia activa y las células biológicas.
  • Este trabajo permite la derivación de la producción de entropía utilizando espectroscopia de fuerza e imágenes de resolución temporal.