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Gibbs Free Energy02:39

Gibbs Free Energy

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One of the challenges of using the second law of thermodynamics to determine if a process is spontaneous is that it requires measurements of the entropy change for the system and the entropy change for the surroundings. An alternative approach involving a new thermodynamic property defined in terms of system properties only was introduced in the late nineteenth century by American mathematician Josiah Willard Gibbs. This new property is called the Gibbs free energy (G) (or simply the free...
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Gibbs Free Energy and Thermodynamic Favorability02:23

Gibbs Free Energy and Thermodynamic Favorability

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The spontaneity of a process depends upon the temperature of the system. Phase transitions, for example, will proceed spontaneously in one direction or the other depending upon the temperature of the substance in question. Likewise, some chemical reactions can also exhibit temperature-dependent spontaneities. To illustrate this concept, the equation relating free energy change to the enthalpy and entropy changes for the process is considered:
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Multi-input and Multi-variable systems01:22

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Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence...
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Statically Indeterminate Problem Solving01:16

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Statically indeterminate problems are those where statics alone can not determine the internal forces or reactions. Consider a structure comprising two cylindrical rods made of steel and brass. These rods are joined at point B and restrained by rigid supports at points A and C. Now, the reactions at points A and C and the deflection at point B are to be determined. This rod structure is classified as statically indeterminate as the structure has more supports than are necessary for maintaining...
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Modeling and Similitude01:12

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Scaled modeling is a fundamental technique in engineering, enabling the study of large and complex systems by creating smaller, manageable replicas that recreate critical characteristics of the original. In hydrology and civil infrastructure, for example, scaled models of dams help analyze water flow, turbulence, and pressure. This method allows for accurate predictions of real-world behavior within a controlled environment, significantly reducing the cost and time involved in full-scale...
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An Introduction to Free Energy01:05

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8.8K
How can we compare the energy that releases from one reaction to that of another reaction? We use a measurement of free energy to quantitate these energy transfers. Scientists call this free energy Gibbs free energy (abbreviated with the letter G) after Josiah Willard Gibbs, the scientist who developed the measurement. According to the second law of thermodynamics, all energy transfers involve losing some energy in an unusable form such as heat, resulting in entropy. Gibbs free energy...
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Video Experimental Relacionado

Updated: Sep 9, 2025

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
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Simulación proyectiva de energía libre (FEPS): inferencia activa con interpretabilidad

Joséphine Pazem1, Marius Krumm1, Alexander Q Vining1,2

  • 1Institut für Theoretische Physik, Universität Innsbruck, Innsbruck, Austria.

PloS one
|September 4, 2025
PubMed
Resumen
Este resumen es generado por máquina.

Presentamos la Simulación Proyectiva de Energía Libre (FEPS), un modelo interpretable para agentes que aprenden sin redes neuronales profundas. Los agentes FEPS resuelven efectivamente la ambigüedad ambiental e inferen políticas óptimas al contextualizar las observaciones basadas en la precisión de la predicción.

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Área de la Ciencia:

  • Neurociencia computacional
  • Inteligencia artificial
  • Sistemas complejos

Sus antecedentes:

  • El Principio de la Energía Libre (FEP) y la Inferencia Activa (AIF) ofrecen un marco unificado para comprender el aprendizaje, la cognición, la percepción y la acción en los sistemas auto-organizados.
  • Los agentes de aprendizaje por refuerzo (RL), que a menudo emplean redes neuronales profundas, se han desarrollado para realizar tareas de inferencia activa, con esfuerzos recientes centrados en mejorar el rendimiento en entornos complejos.

Objetivo del estudio:

  • Desarrollar un enfoque de modelado de agentes interpretable dentro de las limitaciones de FEP y AIF, evitando las redes neuronales profundas.
  • Introducir la simulación proyectiva de energía libre (FEPS) como un nuevo método para el modelado de agentes y la optimización de políticas.

Principales métodos:

  • Los agentes FEPS utilizan recompensas internas para construir modelos mundiales de entornos parcialmente observables.
  • Las políticas se derivan de minimizar la energía libre esperada, un principio básico de AIF.
  • Se incorporan técnicas para gestionar los objetivos a largo plazo y mitigar los errores de predicción de la estimación del estado oculto.

Principales resultados:

  • Los agentes FEPS resolvieron con éxito la ambigüedad en dos entornos de RL (respuesta cronometrada y navegación parcialmente observable) inspirados en la biología del comportamiento.
  • Los agentes demostraron la capacidad de contextualizar las observaciones basadas únicamente en la precisión de la predicción.
  • Las políticas óptimas se inferían de manera flexible para diversas observaciones objetivo dentro de los entornos.

Conclusiones:

  • FEPS proporciona una alternativa interpretable a las redes neuronales profundas para los agentes de modelado bajo FEP y AIF.
  • El modelo maneja efectivamente la ambigüedad ambiental y optimiza las políticas a través de la contextualización basada en la precisión de la predicción.
  • FEPS es prometedor para el desarrollo de agentes adaptativos y dirigidos a objetivos en entornos complejos y parcialmente observables.