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The Second Law of Thermodynamics01:14

The Second Law of Thermodynamics

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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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Third Law of Thermodynamics02:38

Third Law of Thermodynamics

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A pure, perfectly crystalline solid possessing no kinetic energy (that is, at a temperature of absolute zero, 0 K) may be described by a single microstate, as its purity, perfect crystallinity,and complete lack of motion means there is but one possible location for each identical atom or molecule comprising the crystal (W = 1). According to the Boltzmann equation, the entropy of this system is zero.
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Second Law of Thermodynamics02:49

Second Law of Thermodynamics

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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 models, the...
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Second Law of Thermodynamics00:53

Second Law of Thermodynamics

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The Second Law of Thermodynamics states that entropy, or the amount of disorder in a system, increases each time energy is transferred or transformed. Each energy transfer results in a certain amount of energy that is lost—usually in the form of heat—that increases the disorder of the surroundings. This can also be demonstrated in a classic food web. Herbivores harvest chemical energy from plants and release heat and carbon dioxide into the environment. Carnivores harvest the...
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Entropy02:39

Entropy

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Salt particles that have dissolved in water never spontaneously come back together in solution to reform solid particles. Moreover, a gas that has expanded in a vacuum remains dispersed and never spontaneously reassembles. The unidirectional nature of these phenomena is the result of a thermodynamic state function called entropy (S). Entropy is the measure of the extent to which the energy is dispersed throughout a system, or in other words, it is proportional to the degree of disorder of a...
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Entropy01:18

Entropy

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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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Updated: Mar 30, 2026

Differential Scanning Calorimetry — A Method for Assessing the Thermal Stability and Conformation of Protein Antigen
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RNA Thermodynamic Structural Entropy.

Juan Antonio Garcia-Martin1, Peter Clote1

  • 1Department of Biology, Boston College, Chestnut Hill, MA 02467, United States of America.

Plos One
|November 12, 2015
PubMed
Summary
This summary is machine-generated.

We developed new algorithms to accurately and efficiently compute RNA conformational entropy, outperforming previous methods. This advancement aids in understanding RNA structure and function, with available software for broader application.

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Measuring Biomolecular DSC Profiles with Thermolabile Ligands to Rapidly Characterize Folding and Binding Interactions
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Area of Science:

  • Computational Biology
  • Biophysics
  • Molecular Biology

Background:

  • Conformational entropy is crucial for biomolecular interactions like protein-ligand binding.
  • Accurate computation of conformational entropy, especially for RNA, remains a significant challenge.
  • Existing methods, such as stochastic context-free grammars (SCFGs), have limitations in accuracy and dependence on training data.

Purpose of the Study:

  • To develop accurate and efficient algorithms for computing conformational entropy in RNA secondary structures.
  • To compare the performance of novel thermodynamic methods against existing derivational entropy methods.
  • To provide user-friendly software for calculating RNA conformational entropy.

Main Methods:

  • Developed two novel thermodynamic algorithms for RNA secondary structure conformational entropy calculation.
  • Utilized the Turner energy model with parameters derived from UV absorption experiments.
  • Compared computational speed and results against an established SCFG-based derivational entropy algorithm using Rfam database data.

Main Results:

  • The new thermodynamic methods are substantially faster than the SCFG approach.
  • Thermodynamic structural entropy values are smaller than derivational entropy and show a weak to poor correlation.
  • The developed software, RNAentropy, accurately computes structural entropy for user-specified temperatures using Turner'99 and Turner'04 energy parameters.

Conclusions:

  • The novel thermodynamic algorithms provide accurate and efficient computation of RNA conformational entropy.
  • RNAentropy software represents a state-of-the-art tool for RNA secondary structure analysis.
  • The findings facilitate a deeper understanding of RNA structure-function relationships and molecular recognition.