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Related Concept Videos

Entropy02:39

Entropy

36.3K
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

3.6K
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...
3.6K
Standard Entropy Change for a Reaction03:00

Standard Entropy Change for a Reaction

24.9K
Entropy is a state function, so the standard entropy change for a chemical reaction (ΔS°rxn) can be calculated from the difference in standard entropy between the products and the reactants.
24.9K
Entropy and Solvation02:05

Entropy and Solvation

8.4K
The process of surrounding a solute with solvent is called solvation. It involves evenly distributing the solute within the solvent. The rule of thumb for determining a solvent for a given compound is that like dissolves like. A good solvent has molecular characteristics similar to those of the compound to be dissolved. For example, polar solutions dissolve polar solutes, and apolar solvents dissolve apolar solutes. A polar solvent is a solvent that has a high dielectric constant (ϵ...
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Entropy within the Cell01:22

Entropy within the Cell

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A living cell's primary tasks of obtaining, transforming, and using energy to do work may seem simple. However, the second law of thermodynamics explains why these tasks are harder than they appear. None of the energy transfers in the universe are completely efficient. In every energy transfer, some amount of energy is lost in a form that is unusable. In most cases, this form is heat energy. Thermodynamically, heat energy is defined as the energy transferred from one system to another that...
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Entropy and the Second Law of Thermodynamics01:20

Entropy and the Second Law of Thermodynamics

5.0K
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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In-vivo Detection of Protein-protein Interactions on Micro-patterned Surfaces
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Programming entropy production hotspots via interaction patterning.

Caroline Desgranges1, Jerome Delhommelle2

  • 1Department of Physics & Applied Physics, University of Massachusetts, Lowell, MA 01854, USA. caroline_desgranges@uml.edu.

Soft Matter
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Summary
This summary is machine-generated.

Scientists can now program entropy production hotspots in soft matter systems. By controlling local interactions, they can fine-tune energy hotspots to power nanomachines and biological devices.

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Area of Science:

  • Soft matter physics
  • Statistical mechanics
  • Nanotechnology

Background:

  • Dissipation in soft matter and living systems is heterogeneous, creating complex local entropy production patterns.
  • Local entropy production is linked to locally extractable work, suggesting potential for powering nanoscale machines.
  • Efficient strategies are needed to modulate local entropy production for applications in nanotechnology and biology.

Purpose of the Study:

  • To propose and test a method for programming entropy production hotspots using local interaction patterns.
  • To investigate the feasibility of controlling energy landscapes at the nanoscale for targeted applications.

Main Methods:

  • Simulations of fluid flow through a nanopore with patterned surfaces.
  • Simulations of fluid flow past obstacles with patterned interactions.
  • Analysis of entropy production patterns based on surface modifications.

Main Results:

  • Repulsive surface patches in nanopores create entropy production hotspots.
  • Attractive surface patches lead to entropy production cold spots.
  • Interaction strength and patch width allow modulation of hotspot characteristics.
  • Patterned obstacles enable programming specific entropy production maps through steric and attractive forces.

Conclusions:

  • Local interaction patterning is an effective strategy to program entropy production hotspots.
  • This approach offers precise control over energy landscapes for powering nanomachines.
  • Opens possibilities for targeted energy harvesting and directed motion at the nanoscale.