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Related Concept Videos

Entropy02:39

Entropy

36.4K
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...
36.4K
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

25.0K
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.
25.0K
Entropy and Solvation02:05

Entropy and Solvation

8.5K
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...
8.5K
Entropy within the Cell01:22

Entropy within the Cell

13.0K
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...
13.0K
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...
5.0K

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Modification and Functionalization of the Guanidine Group by Tailor-made Precursors
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Tailoring Interfacial Nanoparticle Organization through Entropy.

Guolong Zhu1, Zihan Huang1, Ziyang Xu1

  • 1State Key Laboratory of Chemical Engineering, Department of Chemical Engineering , Tsinghua University , Beijing 100084 , P. R. China.

Accounts of Chemical Research
|March 29, 2018
PubMed
Summary
This summary is machine-generated.

Entropy strategies offer precise control over nanoparticle organization at interfaces. Computational design exploits conformational, shape, and rotational entropy for tunable, stimuli-responsive nanostructures in materials science and biology.

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Area of Science:

  • Materials Science
  • Nanotechnology
  • Physical Chemistry

Background:

  • Tailoring nanoparticle (NP) interfacial behavior is key for advanced materials and understanding biological systems.
  • Janus NPs, with asymmetric Janus nanoparticles, offer tunable interfacial nanostructures.
  • Controlling NP order and stimuli-responsiveness at interfaces remains challenging due to complex interactions.

Purpose of the Study:

  • To exploit entropy strategies for computational design of nanoparticle spatial distribution and ordering at interfaces.
  • To explore how different types of entropy (conformational, shape, rotational, vibrational) drive interfacial self-assembly.
  • To develop environmentally responsive systems using entropy for stimuli-responsive interfacial nanostructures.

Main Methods:

  • Computational design and theoretical analysis of entropic ordering principles.
  • Summarizing and categorizing entropy types used in NP interfacial organization.
  • Investigating molecular architecture effects (chain length, stiffness) on Janus NP organization at block copolymer interfaces.

Main Results:

  • Entropy strategies provide a framework for precise programming of NP interfacial organization.
  • Demonstrated tailoring of molecular architectures to tune entropic contributions for controlled NP assembly.
  • Identified key factors influencing interfacial organization through entropy-driven processes.

Conclusions:

  • Entropy strategies are a powerful and versatile approach for designing ordered NP interfacial assemblies.
  • Future research can further leverage entropy for advanced functional nanomaterials and applications.
  • This work promotes fundamental understanding and broad applications of designed interfacial assemblies.