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Related Concept Videos

Colloids03:22

Colloids

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Children at play often make suspensions such as mixtures of mud and water, flour and water, or a suspension of solid pigments in water known as tempera paint. These suspensions are heterogeneous mixtures composed of relatively large particles that are visible to the naked eye or can be seen with a magnifying glass. They are cloudy, and the suspended particles settle out after mixing. On the other hand, a solution is a homogeneous mixture in which no settling occurs and in which the dissolved...
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The mean is a measure of the central tendency of a data set. In some data sets, the data is inherently multiplicative, and the arithmetic mean is not useful. For example, the human population multiplies with time, and so does the credit amount of financial investment, as the interest compounds over successive time intervals.
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Wood's structural properties derive from fibers aligned along the tree's length, contributing significantly to its mechanical strength. Wood exhibits up to twenty times greater tensile strength along these fibers compared to across them, and generally shows better performance under compression than tension. The length of fibers varies, with hardwoods having fibers around one twenty-fifth inch long and softwoods ranging from one-eighth to one-third inch.
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Structure and Physical Properties of Alkynes02:37

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Introduction:
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Colloids and Suspensions01:17

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Children at play often make suspensions such as mixtures of mud and water, flour and water, or a suspension of solid pigments in water known as tempera paint. These suspensions are heterogeneous mixtures composed of relatively large particles visible to the naked eye or seen with a magnifying glass. They are cloudy, and the suspended particles settle out after mixing. The suspended particles in a suspension settle out after some time of mixing. The separation of particles from a suspension is...
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The high insolubility of some precipitates can result in an unfavorable relative supersaturation. This can lead to colloidal particles with a large surface-to-mass ratio, where adsorption is promoted. For instance, in the precipitation of silver chloride, silver ions are adsorbed on the surface of the colloidal particles, forming a primary layer. This layer attracts ions of opposite charge (such as nitrate ions), forming a diffuse secondary layer of adsorbed ions. This electric double layer...
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Confocal Imaging of Confined Quiescent and Flowing Colloid-polymer Mixtures
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Investigation of Geometric Landscape and Structure-Property Relations for Colloidal Superstructures Using Genetic

Nishan Parvez1, Dhananjai M Rao2, Mehdi B Zanjani1

  • 1Department of Mechanical and Manufacturing Engineering , Miami University , Oxford , Ohio 45056 , United States.

The Journal of Physical Chemistry. B
|August 3, 2019
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Summary
This summary is machine-generated.

This study introduces a Genetic Algorithm (GA) framework for designing colloidal structures with specific properties. The method efficiently identifies building blocks and structures for targeted optical metamaterials, particularly photonic band gaps.

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Area of Science:

  • Colloidal science and materials engineering
  • Computational materials design
  • Nanotechnology and metamaterials

Background:

  • Successful synthesis of diverse colloidal particles over two decades.
  • Colloidal building blocks are crucial for engineering mechanical, electrical, and optical metamaterials.
  • Challenges exist in designing colloidal structures due to complex interactions and structure-property relationships.

Purpose of the Study:

  • To implement an inverse material design framework using Genetic Algorithm (GA) techniques.
  • To streamline the design of colloidal structures based on target properties.
  • To investigate the impact of particle shape, size, and geometric phase space on material properties.

Main Methods:

  • Utilized Genetic Algorithm (GA)-based inverse material design.
  • Investigated spherical particles and colloidal molecules of varying sizes and shapes.
  • Evaluated a Geometric Landscape Accessibility parameter to define feasible geometric phase space domains.

Main Results:

  • Identified sets of building blocks and structures yielding targeted photonic band gap sizes.
  • Demonstrated the GA framework's ability to predict and design colloidal structures for specific optical properties.
  • Quantified feasible design domains within the geometric phase space of colloidal structures.

Conclusions:

  • The GA-assisted framework offers a powerful tool for predictive computational material design.
  • Provides new insights into understanding structure-property relationships in sub-micrometer materials.
  • Establishes more efficient pathways for designing functional colloidal metamaterials.