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Related Concept Videos

Metallic Solids02:37

Metallic Solids

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Metallic solids such as crystals of copper, aluminum, and iron are formed by metal atoms. The structure of metallic crystals is often described as a uniform distribution of atomic nuclei within a “sea” of delocalized electrons. The atoms within such a metallic solid are held together by a unique force known as metallic bonding that gives rise to many useful and varied bulk properties.
All metallic solids exhibit high thermal and electrical conductivity, metallic luster, and malleability....
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Temperature Dependent Deformation01:12

Temperature Dependent Deformation

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In a nonhomogeneous rod made up of steel and brass, restrained at both ends and subjected to a temperature change, several steps are involved in calculating the stress and compressive load. Due to the problem's static indeterminacy, one end support is disconnected, allowing the rod to experience the temperature change freely. Next, an unknown force is applied at the free end, triggering deformations in the rod's steel and brass portions. These deformations are then calculated and added...
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Molecular and Ionic Solids02:54

Molecular and Ionic Solids

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Crystalline solids are divided into four types: molecular, ionic, metallic, and covalent network based on the type of constituent units and their interparticle interactions.
Molecular Solids
Molecular crystalline solids, such as ice, sucrose (table sugar), and iodine, are solids that are composed of neutral molecules as their constituent units. These molecules are held together by weak intermolecular forces such as London dispersion forces, dipole-dipole interactions, or hydrogen bonds, which...
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Relation between Poisson's ratio, Modulus of Elasticity and Modulus of Rigidity01:15

Relation between Poisson's ratio, Modulus of Elasticity and Modulus of Rigidity

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Deformation occurs in axial and transverse directions when an axial load is applied to a slender bar. This deformation impacts the cubic element within the bar, transforming it into either a rectangular parallelepiped or a rhombus, contingent on its orientation. This transformation process induces shearing strain. Axial loading elicits both shearing and normal strains. Applying an axial load instigates equal normal and shearing stresses on elements oriented at a 45° angle to the load axis.
296
Common Ion Effect03:24

Common Ion Effect

41.9K
Compared with pure water, the solubility of an ionic compound is less in aqueous solutions containing a common ion (one also produced by dissolution of the ionic compound). This is an example of a phenomenon known as the common ion effect, which is a consequence of the law of mass action that may be explained using Le Châtelier’s principle. Consider the dissolution of silver iodide:
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Deformation of Member under Multiple Loadings01:11

Deformation of Member under Multiple Loadings

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When a rod is made of different materials or has various cross-sections, it must be divided into parts that meet the necessary conditions for determining the deformation. These parts are each characterized by their internal force, cross-sectional area, length, and modulus of elasticity. These parameters are then used to compute the deformation of the entire rod.
In the case of a member with a variable cross-section, the strain is not constant but depends on the position. The deformation of an...
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Analyzing Melts and Fluids from Ab Initio Molecular Dynamics Simulations with the UMD Package
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Analyzing Melts and Fluids from Ab Initio Molecular Dynamics Simulations with the UMD Package

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Machine learning dislocation density correlations and solute effects in Mg-based alloys.

H Salmenjoki1, S Papanikolaou2, D Shi3

  • 1Department of Applied Physics, Aalto University, PO Box 11000, 00076, Aalto, Finland.

Scientific Reports
|July 10, 2023
PubMed
Summary
This summary is machine-generated.

This study investigates how adding zinc to magnesium alloys affects their ductility. Machine learning analysis of electron back-scatter diffraction images reveals insights into dislocation density changes, aiding the development of stronger, more formable magnesium materials.

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Determining the Mechanical Strength of Ultra-Fine-Grained Metals
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Area of Science:

  • Materials Science and Engineering
  • Computational Materials Science
  • Metallurgy

Background:

  • Magnesium alloys are lightweight but limited by low strength and ductility.
  • Solid solution alloying, particularly with zinc (Zn), can enhance magnesium's ductility and formability.
  • The precise mechanisms behind solute-induced ductility improvement in magnesium remain unclear.

Purpose of the Study:

  • To investigate the evolution of dislocation density in polycrystalline magnesium and Mg-Zn alloys.
  • To utilize data science and machine learning to understand intragranular characteristics and strain history.
  • To predict dislocation density changes after alloying and deformation in Mg-Zn systems.

Main Methods:

  • High-throughput analysis of intragranular characteristics using data science.
  • Application of machine learning techniques to electron back-scatter diffraction (EBSD) images.
  • Comparison of EBSD data before and after alloying, and before and after deformation to extract strain history and predict dislocation density.

Main Results:

  • Machine learning models achieved moderate predictive accuracy (R-squared 0.25–0.32) for dislocation density.
  • These predictions were based on a dataset of approximately 5000 sub-millimeter grains.
  • The study successfully correlated alloying and deformation with changes in dislocation density.

Conclusions:

  • Data science and machine learning approaches show promise for studying microstructural evolution in magnesium alloys.
  • The findings provide a foundation for understanding and optimizing the mechanical properties of Mg-Zn alloys.
  • Further research with larger datasets could improve predictive capabilities for enhanced material design.