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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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Solids in which the atoms, ions, or molecules are arranged in a definite repeating pattern are known as crystalline solids. Metals and ionic compounds typically form ordered, crystalline solids. A crystalline solid has a precise melting temperature because each atom or molecule of the same type is held in place with the same forces or energy. Amorphous solids or non-crystalline solids (or, sometimes, glasses) which lack an ordered internal structure and are randomly arranged. Substances that...
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Lattice Centering and Coordination Number02:33

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The structure of a crystalline solid, whether a metal or not, is best described by considering its simplest repeating unit, which is referred to as its unit cell. The unit cell consists of lattice points that represent the locations of atoms or ions. The entire structure then consists of this unit cell repeating in three dimensions. The three different types of unit cells present in the cubic lattice are illustrated in Figure 1.
Types of Unit Cells
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Gauss's Law: Planar Symmetry01:27

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A planar symmetry of charge density is obtained when charges are uniformly spread over a large flat surface. In planar symmetry, all points in a plane parallel to the plane of charge are identical with respect to the charges. Suppose the plane of the charge distribution is the xy-plane, and the electric field at a space point P with coordinates (x, y, z) is to be determined. Since the charge density is the same at all (x, y) - coordinates in the z = 0 plane, by symmetry, the electric field at P...
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Using Microwave and Macroscopic Samples of Dielectric Solids to Study the Photonic Properties of Disordered Photonic Bandgap Materials
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Backscattering properties of randomly oriented hexagonal hollow columns for lidar application.

Xuanhao Zhu, Zhenzhu Wang, Alexander Konoshonkin

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    This study investigates cirrus cloud optical properties using hollow ice crystals. New modal hollow columns (MHC) help distinguish mixtures of hollow and solid ice crystals using lidar data.

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    Area of Science:

    • Atmospheric optics
    • Cloud physics
    • Remote sensing

    Background:

    • Accurate interpretation of space-borne and ground-based lidar data relies on understanding cirrus cloud optical properties.
    • Current backscattering databases lack data for hollow ice crystal columns, a common cirrus component.

    Purpose of the Study:

    • To investigate the backscattering properties of randomly oriented hollow column ice crystals at lidar wavelengths (355, 532, 1064 nm).
    • To introduce a new concept of modal hollow columns (MHC) for mid-latitude cirrus clouds.
    • To determine methods for distinguishing between hollow and solid ice crystal mixtures using lidar-derived parameters.

    Main Methods:

    • Calculated backscattering cross section (M11), depolarization ratio (δ), lidar ratio (S), and color ratio (χ) using the physical optics (PO) approximation.
    • Simulated randomly oriented hollow columns with sizes from 10 to 316.23 µm.
    • Introduced and applied the modal hollow column (MHC) concept.

    Main Results:

    • Optical properties (M11, δ, S, χ) were computed for hollow columns across various sizes and wavelengths.
    • The study found that a 50% mixture of MHC and solid columns (SC) can be identified.
    • Distinguishing mixtures is possible using the lidar ratio at 1064 nm or the χ(1064,532)-δ(532) relationship.

    Conclusions:

    • The modal hollow column concept provides a simplified yet effective way to model hollow ice crystals in mid-latitude cirrus.
    • Lidar ratios and color-depolarization ratios offer potential for differentiating mixed-phase cirrus clouds.
    • This research improves lidar data interpretation for cirrus cloud characterization.