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Related Concept Videos

Ionic Crystal Structures02:42

Ionic Crystal Structures

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Ionic crystals consist of two or more different kinds of ions that usually have different sizes. The packing of these ions into a crystal structure is more complex than the packing of metal atoms that are the same size.
Most monatomic ions behave as charged spheres, and their attraction for ions of opposite charge is the same in every direction. Consequently, stable structures for ionic compounds result (1) when ions of one charge are surrounded by as many ions as possible of the opposite...
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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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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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Crystal Field Theory - Octahedral Complexes02:58

Crystal Field Theory - Octahedral Complexes

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Crystal Field Theory
To explain the observed behavior of transition metal complexes (such as colors), a model involving electrostatic interactions between the electrons from the ligands and the electrons in the unhybridized d orbitals of the central metal atom has been developed. This electrostatic model is crystal field theory (CFT). It helps to understand, interpret, and predict the colors, magnetic behavior, and some structures of coordination compounds of transition metals.
CFT focuses on...
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Monovalent Cation Doping of CH3NH3PbI3 for Efficient Perovskite Solar Cells
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Computational Design of Antiperovskite Solid Electrolytes.

Ana C C Dutra1, James A Dawson1,2,3

  • 1Chemistry - School of Natural and Environmental Sciences, Newcastle University, Newcastle upon Tyne NE1 7RU, U.K.

The Journal of Physical Chemistry. C, Nanomaterials and Interfaces
|September 27, 2023
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Summary
This summary is machine-generated.

Solid-state batteries using antiperovskite electrolytes offer safer, higher-density energy storage. Computational design accelerates the discovery of new antiperovskite materials for improved battery performance and wider applications.

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Area of Science:

  • Materials Science
  • Electrochemistry
  • Computational Chemistry

Background:

  • Current lithium-ion batteries face limitations in safety, cost, and performance.
  • Solid-state batteries (SSBs) are a promising alternative, replacing liquid electrolytes with solid ones for enhanced safety and energy density.
  • Antiperovskite materials are emerging as key solid electrolytes due to their high ionic conductivity, stability, and tunable properties.

Purpose of the Study:

  • To review the latest advancements in the computational design of lithium- and sodium-based antiperovskite solid electrolytes.
  • To highlight critical aspects for developing antiperovskite solid electrolytes for solid-state batteries.
  • To discuss challenges and future perspectives for antiperovskite materials in energy storage.

Main Methods:

  • High-throughput computational screening for novel antiperovskite compositions.
  • Analysis of synthesizability and doping strategies for antiperovskite materials.
  • Investigation of ion transport mechanisms, grain boundaries, and electrolyte-electrode interfaces using computational approaches.

Main Results:

  • Computational design enables rapid identification of promising antiperovskite compositions.
  • Understanding of structure-property relationships guides material optimization for ionic conductivity and stability.
  • Insights into interfacial phenomena are crucial for efficient solid-state battery performance.

Conclusions:

  • Antiperovskite solid electrolytes show significant potential for revolutionizing energy storage technologies.
  • Computational design is a powerful tool for accelerating the discovery and development of advanced antiperovskite materials.
  • Further research addressing challenges in synthesis and interfacial engineering will unlock the full potential of antiperovskite solid-state batteries.