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Related Concept Videos

Energy Bands in Solids01:01

Energy Bands in Solids

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Isolated atoms have discrete energy levels that are well described by the Bohr model. And, it quantifies the energy of an electron in a hydrogen atom as En. Higher quantum numbers 'n' yield less negative, closer electron energy levels.
 Band Formation:
When atoms are brought close together, as in a solid, these discrete energy levels begin to split due to the overlap of electron orbitals from adjacent atoms. This split occurs because of the Pauli exclusion principle, which states...
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Trends in Lattice Energy: Ion Size and Charge02:54

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An ionic compound is stable because of the electrostatic attraction between its positive and negative ions. The lattice energy of a compound is a measure of the strength of this attraction. The lattice energy (ΔHlattice) of an ionic compound is defined as the energy required to separate one mole of the solid into its component gaseous ions. For the ionic solid sodium chloride, the lattice energy is the enthalpy change of the process:
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Fermi Level Dynamics01:12

Fermi Level Dynamics

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The vacuum level denotes the energy threshold required for an electron to escape from a material surface. It is usually positioned above the conduction band of a semiconductor and acts as a benchmark for comparing electron energies within various materials.
Electron affinity in semiconductors refers to the energy gap between the minimum of its conduction band and the vacuum level and it is a critical parameter in determining how easily a semiconductor can accept additional electrons.
The work...
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The Energies of Atomic Orbitals03:21

The Energies of Atomic Orbitals

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In an atom, the negatively charged electrons are attracted to the positively charged nucleus. In a multielectron atom, electron-electron repulsions are also observed. The attractive and repulsive forces are dependent on the distance between the particles, as well as the sign and magnitude of the charges on the individual particles. When the charges on the particles are opposite, they attract each other. If both particles have the same charge, they repel each other.
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The free energy change for a process taking place with reactants and products present under nonstandard conditions (pressures other than 1 bar; concentrations other than 1 M) is related to the standard free energy change according to this equation:
 
where R is the gas constant (8.314 J/K·mol), T is the absolute temperature in kelvin, and Q is the reaction quotient. This equation may be used to predict the spontaneity of a process under any given set of conditions.
Reaction Quotient...
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Energy Diagrams, Transition States, and Intermediates02:13

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Free-energy diagrams, or reaction coordinate diagrams, are graphs showing the energy changes that occur during a chemical reaction. The reaction coordinate represented on the horizontal axis shows how far the reaction has progressed structurally. Positions along the x-axis close to the reactants have structures resembling the reactants, while positions close to the products resemble the products.  Peaks on the energy diagram represent stable structures with measurable lifetimes, while...
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Exploring energy landscapes for solid-state systems with variable cells at the extended tight-binding level.

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This study introduces a new computational framework for analyzing solid-state energy landscapes, enabling the study of material transitions and pathways. The method provides valuable insights for simulations of defect and ion migration in materials.

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Area of Science:

  • Condensed matter physics
  • Materials science
  • Computational chemistry

Background:

  • Understanding solid-state dynamical processes like polymorphic transitions is crucial for novel material design.
  • The potential energy landscape organization governs these processes, often involving changes in periodic boundaries.

Purpose of the Study:

  • To implement a general framework for periodic condensed matter systems within energy landscape analysis software.
  • To enable variation in unit cell and atomic positions for comprehensive analysis.

Main Methods:

  • Basin-hopping global optimization
  • Doubly nudged elastic band procedure for transition state identification
  • Missing connection approach for multi-step pathways
  • Kinetic transition network construction and analysis
  • Utilized GFN1-xTB semiempirical method for computational efficiency

Main Results:

  • Successfully implemented a framework for periodic condensed matter systems.
  • Characterized potential energy and enthalpy landscapes for silicon, CdSe, ZnS, and NaCl.
  • Demonstrated the utility of semiempirical methods for solid-state energy landscape analysis.

Conclusions:

  • The developed framework provides valuable insights into solid-state simulations.
  • Facilitates detailed analysis of defect and ion migration.
  • Lays groundwork for refinement at higher levels of theory.