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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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Density is an important characteristic of substances, crucial in determining whether an object sinks or floats in a fluid. Its SI unit is kg/m3, and its cgs unit is g/cm3. The density of an object helps in identifying its composition, and also reveals information about the phase of the matter and its substructure. The densities of liquids and solids are roughly comparable, consistent with the fact that their atoms are in close contact. However, gases have much lower densities than liquids and...
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The Debye-Hückel-Onsager equation is a cornerstone of physical chemistry, providing a method to determine the molar conductance (Λm) and molar conductance at infinite dilution (Λ°m) for uni-univalent electrolytes.Uni-univalent electrolytes are electrolytes that dissociate in solution to produce one cation with a +1 charge and one anion with a –1 charge per formula unit.This equation addresses two crucial phenomena: the asymmetry effect and the electrophoretic effect.
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Particles in a solid are tightly packed together (fixed shape) and often arranged in a regular pattern; in a liquid, they are close together with no regular arrangement (no fixed shape); in a gas, they are far apart with no regular arrangement (no fixed shape). Particles in a solid vibrate about fixed positions (cannot flow) and do not generally move in relation to one another; in a liquid, they move past each other (can flow) but remain in essentially constant contact; in a gas, they move...
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Network covalent solids contain a three-dimensional network of covalently bonded atoms as found in the crystal structures of nonmetals like diamond, graphite, silicon, and some covalent compounds, such as silicon dioxide (sand) and silicon carbide (carborundum, the abrasive on sandpaper). Many minerals have networks of covalent bonds.
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Reproducibility in density functional theory calculations of solids.

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Density functional theory (DFT) codes show excellent agreement for crystal properties when using recent methods, comparable to experimental precision. Older DFT approaches exhibit less precise predictions, highlighting the need for benchmarking.

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Area of Science:

  • Solid-state physics
  • Computational materials science
  • Quantum chemistry

Background:

  • Density functional theory (DFT) is widely used for predicting material properties.
  • Numerous DFT codes exist, but variations in implementation raise reproducibility concerns.
  • Standardized benchmarking is needed to assess code accuracy and reliability.

Purpose of the Study:

  • To evaluate the reproducibility and accuracy of DFT codes for crystalline solids.
  • To compare the performance of 15 solid-state DFT codes using various potentials and basis sets.
  • To assess the Perdew-Burke-Ernzerhof (PBE) exchange-correlation functional for elemental crystals.

Main Methods:

  • Community-wide benchmarking effort involving 15 solid-state DFT codes.
  • Utilized 40 different pseudopotential and basis set combinations.
  • Calculated equations of state for 71 elemental crystals using the PBE functional.

Main Results:

  • Recent DFT codes and pseudopotentials demonstrate high agreement for crystal properties.
  • Pairwise differences between modern codes are comparable to experimental uncertainties.
  • Older DFT methods show significantly less precise agreement.
  • The study established a benchmark for assessing PBE predictions.

Conclusions:

  • Modern DFT codes offer reliable and reproducible predictions for crystalline solids.
  • The developed benchmark framework aids in evaluating new DFT methods and improvements.
  • Users and developers can leverage this work to ensure prediction quality and consistency.