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Related Concept Videos

The Aufbau Principle and Hund's Rule03:02

The Aufbau Principle and Hund's Rule

To determine the electron configuration for any particular atom, we can build the structures in the order of atomic numbers. Beginning with hydrogen, and continuing across the periods of the periodic table, we add one proton at a time to the nucleus and one electron to the proper subshell until we have described the electron configurations of all the elements. This procedure is called the aufbau principle, from the German word aufbau (“to build up”). Each added electron occupies the subshell of...
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Electronic Structure of Atoms


An atom comprises protons and neutrons, which are contained inside the dense, central core called the nucleus, with electrons present around the nucleus. Taking into account the wave–particle duality of electrons and the uncertainty in position around the nucleus, quantum mechanics provides a more accurate model for the atomic structure. It describes atomic orbitals as the regions around the nucleus where electrons of discrete energy exist, characterized by four quantum numbers:  n, l, ml, and...
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Electron Configurations

Electron configurations and orbital diagrams can be determined by applying the Aufbau principle (each added electron occupies the subshell of lowest energy available), Pauli exclusion principle (no two electrons can have the same set of four quantum numbers), and Hund’s rule of maximum multiplicity (whenever possible, electrons retain unpaired spins in degenerate orbitals).
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Electron Configuration of Multielectron Atoms03:26

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The alkali metal sodium (atomic number 11) has one more electron than the neon atom. This electron must go into the lowest-energy subshell available, the 3s orbital, giving a 1s22s22p63s1 configuration. The electrons occupying the outermost shell orbital(s) (highest value of n) are called valence electrons, and those occupying the inner shell orbitals are called core electrons. Since the core electron shells correspond to noble gas electron configurations, we can abbreviate electron...
Atomic Structure01:17

Atomic Structure

The Greek philosopher Democritus proposed that everything on Earth is made up of tiny particles called atomos, Greek for "indivisible," from which the modern term "atom" is derived. In the 19th century, John Dalton proposed the atomic theory that is still largely correct today. He put forth five postulates to explain how atoms made up the world around us. (1) All matter is composed of infinitely small particles or atoms. (2) All atoms of a given element are identical to one another and (3) are...
Atomic Structure01:33

Atomic Structure

Overview

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Picometer-Precision Atomic Position Tracking through Electron Microscopy
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Picometer-Precision Atomic Position Tracking through Electron Microscopy

Published on: July 3, 2021

Finding the atomic configuration with a required physical property in multi-atom structures.

Mayeul d'Avezac1, Alex Zunger

  • 1National Renewable Energy Laboratory, Golden, CO 80401, USA.

Journal of Physics. Condensed Matter : an Institute of Physics Journal
|November 4, 2011
PubMed
Summary
This summary is machine-generated.

This study presents two computational methods for discovering optimal atomic structures in alloys. A global-search genetic algorithm efficiently finds minimum energy configurations, while a local-search virtual-atom approach excels at targeting specific material properties.

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Area of Science:

  • Computational Materials Science
  • Solid-State Chemistry
  • Alloy Design

Background:

  • Determining optimal atomic arrangements in materials is crucial for tuning properties.
  • The vast configurational space of alloys presents a significant computational challenge.
  • Existing methods struggle to efficiently explore this space for specific energy or property targets.

Purpose of the Study:

  • To develop and compare two novel computational approaches for identifying specific atomic decorations in alloys.
  • To evaluate the efficiency of these methods in finding both minimum-energy and target-property configurations.
  • To assess the performance on a face-centered cubic Gold-Palladium (Au-Pd) alloy system.

Main Methods:

  • Global-search genetic algorithm with diversity constraints and reciprocal-space mating.
  • Local-search virtual-atom approach.
  • Comparative analysis of efficiency for energy minimization and property targeting.

Main Results:

  • The genetic algorithm effectively identified the global minimum energy configuration for the Au-Pd alloy.
  • The virtual-atom approach demonstrated higher efficiency in locating configurations with a target property.
  • Both methods offer distinct advantages depending on the specific materials discovery objective.

Conclusions:

  • A global-search genetic algorithm is highly efficient for finding the lowest energy structures in complex alloys.
  • A local-search virtual-atom method is superior for discovering alloy structures with desired physical properties.
  • These computational strategies significantly advance materials design by navigating vast configurational spaces.