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Hybridization of Atomic Orbitals I03:24

Hybridization of Atomic Orbitals I

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The mathematical expression known as the wave function, ψ, contains information about each orbital and the wavelike properties of electrons in an isolated atom. When atoms are bound together in a molecule, the wave functions combine to produce new mathematical descriptions that have different shapes. This process of combining the wave functions for atomic orbitals is called hybridization and is mathematically accomplished by the linear combination of atomic orbitals. The new orbitals that...
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sp3d and sp3d 2 Hybridization
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A hydrogen bond is formed when a weakly positive hydrogen atom already bonded to one electronegative atom (for example, the oxygen in the water molecule) is attracted to another electronegative atom from another polar molecule, such as water (H2O), hydrogen fluoride (HF), or ammonia (NH3). The huge electronegativity difference between the H atom (2.1) and the atom to which it is bonded (4.0 for an F atom, 3.5 for an O atom, or 3.0 for an N atom), combined with the very small size of an H atom...
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Hydrogen bonds are weak attractions between atoms that have formed other chemical bonds. One of these atoms is electronegative, like oxygen, and has a partial negative charge. The other is a hydrogen atom that has bonded with another electronegative atom and has a partial positive charge.
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Individual molecules in a gas move in random directions, but a gas containing numerous molecules has a predictable distribution of molecular speeds, which is known as the Maxwell-Boltzmann distribution, f(v).
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Related Experiment Video

Updated: Jan 6, 2026

Multiscale Sampling of a Heterogeneous Water/Metal Catalyst Interface using Density Functional Theory and Force-Field Molecular Dynamics
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Grand Canonical Monte Carlo Simulations for Hydrogen Adsorption on Metal Surfaces Using Neural Network Potentials.

Tomoya Kanno1, Tatsushi Ikeda1, Akira Nakayama1

  • 1Department of Chemical System Engineering, The University of Tokyo, Tokyo 113-8656, Japan.

Journal of Chemical Theory and Computation
|October 30, 2025
PubMed
Summary

This study uses advanced simulations to explore hydrogen adsorption on platinum, palladium, and iridium surfaces. Findings reveal how temperature and pressure affect hydrogen atom behavior, crucial for developing better catalysts and storage materials.

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Area of Science:

  • Materials Science
  • Computational Chemistry
  • Surface Science

Background:

  • Hydrogen adsorption on metal surfaces is key for catalysis and storage.
  • Accurate simulation of these interactions is computationally challenging.

Purpose of the Study:

  • To investigate hydrogen adsorption on Pt, Pd, and Ir surfaces using advanced simulation techniques.
  • To develop and validate high-fidelity, computationally feasible neural network potentials for surface phenomena.

Main Methods:

  • Grand canonical Monte Carlo simulations combined with density functional theory-based neural network potentials.
  • Incorporation of modified cavity bias, generalized hybrid Monte Carlo, and replica exchange methods for efficient sampling.
  • Refinement of neural network potentials using additional loss terms for accurate adsorption energy prediction.

Main Results:

  • Efficient sampling of atomic configurations across various temperatures and pressures was achieved.
  • Hydrogen density profiles on metal surfaces were analyzed with reliable accuracy.
  • The influence of temperature and pressure on hydrogen atom configurations and surface interactions was elucidated.

Conclusions:

  • The study demonstrates the efficacy of neural network potentials for high-fidelity simulations of complex surface phenomena.
  • The findings provide critical insights for optimizing catalytic and hydrogen storage materials.
  • Advanced simulation methods enable a deeper understanding of hydrogen-metal surface interactions under diverse thermodynamic conditions.