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1° Amines to Diazonium or Aryldiazonium Salts: Diazotization with NaNO2 Overview01:26

1° Amines to Diazonium or Aryldiazonium Salts: Diazotization with NaNO2 Overview

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Nitrous acid and nitric acids are two types of acids containing nitrogen, among which nitrous acid is weaker than nitric acid. Nitrous acid with a pKa value of 3.37 ionizes in water to give a nitrite ion and the hydronium ion.
The nitrous acid is unstable. Hence, it is formed in situ from a solution of sodium nitrite and cold aqueous acids such as hydrochloric or sulfuric acid. In an acidic solution, the –OH group of nitrous acid undergoes protonation to give oxonium ion, followed by...
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Molecular Models02:00

Molecular Models

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Physical models representing molecular architectures of chemical compounds play essential roles in understanding chemistry. The use of molecular models makes it easier to visualize the structures and shapes of atoms and molecules.
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Weak Acid Solutions04:02

Weak Acid Solutions

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Few compounds act as strong acids. A far greater number of compounds behave as weak acids and only partially react with water, leaving a large majority of dissolved molecules in their original form and generating a relatively small amount of hydronium ions. Weak acids are commonly encountered in nature, being the substances partly responsible for the tangy taste of citrus fruits, the stinging sensation of insect bites, and the unpleasant smells associated with body odor. A familiar example of a...
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Strong Acid and Base Solutions03:22

Strong Acid and Base Solutions

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A strong acid is a compound that dissociates completely in an aqueous solution and produces a concentration of hydronium ions equal to the initial concentration of acid. For example, 0.20 M hydrobromic acid will dissociate completely in water and produces 0.20 M of hydronium ions and 0.20 M of bromide ions.
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Nuclear Overhauser Enhancement (NOE)01:06

Nuclear Overhauser Enhancement (NOE)

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Irradiation of a spin-active nucleus causes an increase or decrease in the signal intensity of neighboring nuclei that are not necessarily chemically bonded or involved in J-coupling. This phenomenon, called the nuclear Overhauser enhancement (NOE), results from through-space interactions between the nuclear spins. The NOE effect decreases with increasing internuclear distance and is generally not observed beyond 4 angstroms. In NOE, dipole-dipole interactions between neighboring spin-active...
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Mixtures of Acids03:27

Mixtures of Acids

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The pH of a solution containing an acid can be determined using its acid dissociation constant and its initial concentration. If a solution contains two different acids, then its pH can be determined using one of several methods depending upon the relative strength of the acids and their dissociation constants.
A Mixture of a Strong Acid and a Weak Acid
In a mixture of a strong acid and a weak acid, the strong acid dissociates completely and becomes a source of almost all the hydronium ions...
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Updated: Jan 13, 2026

Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry
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Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry

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Modeling the behavior of concentrated aqueous HNO3 using machine learning interatomic potentials.

Mohammadhasan Dinpajooh1, Michael D Lacount2, Scott E Muller2

  • 1Physical and Computational Sciences Directorate, Pacific Northwest National Laboratory, Richland, Washington 99352, USA.

The Journal of Chemical Physics
|January 6, 2026
PubMed
Summary
This summary is machine-generated.

We developed machine learning potentials for nitric acid simulations, accurately predicting its acidity and structural properties across various concentrations. These potentials offer a faster and more accurate alternative to existing models for chemical research.

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Area of Science:

  • Computational Chemistry
  • Materials Science
  • Chemical Physics

Background:

  • Investigating the behavior of nitric acid (HNO3) across different concentrations is crucial for understanding its chemical properties.
  • Existing computational models often struggle to accurately capture the complex structural and thermodynamic properties of nitric acid, especially concerning its dissociation.
  • The development of accurate and efficient interatomic potentials is essential for molecular dynamics simulations.

Purpose of the Study:

  • To develop and validate multi-defect machine learning interatomic potentials (MLIPs) for nitric acid using the DeepMD-kit.
  • To investigate the structural and thermodynamic properties of nitric acid over a wide range of concentrations using molecular dynamics (MD) simulations.
  • To compare the performance of custom DeepMD MLIPs against foundational models like MACE-MP0 and MACE-OFF23.

Main Methods:

  • Training two multi-defect MLIPs using BLYP-D2 and PBE-D3 density functional theories with DeepMD-kit.
  • Performing MD simulations to investigate structural and thermodynamic properties, including the degree of dissociation (α) and pKa.
  • Benchmarking custom DeepMD MLIPs against MACE-MP0 and MACE-OFF23, and comparing with classical force fields (FFs).

Main Results:

  • The developed MLIPs accurately predict the degree of dissociation (α) and pKa of nitric acid, showing good agreement with experimental data.
  • HNO3 exhibits weaker acid behavior at higher concentrations, with a standard-state pKa matching experimental values.
  • Custom DeepMD MLIPs provide more compact solvation shells, reproduce density-concentration trends, and are significantly faster than MACE-MP0, outperforming foundational models in capturing subtle structural features.

Conclusions:

  • Bespoke, reactive MLIPs are necessary for accurately simulating chemical reactivity and properties like dissociation, going beyond universal MLIPs.
  • The developed DeepMD MLIPs offer a significant advancement for studying concentrated nitric acid systems, providing accurate predictions and improved computational efficiency.
  • While classical FFs are efficient for density, they lack the chemical reactivity crucial for predicting dissociation and acidity, highlighting the value of reactive MLIPs.