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Related Concept Videos

Composition of Polyprotic Acid Solutions as a Function of pH01:19

Composition of Polyprotic Acid Solutions as a Function of pH

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Polyprotic acids of the type H2M constitute two ionizable protons. As a result, on titration with a base, they exhibit two equivalence points in the titration curve. During titration, the species H2M, HM−, and M2− will be present in the solution at different points. The fractions of H2M, HM−, and M2− present at the various instances of the titration are denoted by α0, α1, and α2, respectively.
A graph with the alpha values is plotted against the volume of...
493
Sulfur Assimilation01:20

Sulfur Assimilation

Sulfur is an essential element in biological systems, contributing to synthesizing key biomolecules, including amino acids such as cysteine and methionine, and cofactors such as coenzyme A and biotin. Microorganisms primarily assimilate sulfur as sulfate (SO₄²⁻) from the environment, which must undergo a series of biochemical transformations before it can be incorporated into cellular components. As sulfate is highly oxidized, it must undergo assimilatory sulfate reduction to...
Preparation and Reactions of Sulfides02:26

Preparation and Reactions of Sulfides

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Sulfides are the sulfur analog of ethers, just as thiols are the sulfur analog of alcohol. Like ethers, sulfides also consist of two hydrocarbon groups bonded to the central sulfur atom. Depending upon the type of groups present, sulfides can be symmetrical or asymmetrical. Symmetrical sulfides can be prepared via an SN2 reaction between 2 equivalents of an alkyl halide and one equivalent of sodium sulfide.
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Solution Composition During Acid/Base Titrations01:17

Solution Composition During Acid/Base Titrations

561
The titration of a weak acid with a strong base results in the formation of water and the conjugate base of the acid. For instance, titrating acetic acid with sodium hydroxide leads to the formation of water and sodium acetate. A solution of acetic acid and sodium acetate constitutes a buffer whose relative concentration at different stages of the titration is indicated by the α values, which represent percentages of the weak acid and its conjugate base.
The α0 and α1 values...
561
Preparation of Acid Anhydrides01:07

Preparation of Acid Anhydrides

3.1K
One of the methods for preparing symmetrical or unsymmetrical acid anhydrides involves the treatment of acid chlorides with the sodium salt of carboxylic acids. The reaction proceeds via a nucleophilic acyl substitution.
The carboxylate ion acts as a nucleophile that attacks the carbonyl carbon of the acid chloride to form a tetrahedral intermediate. Subsequently, the re-formation of the carbonyl group with the loss of the chloride ion as a leaving group leads to the formation of an acid...
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Ladder Diagrams: Acid–Base Equilibria01:32

Ladder Diagrams: Acid–Base Equilibria

446
Understanding the chemistry between the reagents is necessary for performing any experiment. To this end, scientists have designed a tool called a ladder diagram, which is a graphical representation that helps illustrate the chemistry of a system.
A ladder diagram for acid-base equilibria consists of a vertical axis that represents pH and horizontal bars (steps on the ladder) that help position all the pKa values in the system. At equilibrium, the pH value of the system corresponds to one of...
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Updated: Jun 4, 2025

Curation of Computational Chemical Libraries Demonstrated with Alpha-Amino Acids
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Predicting Composition Evolution for a Sulfuric Acid-Dimethylamine System from Monomer to Nanoparticle Using Machine

Yi-Rong Liu1, Yan Jiang2

  • 1Public Experimental Teaching Center, Panzhihua University, Panzhihua, Sichuan 61700, China.

The Journal of Physical Chemistry. A
|December 26, 2024
PubMed
Summary
This summary is machine-generated.

Machine learning predicts new particle formation in sulfuric acid-dimethylamine systems. Growth occurs via cluster adsorption, explaining acidity changes during nucleation.

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Area of Science:

  • Atmospheric Chemistry
  • Chemical Physics
  • Computational Chemistry

Background:

  • New particle formation (NPF) is crucial for climate and air quality.
  • Understanding early-stage compositional changes in NPF is experimentally difficult.
  • Acid-base systems like sulfuric acid-dimethylamine are key NPF components.

Purpose of the Study:

  • Develop a machine learning (ML) method to predict NPF composition.
  • Analyze the transformation from monomers to nanoparticles in SA-DMA systems.
  • Investigate the role of molecular clusters in early nucleation stages.

Main Methods:

  • Utilized ML to learn structure-composition relationships of small SA-DMA clusters.
  • Applied the ML model to predict compositional evolution during nucleation.
  • Analyzed cluster adsorption patterns based on ML predictions.

Main Results:

  • Sulfuric acid-dimethylamine growth primarily occurs through sequential adsorption of (SA)1(DMA)1, (SA)1(DMA)2, and (SA)1 clusters.
  • These adsorption events account for approximately 70%, 20%, and 10% of growth, respectively.
  • The ML method successfully predicts base-stabilization mechanisms without experimental data.

Conclusions:

  • The ML approach provides insights into the dynamic compositional changes during NPF.
  • Findings explain acidity variations in SA-DMA clusters during initial nucleation.
  • The ML method offers a viable alternative to experimental data for predicting NPF mechanisms.