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Related Concept Videos

Correlation of Experimental Data01:23

Correlation of Experimental Data

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Dimensional analysis simplifies complex physical problems and guides experimental investigations, but it does not provide complete solutions. It identifies the dimensionless groups that influence a phenomenon, but experimental data is needed to establish the specific relationships and validate theoretical predictions.
For example, a spherical particle moving through a viscous fluid experiences drag. Dimensional analysis shows that the drag force depends on the particle's diameter, velocity,...
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Precipitation Gravimetry

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Precipitation gravimetry is based on converting an analyte into a sparingly soluble precipitate, which is separated by filtration and weighed. An ideal precipitate should be pure, insoluble, of known composition, and easily filtered from the reaction mixture.
In determining nickel by gravimetric analysis, a precipitant of ethanolic dimethylglyoxime is added to a hot nickel salt solution. This is quickly followed by the dropwise addition of dilute ammonia solution until precipitation occurs. A...
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Precipitation and Co-precipitation01:17

Precipitation and Co-precipitation

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Precipitation and coprecipitation methods can be used to separate a mixture of ions in a solution. In qualitative inorganic analysis, ions that form sparingly soluble precipitates with the same reagent are separated based on the differences in solubility products. For example, consider the separation of Cu(II) and Fe(II) ions by precipitation as insoluble sulfides. First, copper(II) sulfide is precipitated by the addition of acidic H2S, where the dissociation of H2S is suppressed. Adding H2S...
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Correlations02:20

Correlations

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Correlation means that there is a relationship between two or more variables (such as ice cream consumption and crime), but this relationship does not necessarily imply cause and effect. When two variables are correlated, it simply means that as one variable changes, so does the other. We can measure correlation by calculating a statistic known as a correlation coefficient. A correlation coefficient is a number from -1 to +1 that indicates the strength and direction of the relationship between...
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Scatter Plot01:15

Scatter Plot

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The most common and easiest way to display the relationship between two variables, x and y, is a scatter plot. A scatter plot shows the direction of a relationship between the variables. A clear direction happens when there is either:
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Types of Coprecipitation

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Coprecipitation is the contamination of a precipitate by otherwise soluble species and occurs via different processes. In colloidal precipitates, coprecipitation occurs via surface adsorption. For instance, barium sulfate has a primary layer of adsorbed barium ions and a secondary layer of nitrate counterions. This results in contamination of the precipitate by barium nitrate.
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Updated: Sep 8, 2025

Measuring and Mapping Patterns of Soil Erosion and Deposition Related to Soil Carbonate Concentrations Under Agricultural Management
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Empirical Deposition Correlations.

Andrew R Martin1, Warren H Finlay2

  • 1Department of Mechanical Engineering, 10-324 Donadeo Innovation Center for Engineering, University of Alberta, Edmonton, Canada.

Journal of Aerosol Medicine and Pulmonary Drug Delivery
|June 14, 2022
PubMed
Summary
This summary is machine-generated.

New empirical equations predict inhaled aerosol deposition in the respiratory tract using advanced in vitro models and existing in vivo data. These correlations improve predictions for various aerosol sizes, ages, and breathing patterns.

Keywords:
Reynolds numberStokes numberdimensionless parametersmouth-throat depositionnasal depositionoropharyngeal depositiontotal deposition fractionupper airway

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Area of Science:

  • Aerosol science
  • Respiratory physiology
  • Biomedical engineering

Background:

  • Empirical correlations for respiratory aerosol deposition traditionally relied on limited in vivo data.
  • Advances in medical imaging and 3D printing enable more realistic in vitro airway replicas for deposition studies.

Purpose of the Study:

  • To review and present empirical correlations for predicting total and regional aerosol deposition in the respiratory tract.
  • To provide equations applicable to a wide range of aerosol sizes, subject ages, and breathing maneuvers.
  • To describe the use of these correlations for estimating total lung deposition.

Main Methods:

  • Review of existing empirical correlations derived from both in vivo and in vitro studies.
  • Utilizing data from extensive in vitro deposition experiments in realistic upper and central airway replicas.
  • Analysis of medical image segmentation and additive manufacturing for creating experimental models.

Main Results:

  • A collection of empirical equations for predicting regional aerosol deposition, particularly in the upper, nasal, and oral airways, has been developed.
  • Equations are available for total respiratory deposition fraction, mouth-throat fraction, and nasal/nose-throat fractions.
  • The correlations cover diverse aerosol characteristics, subject demographics, and breathing conditions.

Conclusions:

  • The reviewed empirical correlations, based on both in vivo and in vitro data, offer improved predictions of aerosol deposition.
  • These equations are valuable tools for estimating aerosol deposition across different regions of the respiratory tract.
  • The findings support the use of advanced in vitro methods for developing predictive models in respiratory aerosol research.