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In chemistry, a mixture is a material system made up by two or more different substances which are mixed but are not combined chemically. A mixture refers to the physical combination of two or more substances on which the identities are retained and are mixed in the form of alloys, solutions, suspensions, and colloids.

Mixtures are the product of a mechanical blending or mixing of chemical substances like elements and compounds, without chemical bonding or other chemical change, so that each ingredient substance retains its own chemical properties and makeup. Despite that there are no chemical changes to its constituents, the physical properties of a mixture, such as its melting point, may differ from those of the components. Some mixtures can be separated into their components by physical (mechanical or thermal) means. Azeotropes can be considered as a kind of mixture which usually pose considerable difficulties regarding the separation processes required to obtain their constituents (physical or chemical processes or, even a blend of them).

Examples of mixtures

Mixtures can be either homogeneous or heterogeneous. A homogeneous mixture is a type of mixture in which the composition is uniform. A heterogeneous mixture is a type of mixture in which the components can easily be identified, as there are two or more phases present. Air is a homogeneous mixture of the gaseous substances nitrogen, oxygen, and smaller amounts of other substances. Salt, sugar, and many other substances dissolve in water to form homogeneous mixtures. A homogeneous mixture in which there is both a solute and solvent present is also a solution.The following are some examples of a heterogeneous mixture: •Sand in water •SMOKE •Chicken soup •Protoplasm •Silt in water •Tomato juice •Clouds •Vinegar in oil •Mayonnaise •Ice cream •Concrete •Wood •Salad dressing •Soil •Chocolate chip cookie •Muddy water •sugar and cornstarch •Mixture of different types of cereals The following table shows the main properties of the three families of mixtures.

The following table shows examples of the three types of mixtures.

Physics and chemistry

A heterogeneous mixture is a mixture of two or more chemical substances (elements or compounds}. Examples are: mixtures of sand and water or sand and iron filings, a conglomerate rock, water and oil, a salad, trail mix, and concrete (not cement). A mixture of powdered silver metal and powdered gold metal would represent a heterogeneous mixture of two elements.

Making a distinction between homogeneous and heterogeneous mixtures is a matter of the scale of sampling. On a coarse enough scale, any mixture can be said to be homogeneous, if you'll allow the entire article to count as a "sample" of it. On a fine enough scale, any mixture can be said to be heterogeneous, because a sample could be as small as a single molecule. In practical terms, if the property of interest of the mixture is the same regardless of which sample of it is taken for the examination used, the mixture is homogeneous.

Gy's sampling theory quantitatively defines the heterogeneity of a particle as:

${\displaystyle h_{i}={\frac {(c_{i}-c_{\text{batch}})m_{i}}{c_{\text{batch}}m_{\text{aver}}}}.}$

where ${\displaystyle h_{i}}$, ${\displaystyle c_{i}}$, ${\displaystyle c_{\text{batch}}}$, ${\displaystyle m_{i}}$, and ${\displaystyle m_{\text{aver}}}$ are respectively: the heterogeneity of the ${\displaystyle i}$th particle of the population, the mass concentration of the property of interest in the ${\displaystyle i}$th particle of the population, the mass concentration of the property of interest in the population, the mass of the ${\displaystyle i}$th particle in the population, and the average mass of a particle in the population.

During sampling of heterogeneous mixtures of particles, the variance of the sampling error is generally non-zero.

Pierre Gy derived, from the Poisson sampling model, the following formula for the variance of the sampling error in the mass concentration in a sample:

${\displaystyle V={\frac {1}{(\sum _{i=1}^{N}q_{i}m_{i})^{2}}}\sum _{i=1}^{N}q_{i}(1-q_{i})m_{i}^{2}\left(a_{i}-{\frac {\sum _{j=1}^{N}q_{j}a_{j}m_{j}}{\sum _{j=1}^{N}q_{j}m_{j}}}\right)^{2}.}$

in which V is the variance of the sampling error, N is the number of particles in the population (before the sample was taken), q _i is the probability of including the ith particle of the population in the sample (i.e. the first-order inclusion probability of the ith particle), m _i is the mass of the ith particle of the population and a _i is the mass concentration of the property of interest in the ith particle of the population.

It must be noted that the above equation for the variance of the sampling error is an approximation based on a linearization of the mass concentration in a sample.

In the theory of Gy, correct sampling is defined as a sampling scenario in which all particles have the same probability of being included in the sample. This implies that q _i no longer depends on i, and can therefore be replaced by the symbol q. Gy's equation for the variance of the sampling error becomes:

${\displaystyle V={\frac {1-q}{qM_{\text{batch}}^{2}}}\sum _{i=1}^{N}m_{i}^{2}\left(a_{i}-a_{\text{batch}}\right)^{2}.}$

where a_batch is that concentration of the property of interest in the population from which the sample is to be drawn and M_batch is the mass of the population from which the sample is to be drawn.

Also, milk is a mixture.

References

1. Atkins' Physical Chemistry, 7th Ed. by Julio De Paula, P.W. Atkins ISBN 0-19-879285-9
2. ^ http://iupac.org/publications/pac/pdf/1972/pdf/3104x0577.pdf
3. Gy, P (1979) Sampling of Particulate Materials: Theory and Practice, Elsevier: Amsterdam

IUPAC, Compendium of Chemical Terminology, 2nd ed. (the "Gold Book") (1997). Online corrected version: (2006–) "mixture". doi:10.1351/goldbook.M03949

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• Chemical mixtures
• Physical chemistry
• Chemistry