Importance of Sample Preparation in Scientific Analysis

    Performing sample analysis through an advanced scientific instrument or equipment requires that the sample is properly treated and prepared. In this regard, extraction is the first step, considering that a representative portion of the material or substance must be isolated for its study. This post will tell you more about sample preparation, its importance, and some methods used to perform this procedure.

    What is Sample Preparation?

    This refers to a process where we take a representative portion of a material, chemical product, or substance to be subjected to various procedures to analyze it. It should be noted that this representative sample should reflect the bulk or batch from which it has been extracted and concentrate the characteristics of the material, product, or substance chosen to be analyzed. Preferably, the representative sample should be as homogeneous as possible or of a similar nature, as is done to obtain the proteins and nuclear components present in the cells through a process known as tissue homogenization. But when this is not possible, we then use a sample that gathers the characteristics of the predominant group.

    Homogeneity as the Main Objective of Sample Collection

    To obtain representative samples, it is often necessary to reduce the size of the particles, which usually present a general heterogeneous state. This aims to comply with a homogeneity criterion when laboratory or test samples require it. In the case of air, the particles in this element are obtained through an air sampler, which may be equipped with a liquid or solid material to facilitate this task. A sample’s homogeneity and heterogeneity will be subject to perspective and context since the smaller the sampling frame, the less homogeneous the material or substance.

    A process known as crushing is used to reduce a large sample size to obtain the required measure of homogeneity. For other samples, a technique known as milling is used to reduce the sample to fine particles and achieve the necessary homogeneity. A process known as crushing is used to reduce a large sample size to obtain the required measure of homogeneity. For other samples, a process known as milling is used to reduce the sample to fine particles and achieve the necessary homogeneity.

    Considerations in the Sampling of Solids, Liquids and Gases

    Within the sampling process, two forms of solids are contemplated: monolithic and particulate. Liquids and gases accompany these. Each type of material should be handled as a separate category.

    However, on some occasions, it will be required to sample from mixed materials, i.e., gases dissolved in solids and liquids, particles suspended in liquids, or solid and liquid aerosols. There are cases where the object of study is available in one phase form but must be converted to another form to obtain the sample. For its analysis, an example would be molten steel generated from the melting of solid forms.

    When it comes to monolithic solids, they are difficult to sample rationally, even those with a very low level of heterogeneity. Even so, understanding the physical nature of the study object can help devise an effective sampling plan. This idea can be best understood in a large mineral deposit that extends long distances underground in three dimensions. Here, mineralogical clues serve as a reference to guide the sampling for the mapping effort. Steel castings are usually sampled at the mid-radius of their cross-section because this area has not been affected by edge effects and central porosity.

    Types of Sampling

    Regardless of the method, the objective will always be to take a sample representing a specific group or population. In addition, through these sampling methods, it must be ensured that there is an approximately equal probability that each part of the sample population is suitable for selection and analysis. This requires a random element in the chosen sampling strategy. Some of the best-known are:

    • Simple Random Sampling: here, the population is divided into units. Then, a sample is selected from each unit with the same probability of selection for each unit in each draw.
    • Systematic Grid Sampling: in this process, samples are collected in grids, i.e., dividing the population into two- or three-dimensional grids. This type of sampling is usually used when locating possible hot spots in a population.
    • Two-Stage Sampling: this sampling method randomly selects elementary units from a population. Then, the increments generated by the sample are taken at locations within each unit.
    • Stratified Random Sampling: this refers to the division of a population into sections, also called strata. Here, the strata’s number, size, and shape are essential factors to consider in designing an efficient and cost-effective sampling plan.
    • Survey Sampling: in this type of sampling, a group of distinct and identifiable units is taken from the population and assigned the name cluster. Cluster sampling is choosing a group of units and referring to it as a single unit. So, the formation of clusters is the same as the formation of groups of heterogeneous nature.

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