In the quality control of granules in the pharmaceutical industry, in the research and characterization of nanomaterials, and in the optimization of particle size in food powders,The particle size and shape analyzer, with its high precision and fast analysis capabilities, has become a crucial "particle decoder" in scientific research and production.This device uses optical imaging or laser scattering technology to accurately measure the size and morphology of particles in the range of 0.1 μ m to 3mm, providing key data for process optimization and product performance improvement. The following outlines the core usage methods from sample preparation, instrument operation to data analysis, to help you efficiently master particle characterization technology.

　　1、 Sample preparation: details determine data quality

1. Decentralized processing

Particle agglomeration is the main interfering factor affecting the analysis results. For micrometer sized particles, a 0.1% solution of sodium hexametaphosphate should be added as a dispersant and subjected to ultrasonic treatment (power 200W, time 5 minutes) to fully disperse the particles; Nanoparticles need to be dispersed with surfactants (such as SDS) to avoid aggregation due to van der Waals forces.

2. Concentration control

The sample concentration needs to be adjusted according to the instrument type: the laser diffractometer requires a light shielding ratio between 5% and 15%; The image analysis rule requires particles to be evenly distributed and non overlapping in the field of view.

3. Media selection

Select appropriate dispersion medium based on particle properties: water-soluble particles with water or ethanol; Oil soluble particles are prepared using n-hexane or silicone oil; Biological particles require physiological saline or PBS buffer solution.

　　2、 Instrument operation: Standardize processes to ensure accuracy

1. Calibration and baseline testing

After startup, standard particles are required for calibration. The laser diffractometer needs to verify that the D50 (median particle size) deviation is ≤ 2%; The image analyzer needs to check the accuracy of the ruler (error ≤ 1%).

2. Parameter settings

Laser diffractometer: Select optical parameters such as refractive index (such as 1.46 for silicon dioxide) and absorption index (usually set to 0.1 for organic particles);

Image analyzer: Set threshold (to distinguish particles from background) and minimum recognition particle size (usually twice the instrument resolution).

3. Sample testing

Inject the dispersed sample into the sample pool (laser method) or drop it onto a glass slide (image method), and start the analysis program. The laser method requires waiting for the signal to stabilize (usually 30 seconds); The image rule needs to ensure that the number of particles in the field of view is ≥ 500 to obtain statistical significance.

　　3、 Data analysis: from raw data to process insights

1. Interpretation of Particle Size Distribution

Pay attention to key indicators such as D10 (10% particles smaller than this value), D50, D90, and span (Span=(D90-D10)/D50) to reflect the width of distribution.

2. Shape parameter analysis

The image analysis method can output morphological data such as roundness and aspect ratio (reflecting the degree of particle elongation).

3. Data export and reporting

Supports exporting in Excel/CSV format, capable of generating visual reports such as granularity distribution curves and shape parameter histograms. Some models also support integration with LIMS systems to achieve automated data flow.

　　Conclusion: Particle characterization, precision first

From sample dispersion to data interpretation, every step of the particle size and shape analyzer operation is related to the reliability of the results. Mastering standardized usage methods can not only improve experimental efficiency, but also provide a solid basis for process optimization and product innovation. Choose suitable instrument models and customize analysis solutions based on industry needs, making particle characterization your "smart eye" in research and production.