A Particle Size Analyzer is an instrument used to measure the size distribution of particles in a sample. These analysers are essential in a variety of industries like pharmaceuticals, mining, food, cosmetics, and chemicals, where particle size can significantly impact product quality and performance.

 Types of Particle Size Analysers

1. Laser Diffraction (LD)
   • Principle: Measures light scattering patterns to determine size.
   • Range: ~0.01 µm to 3,000 µm.
   • Common Uses: Powders, suspensions, emulsions.
   • Pros: Fast, wide range, high repeatability.
2. Dynamic Light Scattering (DLS)
   • Principle: Analyzes Brownian motion to calculate size.
   • Range: ~1 nm to 1 µm.
   • Common Uses: Nanoparticles, proteins, polymers.
   • Pros: Great for nano-sized particles, quick.
3. Sieve Analysis
   • Principle: Physical separation through stacked sieves.
   • Range: >45 µm.
   • Common Uses: Granular materials (sand, grain).
   • Pros: Simple, low-cost, robust.
4. Image Analysis
   • Principle: Digital imaging and software measure particle dimensions.
   • Range: ~1 µm to several mm.
   • Common Uses: Irregular particles, shape analysis.
   • Pros: Gives size and shape data.
5. Coulter Counter
   • Principle: Measures electrical resistance as particles pass through an aperture.
   • Range: ~0.4 µm to 1,200 µm.
   • Common Uses: Cells, biological particles.
   • Pros: High accuracy for count and size.
6. Sedimentation Techniques
   • Principle: Based on the settling rate of particles in a fluid.
   • Range: ~0.5 µm to 100 µm.
   • Common Uses: Pigments, ceramics.
   • Pros: Good for fine particles.

1. What is a particle size analyzer and why is it important?
This tests your basic understanding. A good answer should cover the analyzer’s role in determining particle size distribution, which affects properties like solubility, stability, texture, reactivity, and quality in many industries (e.g., pharma, food, cosmetics, etc.).

2. What are the common methods of particle size analysis?
Interviewers want to see if you understand the main techniques like:

• Laser diffraction
• Dynamic light scattering
• Sieve analysis
• Image analysis
• Coulter counter
• Sedimentation
• Mentioning when and why each method is used is a plus.

3. How does laser diffraction work for particle size analysis?
This is a widely used method. You should explain the principle (light scattering at different angles depending on particle size), and that software calculates the size distribution using models like Mie theory or Fraunhofer approximation.

4. What is D10, D50, and D90 in particle size distribution?
These are statistical values representing the diameter below which 10%, 50%, and 90% of the sample volume lies. D50 is the median particle size — a key parameter in quality control.

5. How does Dynamic Light Scattering (DLS) measure nanoparticle size?
DLS measures Brownian motion of particles suspended in a fluid and uses the Stokes-Einstein equation to determine hydrodynamic diameter. It’s mostly used for nanoparticles, proteins, and colloids.

6. What factors can affect the accuracy of particle size measurements?
Show you know the practical aspects. Key factors include:

1. Sample preparation (dispersion, agglomeration)
2. Refractive index (for laser diffraction)
3. Instrument calibration
4. Particle shape and density
5. Medium viscosity (for DLS)

7. How do you prepare a sample for particle size analysis?
Good preparation prevents agglomeration and ensures a representative result. You might mention dispersing agents, sonication, dilution, and proper mixing. The goal is a homogenous and stable dispersion.

8. What is the difference between number-based and volume-based particle size distributions?
A key conceptual question:

• Number-based: Counts particles, better for small particles.
• Volume-based: Measures total volume of particles in each size class, common in laser diffraction. Understanding this helps interpret data correctly.

9. How would you validate a particle size analyzer method?
Shows knowledge of QA/QC. You should talk about:

• Repeatability and reproducibility
• Accuracy (use of standards)
• Robustness (varying conditions)
• Calibration and maintenance

10. How do particle size and distribution affect product performance?
Relates technical data to real-world applications.

Examples:

1. Pharma: Dissolution rate and bioavailability.
2. Paints: Finish quality and color consistency.
3. Cement: Strength and setting time.
4. Food: Texture and mouthfeel.

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