Tests Granularity

Tests Granularity – Particle Size Distribution Analysis for Powders, Granules and Bulk Materials

As an ISO/IEC 17025 accredited (CNAS) independent laboratory, we provide comprehensive particle size analysis (granularity testing) services for industries across Angola, including mining, construction materials, pharmaceuticals, food processing, agriculture, and chemical manufacturing. Granularity – the distribution of particle sizes in a powder, granule, or bulk material – is a critical quality attribute that affects flowability, dissolution rate, packing density, reactivity, filtration efficiency, and final product performance. Whether you are producing cement, flour, metal powders, fertilizers, or pharmaceutical excipients, controlling particle size ensures consistent processing and product quality. Our laboratory employs multiple complementary techniques: mechanical sieve analysis (for coarse particles down to 20 µm), laser diffraction (for dry and wet powders from 0.01 µm to 3 mm), dynamic image analysis (for shape and size), and sedimentation methods. We serve the Angolian cement plants, diamond and iron ore mines, agricultural cooperatives, and local manufacturing industries with reliable, accredited test results that help optimize milling processes, verify supplier quality, and troubleshoot production issues.

Types of Materials We Test for Granularity

• Minerals and ores (limestone, iron ore, diamondiferous gravel, copper concentrate, phosphate rock, bauxite)
• Construction materials (cement, sand, aggregates, fly ash, slag, gypsum, lime, fillers)
• Metal powders (aluminum, iron, steel, bronze, copper, zinc, titanium, alloy powders for additive manufacturing)
• Pharmaceutical powders (active ingredients, excipients, granulates, tablet blends, dry powder inhalers)
• Food ingredients (flour, starch, sugar, cocoa powder, spices, protein powders, instant coffee, salt)
• Agricultural products (fertilizers, seeds, animal feed pellets, pesticide granules, soil conditioners)
• Plastic granules (raw material pellets for injection molding, extrusion, blow molding, regrind material)
• Chemical powders (catalysts, pigments, dyes, detergents, carbon black, precipitated silica, zeolites)
• Ceramic powders (clays, glazes, alumina, zirconia, silicon carbide, porcelain bodies)
• Environmental samples (soil, sediment, sludge, fly ash from incinerators, dust from bag filters)
• Recycled materials (crusher fines, glass cullet, rubber powder from tire recycling, construction demolition fines)

Fundamental Concepts – Particle Size, Distribution and Granularity Parameters

Granularity (particle size distribution) describes the relative percentages of particles present in a sample according to their size. It is typically expressed as a cumulative or differential curve. Key parameters derived from the distribution include:

• d10 (µm or mm) – The size at which 10% by volume (or mass) of the particles are smaller. Indicates fine particle tail.
• d50 (median size) – The midpoint of the distribution; 50% of the particles are smaller, 50% larger. Also known as the median particle size.
• d90 (µm or mm) – The size at which 90% of the particles are smaller. Indicates the coarse particle tail.
• Span (distribution width) – Calculated as (d90 – d10) / d50. A smaller span indicates a narrower distribution; a larger span means a wider spread of particle sizes.
• Fineness modulus (for aggregates and sands) – An empirical index used in construction to control concrete mix workability.
• Specific surface area (m²/g) – Related to particle size; finer particles give higher surface area, affecting reactivity and dissolution.

The choice of analytical method depends on the particle size range, material properties (friability, solubility, shape), and the quality system requirements.

Test Methods for Particle Size Analysis

Our laboratory offers a range of methods, from classical sieving to advanced laser diffraction, to cover the full spectrum of industrial particle sizing needs.

1. Mechanical Sieve Analysis (Dry and Wet Sieving)

This is the oldest and most direct method for coarse particles, typically for sizes above 20 µm. A stack of woven wire mesh sieves with decreasing aperture sizes is placed on a vibratory shaker. The powder sample is poured onto the top sieve, and after a set time (5–30 minutes), the mass retained on each sieve is weighed. The results are plotted as a cumulative or differential distribution. Wet sieving is used for materials that tend to agglomerate or are sensitive to attrition; a stream of water (or solvent) assists the separation. Sieve analysis is mandatory for construction aggregates, sands, and many mining products according to international and local standards.

• Advantages – Simple, low cost, gives mass‑based distribution, standardized meshes.
• Limitations – Time‑consuming for multiple sizes, poor resolution below 20 µm, can be destructive for friable materials, limited shape information.
• Typical range – 20 µm to 125 mm.
• Acceptance – For cement and aggregates, common specifications require that a certain percentage passes a given sieve (e.g., 90% passing 100 µm for cement).

2. Laser Diffraction Particle Size Analysis (Wet or Dry Dispersion)

Laser diffraction is the most widely used modern method for powders ranging from 0.01 µm to 3 mm. A dispersed sample (in air or a liquid) is passed through a laser beam; particles scatter light at angles inversely proportional to their size. An array of detectors measures the scattered light intensity, and a mathematical model (Mie or Fraunhofer) calculates the volume‑based particle size distribution. Our instrument has both dry powder feeder (for free‑flowing powders) and wet sample dispersion unit (for suspensions, emulsions, and samples that require liquid carrier).

• Advantages – Wide range, fast (30–90 seconds per measurement), excellent repeatability, works for dry and wet samples, provides volume distribution directly.
• Limitations – Expensive equipment, requires refractive index input, limited shape information (assumes spherical particles), may not detect very low percentages of oversized particles.
• Typical range – 0.01 µm to 3000 µm.
• Acceptance – Pharmaceutical powders often require tight control of d10, d50, d90 with RSD < 5%.

3. Dynamic Image Analysis (Shape and Size)

For particles where shape is important (needles, plates, fibers, irregular grains), we use dynamic image analysis. Particles are dispersed and pass through a measurement cell while a high‑speed camera captures thousands of images per second. Software measures the size (equivalent circular diameter, length, width) and shape parameters (aspect ratio, circularity, convexity). This method is essential for needle‑like crystals (e.g., some pharmaceuticals) or platelet‑shaped powders (e.g., graphite, talc).

• Advantages – Direct visualization, provides both size and shape, good for troubleshooting unusual granules.
• Limitations – Lower throughput than laser diffraction, requires calibration with a reference standard.
• Typical range – 1 µm to 30 mm (depending on camera/lens).

4. Sedimentation Methods (Andreasen Pipette / X‑ray Sedimentation)

Used primarily for fine clays, pigments, and certified reference materials, sedimentation measures the settling velocity of particles in a liquid (Stokes’ law). The time of settling corresponds to an equivalent spherical diameter. While less common today, it is still requested for certain building materials and geological samples.

5. Screen (Sieve) Calibration and Verification

For critical applications, we verify sieve mesh openings using an optical microscope or calibrated glass microspheres to ensure that sieves have not been stretched or damaged.

Sample Preparation and Conditioning

Correct sample preparation is critical to obtaining a representative and repeatable particle size distribution. The following steps are followed in our laboratory.

• Sampling (riffling or quartering) – From a bulk lot, we take a representative sample using a spinning riffler or cone‑and‑quartering method. The sample mass is determined by the particle size distribution and the required precision (typically 10–500 g).
• Drying – Powders that absorb moisture (hygroscopic) are dried at 105°C for 2–4 hours before analysis to avoid clumping.
• Dispersion (for laser diffraction) – Dry powders are dispersed with compressed air using a venturi nozzle; the air pressure is optimized to break soft agglomerates without shattering primary particles. For wet dispersion, we select a liquid (water, ethanol, isopropanol, or hexane) and a surfactant (e.g., sodium hexametaphosphate or Tween 80) to prevent agglomeration. Ultrasonic energy may be applied for a short time (30–120 seconds) to de‑agglomerate without damaging the particles.
• Sieve preparation – Sieves are cleaned with a soft brush, and their tare weights recorded. For wet sieving, the sieve stack is placed in a water bath with recirculation.
• Number of replicates – At least three measurements per sample for laser diffraction; for sieving, one measurement is typical but duplicates are performed for high‑precision requirements.

Test Procedure (Example – Laser Diffraction)

The following describes the standard procedure for laser diffraction particle size analysis (wet dispersion).

• Instrument warm‑up and background measurement – The laser is turned on and allowed to stabilize (30 minutes). A background scan is performed with the dispersion liquid (no sample) to account for any particles or bubbles in the fluid.
• Loading the sample – A small amount of powder (about 0.1–2 g, depending on particle size) is added to the dispersion unit to achieve an optimal obscuration (typically 5–15%).
• Ultrasonic de‑agglomeration – Ultrasonic energy is applied for 30–90 seconds to disperse agglomerates.
• Measurement – The instrument automatically measures the scattered light pattern 5–10 times (each measurement takes a few seconds) and reports the average particle size distribution (volume‑based).
• Rinse and cleaning – Between samples, the dispersion unit is thoroughly rinsed and a background check is performed to confirm cleanliness.
• Data processing – The software calculates d10, d50, d90, span, and optionally the specific surface area.
• Validation – A certified reference material (e.g., glass beads or quartz powder of known distribution) is measured at the beginning and end of each batch to verify instrument performance.

Factors Influencing Granularity Test Results

• Sample preparation and splitting – Poor sampling (not representative) is the most common source of error. We use rotary rifflers to minimize bias.
• Dispersion energy (laser diffraction) – Too little energy leaves agglomerates, artificially increasing coarse particle fraction. Too much energy can break fragile particles, creating fines. The optimum is validated by testing at different energy levels.
• Refractive index (laser diffraction) – Incorrect optical parameters can shift the distribution significantly. We use literature values or reverse‑calculate from reference measurements.
• Sieve condition – Worn, stretched, or clogged sieves give erroneous results. We inspect each sieve after every use and replace annually.
• Particle shape – Nonspherical particles produce a “size” that depends on the measurement principle (sieving gives the smallest dimension; laser diffraction gives a volume‑equivalent sphere; image analysis gives Feret diameter). We advise clients on which method matches their process model.
• Moisture content – Moist powders clump, causing poor dispersion and artificially large sizes. Dry before testing.
• Electrostatic charge – Dry, fine powders can charge and stick to sieves or the dispersion unit. Adding a small amount of flow aid (e.g., 0.5% fumed silica) or using anti‑static devices reduces this effect.

Quality Control and Interpretation of Results

• Each sample is measured at least in duplicate. The relative standard deviation (RSD) for d50 should be < 3% for laser diffraction and < 5% for sieve analysis when the distribution is unimodal. Higher RSD suggests sample heterogeneity or poor dispersion.
• Certified reference materials (CRM) are measured monthly to validate the instrument’s accuracy.
• For acceptance testing, we compare the measured d10, d50, d90, or percent passing a given sieve against the client’s specification. If the values fall within the tolerance (e.g., d50 = 50 ± 5 µm), the batch is declared conforming. If outside, the batch is flagged and the client receives a detailed report of the deviation.
• When comparing two particle size distributions (e.g., before and after a milling step), we calculate the shift in d50 and the change in span. A decrease in d50 indicates size reduction; a narrowing of span indicates more uniform product.

Reporting and Deliverables

Each granularity test report includes the following information:

• Sample identification (material description, batch number, source, sampling method, conditioning history)
• Analytical method (sieving, laser diffraction, image analysis) with key parameters (dispersion medium, pressure, sonication time, refractive index, sieve sizes used)
• Individual results for each replicate (d10, d50, d90, span, or percent retained/passing each sieve)
• Statistical summary: average, standard deviation, coefficient of variation
• Graphical representation: cumulative distribution curve (percent undersize vs. size) and differential (density) curve (frequency vs. size)
• For sieve analysis: particle size distribution table and graph (log scale)
• Comparison with client‑supplied specification (if provided) – pass/fail conclusion
• Raw data (scattering intensity patterns, sieve weights) archived for 10 years

No statement of compliance with any external standard or regulation is made unless the client has provided specific acceptance criteria in writing. The report is intended for process optimization, quality assurance, and material certification.

Practical Applications for Angolan Industries

• Cement production (Nova Cimangola, Lobito, Sumbe): Monitoring cement fineness (specific surface area and sieve residue at 45 µm) to control strength development.
• Diamond mining (Catoca, Luele, Somiluana): Particle size analysis of kimberlite crush products and diamond recovery concentrates.
• Iron ore (Kassinga, Cassinga, Jamba): Characterizing ore crush size for blast furnace feed and sinter plant feed.
• Agriculture: Fertilizer granule size distribution to ensure uniform spreading and dissolution; feed pellet size for animal nutrition.
• Pharmaceutical manufacturing (local drug formulators): Particle size control of active ingredients to ensure consistent dissolution and bioavailability.
• Ceramic and brick industries: Control of clay and feldspar powder fineness for pressing and firing.