Particle size is one of the most critical material properties across industries. It influences how a drug is absorbed, how a pigment disperses, how an ore is processed, and how a powder flows through manufacturing equipment. The data that describes it is rich with information — but it’s only useful if you know how to read it.
Like any specialized field, particle science has its own language. The terminology is precise, the notation is specific, and the way results are visualized can vary depending on the instrument and how it’s configured. That’s not a flaw in the field — it’s a reflection of how nuanced and information-dense a single particle size report can be. Knowing how to read that language clearly is what separates a good analysis from a truly useful one.
Today, we’re breaking down two foundational concepts that show up on nearly every particle size report: what a distribution actually tells you, and why the difference between a number and a volume distribution matters more than most people realize.
Every Sample Is a Mix — That’s Why We Call It a Distribution
Here’s something that might seem obvious once you hear it: almost no real-world sample contains particles that are all exactly the same size. Whether you’re looking at a pharmaceutical powder, a pigment slurry, mineral ore, or a water sample, you’re dealing with a range of sizes — not a single one. That range is what we call a particle size distribution.
Example: Histogram
To make that range visible, particle size data is typically displayed as a histogram — a bar chart where the horizontal axis shows particle size, and the height of each bar shows how much material falls within that size range. Each bar represents a “size bin,” essentially a bracket of sizes grouped together.
Think of it like sorting a bag of mixed nuts by size. You might have a handful that are tiny, a large cluster in the medium range, and a few big ones at the top. The histogram shows you the whole picture at once.
Example: Continuous Cumulative Curve
As more data points are collected and the bins get narrower, the histogram smooths out into a continuous curve. This curve can also be displayed as a cumulative distribution, which shows the running total — for example, what percentage of particles are smaller than a given size. You may see this expressed as d50, which means 50% of particles are smaller than that diameter. Similarly, d10 and d90 mark the 10th and 90th percentiles. These are among the most commonly referenced values on any particle size report.
Why does this matter across industries?
- Pharmaceutical: Particle size directly affects how a drug dissolves, is absorbed by the body, and flows through manufacturing equipment. Inhaled medications are especially sensitive: particles that are too large won’t reach the lungs, while those that are too small may be exhaled before they can take effect. Getting the distribution right is both a regulatory and a performance requirement.
- Paints & Coatings: Pigment particle size drives color strength, gloss, hiding power, and stability in suspension. A distribution that’s too broad can mean batch-to-batch inconsistency in color.
- Mining & Minerals: Ore is crushed and ground to specific size ranges to maximize the efficiency of separation processes. Too coarse, and valuable minerals aren’t liberated from the rock. Too fine, and you’ve spent energy over-grinding — and potentially created handling problems downstream.
- Food & Beverage: Texture, mouthfeel, and stability in products like chocolate, sauces, dairy, and powdered beverages are all tied to particle size. A finer grind in cocoa produces a smoother chocolate; inconsistent particle size in a powder can cause clumping or uneven dissolution.
- Cosmetics & Personal Care: Sunscreen efficacy, the feel of a lotion, and the coverage of a foundation are all influenced by particle size.
- Ink & Pigment: Inkjet printing demands extremely tight particle size control — even a small number of oversized particles can clog print heads or cause streaking. Distribution width is just as important as the average size.
- Ceramics: The particle size of raw ceramic materials affects sintering behavior, density, and the strength of the final fired product. Tight control over the distribution is essential for producing consistent, high-performance components — especially in advanced ceramics used in electronics or aerospace.
- Agricultural Chemicals: Pesticide and herbicide formulations depend on particle size for effective delivery. Particles that are too large may settle out of suspension; particles that are too fine may drift off-target or degrade too quickly.
- Aerospace & Defense: Metal powders used in additive manufacturing require tight particle size specifications to ensure proper flow, packing, and fusion during the build process. Inconsistent distributions can lead to structural defects in the final part.
Number vs. Volume: Two Ways of Telling the Same Story
Once you have a distribution, the next question is: a distribution of what, exactly?
This is where a lot of confusion happens, because the answer depends on the instrument and how results are reported. The two most common options are a volume distribution and a number distribution — and they can look dramatically different even when describing the exact same sample.
Here’s an easy way to picture it. Imagine a fruit basket with one large watermelon and a dozen small grapes. If you count the pieces of fruit, the grapes win by a landslide — that’s your number distribution. But if you measure how much space each type of fruit takes up, the watermelon dominates — that’s your volume distribution.
The same logic applies to particles. A volume distribution, which is what laser diffraction instruments report by default, reflects how much space particles of a given size occupy. A number distribution, produced by particle counters that measure one particle at a time, reflects how many particles of each size are actually present.
Why does this matter? Because fine particles, even when there are enormous numbers of them, can be nearly invisible on a volume distribution. A single 100-micron particle takes up the same volume as one million 1-micron particles. So if fine particles are a concern in your application, a volume-based report may not tell the full story. A particle counter and a number-based distribution will give you a much clearer picture.
Take pharmaceuticals, for example — regulatory specifications for injectables often focus on particle counts, making a number distribution essential for compliance and contamination assessment. The same is true in environmental monitoring, where fine particulate matter is measured by count and size, and a volume-based report would underrepresent the very particles regulators care most about. On the other hand, paints and coatings typically rely on volume distributions, since pigment mass distribution ties directly to color strength and opacity. Knowing which type of distribution your application calls for (and why) is what ensures the data you’re looking at is actually answering the right question.
Conclusion
Particle size data is precise by design and so is the language used to describe it. In this article, we explored two of the most fundamental concepts in particle size reporting: how distributions are built and what they reveal about a material, and why the distinction between number and volume distributions can meaningfully change what the data is telling you. Understanding these foundations puts you in a much stronger position to ask the right questions, set meaningful specifications, and get more value out of every analysis. If you’re looking for a lab that speaks this language fluently — and can help you put it to work — PTL is here to help.
