Researchers at the National Institute of Standards and Technology (NIST) have identified a common data-analysis problem that can distort conclusions about how the size of a nanomaterial affects its properties. The team also developed a mathematical correction designed to account for those measurement errors.
The findings, published in ACS Nano, address a fundamental challenge in nanotechnology: nanomaterial properties can change significantly with size, but nanoscale measurements are not perfectly precise or accurate. If researchers treat those size measurements as error-free during statistical analysis, the apparent relationship between particle size and properties such as brightness, drug capacity, or electrical behavior can appear weaker than it actually is.
Size measurement errors can distort trends
Researchers often plot a nanomaterial’s measured size against a performance characteristic to determine how the two are related. Reliable particle sizing is therefore important across applications ranging from pharmaceuticals to materials science.
The NIST team found that uncertainty in the size measurement itself can flatten the apparent relationship between size and performance. In practical terms, a researcher could underestimate how strongly nanoparticle dimensions influence a material’s behavior. NIST electrical engineer Andrew Madison described the effect as dimming the apparent relationship between particle size and its properties.
The issue reflects a broader challenge for laboratories working with measurement uncertainty. Precision and accuracy limitations do not necessarily indicate that an instrument or method has failed, but labs need to quantify those limitations and account for them when interpreting results.
Statistical correction accounts for sizing uncertainty
After identifying the problem in published nanomaterials research, the NIST team developed and tested mathematical corrections that incorporate the limited precision and accuracy of particle-size measurements. According to NIST, accounting for those errors can reveal a more accurate relationship between a nanoparticle’s structure and its properties.
Researchers first need an estimate of the error associated with their sizing measurements. NIST recommends measuring a reliable reference material with the same instruments and methods used for the experimental samples and comparing the results with the reference values. When a suitable reference material is unavailable, researchers can instead estimate the uncertainty associated with their sizing method.
The approach reinforces the role of reference standards and calibration materials in establishing traceability and understanding measurement uncertainty. For labs working with emerging materials, these considerations can become particularly important because characterization methods and standards are still evolving.
Implications for nanomaterials labs
The findings apply to research in which scientists are trying to connect nanoscale dimensions with material performance. Potential applications include nanoparticles used for drug delivery, nanoscale electronics, ceramics, coatings, and other engineered materials.
For lab managers overseeing nanomaterial characterization and testing, the study highlights the need to look beyond instrument precision when evaluating a measurement workflow. Reference materials, method validation, uncertainty estimates, and the statistical models used to analyze results can all influence whether the lab draws the correct conclusions from its data.
This article was created with the assistance of Generative AI and has undergone editorial review before publishing.
