The vexing error of excess variance in the sizing of single particles degrades accuracy in applications ranging from quality control of nanoparticle products to hazard assessment of nanoplastic byproducts. The particular importance of lipid nanoparticles for vaccine and medicine delivery motivates this comment on a publication in ACS Nano. In ref 1, the benchmark measurements of a nanoparticle standard manifest large errors of the size distribution that contradict the claim of validation. Such errors can bias the correlation of fluorescence intensity as an optical proxy for the molecular loading of lipid nanoparticles and give misleading insights from power-law models of intensitysize data. Looking forward, measurement error models have the potential to address this widespread issue.

生成讲解博客的中文版本

生成AI智能校验的中文版本