A major bottleneck in nanoparticle sizing is the lack of data comparability between techniques and between laboratories. However, this can be overcome by making the measurements traceable to the SI together with realistic uncertainty evaluation. In the present work, a novel approach is proposed to perform measurement uncertainty evaluation in a Bayesian framework by statistically modeling appropriately selected measurement data when no comprehensive physical model is available. The method is applied to the dimensional measurement of nanoparticles by atomic force microscopy (AFM) measurement and the calibration is performed by a multiple points calibration curve. Nevertheless, the proposed method can be applied to other microscopy techniques. The experimental data used to construct the statistical model are collected so that the influence of relevant measurement parameters can be assessed. An optimized experiment is designed under the intermediate precision conditions in order to limit the number of measurements to perform. Among the different influencing parameters, it is found that the AFM operator and image analyst do not significantly affect the measurement variability while the tip tapping force, the probe nature and the tip scan speed do. The particular case of gold nanoparticle of nominal diameter 30 nm is treated as an example of the method.

纳米颗粒尺寸测定的一个主要瓶颈是技术之间和实验室之间缺乏数据可比性。然而，这可以通过使测量可追溯到 SI 以及实际的不确定性评估来克服。在本作工作中，提出了一种新的方法，通过统计地建模在没有综合物理模型时，通过统计建模在差异选择的测量数据中进行贝叶斯框架中的测量不确定性评估。该方法应用于通过原子力显微镜 (AFM) 测量的纳米粒子的尺寸测量，并通过多点校准曲线进行校准。然而，所提出的方法可以应用于其他显微技术。收集用于构建统计模型的实验数据，以便评估相关测量参数的影响。优化实验是在中等精度条件下设计的，以限制要执行的测量次数。在不同的影响参数中，发现 AFM 操作员和图像分析员对测量变异性没有显着影响，而尖端敲击力、探头性质和尖端扫描速度有显着影响。标称直径为 30 nm 的金纳米颗粒的特殊情况被视为该方法的一个例子。发现 AFM 操作员和图像分析员不会显着影响测量变异性，而尖端敲击力、探头性质和尖端扫描速度会产生影响。标称直径为 30 nm 的金纳米颗粒的特殊情况被视为该方法的一个例子。发现 AFM 操作员和图像分析员不会显着影响测量变异性，而尖端敲击力、探头性质和尖端扫描速度会产生影响。标称直径为 30 nm 的金纳米颗粒的特殊情况被视为该方法的一个例子。