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High throughput nanoindentation techniques can provide rapid materials screening and property mapping and can span millimeter length scales and up to 106 data points. To facilitate rapid sorting of these data into similar groups, a necessary task for establishing structure–property relationships, use of an unsupervised machine learning analysis called clustering has grown in popularity. Here, a method is proposed and tested that evaluates the uncertainty associated with various clustering algorithms for an example high entropy alloy data set and explores the effect of the number of data points in a second Damascus steel data set. The proposed method utilizes the bootstrapping method of Efron to resample a modeled probability distribution function based upon the original data, which allows the uncertainty related to the clustering to be evaluated in contrast to the classical standard error on the mean calculations. For the Damascus, it was found that results data from a 104 point subsample are comparable to those from the full 106 set while representing a significant reduction in data acquisition. [ABSTRACT FROM AUTHOR]

We present a highly sensitive force-displacement transducer capable of performing ultra-shallow nanoindentation and adhesion measurements. The transducer utilizes electrostatic actuation and capacitive sensing combined with microelectromechanical fabrication technologies. Air indentation experiments report a root-mean-square (RMS) force resolution of 1.8 nN and an RMS displacement resolution of 0.019 nm. Nanoindentation experiments on a standard fused quartz sample report a practical RMS force resolution of 5 nN and an RMS displacement resolution of 0.05 nm at sub-10 nm indentation depths, indicating that the system has a very low system noise for indentation experiments. The high sensitivity and low noise enables the transducer to obtain high-resolution nanoindentation data at sub-5 nm contact depths. The sensitive force transducer is used to successfully perform nanoindentation measurements on a 14 nm thin film. Adhesion measurements were also performed, clearly capturing the pull-on and pull-off forces during approach and separation of two contacting surfaces. [ABSTRACT FROM AUTHOR]