Calibration of Scanning Thermal Microscope using Optimal Estimation of Function Parameters by Iterated Linearization

TL;DR

This paper introduces an optimal estimation algorithm to calibrate scanning thermal microscopy, enabling robust, single-step evaluation of local thermal conductivities and uncertainties, thus improving nanoscale thermal property measurements.

Contribution

The paper presents the OEFPIL algorithm for efficient calibration of SThM, addressing non-linear dependence and limited calibration points, which simplifies the process.

Findings

OEFPIL provides robust thermal conductivity estimates

Calibration process is simplified and automated

Uncertainty quantification is integrated into calibration

Abstract

Scanning thermal microscopy is a unique tool for the study of thermal properties at the nanoscale. However, calibration of the method is a crucial problem. When analyzing local thermal conductivity, direct calibration is not possible and reference samples are used instead. As the calibration dependence is non-linear and there are only a few calibration points, this represents a metrological challenge that needs complex data processing. In this contribution we present use of the OEFPIL algorithm for robust and single-step evaluation of local thermal conductivities and their uncertainties, simplifying this procedure. Furthermore, we test the suitability of SThM calibration for automated measurement.