Publication detail

Self-consistent autocorrelation for finite-area bias correction in roughness measurement

NEČAS, D.

Original Title

Self-consistent autocorrelation for finite-area bias correction in roughness measurement

Type

journal article in Web of Science

Language

English

Original Abstract

Scan line levelling, a ubiquitous and often necessary step in AFM data processing, can cause a severe bias on measured roughness parameters such as mean square roughness or correlation length. Although bias estimates have been formulated, they aimed mainly at assessing the severity of the problem for individual measurements. Practical bias correction methods are still missing. This work exploits the observation that the bias of autocorrelation function (ACF) can be expressed in terms of the function itself, permitting a self-consistent formulation. From this two correction approaches are developed, both with the aim to obtain convenient formulae which can be easily applied in practice. The first modifies standard analytical models of ACF to incorporate, in expectation, the bias and thus actually match the data the models are used to fit. The second inverts the relation between true and estimated ACF to realise a model-free correction. Both are tested using simulated and experimental data and found effective, reducing the total error of roughness parameters several times in the typical cases.

Keywords

scanning probe microscopy; roughness; autocorrelation; bias

Authors

NEČAS, D.

Released

1. 6. 2024

Publisher

IOP Publishing Ltd

Location

BRISTOL

ISBN

2631-8695

Periodical

Engineering Research Express

Year of study

6

Number

2

State

United Kingdom of Great Britain and Northern Ireland

Pages count

14

URL

BibTex

@article{BUT189989,
  author="David {Nečas}",
  title="Self-consistent autocorrelation for finite-area bias correction in roughness measurement",
  journal="Engineering Research Express",
  year="2024",
  volume="6",
  number="2",
  pages="14",
  doi="10.1088/2631-8695/ad5302",
  issn="2631-8695",
  url="https://iopscience.iop.org/article/10.1088/2631-8695/ad5302"
}