Applying the field emission orthodoxy test to Murphy-Good plots

TL;DR

This paper evaluates the Murphy-Good plot's effectiveness in field emission analysis, compares it with traditional plots, and develops a web tool to apply the orthodoxy test across multiple plotting methods.

Contribution

It introduces a revised method to apply the orthodoxy test to Murphy-Good plots and develops a web tool for comprehensive FE data analysis.

Findings

Murphy-Good plots can be tested for orthodoxy using a revised formula.

The web tool enables orthodoxy testing for FN, MG, and ML plots.

Comparison shows MG plots offer improved parameter extraction accuracy.

Abstract

In field electron emission (FE) studies, it is important to check and analyse the quality and validity of results experimentally obtained from samples, using suitably plotted current-voltage [I(V)] measurements. For the traditional plotting method, the Fowler-Nordheim (FN) plot, there exists a so-called "orthodoxy test" that can be applied to the FN plot, in order to check whether the FE device/system generating the results is "ideal". If it is not ideal, then emitter characterization parameters deduced from the FN plot are likely to be spurious. A new form of FE I(V) data plot, the so-called "Murphy-Good (MG) plot" has recently been introduced (R.G. Forbes, Roy. Soc. Open Sci. 6 (2019) 190912. This aims to improve the precision with which characterization-parameter values (particularly values of formal emission area) can be extracted from FE I(V) data. The present paper compares this new plotting form with the older FN and Millikan-Lauritsen (ML) forms, and makes an independent assessment of the consistency with which slope (and hence scaled-field) estimates can be extracted from a MG plot. It is shown that, by using a revised formula for the extraction of scaled-field values, the existing orthodoxy test can be applied to Murphy-Good plots. The development is reported of a prototype web tool that can apply the orthodoxy test to all three forms of FE data plot (ML, MG and FN).