STEP Version 1.1

(Electromechanical Response Characterisation Program)

Electromechanical response depends on the interaction of four fundamental variables. Each of these are either of the electrical or mechancial variable type;

(S) Strain - mechanical

(T) Stress - mechanical

(E) Electric Field - electrical

(P) Polarisation or Electric Displacement - electrical

In a general electromechanical response measurement, one of the electrical or mechanical variables is controlled while one of the variables of the opposite variable type is held constant. The remaining electrical and mechanical variables can be measured. As an example, a measurement can be electric field-controlled while the sample is unclamped, meaning stress is fixed at zero. It is not physically possible to simultaneously control both variables of a measurement type.

The curves of measured electromechanical response characterise four fundamental kinds of active materials; piezoelectric, electrostrictive, ferroelectric, and antiferroelectric. For a discussion of typical electromechanical response curves, please see;

Electromechanical Response Curves

STEP runs under Windows 95, 98, Windows NT, and Windows 2000. The user-friendly interface of STEP ensures expert analysis is maintained in your laboratory regardless of personnel changes.

The STEP package accepts a variety of optional plug-in analysis modules and optional plug-in data acquisition modules.

STEP Analysis Modules

STEP Data Acquisition Modules

Included with the Basic STEP Package are the Piezoelectric Module, Ferroelectric Module, Electrostrictive Module, and the Antiferroelectric Module. These modules provide a variety of common emperical models that can be applied to measured electromechanical response data. The optional Basic Data Acquisition Module allows data sets to be acquired directly from a variety of instruments under a variety of measurement conditions. Additional optional plug-in data acquisition modules require the Basic Data Acquisition Module.

The following provide overviews of analysis and data acquisition with STEP. For details about specific analysis or data acquisition modules, see the above links.

Features of Analysis

After the analysis of any data set, STEP uses determined model parameters to generate a fit over the analysed data set. Conversely, any set of model parameters can be used to generate a theoretical data set. Aside from the visual confirmation of analysis provided by the fitted data set, a norm parameter is generated as an estimate of the 'goodness-of-fit'.

Analysis with STEP is enhanced with the STEP Compound file. The Compound file allows one or more related data sets to be brought together in one document. This allows collective analysis of the data sets to be performed. Types of analysis include determining the dependence of a model parameter on a measurement or process variable (such as coercive field of a ferroelectric as a function of time or temperature).

Other features exploit the analytical capability of STEP;

  • Display data sets with any measurement variable as the x-axis, including time

  • Easily zoom in on regions of your data sets with a convenient mouse zoom feature

  • Quickly copy results to the Windows clipboard for use in other software packages

  • Study the dependence of model parameters or results on aspect ratio, geometry, density, etc.

Features of Data Acquisition

Aside from the simplicity and speed of acquiring data sets with the optional Basic STEP Data Acquisition Module, the additional optional plug-in data acquisition modules of STEP provide advanced analytical capability. Examples of capability added by these modules include;

  • Study time dependencies through ageing

  • Study temperature dependence of model parameters or results

Technical Information about STEP

This web site provides a wealth of technical information about analysis using STEP. Please see the following link for details.

STEP Technical Information

STEP Tutorials

Users of STEP can perform a variety of tutorials from this web site designed to familiarise them with the sequence of steps required to analyse data sets. Please see the following link for details;

STEP Tutorials

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