
An automated tool developed in MATLAB is provided for analysing the viscoelastic properties of viscous materials in the frequency domain using Dynamic Mechanical Analysis (DMA) data. An example Excel file is included, containing DMA data for a tested polymer, to demonstrate the required data format and fitting process. Note: The DMA input data must be provided in an Excel file (.xlsx) with three columns in the following order: Frequency Temperature Storage modulus To run the tool, simply open the main_program.m file by MATLAB. Tool Overview The tool comprises four main components: 1. Start Menu A user interface for specifying key input parameters: Reference temperature Infinite modulus Number of Prony series terms File path to DMA data Fitting visualisation option (Note: enabling this will slow down the fitting due to additional graphical rendering) 2. Master Curve Generation Algorithm Generates the master curve by applying the time–temperature superposition (TTS) principle. The algorithm uses least-squares fitting to align frequency–modulus data across temperatures into a single reference curve. 3. Prony Series Fitting Algorithm Fits the master curve to a Prony series model using a single-objective genetic algorithm, optimising the model parameters for best fit. 4. Data Saving Module Saves output data in CSV files, including: Master curve data Fitted Prony series parameters Shift factors Note: A more detailed introduction to this tool can be found in the published article (A genetic-algorithm-optimised viscoelastic fitting tool for polymers and polymer nanocomposites, or DOI:10.1016/j.polymertesting.2025.108951) in Polymer Testing. Please feel free to contact us if you have any comments/questions about the tool!
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
