BOTTS: broadband optimized time-temperature superposition for vastly accelerated viscoelastic data acquisition

Area of Science:

• Materials Science
• Polymer Science
• Rheology

Background:

• Modern materials design relies on large datasets and complex algorithms.
• Viscoelastic materials pose challenges due to time-dependent properties, slowing data collection.
• Traditional time-temperature superposition (TTS) methods using discrete frequency sweeps (DFS) are time-limited.

Purpose of the Study:

• To develop a faster method for generating master curves for viscoelastic materials.
• To overcome the speed limitations of traditional DFS-TTS techniques.
• To improve data acquisition rates in materials characterization.

Main Methods:

• Utilized windowed chirp rheometry to collect simultaneous complex modulus data across three decades.
• Developed a new technique called Binary Overlap Time-Temperature Superposition (BOTTS).
• Employed linear error propagation and noise-weighted least squares for data analysis and shifting.

Main Results:

• Achieved a ~500% increase in data collection rate compared to DFS-TTS.
• BOTTS successfully superposed isothermal chirp responses to create master curves rapidly.
• Demonstrated comparable results between BOTTS and DFS-TTS for model thermoset polymers.

Conclusions:

• BOTTS offers a significant speed improvement for master curve generation.
• This method represents a crucial advancement for accelerating viscoelastic materials characterization.
• BOTTS is compatible with unmodified rheological measurement instruments.