Evaluating the Mechanical Properties of PPE-HIPS

Polyphenylene Ether (PPE) is characterized by its thermal stability, mechanical strength, chemical resistance, dimensional stability, and electrical insulating properties, making it a preferred material in many industries, such as automotive, electronics, and medical devices. However, the processing of PPE poses a challenge due to its high glass transition temperature. Thus, it is often blended with High Impact Polystyrene (HIPS).

This combination improves the processability of PPE and enhances the overall mechanical properties. However, the material datasheet may not provide the critical information required for a manufacturer to make a reliable assessment of performance, potential failure, effects of processing methods, and response to different environmental conditions.

In this webinar, we will delve into the PPE+HIPS characterization using various mechanical testing such as Dynamic Mechanical Analysis (DMA), tensile, and fatigue testing.

Key takeaways from this webinar:

  • Understand the importance of testing beyond the material datasheet to accurately predict PPE + HIPS performance, failure risks, and environmental response under real-world conditions.
  • Gain insights into the unique properties of Polyphenylene Ether (PPE) and why it is commonly blended with High Impact Polystyrene (HIPS) to improve processability and mechanical performance.
  • Explore how mechanical characterization can guide you in selecting appropriate processing methods and assessing the material’s suitability for specific applications.


Meet the Speakers


Speaker 01 Image


Shoab Chowdhury

Applications Engineer

Shoab Chowdhury has a background in mechanical engineering and completed his Ph.D. at Clemson University, where he conducted research on multi-stable composite materials. After graduation, he joined TA Instruments as a Field Applications Engineer. He has published several journal articles and conference papers on fatigue analysis and environmental response and has developed mathematical, FEA, and machine learning models to predict failure characteristics and long-term material performance in service. His scientific interests are focused on the mechanical testing and characterization of composites, medical devices/implants, and polymers.

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