Achieving High-Volume, Zero-Defect Quality Polymer Purification
Brewer Science, Inc., a high-volume manufacturer of ultrapure semiconductor materials, is presenting their latest innovation in polymer purification at the AIChE Conference from October 27th through 31st.
Traditional Batch Polymer Precipitation Methods are Inefficient
Balancing the industry’s needs to scale materials, while maintaining ultra high purity standards requires an efficient purification process. Traditional batch polymer precipitation methods are energy-intensive, time-consuming, and costly, making it difficult to meet the growing demand for high-volume production without compromising quality.
Using the Design of Experiments (DOE) approach, a continuous polymer precipitation system shows >50% reduction in antisolvent used, 53% reduction of the sublimation defects for the final product, and over 63% reduction in total processing time compared to the batch process.
Continuous Polymer Precipitation Process using Bayesian Optimization Provides Efficiency
To further improve the process of determining the optimal operating parameters, Brewer Science presents a solution that uses Bayesian optimization (BO) to reduce experimental efforts and enhance process development efficiency. When compared to the predicted parameters of the traditional DOE, the parameters tuned by BO ensure the continuous polymer precipitation system delivers polymers with lower impurity levels and polydispersity index (PDI).
Bayesian Optimization of a Continuous Polymer Precipitation Process, presented by Dr. Zhiqiang Fan, Senior Computational Engineer/Analyst at Brewer Science, unveils a transformative leap in polymer purification, illustrating how a shift from traditional batch processes to continuous polymer precipitation system will scale production efficiently while ensuring the purity and quality required for high-performance applications. The presentation answers key challenges in maintaining high-purity quality when scaling,
- How can polymer purification processes be scaled efficiently while maintaining ultrahigh purity standards required for semiconductor applications?
- What are the optimal process parameters for achieving consistent impurity reduction and desired polymer properties, such as polydispersity index (PDI), in large-scale production?
- How can manufacturing costs and energy consumption be reduced in the polymer purification process while still ensuring high-performance outcomes?
The presentation, Bayesian Optimization of a Continuous Polymer Precipitation Process is presented by Dr. Zhiqiang Fan on October 30, 2024 at 1:50 pm PST in Room 23B at the San Diego Convention Center.
Additionally, Dr. Walter Barnes, Director of Corporate New Product Engineering, presents Challenges & Opportunities for Specialty Materials Manufacturing in the Semiconductor Industry on October 30, 2024 at 12:30 pm PST. Dr. Barnes is the keynote speaker for the topical conference “Next-Gen Manufacturing in Chemical and Energy Systems.” The presentation focuses on how zero defect standards and the need for enabling technologies impacts the manufacturing of specialty materials in this industry.
Dr. Qing Pu, New Product Engineering Manager at Brewer Science, is a co-chair for the Next-Gen Manufacturing in Chemical and Energy Systems topical conference on October 30, 2024 at 12:30 pm in Room 23B.
“Our continuous polymer precipitation process represents a breakthrough in achieving the ultrahigh purity standards critical for semiconductor manufacturing. By leveraging machine learning optimization, we are making this technology more scalable and energy efficient. But we are also ensuring that we can consistently deliver the precision and performance demanded by our industry,” states Dr. Walter Barnes, Director of Corporate New Product Engineering at Brewer Science. “This advancement is not just transformative for semiconductor materials, but also holds potential for other advanced material markets, where purity and efficiency are equally paramount.”
For those unable to attend the event, contact Brewer Science to learn more.
