Add BrightSurf on Google Email

Predictive modeling and systematic evaluation identify superior foam control agent for industrial fermentation

07.26.26 | Higher Education Press
Apple Watch Series 11 (GPS, 46mm)

Apple Watch Series 11 (GPS, 46mm) tracks health metrics and safety alerts during long observing sessions, fieldwork, and remote expeditions.


Foam formation is a persistent challenge in industrial fermentation processes, leading to broth loss, reduced reactor capacity, impaired oxygen transfer, increased contamination risk, and compromised product quality. While foam control agents (FCAs) are commonly used to mitigate these issues, their performance is highly sensitive to both formulation and process conditions. In a study published in ENG. Chem. Eng. , researchers at The Dow Chemical Company systematically evaluated 14 polyglycol based FCAs—alcohol initiated EO/PO block copolymers with varying molecular shapes and functionalities—to identify the optimal candidate for fermentation applications.

The study employed a commercial fermentation broth (LB broth) as the foaming medium and used FOAMSCANTM equipment with continuous airflow to simulate industrial fermentation conditions. FCA physicochemical properties—including cloud point, surface tension, foam height, viscosity, and specific gravity—were comprehensively characterized. Foam suppression was evaluated at 30–40 °C with FCA concentrations of 100–300 ppm, while microbial compatibility was assessed using yeast and mold cultures at 0.5 and 1.0 wt% FCA concentrations.

Among all tested candidates, FCA332 demonstrated superior overall performance. At 300 ppm, it reduced foam volume from approximately 195 mL (control) to minimal levels across all tested temperatures (30–40 °C) and broth concentrations (25–50 g·L⁻¹). In microbial growth assays, FCA332 consistently supported robust mold and yeast viability comparable to or exceeding the control group, even at 1.0 wt% concentration. In contrast, the benchmark FCA302 reduced mold growth by approximately 10 % at 0.5 wt%, and other FCAs such as FCA412 exhibited significant inhibitory effects.

Generalized linear regression models were developed to correlate FCA physicochemical properties with foam volume and microbial growth. The foam volume model (R² = 0.97) included cloud point, specific gravity, surface tension, viscosity, and their interactions. The mold growth model (R² = 0.99) included surface tension, specific gravity, and viscosity interactions. Model validation using two withheld data points confirmed adequate predictive performance. Optimization using the models identified optimal foam control and microbial compatibility at low viscosity, low specific gravity, intermediate surface tension, and moderate cloud point.

The modeling results align with theoretical expectations: optimal foam control occurs when the working temperature is above the cloud point; branched molecular structures enhance interfacial activity; and lower viscosity agents offer better handling and consistent performance.

This work demonstrates that FCA332—with its low viscosity, moderate cloud point, favorable surface tension, excellent foam suppression, and superior microbial compatibility—is a robust and reliable option for industrial fermentation processes. The predictive model provides a practical framework for rapid FCA screening without extensive biological testing, accelerating product development and enabling rational design of foam control strategies that balance operational efficiency with biological safety.

ENGINEERING Chemical Engineering

10.1007/s11705-026-2676-0

Experimental study

Not applicable

Microbial growth study of advanced foam control agents (FCAs) for fermentation process

7-May-2026

Keywords

Article Information

Contact Information

Rong Xie
Higher Education Press
xierong@hep.com.cn

Source

This article is based on a news release from Higher Education Press. BrightSurf curates and republishes science news from research institutions worldwide; the original release is linked below.

How to Cite This Article

APA:
Higher Education Press. (2026, July 26). Predictive modeling and systematic evaluation identify superior foam control agent for industrial fermentation. Brightsurf News. https://www.brightsurf.com/news/147ZEQJ1/predictive-modeling-and-systematic-evaluation-identify-superior-foam-control-agent-for-industrial-fermentation.html
MLA:
"Predictive modeling and systematic evaluation identify superior foam control agent for industrial fermentation." Brightsurf News, Jul. 26 2026, https://www.brightsurf.com/news/147ZEQJ1/predictive-modeling-and-systematic-evaluation-identify-superior-foam-control-agent-for-industrial-fermentation.html.