Multiscale modelling of hydrothermal biomass pretreatment for chip size optimization

Area of Science:

• Biomass energy conversion
• Chemical engineering
• Process optimization

Background:

• Current severity factors for hydrothermal pretreatment do not account for biomass chip size.
• Chip size significantly impacts pretreatment efficiency and energy requirements.
• Existing models lack the granularity to link chip size to process energy demands.

Purpose of the Study:

• To establish a relationship between biomass chip size and energy consumption in hydrothermal pretreatment.
• To develop a multiscale modeling approach for this relationship.
• To propose an optimization method for determining the ideal chip size to minimize energy usage.

Main Methods:

• Developed a multiscale model based on liquid/steam diffusion within biomass.
• Incorporated the interrelationship between chip size and processing time into the model.
• Proposed an optimization strategy to identify the optimal chip size.

Main Results:

• The developed model accurately reflects the influence of chip size on hydrothermal pretreatment energy requirements.
• The proposed optimization method identifies an ideal chip size.
• Achieved an average saving equivalent to a 5% improvement in biomass to ethanol conversion yield.

Conclusions:

• Biomass chip size is a critical, previously underrepresented factor in hydrothermal pretreatment.
• The multiscale model and optimization method offer a pathway to significantly reduce energy consumption.
• Optimizing chip size can lead to substantial improvements in the overall efficiency of biomass conversion processes.