Modelling of continuous synthesis of bio-inspired silica particles using gaseous CO2

• Developed a model to simulate pH profile and yield in BIS synthesis using CO 2 . • Validated the model using experiments with continuous bubble column reactor. • Developed ML-based soft sensors with three different formalisms to predict the silica yield. • The approach and results will facilitate optimization of the BIS synthesis using CO 2 . Bio-inspired route to synthesis of porous silica particles involves fast reactive precipitation (solid–liquid system). The concentration and pH profiles within the reactor determine the properties of produced silica particles and therefore need to be controlled tightly. Unlike conventional synthesis of bio-inspired silica (BIS) using strong aqueous acids, recently we developed a process of synthesizing BIS particles using gaseous CO 2 . This gas-liquid-solid (G-L-S) system looks promising as it is easy to maintain desired pH profiles and hence control particle properties by manipulating the mass transfer rate. In this work, we present the mathematical model for simulating pH profile and yield in BIS synthesis using CO 2 . The developed model was used to simulate specific silica synthesis experiments. The model was able to capture the experimental data well. It was then used to carry out several numerical experiments for understanding the sensitivity of BIS synthesis using CO 2 to various design and operating parameters. The simulated data was used to train the surrogate models for the silica yield prediction. The models demonstrated good performance with the unseen experimental data. The presented results provide useful insights and guidelines for optimizing CO 2 based silica synthesis process. The presented model is generic and may be extended to other similar fast reactions.