Current methods for determining gas-liquid mass transfer or reaction performance in micro-packed bed reactors (μPBRs) are inefficient and complex, hindering their application in high throughput screening, process optimization, and on-line monitoring. New fast determining technology is highly required. This study introduced an innovative soft measurement technology for reliable determining gas-liquid mass transfer by directly correlating pressure drop with mass transfer coefficients through on-line measurement. We systematically analyzed the effect of various factors, including two-phase flow rate, packing particle size, front-end pre-dispersion, gas composition, and liquid concentration on gas-liquid flow pressure drop and mass transfer in μPBRs. A predictive mathematical model for mass transfer coefficients was successfully established and its capacity was successfully validated in the hydrogenation experiments within the Reidl-Pfleiderer process. This technology offers a fast, reliable, and real-time online approach for the process monitoring, process optimization, and rapid catalyst screening within μPBRs.
