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Wall-induced dispersion in multicapillary columns with diffusional bridging
Alessandra Adrover1, Claudia Venditti1, Bram Huygens2
1Dipartimento di Ingegneria Chimica Materiali Ambiente, Sapienza Università di Roma, Italy.
Abstract:
The two-zone moment approach (TZMA) is applied to quantify axial dispersion in multicapillary open-tubular columns enabling transverse diffusion (MOTTD). Owing to their axial invariance, these systems allow a rigorous and computationally efficient decomposition of the plate height into mobile- and stationary-zone contributions. First, periodic unit cells corresponding to triangular, square, and mixed capillary arrangements are analysed to assess the influence of geometry and capillary diameter on the C-term. For moderate capillary diameters, TZMA results are accurately described by simplified analytical expressions assuming weak coupling between the mobile and stationary zones, with the triangular arrangement providing the lowest plate height and highest kinetic performance. The analysis is then extended to full chromatographic columns, where the presence of an impermeable column wall induces strong coupling between the two zones, leading to a pronounced increase of the C-term that scales linearly with the number of capillaries and significantly degrades performance relative to unit-cell predictions. Beyond asymptotic dispersion, the TZMA framework is further exploited to investigate the transient evolution of the effective velocity and dispersion coefficient. Wall-induced coupling is shown to dramatically increase the characteristic length required to reach macro-transport conditions, with convergence lengths scaling linearly with the number of capillaries. Finally, the effect of capillary diameter polydispersity is investigated, showing that while polydispersity increases band broadening, its relative contribution decreases as the number of capillaries increases. The results highlight the dominant role of wall effects in real MOTTD columns and provide quantitative guidelines for their geometric design and optimization.
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