HPLC 2026 Preview: Bo Zhang on Moving Towards Precision Design and Manufacture of Chromatographic Materials

You are presenting a talk at HPLC 2026 called “Towards Precision Design and Manufacture of Chromatographic Materials,”. How does your droplet microfluidic platform enable deterministic control over particle morphology and pore architecture compared to conventional stochastic synthesis approaches?

In conventional stochastic synthesis approaches, the entanglement of multiple parameters of chromatographic materials is the main reason why deterministic control cannot be achieved. Adjusting either particle morphology or pore structure inevitably affects the other. Therefore, the core concept of the droplet microfluidic synthesis strategy is to decouple these chemically entangled processes. We use micrometre-sized droplets to define the particle morphology of chromatographic materials. Through in-situ sol-gel solidification and the spatial confinement effect of droplets, the resulting materials retain exceptionally high monodispersity, perfect sphericity, and predetermined particle size. Having secured independent control over particle morphology without interference, we found that we could make substantial progress in pore structure manipulation. By loading phase-separable multicomponent chemical systems inside the droplets, we achieved precise control over mesopores, macropores, and perfusive pores. Furthermore, drawing on the micelle-templated porogenic strategy, we successfully assembled, for the first time, multiple ordered mesoporous architectures in microspherical materials, including 2D hexagonal, body-centred cubic, face-centred cubic, and cubic double gyroidal structures.

You highlight integration of micelle-templated self-assembly within microfluidics—how do you control mesostructural ordering, such as pore size distribution and connectivity, under flow conditions, and what impact does this have on mass transfer kinetics?

Micelle-templated self-assembly requires sufficient time. The time from droplet generation to reaching the outlet can be less than 1 ms, but the transition of micelles from a disordered state to a highly ordered mesostructure often takes half a day or even longer. Therefore, inside the droplet, the self-assembly behaviour of structure-directing agents is primarily driven by thermodynamic equilibrium rather than by flow shear. By tuning the hydrophilic/hydrophobic volume ratio of structure-directing agents, the charge density of co-structure-directing agents, the solvent evaporation rate, and subsequent hydrothermal conditions (temperature, time, solvent), we achieve fine control over mesostructure ordering. Our experimental results show that such highly ordered pore architectures significantly reduce molecular mass-transfer resistance, which can affect the final performance of chromatographic materials in two respects. First, during the bonding process, ordered mesoporous materials can readily achieve high bonding density. Second, during chromatographic separations, the mass-transfer resistance (The C term of the van Deemter equation) is reduced by 56% on the ordered mesoporous materials, in comparison with conventional fully porous materials. This results in a lower hmin, which means higher separation efficiency, and also good operability at higher flow rates without substantial loss of efficiency.

The generation of Janus droplets for spatially resolved stationary phases is particularly intriguing—how reproducible is the phase boundary within particles, and how does this anisotropy influence retention mechanisms in mixed-mode separations?

The reproducibility of phase boundary within particles is closely related to the stability among the three immiscible phases during microfluidic synthesis. To maintain stability, we designed damping structures in the chip to balance pressure across the channels, adopted a phase system of H2O/DMC/fluorinated oil, and synthesized two efficient fluorosurfactants to stabilize the droplets. Through these efforts, we successfully generated highly uniform Janus droplets on the microfluidic chip, characterized by excellent monodispersity (CV ≤ 6.2%), a clear phase boundary, and good reproducibility. Compared to conventional randomly and co-locatedly bonded stationary phases, the spatially resolved stationary phase physically separates different functional groups, eliminating the chemical interference caused by steric hindrance or electrostatic shielding among others. Experimental results demonstrate that, under identical chemical composition, the spatially resolved stationary phase enhances hydrophobic retention by 152% and hydrophilic retention by 213%, while dramatically improving peak shape (asymmetry factor reduced from 4.57 to 1.54), in comparison with its randomly bonded counterparts.

Compared to established materials such as sub-2 µm fully porous and core-shell particles, how do your precision-engineered materials perform in terms of reduced plate height and van Deemter behavior across a range of linear velocities?

We have not yet performed a comparison with core-shell particles, as their fundamentally different structural design makes it difficult to isolate the actual role of ordered pore architectures through direct comparison. Likewise, we have not conducted parallel comparisons with sub‑2 µm particles. Although these particles can achieve very high efficiency, most sub‑2 µm particles rarely reach a hmin of 2. If we use this reduced plate height term for a trans-particle comparison, they may even underperform common 3 µm or 5 µm particles, possibly due to packing difficulties or other factors that prevent them from attaining their theoretical limit. In contrast, the microfluidic-synthesised microspheres achieve a hmin of 1.67, which is significantly lower than the generally accepted performance limit of 2 for spherical chromatographic materials. van Deemter analysis shows that the eddy diffusion (A term) of the microfluidic-synthesised microspheres is 258% better than that of conventional polydisperse particles, explaining why the minimum reduced plate height reaches such a good level.

From a manufacturing perspective, what are the current scalability limits of the microfluidic approach, and what engineering challenges must be addressed to transition from lab-scale synthesis to industrial column production?

The current scalability limit of the microfluidic approach lies in the fact that the PDMS chips adopted in this work cannot maintain permanent operations. The surface functionalization of the microfluidic chips gradually degrades with time. Currently, we have developed a 120-channel array super-throughput chip with a production throughput of 240,000 Hz, capable of producing approximately 10⁹ microspheres per hour, enabling the preparation of packing materials for one thousand 15 cm-long, 100-μm-i.d. chromatographic columns, or ten 10 cm-long, 2.1-mm- i.d. analytical scale columns. However, for industrial‑scale column production, the issue of the long‑term operation of the array chip must be resolved. At present, we are investigating a dynamic, semi‑permanent surface functionalization method for PDMS chips and have made some progress. Further advancement of this technology is expected to facilitate the transition of microfluidic synthesis from laboratory‑scale to industrial‑scale column production.

What practical application could this research have in the future?

We believe that the current work can inspire the next generation of chromatographic stationary phases, and it may align closely with two major contemporary trends: biopharmaceuticals and artificial intelligence. For biopharmaceuticals, the separation efficiency and maximum pore size of current macroporous chromatographic microspheres struggle to meet the demands of very large biomolecules or other therapeutics. In contrast, chromatographic microspheres prepared by microfluidics not only achieve higher efficiency but also surpass the traditional limit of pore size control. The flexible tunability of pore size offered by the microfluidic preparation method can be beneficial for developing targeted separation strategies for diverse biopharmaceuticals. Meanwhile, AI has shown great potential in predicting chromatographic retention behaviour. The precise definition of pore structures in ordered mesoporous microspheres, along with the accurate control over chemical selectivity afforded by Janus materials, will empower the development of AI‑based prediction models, thereby achieving a long‑sought but not yet fully realised goal in the field of chromatography and separation science at large.