Ya-Nan Zhang

In this paper, we propose a novel dual-based Lawson's method, termed b-d-Lawson, designed for addressing the rational minimax approximation under specific interpolation conditions. The b-d-Lawson approach incorporates two pivotal components that have been recently gained prominence in the realm of the rational approximations: the barycentric representation of the rational function and the dual framework for tackling minimax approximation challenges. The employment of barycentric formulae enables a streamlined parameterization of the rational function, ensuring natural satisfaction of interpolation conditions while mitigating numerical instability typically associated with Vandermonde basis matrices when monomial bases are utilized. This enhances both the accuracy and computational stability of the method. To address the bi-level min-max structure, the dual framework effectively transforms the challenge into a max-min dual problem, thereby facilitating the efficient application of Lawson's iteration. The integration of this dual perspective is crucial for optimizing the approximation process. We will discuss several applications of interpolation-constrained rational minimax approximation and illustrate numerical results to evaluate the performance of the b-d-Lawson method.

Water fluctuates in a hydrophobic confinement, forming multiple dry and wet hydration states through evaporation and condensation. Transitions between such states are critical to both thermodynamics and kinetics of solute molecular processes, such as protein folding and protein–ligand binding and unbinding. To efficiently predict such dry–wet transition paths, we develop a hybrid approach that combines a variational implicit solvation model, a generalized string method for minimum free-energy paths, and the level-set numerical implementation. This approach is applied to three molecular systems: two hydrophobic plates, a carbon nanotube, and a synthetic host molecule Cucurbit[7]uril. Without an explicit description of individual water molecules, our mesoscale approach effectively captures multiple dry and wet hydration states, multiple dry–wet transition paths, such as those geometrically symmetric and asymmetric paths, and transition states, providing activation energy barriers between different states. Further analysis shows that energy barriers depend on mesoscopic lengths, such as the separation distance between the two plates and the cross section diameter of the nanotube, and that the electrostatic interactions strongly influence the dry–wet transitions. With the inclusion of solute atomic motion, general collective variables as reaction coordinates, and the finite-temperature string method, together with an improved treatment of continuum electrostatics, our approach can be further developed to sample an ensemble of transition paths, providing more accurate predictions of the transition kinetics.

Droplets on a solid surface patterned with microstructures can exhibit the composite Cassie-Baxter (CB) state or the wetted Wenzel state. The stability of the CB state is determined by the energy barrier separating it from the wetted state. In this work, we study the CB to Wenzel transition using the string method [E et al., J. Chem. Phys. 126, 164103 (2007); W. Ren and E. Vanden-Eijnden, J. Chem. Phys. 138, 134105 (2013)]. We compute the transition states and energy barriers for a three-dimensional droplet on patterned surfaces. The liquid-vapor coexistence is modeled using the mean field theory. Numerical results are obtained for surfaces patterned with straight pillars and nails, respectively. It is found that on both type of surfaces, wetting occurs via infiltration of the liquid in a single groove. The reentrant geometry of nails creates large energy barrier for the wetting of the solid surface compared to straight pillars. We also study the effect of surface chemistry, pillar height, and inter-pillar spacing on the energy barrier and compare it with nails.