The regulation of water content in polymeric membranes is important in a number of applications, such as reverse electrodialysis and proton-exchange fuel-cell membranes. External thermal and water management systems add both mass and size to systems, and so intrinsic mechanisms of retaining water and maintaining ionic transport in such membranes are particularly important for applications where small system size is important. For example, in proton-exchange membrane fuel cells, where water retention in the membrane is crucial for efficient transport of hydrated ions, by operating the cells at higher temperatures without external humidification, the membrane is self-humidified with water generated by electrochemical reactions. Here we report an alternative solution that does not rely on external regulation of water supply or high temperatures. Water content in hydrocarbon polymer membranes is regulated through nanometre-scale cracks ('nanocracks') in a hydrophobic surface coating. These cracks work as nanoscale valves to retard water desorption and to maintain ion conductivity in the membrane on dehumidification. Hydrocarbon fuel-cell membranes with surface nanocrack coatings operated at intermediate temperatures show improved electrochemical performance, and coated reverse-electrodialysis membranes show enhanced ionic selectivity with low bulk resistance.

Molecular cavities, which include voids and channels, are critical for molecular function. We present a webserver, BetaCavityWeb, which computes these cavities for a given molecular structure and a given spherical probe, and reports their geometrical properties: volume, boundary area, buried area, etc. The server's algorithms are based on the Voronoi diagram of atoms and its derivative construct: the beta-complex. The correctness of the computed result and computational efficiency are both mathematically guaranteed. BetaCavityWeb is freely accessible at the Voronoi Diagram Research Center (VDRC) (http://voronoi.hanyang.ac.kr/betacavityweb).

Many applications, such as protein design, homology modeling, flexible docking, etc. require the prediction of a protein's optimal side-chain conformations from just its amino acid sequence and backbone structure. Side-chain prediction (SCP) is an NP-hard energy minimization problem. Here, we present BetaSCPWeb which efficiently computes a conformation close to optimal using a geometry-prioritization method based on the Voronoi diagram of spherical atoms. Its outputs are visual, textual and PDB file format. The web server is free and open to all users at http://voronoi.hanyang.ac.kr/betascpweb with no login requirement.

Recent work has demonstrated that the interior material layout of a 3D model can be designed to make a fabricated replica satisfy application-specific demands on its physical properties such as resistance to external loads. A widely used practice to fabricate such models is by layer-based additive manufacturing (AM) or 3D printing, which however suffers from the problem of adding and removing interior supporting structures. In this paper, we present a novel method for generating support-free elliptic hollowing for 3D shapes which can entirely avoid additional supporting structures. To achieve this, we perform the ellipse hollowing in the polygons on parallel section planes and protrude the ellipses of one plane to its neighboring planes. To pack the ellipses in a polygon, we construct the Voronoi diagram of ellipses to efficiently reason the free-space around the ellipses and other geometric features by taking advantage of the available algorithm for the efficient and robust construction of the Voronoi diagram of circles. We demonstrate the effectiveness and feasibility of our proposed method by generating interior designs for and printing various 3D shapes.

Voronoi diagrams are useful for spatial reasoning, and the robust and efficient construction of the ordinary Voronoi diagram of points is well known. However, its counterpart for circular disks in R 2 and spherical balls in R 3 remains a challenge. In this article, we propose a topology-oriented incremental algorithm which robustly and efficiently computes a Voronoi diagram by incrementing a new disk generator to an existing one. The key idea is to enforce the convexity of the Voronoi cell corresponding to the incrementing disk so that a simple variation of the algorithm for points proposed by Sugihara in 1992 can be applied. A benchmark using both random and degenerate disks shows that the proposed algorithm is superior to CGAL in both computational efficiency and algorithmic robustness.