Multiscale hybrid modeling of film deposition within porous substrates

Experimental Investigation and Optimal 3D Bioprinting Parameters of SA-Gel Porous Cartilage Scaffold

The main aim of this paper is to achieve the suitable SA-GEL (sodium alginate and gelatin) porous cartilage scaffold by 3D printing technology with optimal prediction parameters. Firstly, the characteristics of SA-GEL were analyzed, the influence of calcium chloride on the gel was explored, and the optimal cross-linking concentration and gelation temperature were determined. Secondly, a prediction model of the extrusion line width of SA-GEL was established, in which the printing pressure, the moving speed of the needle and the fiber interval were the important parameters affecting the printing performance of the SA-GEL composite material. Thirdly, the SA-GEL composite scaffolds were printed on the Bio-plotter platform, the C5.18 chondrocytes cells were cultured in the SA-GEL biomaterial scaffold, and the results show that the cells could survive well. These results show that, under the control of the printing parameters pressure 1.8 bar, moving speed 10.7 mm/s and the internal structure parameters of the scaffold is 0/45-1.2 (Printing interval: 1.2 mm, angle value: 45 degree), SA-GEL scaffold printing results can be obtained which have good mechanical properties and biocompatibility.

Separation membranes. Interfacial microfluidic processing of metal-organic framework hollow fiber membranes

Molecular sieving metal-organic framework (MOF) membranes have great potential for energy-efficient chemical separations, but a major hurdle is the lack of a scalable and inexpensive membrane fabrication mechanism. We describe a route for processing MOF membranes in polymeric hollow fibers, combining a two-solvent interfacial approach for positional control over membrane formation (at inner and outer surfaces, or in the bulk, of the fibers), a microfluidic approach to replenishment or recycling of reactants, and an in situ module for membrane fabrication and permeation. We fabricated continuous molecular sieving ZIF-8 membranes in single and multiple poly(amide-imide) hollow fibers, with H2/C3H8 and C3H6/C3H8 separation factors as high as 370 and 12, respectively. We also demonstrate positional control of the ZIF-8 films and characterize the contributions of membrane defects and lumen bypass.

Multiscale spatial Monte Carlo simulations: Multigriding, computational singular perturbation, and hierarchical stochastic closures

Monte Carlo (MC) simulation of most spatially distributed systems is plagued by several problems, namely, execution of one process at a time, large separation of time scales of various processes, and large length scales. Recently, a coarse-grained Monte Carlo (CGMC) method was introduced that can capture large length scales at reasonable computational times. An inherent assumption in this CGMC method revolves around a mean-field closure invoked in each coarse cell that is inaccurate for short-ranged interactions. Two new approaches are explored to improve upon this closure. The first employs the local quasichemical approximation, which is applicable to first nearest-neighbor interactions. The second, termed multiscale CGMC method, employs singular perturbation ideas on multiple grids to capture the entire cluster probability distribution function via short microscopic MC simulations on small, fine-grid lattices by taking advantage of the time scale separation of multiple processes. Computational strategies for coupling the fast process at small length scales (fine grid) with the slow processes at large length scales (coarse grid) are discussed. Finally, the binomial tau-leap method is combined with the multiscale CGMC method to execute multiple processes over the entire lattice and provide additional computational acceleration. Numerical simulations demonstrate that in the presence of fast diffusion and slow adsorption and desorption processes the two new approaches provide more accurate solutions in comparison to the previously introduced CGMC method.