Multiple functional and hard-to-quantify sensorial product attributes that can be satisfied by a large number of cosmetic ingredients are required in the design of cosmetics. To overcome this challenge, a new optimization-based approach for expediting cosmetic formulation is presented. It exploits the use of a hierarchy of models in an iterative manner to refine the search for creating the highest-quality cosmetic product. First, a systematic procedure is proposed for optimization problem formulation, where the cosmetic formulation problem is defined, design variables are specified, and a set of models for sensorial perception and desired product properties are identified. Then, a solution strategy that involves iterative model adoption and two numerical techniques (i.e., generalized disjunctive programming reformulation and model substitution) is applied to improve the efficiency of solving the optimization problem and to find better solutions. The applicability of the proposed procedure and solution strategy is illustrated with a perfume formulation example.

In this study, we deployed a modified interfacial polymerization process to incorporate multifunctional crown ethers (CEs) into thin-film composite (TFC) polyamide membranes. These CE additives acted as both the phase-transfer catalyst and co-solvent to facilitate the diffusion of amine monomers into the organic phase and also enhanced the free volume content of the selective layer, facilitating water transport and inhibiting the diffusion of draw solutes. Various characterization techniques were employed to elucidate the modification mechanism as a function of CE chemical and physical properties on the microstructure of resultant TFC membranes and consequently separation performances. Compared to TFC membranes produced from traditional interfacial polymerization method, CE-modified membranes exhibited a 146% water flux enhancement and 59% lower reverse salt fluxes with a suitable draw solution. CE-modified membranes also exhibited improved antifouling performance with a lower flux drop (34% decline) and a higher flux recovery ratio (38% improvement).

In this study, a Schulze Ring Shear Tester and the Discrete Element Method (DEM) are employed to investigate the effect of polydispersity on the binary shear flows. Both experimental results and DEM simulations show that the pre-shear stresses are greater for binary blends than for monodispersed particles. The flowability of these mixtures is strongly affected by the solid fraction, with minimal flow function values correlating to maximum packing fraction. However, minimum flow function values are not observed at the same packing fractions where the maximum pre-shear stress occurs. The powder friction has a slightly higher contribution to powder strength than powder adhesion, and the frictional component follows the same trend as shear stress with mixture composition. Using DEM, it is demonstrated that the addition of small adhesive particles reduces the averaged angular velocity of the larger particles, which makes a contribution to the larger shear stress for binary blends.

Techniques such as micro-tomography (µCT) and nuclear magnetic resonance (NMR) methods have been used to characterize porous media for decades. Magnetic Resonance Imaging (MRI) offers direct visualization of pore architecture through a vast number of pulse sequences. In this work, we tested the MRI pulse sequence Zero Echo Time (ZTE) in the study of sandstone and carbonate. ZTE has been used previously to image highly porous geological material with relative success. In this research, ZTE was used to study porous systems tighter than those previously reported. We show that ZTE can resolve not only pore systems, but also a combination of fractures and pores simultaneously. Additionally, Pore Cluster Analysis (PCA), combined with ZTE, can be used to analyze connectivity of relatively large volume core plugs. By combining Time-Domain NMR pore-size analysis and PCA, we show that careful selection of resolution is necessary to understand transport in porous media.

Diverse engineering fields request flash calculations like isothermal flash, isenthalpic flash, and isentropic flash. They can be cast as minimization of a thermodynamic state-function and solved by Michelsen’s Q-function approach. Flash calculations for open systems, i.e. systems where chemical potentials are specified instead of the mole numbers for some components, also belong to this scope. By analyzing the construction of Q-functions through Legendre transforms, we extend this approach to the flash for open systems in the absence or presence of chemical reactions, resulting in general formulations for various specifications. For systems without reactions, the classical framework using mole numbers as independent variables is employed; for those with reactions, the modified-RAND framework is employed. We present examples for open systems at constant temperature and pressure. Using the Q-function minimization, we can solve multicomponent non-reactive or reactive systems at a specified chemical potential with quadratic convergence over a wide range of conditions.

As the hydrodesulfurization (HDS) of diesel achieves ultra-deepness, our understanding of its kinetics is still far from in-depth. Therefore, herein, two lumped kinetic models for the ultra-deep hydrodesulfurization (UHDS) and hydrodenitrogenation (HDN) are established based on experiments under a wide range of operating conditions. Meanwhile, a four-lump kinetic model of the aromatic hydrosaturation (AHS) is erected. Our kinetic models disclose thermodynamic decisiveness in UHDS, which is unreachable beyond a temperature upper limit or a pressure lower limit. We also reveals the unexpected temperature dependence of nitrogen inhibition to HDS, for less than 300℃ the nitrogen inhibition becomes even more potent despite nitrogen removal by HDN reactions. Subsequently, the HDS kinetics of total sulfur are deciphered as multi stages exist in the whole reaction coordinate. Accordingly, a four-stage conceptual model involving mechanism and rate laws is proposed to offer a better understanding of nitrogen inhibition, thermodynamics and kinetics in UHDS.