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With the aid of DFT calculation, deep eutectic solvents can be designed more powerful for the pretreatment of lignocellulose and the production of biochemicals.

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The content of cellulose in biomass is important for producing nanocellulose in high yields. Cotton fibers containing ultrahigh purity (∼95%) cellulose are ideal feedstock for nanocellulose production. However, the presence of strong hydrogen bonding between the cellulose chains limits the use of cotton fibers for the production of nanocellulose in a facile and mild process. Here, efficient cleavage of the strong hydrogen bonds in cotton and ultrafast fabrication of cellulose nanocrystals (CNCs) with a high yield of 74.2% were first realized through a 3 min microwave-assisted deep eutectic solvent pretreatment and a subsequent high-intensity ultrasonication process. The obtained CNCs had diameters of 3− 25 nm, and lengths ranged between 100 and 350 nm. The CNCs also displayed a relative crystallinity of 82%, and the thermal degradation temperature started from 320 °C. The study provides a green and efficient method for the mass production of cotton CNCs, and is expected to contribute to improving the refinery utilization of cotton feedstock.

Surface biofunctionalization of the hydrophobic lanthanide ion doped hexagonal phase NaYF4:Yb,Er upconversion nanophosphors (UCNPs) was achieved by introducing amino and carboxyl groups, respectively. Amino groups were added by using the 3-aminopropyltrimethoxysilane reaction after a thin layer of SiO2 coating. The carboxyl groups on surface were added directly by coating modified amphiphilic polyacrylic acid polymer. Experimental studies of cytotoxicity and cell uptake of UCNPs were conducted. The cytotoxicity analysis of the functionalized UCNPs was conducted by methylthiazol tetrazolium assays. Cell uptake was accomplished by incubating the UCNPs with human osteosarcoma cells and proved by transmission electron microscopy. The results showed that the functionalized UCNPs had very low toxicity compared with the control group, while UCNPs taken into the cells indicated that they had very high biocompatibility. The imaging of UCNPs, which were incubated with AB12 mouse mesothelioma cells and excited by 1 W 980 nm light, showed individual particles with visible light emission. These results exhibited promising applications of functionalized UCNPs in cell imaging and photodynamic therapy.

In this work, we have theoretically analyzed and numerically evaluated the accuracy of high-order lattice Boltzmann (LB) models for capturing non-equilibrium effects in rarefied gas flows. In the incompressible limit, the LB equation is proved to be equivalent to the linearized Bhatnagar-Gross-Krook (BGK) equation. Therefore, when the same Gauss-Hermite quadrature is used, LB method closely assembles the discrete velocity method (DVM). In addition, the order of Hermite expansion for the equilibrium distribution function is found not to be correlated with the approximation order in terms of the Knudsen number to the BGK equation, which was previously suggested by Shan et al. (2006). Furthermore, we have numerically evaluated the LB models for a standing-shearwave problem, which is designed specifically for assessing model accuracy by excluding the influence of gas molecule/surface interactions at wall boundaries. The numerical simulation results confirm that the high-order terms in the discrete equilibrium distribution function play a negligible role. Meanwhile, appropriate Gauss-Hermite quadrature has the most significant effect on whether LB models can describe the essential flow physics of rarefied gas accurately. For the same order of the Gauss-Hermite quadrature, the exact abscissae will also modestly influence numerical accuracy. Using the same Gauss-Hermite quadrature, the numerical results of both LB and DVM methods are in excellent agreement for flows across a broad range of the Knudsen numbers, which confirms that the LB simulation is similar to the DVM process. Therefore, LB method can offer flexible models suitable for simulating continuum flows at Navier Stokes level and rarefied gas flows at the linearized Boltzmann equation level. †

A thermal lattice Boltzmann model is constructed on the basis of the ellipsoidal statistical Bhatnagar-Gross-Krook (ES-BGK) collision operator via the Hermite moment representation. The resulting lattice ES-BGK model uses a single distribution function and features an adjustable Prandtl number. Numerical simulations show that using a moderate discrete velocity set, this model can accurately recover steady and transient solutions of the ES-BGK equation in the slip-flow and early transition regimes in the small Mach number limit that is typical of microscale problems of practical interest. In the transition regime in particular, comparisons with numerical solutions of the ES-BGK model, direct Monte Carlo and low-variance deviational Monte Carlo simulations show good accuracy for values of the Knudsen number up to approximately 0:5. On the other hand, highly non-equilibrium phenomena characterized by high Mach numbers, such as viscous heating and force-driven Poiseuille flow for large values of the driving force, are more difficult to capture quantitatively in the transition regime using discretizations that have been chosen with computational efficiency in mind such as the one used here, although improved accuracy is observed as the number of discrete velocities is increased

For multiscale gas flows, kinetic-continuum hybrid method is usually used to balance the computational accuracy and efficiency. However, the kinetic-continuum coupling is not straightforward since the coupled methods are based on different theoretical frameworks. In particular, it is not easy to recover the non-equilibrium information required by the kinetic method which is lost by the continuum model at the coupling interface. Therefore, we present a multiscale lattice Boltzmann (LB) method which deploys high-order LB models in highly rarefied flow regions and low-order ones in less rarefied regions. Since this multiscale approach is based on the same theoretical framework, the coupling precess becomes simple. The non-equilibrium information will not be lost at the interface as low-order LB models can also retain this information. The simulation results confirm that the present method can achieve model accuracy with reduced computational cost.