A SAFT equation of state (EOS) combined with eight mixing rules was used to evaluate the capability of the SAFT approach for modeling the solubility of solids in supercritical fluids (SCFs). The results show that the SAFT approach gives good correlative accuracy in general, and the results are satisfactory when the three-parameter mixing rules are used, where the average absolute deviation of solid solubility in the SCF phase is normally smaller than 10%. The present work shows that the SAFT approach can be used to model solid-SCF equilibria, which gives slightly better correlative accuracy than the cubic EOSs.

The SAFT equation of state (EOS) combined with a one-parameter mixing rule was used to evaluate the capability of the SAFT approach for modeling the solubility of solid aromatic compounds in supercritical fluids (SCFs) with cosolvents. Binary interaction parameters were obtained by fitting the phase equilibrium data of the constituent binary systems. The SAFT EOS was used to predict the solubility of solids in carbon dioxide with cosolvents for five systems, and the overall average absolute relative deviation (AARD) was 20.43%. For the other 11 systems, the binary interaction parameters between the solids and the cosolvents were obtained by fitting the ternary solubility data, and the overall AARD was 16.45%. Comparison with the PRSV EOS showed that the SAFT EOS was superior in terms of both prediction and correlation. The present work demonstrates that the SAFT approach is useful for modeling the solubility of solids in SCFs with cosolvents with reasonable accuracy.

Aqueous liquefaction of Cunninghamia lanceolata, Fraxinus mandshurica, Pinus massoniana Lamb. and Populus tomentosa Carr. was carried out in an autoclave in the reaction temperature range of 553. 15-633. 15 K, where both non-catalytic and catalytic liquefaction were performed. The experimental results show that the lignin content has a large effect on the yield of liquefaction products in the noncatalytic liquefaction. The addition of K2CO3 as a catalyst can significantly reduce the residue yield for all the woods tested, while its effect on the heavy oil yield becomes weaker with decreasing amounts of lignin. The present study shows that a heavy oil yield of 30% coupled with a residue yield of less than 10% can be obtained for all the wood samples tested in the catalytic liquefaction.

A correlation for estimation of the aqueous solubility of organic compounds that is based on a training set of 120 chemicals is proposed. The new model proposed is predictive and requires only molecular connectivity indices in the calculations. The calculated results of the new model are comparable to those from the existing general solubility equation (GSE) and the Klopman-Zhu models. The new model was also applied to a testing set of 80 compounds, and the predictions show that the new model is reliable with good predictive accuracy. Because the new model does not require any experimental physicochemical properties in the calculation, it is simple and easy to apply. This work shows again that molecular connectivity indices are useful structural descriptors in quantitative structure-property (QSPR) studies in pharmaceutical research.

Metal-organic frameworks (MOFs) are thought to be a set of promising hydrogen storage materials; however, little is known about the interactions between hydrogen molecules and pore walls as well as the diffusivities of hydrogen in MOFs. In this work, we performed a systematic molecular simulation study on the adsorption and diffusion of hydrogen in MOFs to provide insight into molecular-level details of the underlying mechanisms. This work shows that metal-oxygen clusters are preferential adsorption sites for hydrogen in MOFs, and the effect of the organic linkers becomes evident with increasing pressure. The hydrogen storage capacity of MOFs is similar to carbon nanotubes, which is higher than zeolites. Diffusion of hydrogen in MOFs is an activated process that is similar to diffusion in zeolites. The information derived in this work is useful to guide the future rational design and synthesis of tailored MOF materials with improved hydrogen adsorption capability.