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Conventional extraction techniques for phenolic compounds are always associated with large amount of wastewater production or high energy consumption. To establish an environmentally benign method for the phenolic compounds separation from coal liquefaction oil, deep eutectic solvents (DES) as a green alternative to traditional solvent have been considered. Initially, four kinds of choline chloride (ChCl)-based DES containing carboxylic acid, alcohol amine, polyol, or glycol as a hydrogen bond donor (HBD) were screened for the proposed extraction. The FT-IR spectra demonstrated that it is hydrogen bonding between phenols and DESs that promotes the extraction process to achieve superior phenols removal efficiency. Among the investigated DESs, the ChCl-glycerol (1:1, molar ratio) eutectic mixture (DES-1) exhibited the best extractive performance, showing high phenols removal efficiency and low neutral oil entrainment. Then the extraction of phenolic compounds by this DES at various mole ratios of DES to phenols and the extractive temperature ranged from 25 to 50 °C were investigated. In an optimal condition, the phenols removal efficiency can be as high as 98.5%, and the neutral oil entrainment can be as low as 3.4%. Moreover, the extracted phenolic compounds can be easily back-extraction and the good property of high phenols removal efficiency remained during four consecutives extraction/back-extraction cycles. Last, the extraction of phenolic compounds from real coal liquefaction oil using the DES was also explored, which obtained better extractive performances compared to that of single ChCl or glycerol aqueous solution extraction. The knowledge acquired in this study will present a new approach to remove phenolic compounds from coal-based liquid oil.

Pyrolysis is an initial step of the upgrading lignite that exhibits a structurally complex connection between physicochemical changes and unknown pyrolyzed compounds, which complicates process simulation for downstream processing. Combined the functional group-depolymerization vaporization cross-linking (FG-DVC) model with non-linear programming (NLP) theory would link between coal pyrolysis and process simulation. First, we adjust the range of the van Krevelen diagram and predict the char and volatiles yields from coal pyrolysis using the FG-DVC model. The tar ultimate analysis is then estimated based on mass/element conservation, and the tar group composition is calculated using the NLP model on the basis of the total tar yield and ultimate analysis. Upon completion of these steps, the process simulation and energy consumption distribution of coal pyrolysis is carried out using Aspen Plus. Results show that the FG-DVC model with the adjusted van Krevelen diagram can accurately predict coal pyrolysis products with better performance than that obtained using empirical correlations. Results show that the energy consumption of drying coal was the largest with 653.2 MJ when drying 1000 kg of coal, followed by pyrolysis with 482.2 MJ. The combined coal pyrolysis model, being independent on experiments, can be used for process design.

The development of new drugs especially novel anti-cancer drugs has become a hot-spot issue that catches scholars’ attention in every field. Here a IAP antagonist analogue (IAPA) was synthesized and characterized by NMR and HRMS spectra. Its interaction with proteins, including bovine serum albumin (BSA) and human serum albumin (HSA), were investigated by spectral methods and molecular simulation. Fluorescence quenching, together with UV absorption spectrum and time-resolved fluorescence spectrums indicated a static process in BSA/HSA-IAPA system. Thermodynamic parameters including ΔH and ΔS calculated by Vant't Hoff equation were all positive, showing that hydrophobic force was the major force in the interaction of compound IAPA and BSA/HSA. Site marker competitive displacement experiments proved that IAPA bound to site I at BSA/HSA. Synchronous fluorescence spectrum and three-dimensional fluorescence spectrum were also used to investigate the conformational changes of BSA/HSA after binding with compound IAPA. The above results were further verified by molecular docking.

Given that China has launched the largest carbon market in the world, it is of great significance to evaluate the “maturity” of the China's 7 regional pilot carbon emissions trading system. Based on an in-depth survey of 33 experts from more than 10 related institutions in the 7 pilots, this study develops a carbon market maturity evaluation index system that consists of 4 target layers including the attributes of environment, market and finance, supporting policies and infrastructure, and service capability of trading platform. By combining factor analysis and analytic hierarchy process methods, this study conducts a comprehensive evaluation on the maturity of 7 pilots. The results show that：The maturity of 7 pilots can be clearly categorized into several hierarchies, with Shenzhen (0.8113) ranks first due to its market-oriented mechanism; Beijing (0.5735), Hubei (0.5432), Shanghai (0.5004) and Guangdong (0.4846) are of similar degrees of maturity but with different characteristics - Beijing with most diversified emission controlled entities and strong environmental constraints, Hubei primarily driven by institutional arrangement, Shanghai with outstanding ability of platform service, Guangdong emphasizing on development of its primary market; while Tianjin (0.2616) and Chongqing (0.1338) exhibits lowest level of maturity. Overall, China's 7 pilots are still in their infancy and demonstrate a phenomenon of “low trading volume and superficial prosperity”. Therefore, recommendations are brought out that the maturity of China's carbon markets should be promoted from the aspects of tightening environmental constraints, strengthening market capacity-building and cultivating related consulting industry.