Institutional Repository of Institute of Process Engineering, CAS (IPE-IR）
Not a member yet
40778 research outputs found
Sort by
Separation of anthracene and carbazole from crude anthracene via imidazolium-based ionic liquids
No full textAnthracene and carbazole, the main components of crude anthracene, have high added value in chemical in-dustry. In this study, two imidazolium-based ILs, [PM2IM][TFAc] (ILa) and [PM2IM][Ac] (ILb), were synthesized to separate anthracene and carbazole. The effective separation of anthracene and carbazole was achieved by hydrogen bonding between carbazole and imidazolium-based ILs. The results of density functional theory simulation and 1H NMR verification showed that the hydrogen bond interaction between carbazole and ILs was via C=O...H-N, and the hydrogen bond strength between ILb and carbazole was stronger than that of ILa. Based on the process for the separation of anthracene and carbazole from crude anthracene by imidazolium-based ILs, the purity of refining anthracene reached 94.89% and that of crude carbazole reached 81.60%. In addition, this process test realized recovery and recycling of ILs
Interfacial oxygen vacancies at Co3O4-CeO2 heterointerfaces boost the catalytic reduction of NO by CO in the presence of O2
No full textSimultaneously improving both NOx conversion and N2 selectivity in the selective catalytic reduction of NO by CO (CO-SCR) under O2-containing conditions is highly challenging because of the competitive reactions of NOx and CO with O2. Here, we demonstrate that the interfacial oxygen vacancies (IOVs) generated at the Co3O4-CeO2 heterointerfaces by ball-milling-induced strain can remarkably boost both NOx conversion and N2 selectivity in the temperature range of 100-400 degrees C. The Co3O4-CeO2-IOV catalyst achieved approximately 100% NOx con-version and 100% N2 selectivity (200-350 degrees C, 1-5 vol% O2, and 20,000 h-1); even under 10 vol% O2, it still showed good catalytic performance. The spectroscopy analysis and theoretical calculations reveal that compared with O2 activation, IOVs are more favorable for the rate-limiting step of NO adsorption and dissociation. This work provides an effective strategy to create IOVs within metal oxide composite catalysts using ball-milling -induced interfacial strain for improving CO-SCR performance
Structure-based simulation of mass transfer in turbulent fluidized beds without local equilibrium assumption
No full textTraditional methods based on local equilibrium assumption are unsuitable to describe the non-linear and non-equilibrium mass transfer in turbulent fluidized beds (TFBs), especially for industrial-scale reactors. In this work, the structure-based mass balance equations are proposed to describe the transfer and reac-tion of component on the surface of particles. These equations are valid and reasonable whether mass transfer and chemical reaction are in local equilibrium or not. Since local equilibrium assumption is not used, the proposed method can directly describe the transfer-reaction systems in TFBs, which are not in local equilibrium. Moreover, the proposed mass balance equations have also considered the meso-scale flow of particles. This can better reflect the transfer of component caused by the convection of particles in TFBs than the traditional models. The accuracy of the present model prediction was con-firmed by comparison of the predicted results and the experimentation being available in literatures.(c) 2022 Elsevier Ltd. All rights reserved
A Foldable Aqueous Zn-Ion Battery with Gear-Structured Composite as Freestanding Cathode
No full textA foldable battery with high flexibility provides great potential in various wearable electronic devices for health and fitness tracking, chronic disease management, performance monitoring, navigation tracking, and portable gears for soldiers. We report a highly flexible, self-healing Zn-ion battery with a free-standing cathode that is composed of a 3D gear-like NH4V4O10@C composite on carbon paper. The battery retained a capacity of up to 102.4 mAh g(-1) even after being folded 60 times with a high angle of 180 degrees. An aqueous hydrogel consisting polyvinyl alcohol, glycerin and Zn(CF3SO3)(2) was used as electrolyte, which showed as high as 580 % tensile strain under a loading weight of 78 N. The battery exhibited a better capacity retention of over 100 mAh g(-1) and Coulombic efficiency of over 99.8 % after cutting and twisting to 90 degrees, thereby indicating a great self-healing performance. The gear-like geometry greatly improved the volume accommodation due to the increased interval space between the blades and the outward configuration. Meanwhile the Zn2+ ionic conductivity was improved by rapid re-binding of many existing hydroxy groups from the electrolyte and the enhanced contact surface area and diffusion route from the cathode material. The highly flexible, safe aqueous Zn-ion battery opens a practical way to power various carry-on electronics under mechanical agitation
Generalised Latent Assimilation in Heterogeneous Reduced Spaces with Machine Learning Surrogate Models
No full textReduced-order modelling and low-dimensional surrogate models generated using machine learning algorithms have been widely applied in high-dimensional dynamical systems to improve the algorithmic efficiency. In this paper, we develop a system which combines reduced-order surrogate models with a novel data assimilation (DA) technique used to incorporate real-time observations from different physical spaces. We make use of local smooth surrogate functions which link the space of encoded system variables and the one of current observations to perform variational DA with a low computational cost. The new system, named generalised latent assimilation can benefit both the efficiency provided by the reduced-order modelling and the accuracy of data assimilation. A theoretical analysis of the difference between surrogate and original assimilation cost function is also provided in this paper where an upper bound, depending on the size of the local training set, is given. The new approach is tested on a high-dimensional (CFD) application of a two-phase liquid flow with non-linear observation operators that current Latent Assimilation methods can not handle. Numerical results demonstrate that the proposed assimilation approach can significantly improve the reconstruction and prediction accuracy of the deep learning surrogate model which is nearly 1000 times faster than the CFD simulation
