Institutional Repository of Institute of Process Engineering, CAS (IPE-IR）
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Synergetic interaction of capsid proteins for virus-like particles assembly of foot-and-mouth disease virus (serotype O) from the inclusion bodies
No full textRecombinant virus-like particles (VLP) with single capsid protein have been successfully produced through prokaryotic system, but for those with multiple capsid proteins such as the foot-and-mouth disease virus (FMDV), this approach is more challenging. In this study, in vitro assembly of FMDV VLP was investigated with its capsids VP1, VP2 and VP3 separately expressed as inclusion bodies. After extraction and solubilization, three capsids were purified in denatured state through a flow-through model, increasing its purity to 90%. VLP assembly for FMDV was observed after diluting the mixture of denatured capsids in the ration of 1: 1: 1, while no VLP appeared if the separately diluted and refolded capsids were co-incubated. This result suggests certain synergetic interactions exist among the three capsids, which are crucial for FMDV VLP assembly. Sodium chloride and capsid protein concentration both greatly affect the assembling efficiency. After purification through size exclusion chromatography, VLP with similar diameter and morphology as inactivated FMDV were obtained, which elicited high IgG titers and B cell activation when vaccinated in mouse. It could also induce specific humoral and cellular immune responses in splenocytes proliferative experiments. Our study demonstrated the feasibility of in vitro assembling FMDV VLP from inclusion bodies of VP1, VP2 and VP3 for the first time
A deep learning approach using temporal-spatial data of computational fluid dynamics for fast property prediction of gas-solid fluidized bed
No full textTo deal with the critical issue of long computational time in practical application of computational fluid dynamics (CFD), this paper presents a new approach of deep learning for voidage prediction (DeepVP) that couples short time CFD simulations (limited CFD iterations) with the deep learning method to accelerate the 2D voidage distribution prediction for a gas-solid fluidized bed at steady state. Short time CFD simulations are first performed to obtain a sequence of voidage distribution images containing the temporal-spatial property of a gas-solid fluidized bed of the early period. A deep learning model is built to predict the voidage distribution at steady state, which is achieved by implementing multi-scale convolutional neural networks based on the sequence of voidage images. The case study results for a bubbling bed show that the voidage distribution at steady state for the bubbling bed can be predicted with comparable accuracy of conventional CFD simulations at about 1/30th computational cost. Moreover, the DeepVP method exhibits better extrapolation capability than the deep learning approach merely based on CFD condition parameters
Temperature dependence of deposition behavior and corrosion resistance of zinc coatings electroplated on copper substrates from ethaline electrolyte
No full textElectrodeposition of zinc (Zn) coatings on copper (Cu) substrates was conducted from choline chloride-ethylene glycol-based deep eutectic solvent under the temperatures varying from 323 to 343 K. The electrochemical behavior of Zn ions on Cu electrodes at different temperatures was studied through cyclic voltammetry and chronoamperogram testing. The obtained results illustrate that the electrodeposition of Zn coatings is a diffusion-controlled quasi-reversible process with an instantaneous two-dimensional nucleation and growth mechanism. The crystal structure and chemical composition analysis demonstrates that the electrodeposition from ChCl-EG-ZnCl2 system is an effective strategy to achieve a Zn coating with high crystallinity and purity. The surface morphological analysis further reveals that the electroplated coatings are stacks of flake Zn grains. The dependence of the deposition behavior and quality of electroplated Zn coatings on temperature was studied systematically. The growth behavior of Zn grains is enhanced with increasing the temperature, but too high a temperature inevitably leads to the undesired coarsen microstructure instead. On the basis of the polarization curves and EIS testing results, the temperature was optimized at 333 K to obtain a Zn coating with superior corrosion resistance in 3.5 wt% NaCl solution to that of Zn coatings electroplated at other conditions
Interfacial role of Ionic liquids in CO2 electrocatalytic Reduction: A mechanistic investigation
No full textIonic liquids (ILs) can significantly reduce the overpotential of CO2 electrocatalytic reduction reaction (CO2RR) and thus show a huge application potential in the CO2 conversion. However, it has not been clear what role ILs play in the reaction occurring at the solid-liquid interface of the electrodes. In this work, we performed comprehensive DFT calculations to investigate the mechanism of CO2RR to CO on Ag electrode surfaces with ILs. Our results showed that the Ag(1 1 0) surface exhibits better catalytic performance than both Ag(1 0 0) and Ag(1 1 1) surfaces since the energy barrier of the transition state (Ts) is lower and the intermediate (*COOH) is more stable on the former surface. When ILs exist near the surface, the energy barrier of the Ts decreases and varies when the CO2 molecule is localized at different positions of the [Emim](+ )cation. The optimized structures showed that the CO2 molecule prefers to stay near the C-4/5 position rather than the C-2 position. It was also found that proton transferring on the Ag surface by the hydrogen bond mode has a lower energy barrier than the shuttling mode, which indicates that the IL can act as an assist-catalyst by forming hydrogen-bonding complex in the reaction. Furthermore, the role of water was explored by using the implicit-solvent model. It was found that the solvation effect of the water always decreases the energy barrier, and the decline is more pronounced when there are ILs. Molecular dynamics (MD) simulations also showed that near the electrode surface, each CO2 molecule is enclosed by 3-4 [Emim](+) cations with their C-4/5 more likely approaching the CO2. Such a distri-bution embodies the mesoscale multi-ions synergistic catalytic mechanism that will be elucidated in our future work
Interfacial role of Ionic liquids in CO2 electrocatalytic Reduction: A mechanistic investigation
No full textIonic liquids (ILs) can significantly reduce the overpotential of CO2 electrocatalytic reduction reaction (CO2RR) and thus show a huge application potential in the CO2 conversion. However, it has not been clear what role ILs play in the reaction occurring at the solid-liquid interface of the electrodes. In this work, we performed comprehensive DFT calculations to investigate the mechanism of CO2RR to CO on Ag electrode surfaces with ILs. Our results showed that the Ag(1 1 0) surface exhibits better catalytic performance than both Ag(1 0 0) and Ag(1 1 1) surfaces since the energy barrier of the transition state (Ts) is lower and the intermediate (*COOH) is more stable on the former surface. When ILs exist near the surface, the energy barrier of the Ts decreases and varies when the CO2 molecule is localized at different positions of the [Emim](+ )cation. The optimized structures showed that the CO2 molecule prefers to stay near the C-4/5 position rather than the C-2 position. It was also found that proton transferring on the Ag surface by the hydrogen bond mode has a lower energy barrier than the shuttling mode, which indicates that the IL can act as an assist-catalyst by forming hydrogen-bonding complex in the reaction. Furthermore, the role of water was explored by using the implicit-solvent model. It was found that the solvation effect of the water always decreases the energy barrier, and the decline is more pronounced when there are ILs. Molecular dynamics (MD) simulations also showed that near the electrode surface, each CO2 molecule is enclosed by 3-4 [Emim](+) cations with their C-4/5 more likely approaching the CO2. Such a distri-bution embodies the mesoscale multi-ions synergistic catalytic mechanism that will be elucidated in our future work
Adsorption of phosphorus from eutrophic seawater using microbial modified attapulgite- cleaner production, remove behavior, mechanism and cost-benefit analysis
No full textA novel seawater phosphorus adsorption material (AT@SiB-X) has been developed through the modification of attapulgite (AT) by silicate bacteria (SiB-X) in this study, enabling efficient separation of phosphate from seawater. The phosphorus adsorption capacity of AT@SiB-X reached 9.54 mg/g, and its specific surface area and pore volume increased by 49.3-175.0 % and 12.5-47.4 %, respectively when compared with unmodified AT. Moreover, the SiB-X accelerated the decomposition of minerals and dissolution of metal elements (e.g., Ca, Mg, Al and Fe), resulting in a 16.7-fold increase in phosphorus adsorption. The adsorption process is controlled by multiple mechanisms, including electrostatic attraction, ion exchange, complexation, chemical precipitation, and physical adsorption. The path analysis suggested that both physical structure and chemical element release played a joint role in phosphorus adsorption. What's more, pore structure change of the material was the main mechanism affecting its adsorption capacity. The fixed bed column dynamically removed 98 % of phosphorus from mariculture wastewater, which achieved of 7.02 yen /ton wastewater treatment cost. The production cost of AT@SiB-X is about 2000 yen /ton, which is much lower than the current average market value of commercial adsorption materials (e.g., activated carbon). The experimental results demonstrated that the AT@SiB-X exhibited excellently in regeneration, which is resulted by the impressive adsorption efficiency and little pos-sibilities of overcrowding. Thus, it is highly feasible to achieve commercial application of microbially modified attapulgite
