查看更多>>摘要：The short-circuit flow has a great influence on the separation performance in cyclone separator.Herein,we used the LES model and particle random trajectory model to simulate gas-solid two-phase flow,and analyzed the particle motion from two aspects of particle trajectory and residence time.The results showed that the separation efficiency of particles from 1 um to 10 um diameter presented an increasing first and then a gentle distribution.The separation efficiency began to decrease when the particle size was less than 10 μm.When the particle size was larger than 3 μm,the separation efficiency was above 80%,and the separation efficiency decreased sharply when the particle size was less than 3 μm.There was a phenomenon of top ash ring in the annular space,especially near the cyclone proof,where a lot of particles gathered.The particle aggregation was serious in 130-180 degrees.The top ash ring could be formed only when the force of particles was balanced,which was unevenly distributed and had a quasi-periodic shedding characteristic.In addition,part of the airflow blew obliquely to the incoming airflow after a rotation,resulting in compression phenomenon.These performances would not only cause the escape of particles and reduce the separation efficiency,but also cause abrasion of the wall.
查看更多>>摘要：Herein,we report adsorptive removal of methylene blue as model pollutant dye by polythiophene/zeolite/iron magnetic nanocomposite,which was synthesized by chemical polymerization method.The operating process parameters,including adsorbent dose,pH,temperature,contact time,and initial concentration of dye,were optimized by Taguchi experimental design(L16 orthogonal array).The results showed that the nanocomposites containing 50 wt% of zeolite and 25 wt% of iron magnetic nanoparticles(i.e.,relative to the molecular mass of thiophene monomer)had a robust structure with high removal efficiency.The analysis of experimental isotherm data revealed that Toth model better described the adsorption process,and the maximum adsorption capacity of 319.4 mg/g was obtained at 80 ℃.Additionally,it was found that the adsorption process was endothermic.The kinetic study also showed that the adsorption kinetic follows a pseudo-second order.The as-synthesized nanocomposite showed an excellent reusability up to 6 cycles of adsorption,owing to its multifunctional structure and magnetic properties.This study indicates the importance of designing nanoporous nanocomposites based on various nanomaterials to obtain recyclable adsorbents with high adsorption capacity for the removal of pollutant dyes from wastewater streams.
查看更多>>摘要：This short review aims to introduce the uniqueness,advantages,and recent progress in using calixarenes for membrane modifications and separations.This type of unique nano-porous materials may provide great prospects for next-generation membrane modifications and development.
查看更多>>摘要：The presence of phenol as an organic pollutant in industrial effluents is the biggest threat to the aquatic environment and human health.The aqueous-aqueous extraction process is an attractive method to treat saline phenolic wastewater(feed solution)via diffusion through a semi-permeable polydimethylsiloxane(PDMS)to the receiving solution.To improve the value of mass transfer coefficient,thinning the PDMS layer and embedding it with nanoparticles/metal-organic frameworks(MOFs)can lead to membrane defects or weakened mechanical strength,which is not promising for large-scale practical applications.Therefore,herein,an interfacial design strategy is demonstrated to disperse TiO2@ZIF-8 composites as hybrid particles into the top selective layer(PDMS)of TFC(thin-film composite)membrane to enhance polymer-filler compatibility and mass transfer coefficient.The TiO2@ZIF-8 composites enhanced the affinity to the polymer matrix,thereby increasing the mechanical stability and preventing interfacial voids and agglomeration.Moreover,the TiO2@ZIF-8 incorporated TFC membranes exhibited an enhanced mass transfer coefficient(kQ)of(25.28 ± _(0.5))x 1CT7 and a reduced reverse salt flux of 9.5 mg/m~2.h.The enhanced mechanical stability and mass transfer coefficient were attributed to the synergistic effect provided by TiO2@ZIF-8 composites,as ZIF-8 particles provided continuous pathways(pore-flow mode)and TiO2 nanoparticles provided compactivity with PDMS.The synergistic effects of hybrid particles could provide a new strategy to develop PDMS for the extraction of various organic compounds.
查看更多>>摘要：The sluggish kinetics of the Sodium borohydride(NaBH4)hydrolysis process particularly in alkaline conditions requires the design of high-performance low-cost catalysts.Herein,it was aimed to tailor cobalt ferrite anchored nitrogen-and sulfur-doped graphene architecture(CoFe2O4@N,S-G)via a facile production pathway,to explore its potential application as a catalyst in alkaline NaBH4 hydrolysis reaction for hydrogen production,and to develop an optimal artificial neural network(ANN)architecture to predict hydrogen production rate.In this regard,the influence of several variables such as reaction temperature,NaBH4 concentration,and catalyst loading was explored to determine the optimal operational conditions for effective hydrogen generation.Furthermore,the performance metrics of ANN topologies were investigated to establish the best ANN model for predicting hydrogen generation rate under different operational conditions.The experimental results of fered the outstanding catalytic activity of CoFe2O4@N,S-G towards NaBH4 hydrolysis with the volumetric hydrogen production rate of 8.5 L.min~(-1).g_(cat)~(-1)at 25 ℃,and catalyst loading of 0.02 g,and 1.0 M NaBH4 concentration.The CoFe2O4@N,S-G nanocatalyst was found to retain 94.9% of its initial catalytic activity after 5 consecutive uses,according to the reusability tests.The optimum performance metrics that were determined by the mean squared error(MSE)of 0.00052 and the coefficient of determination(R~2)of 0.9989 were achieved for the ANN model with the configuration of 3-10-5-1 trained by Levenberg-Marquardt backpropagation algorithm.The activation function of tansig and purelin functions at hidden and output layers,respectively.The findings revealed that the experimental data were in harmony with the ANN-predicted one,thereby inferring the optimized ANN model could be employed in the forecasting of hydrogen production rate at various operational conditions.
查看更多>>摘要：Accurate damage degree prediction is important to ensure the safety,stability,and economic operation of the natural gas pipeline in service,especially those in long-term service.In order to maintain the efficiency and safety of natural gas pipeline transportation,the intelligent diagnosis and evaluation technology of pipeline is very important.In this paper,The opposition-based learning strategy and adaptive T-distribution mutation operator are introduced to optimize the sparrow search algorithm(SSA),improve the search ability,convergence speed and accuracy of SSA algorithm.12 classical benchmark functions are used to evaluate the performance of the improved algorithm.Experimental results demonstrate the feasibility and validity of ISSA compared with the original Sparrow search algorithm.Based on its excellent performance,ISSA is used to optimize the input layer weight and bias parameters of deep extreme learning machine(DELM).Therefore,a comprehensive ISSA-DELM network model is constructed for intelligent quantitative evaluation of natural gas pipeline defects.The results show that the model can effectively overcome the problem that the DELM effect is affected by the random input weight and random bias of each ELM-AE,and improve the quantitative prediction performance.This will facilitate the assessment of the integrity and safety status of natural gas pipelines.2022 Published by Elsevier Ltd on behalf of Institution of Chemical Engineers.
Jonathan M.Sanchez-SilvaVirginia H.Collins-MartinezErika PadiIIa-Ortega
15页
查看更多>>摘要：Metformin(MET)is one of the main drugs to treat type 2 diabetes in humans,consequently its presence in the environment has increased in recent years.Therefore,in this work,hydrochars were synthesized from Byrsonima crassifolia stones using hydrothermal carbonization followed by cold chemical activation to enhance the removal of MET in aqueous solution.A response surface experimental design was employed to correlate the experimental adsorption capacity(q_(MET))with the synthesis conditions(hydrocarboniza-tion time,activation time,and NaOH concentration)and the physicochemical properties of the adsorbents.The results showed that the hydrocarbonization and activation times are the most significant factors influencing the MET removal.According to the textural and physicochemical analyses,it was found that the combination of hydrothermal treatment and cold chemical activation increased both the presence of acid and basic active sites with the O/C ratio,which favored the removal of MET in lignin-rich hydro-carbonized materials.The adsorption equilibrium studies employing the best adsorbent evidenced that MET removal was favored at pH = 7 due to a reduction of repulsive electrostatic interactions that played a main role in the adsorption process.The maximum adsorption capacity obtained was 113.6 mg/g,which was the highest value reported in the literature.Finally,the transformation of the Byrsonima crassifolia stones suggests that the activated hydrochars synthesized by the method proposed in this work results in an effective adsorbent for MET removal in aqueous solution.
查看更多>>摘要：Recently,thin-film deposition of quantum dot(QDs)to manufacture solar cells and displays have received significant attention due to the lucrative optoelectronic properties of these devices.Unfortunately,(a)the existing macroscopic thin-film deposition models in the literature do not consider the surface-level interactions;(b)the detailed surface-level models do not consider the entire thin-film deposition ensemble; and(c)multiscale modeling studies considering both the scales are not tailored for QD systems.Thus,to address this knowledge gap,in this work,a multiscale thin-film deposition model is developed.First,the droplet distribution and evaporation dynamics during the thin-film deposition of QDs are described using heat and mass balance equations.Second,a microscopic discrete-element method(DEM)-based particle aggregation model that describes the surface-level particle interactions is developed and combined with the macroscopic dynamics.Furthermore,a model predictive controller(MPC)is designed to regulate the film thickness and minimize the film roughness by manipulating key process variables.To design a feasible MPC,a computationally efficient artificial neural network(ANN)model of the thin-film deposition model is constructed,and it is incorporated within the MPC.The closed-loop simulation results showcase the capability of the MPC to achieve the required film thickness and minimize the roughness.
查看更多>>摘要：The development of an impurity and form controlling continuous crystallization process to deliver the JAK1 inhibitor GDC-4379 is described.Explored as a next generation process for the two-step batch recrystallization procedure used in production,the translation of the impurity control step to a continuous mixed suspension,mixed product removal(MSMPR)crystallizer enabled superior kinetic rejection of a key regioisomer impurity(97.9%)versus the batch process(32.4%).By operating the MSMPR crystallizer at sufficient water content and temperature it was verified that the target hydrate form A of GDC-4379 for the active pharmaceutical ingredient(API)could be selectively crystallized from the DMSO/MeOH solvent system of the purification step.This demonstration provided proof of concept for a telescoped continuous crystallization process for GDC-4379 to replace the separate batch impurity and form control recrystallizations carried out in production.
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