Preparation of Fe3O4-octadecyltrichlorosilane for Removal of Methyl Orange and Methylene Blue:Influence of p H and Ionic Strength on Competitive Adsorption

Fe3O4-octadecyltrichlorosilane（Fe3O4-OTS）was synthesized and used to remove dyes in a competitive system.Fe3O4-OTS was prepared by slow hydrolysis of OTS in cyclohexane on the surface of Fe3O4obtained through coprecipitation method.Scanning electron microscope（SEM）,energy dispersive spectrometer（EDS）,and contact angle analyzer（CA）were used to analyze the properties of Fe3O4-OTS.Methyl orange（MO）and methylene blue（MB）were selected as model molecules to study the influence mechanism of p H and ionic strength on competitive adsorption.The results of EDS and CA indicated that Fe3O4 was modified successfully with OTS on the surface.Silicon appeared and carbon content increased obviously on the surface of adsorbent.Contact angle of adsorbent increased from 0~o to 107~o after being modified by OTS.Fe3O4-OTS showed good separation for MO and MB in competitive system,which has potential to separate dyes in sewage.Separation factor（β~OB）changed from 18.724 to 0.017,when p H changed from 7 to 12,revealing that MO and MB could be separated almost thoroughly by Fe3O4-OTS.p H could change the surface charge of Fe3O4-OTS and structure of dyes,and thus change the interactions of competitive system indirectly.Even though hydrophobic interaction was enhanced,ionic strength reduced the difference of electrostatic interaction between dyes and Fe3O4-OTS.So it is unfavorable to separate dyes with opposite charges when ionic strength increases.These findings may provide theoretical guidances to separate two-component dye pollutants.

Mechanism transformation of cyclohexene-thiophene competitive adsorption in FAU zeolite

Competition of hydrocarbon compounds with sulfides in gasoline has caused a not very high selectivity of sulfides in adsorption desulfurization so far,resulting in a reduction of catalyst lifetime as well as more sulfur oxide emissions.Tostudy the whole competitive process changing with the increase of the loading,the dynamic competition adsorption mechanism of cyclohexene and thiophene in siliceous faujasite(FAU)zeolite was analyzed by the Monte Carlo simulation.The results showed that with the increase of the loading,thiophene and cyclohexene had different performances before and after the inflection point of 40 molecule/UC.The adsorbates were distributed ideally at optimal sites during the stage that occurred before the inflection point,which is called the“optimal-displacement adsorption”stage.When approaching the inflection point,the competition became apparent and the displacement appeared accordingly,some thiophene molecules at S sites(refers to the sites inside the supercages)were displaced by cyclohexene.After the inflection point,the concentration of adsorbates at W sites(refers to the 12-membered ring connecting the supercages)was significantly reduced,whereas the adsorbates at S sites got more concentrated.The stage some cyclohexene molecules displaced by thiophene and inserted into the center of the supercage can be named as the“insertion-displacement adsorption”stage,and both the adsorption behavior and the competitive relationship became localized when the adsorption amount became saturated.This shift in the competitive adsorption mechanism was due to the sharp increase of interaction energy between the adsorbates.Besides,the increase in temperature and ratio of Si/Al will allow the adsorbates,especially thiophene molecules to occupy more adsorption sites,and it is beneficial to improve the desulfurization selectivity.

Design Optimization of Permanent Magnet Eddy Current Coupler Based on an Intelligence Algorithm

The permanent magnet eddy current coupler(PMEC)solves the problem of flexible connection and speed regulation between the motor and the load and is widely used in electrical transmission systems.It provides torque to the load and generates heat and losses,reducing its energy transfer efficiency.This issue has become an obstacle for PMEC to develop toward a higher power.This paper aims to improve the overall performance of PMEC through multi-objective optimization methods.Firstly,a PMEC modeling method based on the Levenberg-Marquardt back propagation(LMBP)neural network is proposed,aiming at the characteristics of the complex input-output relationship and the strong nonlinearity of PMEC.Then,a novel competition mechanism-based multi-objective particle swarm optimization algorithm(NCMOPSO)is proposed to find the optimal structural parameters of PMEC.Chaotic search and mutation strategies are used to improve the original algorithm,which improves the shortcomings of multi-objective particle swarm optimization(MOPSO),which is too fast to converge into a global optimum,and balances the convergence and diversity of the algorithm.In order to verify the superiority and applicability of the proposed algorithm,it is compared with several popular multi-objective optimization algorithms.Applying them to the optimization model of PMEC,the results show that the proposed algorithm has better comprehensive performance.Finally,a finite element simulation model is established using the optimal structural parameters obtained by the proposed algorithm to verify the optimization results.Compared with the prototype,the optimized PMEC has reduced eddy current losses by 1.7812 kW,increased output torque by 658.5 N·m,and decreased costs by 13%,improving energy transfer efficiency.

Dual-resource integrated scheduling method of AGV and machine in intelligent manufacturing job shop

In view of the fact that traditional job shop scheduling only considers a single factor, which affects the effect of resource allocation, the dual-resource integrated scheduling problem between AGV and machine in intelligent manufacturing job shop environment was studied. The dual-resource integrated scheduling model of AGV and machine was established by comprehensively considering constraints of machines, workpieces and AGVs. The bidirectional single path fixed guidance system based on topological map was determined, and the AGV transportation task model was defined. The improved A* path optimization algorithm was used to determine the optimal path, and the path conflict elimination mechanism was described. The improved NSGA-Ⅱ algorithm was used to determine the machining workpiece sequence, and the competition mechanism was introduced to allocate AGV transportation tasks. The proposed model and method were verified by a workshop production example, the results showed that the dual resource integrated scheduling strategy of AGV and machine is effective.

Enabling dendrite-free charging for lithium batteries based on transport-reaction competition mechanism in CHAIN framework

Worldwide trends in mobile electrification will skyrocket demands for lithium-based battery production,driven by the popularity of electric vehicles.However,both lithium metal batteries and lithium ion batteries face severe safety issues due to dendrite nucleation and growth process.Li deposition is significantly influenced by interfacial factors and charging conditions.In this paper,an electrochemical model considering the internal and external factors is proposed based on Monte Carlo method.The influence of internal solid electrolyte interphase(SEI)porosity,thickness and the external conditions on dendrite growth process is systematically described.The simulation results support that the three factors investigated in this model could synergistically regulate the dendrite growth process.Three competition mechanisms are proposed to tailor lithium deposition for Li-based batteries and numerical solutions for variation pattern of dendrite growth with time are fitted.A three-step process describing kinetic process of lithium deposition is proposed.To achieve dendrite-free charging process,charging strategies and emerging materials design should be considered,including physicochemical materials engineering,artificial SEI,and design for dynamic safety boundary.This work could contribute to the foundation for insights of Li deposition mechanism,which is promising to provide guidelines for next-generation high-energy-density and safe batteries in CHAIN framework.

Strategies for Applying the Talented Personnel Competition Mechanism in the Commercial Age

With the increasingly fiercer talented personnel competition, the introduction of a talented personnel competition mechanism has become imperative in the commercial age. In this paper, the necessities of introducing a talented personnel competition mechanism are analyzed, and then the guiding ideology and principles of the talented personnel competition mechanism are proposed, and finally the application strategies of the talented personnel competition mechanism are discussed

Mechanism of Competition between Nutlin3 and p53 for Binding with Mdm2

The tumour suppressor p53 is a transcription factor that regulates multiple biological functions including metabolism, DNA repair, cell cycle arrest, apoptosis and senescence. About half of human cancers show a normal TP53 gene and aberrant overexpression of Mdm2. This fact promotes a promising cancer therapeutic strategy by inhibiting the interactions between p53 and Mdm2. Various inhibitors have been designed to achieve this novel approach for cancer therapy. However, the detailed competition mechanism between these inhibitors and the p53 molecule in their binding process to Mdm2 is still unclear. We investigate this competition mechanism between Nutlin3 and p53 using molecular dynamics simulations. It is found that Nutlin3 binds faster than the p53 molecule to Mdm2 to prevent p53 binding to Mdm2 when Nutlin3 and p53 have equal distance from Mdm2. Nutlin3 can also bind to the p53-Mdm2 complex to disturb and weaken the interactions between p53 and Mdm2. Consequently, p53 cannot bind to Mdm2 and its tumour suppression function is reactivated. These results provide the detailed competition mechanism between Nutlin3 and p53 in their binding to Mdm2. Because the binding site of most other inhibitors to Mdm2 is the same as Nutlin3, therefore this competition mechanism can extend to most inhibitors which target the p53-Mdm2 interaction.

D-band center coordination modulated enzyme-like activity in Fe-Cu dual-metal single-atom nanozymes

After explorations in a diversity of single-atom nanozymes(SAzymes),developing dual-centered SAzymes becomes a promising approach for superior catalytic performance.But confusing mechanisms including atomic coordination,spatial configuration,and metal–metal atom interaction hinder the development and design of SAzymes.Herein,a dual-centered Fe-Cu-N_(x)SAzyme exhibits excellent peroxidase(POD)-and catalase(CAT)-like activities with d-band center(ε_(d))coordination of Fe and Cu in multiple reaction stages,which plays a critical role in the adsorption of H_(2)O_(2)molecule and H_(2)O and O_(2)release.Therefore,the dband center coordination,which can be represented byε_(d)(Fe)–ε_(d)(Cu)shifts,leads to the competition between one-side and bilateral adsorption,which determines the favorable reaction path with lower energy barriers.Based on experimental statistics,simulated formation energies,and reaction barriers,3 configurations,Fe-Cu-N6-I,Fe-Cu-N_(8)-II,and Fe-Cu-N_(8)-III,are modeled and validated.Impressively,configuration-dependent catalytic selectivity and the competition between one-side and bilateral adsorption can be unveiled by d-band center coordination paradigm analysis.Theoretical simulations suggest that the unsymmetrical charge distribution over the three Fe-Cu configurations could tune the adsorption strength compared with the counterparts FeN_(4)and CuN_(4).The present work provides a potential route for optimizing enzyme-like catalysis by designing the dual-or even triple-metal SAzymes,which demonstrates the large space to modulate the metal atomic configuration and interaction.

Maritime Target Saliency Detection for UAV Based on the Stimulation Competition Selection Mechanism of Raptor Vision

A maritime target saliency detection method inspired by the stimulation competition and selection mechanism of raptor vision is presented for the airborne vision system of unmanned aerial vehicle(UAV)in an unknown maritime environment.The stimulation competition and selection mechanism in the visual pathway of raptor vision based on the phenomenon of raptor capturing prey in complex scenes are studied.Then,the mathematical model of the stimulation competition and selection mechanism of raptor vision is established and employed for the salient object detection.Popular image datasets and practical scene datasets are applied to verify the effectiveness of the presented method.Results show that the detection performance of the proposed method is better than that of other comparison methods.The proposed algorithm provides an idea for maritime target salient detection and cross-domain joint mission for UAV or other unmanned equipment.