In the application of polymer gels to profile control and water shutoff,the gelation time will directly determine whether the gel can"go further"in the formation,but the most of the methods for delaying gel ...In the application of polymer gels to profile control and water shutoff,the gelation time will directly determine whether the gel can"go further"in the formation,but the most of the methods for delaying gel gelation time are complicated or have low responsiveness.There is an urgent need for an effective method for delaying gel gelation time with intelligent response.Inspired by the slow-release effect of drug capsules,this paper uses the self-assembly effect of gas-phase hydrophobic SiO_(2) in aqueous solution as a capsule to prepare an intelligent responsive self-assembled micro-nanocapsules.The capsule slowly releases the cross-linking agent under the stimulation of external conditions such as temperature and pH value,thus delaying gel gelation time.When the pH value is 2 and the concentration of gas-phase hydrophobic SiO_(2) particles is 10%,the gelation time of the capsule gel system at 30,60,90,and 120℃is12.5,13.2,15.2,and 21.1 times longer than that of the gel system without containing capsule,respectively.Compared with other methods,the yield stress of the gel without containing capsules was 78 Pa,and the yield stress after the addition of capsules was 322 Pa.The intelligent responsive self-assembled micronanocapsules prepared by gas-phase hydrophobic silica nanoparticles can not only delay the gel gelation time,but also increase the gel strength.The slow release of cross-linking agent from capsule provides an effective method for prolongating the gelation time of polymer gels.展开更多
Alkali-activated materials/geopolymer(AAMs),due to their low carbon emission content,have been the focus of recent studies on ecological concrete.In terms of performance,fly ash and slag are preferredmaterials for pre...Alkali-activated materials/geopolymer(AAMs),due to their low carbon emission content,have been the focus of recent studies on ecological concrete.In terms of performance,fly ash and slag are preferredmaterials for precursors for developing a one-part geopolymer.However,determining the optimum content of the input parameters to obtain adequate performance is quite challenging and scarcely reported.Therefore,in this study,machine learning methods such as artificial neural networks(ANN)and gene expression programming(GEP)models were developed usingMATLAB and GeneXprotools,respectively,for the prediction of compressive strength under variable input materials and content for fly ash and slag-based one-part geopolymer.The database for this study contains 171 points extracted from literature with input parameters:fly ash concentration,slag content,calcium hydroxide content,sodium oxide dose,water binder ratio,and curing temperature.The performance of the two models was evaluated under various statistical indices,namely correlation coefficient(R),mean absolute error(MAE),and rootmean square error(RMSE).In terms of the strength prediction efficacy of a one-part geopolymer,ANN outperformed GEP.Sensitivity and parametric analysis were also performed to identify the significant contributor to strength.According to a sensitivity analysis,the activator and slag contents had the most effects on the compressive strength at 28 days.The water binder ratio was shown to be directly connected to activator percentage,slag percentage,and calcium hydroxide percentage and inversely related to compressive strength at 28 days and curing temperature.展开更多
The plastic cement belongs to a sort of polymer material, the chemical composition is very complex, and the plastic cement work-piece is generally manufactured by die press forming. Aimed at being difficult to control...The plastic cement belongs to a sort of polymer material, the chemical composition is very complex, and the plastic cement work-piece is generally manufactured by die press forming. Aimed at being difficult to control in parameters of forming process, the paper explored the humanoid based intelligence control strategy. In the paper, it made the anatomy in control puzzle resulted in uncertainty such as chemical component of plastic cement etc., summarized up the characteristic of cybernetics in forming process, researched on the humanoid based intelligence control strategy, and constructed the control algorithm of forming process in plastic cement work-piece. Taking the process experiment of temperature and pressure control as an example, it validated the good dynamic and static control quality through simulation of control algorithm constructed in this paper. The experimental results show that the control algorithm explored in this paper is reasonably available.展开更多
Intelligent polymers or stimuli-responsive polymers may exhibit distinct transitions in physical-chemical properties, including conformation, polarity, phase structure and chemical composition in response to changes i...Intelligent polymers or stimuli-responsive polymers may exhibit distinct transitions in physical-chemical properties, including conformation, polarity, phase structure and chemical composition in response to changes in environmental stimuli. Due to their unique 'intelligent' characteristics, stimuli-sensitive polymers have found a wide variety of applications in biomedical and nanotechnological fields. This review focuses on the recent developments in biomedical application of intelligent polymer systems, such as intelligent hydrogel systems, intelligent drug delivery systems and intelligent molecular recognition systems. Also, the possible future directions for the application of these intelligent polymer systems in the biomedical field are presented.展开更多
Biomedical magnesium is an ideal material for hard tissue repair and replacement.However,its rapid degradation and infection after implantation significantly hindersclinical applications.To overcome these two critical...Biomedical magnesium is an ideal material for hard tissue repair and replacement.However,its rapid degradation and infection after implantation significantly hindersclinical applications.To overcome these two critical drawbacks,we describe an integrated strategybased on the changes in pH and Mg^(2+)triggered by magnesiumdegradation.This system can simultaneously offer anticorrosion and antibacterial activity.First,nanoengineered peptide-grafted hyperbranched polymers(NPGHPs)with excellent antibacterial activity were introduced to sodium alginate(SA)to construct a sensitive NPGHPs/SA hydrogel.The swelling degree,responsiveness,and antibacterial activity were then investigated,indicating that the system can perform dual stimulation of pH and Mg^(2+)with controllable antimicrobial properties.Furthermore,an intelligent platform was constructed by coating hydrogels on magnesium with polydopamine as the transition layer.The alkaline environment generated by the corrosion of magnesium reduces the swelling degree of the coatingso that the liquid is unfavorable for contacting the substrate,thus exhibiting superior corrosion resistance.Antibacterial testing shows that the material can effectively fight against bacteria,while hemolytic and cytotoxicity testing suggest that it is highly biocompatible.Thus,this work realizes the smart integration of anticorrosion and antibacterial properties of biomedical magnesium,thereby providing broader prospects for the use of magnesium.展开更多
An artificial intelligence system for interpretation of proton NMR spectra of polymers is reported in this paper. The system, including spectra data base, knowledge data base and reasoning engine, is based on the char...An artificial intelligence system for interpretation of proton NMR spectra of polymers is reported in this paper. The system, including spectra data base, knowledge data base and reasoning engine, is based on the characteristics of the proton NMR spectra of polymers and the spectra interpretation experiences of specialist. The system can partly simulate human thinking and interpret proton NMR spectra of polymers at different levels of sophistication. The program in the system was written in Turbo Prolog 2.0 and translated into machine language by computer compiler. It has been tested on an IBM PC/XT computer and a satisfactory result was given.展开更多
基金support and funding from the National Natural Science Foundation of China (No.52174047)Sinopec Project (No.P21063-3)。
文摘In the application of polymer gels to profile control and water shutoff,the gelation time will directly determine whether the gel can"go further"in the formation,but the most of the methods for delaying gel gelation time are complicated or have low responsiveness.There is an urgent need for an effective method for delaying gel gelation time with intelligent response.Inspired by the slow-release effect of drug capsules,this paper uses the self-assembly effect of gas-phase hydrophobic SiO_(2) in aqueous solution as a capsule to prepare an intelligent responsive self-assembled micro-nanocapsules.The capsule slowly releases the cross-linking agent under the stimulation of external conditions such as temperature and pH value,thus delaying gel gelation time.When the pH value is 2 and the concentration of gas-phase hydrophobic SiO_(2) particles is 10%,the gelation time of the capsule gel system at 30,60,90,and 120℃is12.5,13.2,15.2,and 21.1 times longer than that of the gel system without containing capsule,respectively.Compared with other methods,the yield stress of the gel without containing capsules was 78 Pa,and the yield stress after the addition of capsules was 322 Pa.The intelligent responsive self-assembled micronanocapsules prepared by gas-phase hydrophobic silica nanoparticles can not only delay the gel gelation time,but also increase the gel strength.The slow release of cross-linking agent from capsule provides an effective method for prolongating the gelation time of polymer gels.
基金funded by the Deanship of Graduate Studies and Scientific Research at Jouf University under grant No.(DGSSR-2023-02-02385).
文摘Alkali-activated materials/geopolymer(AAMs),due to their low carbon emission content,have been the focus of recent studies on ecological concrete.In terms of performance,fly ash and slag are preferredmaterials for precursors for developing a one-part geopolymer.However,determining the optimum content of the input parameters to obtain adequate performance is quite challenging and scarcely reported.Therefore,in this study,machine learning methods such as artificial neural networks(ANN)and gene expression programming(GEP)models were developed usingMATLAB and GeneXprotools,respectively,for the prediction of compressive strength under variable input materials and content for fly ash and slag-based one-part geopolymer.The database for this study contains 171 points extracted from literature with input parameters:fly ash concentration,slag content,calcium hydroxide content,sodium oxide dose,water binder ratio,and curing temperature.The performance of the two models was evaluated under various statistical indices,namely correlation coefficient(R),mean absolute error(MAE),and rootmean square error(RMSE).In terms of the strength prediction efficacy of a one-part geopolymer,ANN outperformed GEP.Sensitivity and parametric analysis were also performed to identify the significant contributor to strength.According to a sensitivity analysis,the activator and slag contents had the most effects on the compressive strength at 28 days.The water binder ratio was shown to be directly connected to activator percentage,slag percentage,and calcium hydroxide percentage and inversely related to compressive strength at 28 days and curing temperature.
文摘The plastic cement belongs to a sort of polymer material, the chemical composition is very complex, and the plastic cement work-piece is generally manufactured by die press forming. Aimed at being difficult to control in parameters of forming process, the paper explored the humanoid based intelligence control strategy. In the paper, it made the anatomy in control puzzle resulted in uncertainty such as chemical component of plastic cement etc., summarized up the characteristic of cybernetics in forming process, researched on the humanoid based intelligence control strategy, and constructed the control algorithm of forming process in plastic cement work-piece. Taking the process experiment of temperature and pressure control as an example, it validated the good dynamic and static control quality through simulation of control algorithm constructed in this paper. The experimental results show that the control algorithm explored in this paper is reasonably available.
基金Supported by the National Natural Science Foundation of China (Grant Nos.20604028, 50573078, and 50733003)National Fund for Distinguished Young Scholar (Grant No. 50425309)+1 种基金A3 Foresight Program of the National Natural Science Foundation of China (Grant No. 20621140369)Key International Science and Technology Cooperation Project of Ministry of Science and Technology of China (Grant No. 20071314)
文摘Intelligent polymers or stimuli-responsive polymers may exhibit distinct transitions in physical-chemical properties, including conformation, polarity, phase structure and chemical composition in response to changes in environmental stimuli. Due to their unique 'intelligent' characteristics, stimuli-sensitive polymers have found a wide variety of applications in biomedical and nanotechnological fields. This review focuses on the recent developments in biomedical application of intelligent polymer systems, such as intelligent hydrogel systems, intelligent drug delivery systems and intelligent molecular recognition systems. Also, the possible future directions for the application of these intelligent polymer systems in the biomedical field are presented.
基金This work was financially supported by the National Natural Science Foundation of China(no.51671179,51971014)the Excellent teacher ability improvement project(E1E40308).
文摘Biomedical magnesium is an ideal material for hard tissue repair and replacement.However,its rapid degradation and infection after implantation significantly hindersclinical applications.To overcome these two critical drawbacks,we describe an integrated strategybased on the changes in pH and Mg^(2+)triggered by magnesiumdegradation.This system can simultaneously offer anticorrosion and antibacterial activity.First,nanoengineered peptide-grafted hyperbranched polymers(NPGHPs)with excellent antibacterial activity were introduced to sodium alginate(SA)to construct a sensitive NPGHPs/SA hydrogel.The swelling degree,responsiveness,and antibacterial activity were then investigated,indicating that the system can perform dual stimulation of pH and Mg^(2+)with controllable antimicrobial properties.Furthermore,an intelligent platform was constructed by coating hydrogels on magnesium with polydopamine as the transition layer.The alkaline environment generated by the corrosion of magnesium reduces the swelling degree of the coatingso that the liquid is unfavorable for contacting the substrate,thus exhibiting superior corrosion resistance.Antibacterial testing shows that the material can effectively fight against bacteria,while hemolytic and cytotoxicity testing suggest that it is highly biocompatible.Thus,this work realizes the smart integration of anticorrosion and antibacterial properties of biomedical magnesium,thereby providing broader prospects for the use of magnesium.
文摘An artificial intelligence system for interpretation of proton NMR spectra of polymers is reported in this paper. The system, including spectra data base, knowledge data base and reasoning engine, is based on the characteristics of the proton NMR spectra of polymers and the spectra interpretation experiences of specialist. The system can partly simulate human thinking and interpret proton NMR spectra of polymers at different levels of sophistication. The program in the system was written in Turbo Prolog 2.0 and translated into machine language by computer compiler. It has been tested on an IBM PC/XT computer and a satisfactory result was given.
