With the rapid development of semiconductors,the number of materials needed to be polished sharply increases.The material properties vary significantly,posing challenges to chemical mechanical polishing(CMP).According...With the rapid development of semiconductors,the number of materials needed to be polished sharply increases.The material properties vary significantly,posing challenges to chemical mechanical polishing(CMP).Accordingly,the study aimed to classify the material removal mechanism.Based on the CMP and atomic force microscopy results,the six representative metals can be preliminarily classified into two groups,presumably due to different material removal modes.From the tribology perspective,the first group of Cu,Co,and Ni may mainly rely on the mechanical plowing effect.After adding H_(2)O_(2),corrosion can be first enhanced and then suppressed,affecting the surface mechanical strength.Consequently,the material removal rate(MRR)and the surface roughness increase and decrease.By comparison,the second group of Ta,Ru,and Ti may primarily depend on the chemical bonding effect.Adding H_(2)O_(2)can promote oxidation,increasing interfacial chemical bonds.Therefore,the MRR increases,and the surface roughness decreases and levels off.In addition,CMP can be regulated by tuning the synergistic effect of oxidation,complexation,and dissolution for mechanical plowing,while tuning the synergistic effect of oxidation and ionic strength for chemical bonding.The findings provide mechanistic insight into the material removal mechanism in CMP.展开更多
The mechanical,tribological and corrosion protection offered to Mg-9Li-7Al-1Sn and Mg-9Li-5Al-3Sn-1Zn alloys by the epoxy coating containing polyaniline/graphene(PANI/Gr)pigments is undertaken in the current work.PANI...The mechanical,tribological and corrosion protection offered to Mg-9Li-7Al-1Sn and Mg-9Li-5Al-3Sn-1Zn alloys by the epoxy coating containing polyaniline/graphene(PANI/Gr)pigments is undertaken in the current work.PANI/Gr containing coatings were observed to be strongly adherent with a higher scratch hardness(Hs)and plowing hardness(Hp),i.e.Hsof 0.43 GPa,and Hpof 0.61 GPa,respectively when compared to that of neat epoxy coating(Hsof 0.17 GPa,and Hpof 0.40 GPa,respectively).Due to their higher Hsand Hpvalues,PANI/Gr based coatings displayed an enhanced wear resistance(Wear volume,Wv=4.53×10^-3 m^3)than that of neat epoxy coating(Wv=5.15×10^-3 m^3).The corrosion protection efficiency in corrosive environment of 3.5 wt%NaCl solution was obtained to be>99% for PANI/Gr containing coatings when compared to that of neat epoxy coating.The charge-transfer resistance(R(ct))of the PANI/Gr containing coatings were estimated to be>10^6 cm^2,which indicates their highly protective nature when compared to that of neat epoxy coating(R(ct)10^5 Ω cm^2).Hence,PANI/Gr containing coatings can be potentially used for wear resistance and corrosion protection applications in marine environments.展开更多
This paper deals with implementation of intelligent simulation configurations for prediction of tractor wheel slip in tillage operations.The effects of numeral variables of forward speed(2,4,and 6 km/h)and plowing dep...This paper deals with implementation of intelligent simulation configurations for prediction of tractor wheel slip in tillage operations.The effects of numeral variables of forward speed(2,4,and 6 km/h)and plowing depth(10,20,and 30 cm),and nominal variable of tractor driving mode(two-wheel drive(2WD)and four-wheel drive(4WD))on tractor rear wheel slip were intelligently simulated utilizing data mining methodologies of artificial neural network(ANN)and adaptive neuro-fuzzy inference system(ANFIS).Neuro-fuzzy potential of the ANFIS simulation framework against neural ability of the ANN simulation framework was apprised.Results confirmed higher efficiency of the best configuration of the ANFIS simulation framework with satisfactory statistical performance criteria of coefficient of determination(0.981),root mean square error(1.124%),mean absolute percentage error(1.515%),and mean of absolute values of prediction residual errors(1.135%)than that of the ANN simulation framework.Physical perception obtained from the ANFIS simulation results demonstrated that the wheel slip increased nonlinearly with increment of forward speed and plowing depth,while it decreased as tractor driving mode changed from the 2WD to 4WD.Therefore,the best configuration of the ANFIS based intelligent simulation framework implemented in this study can be used for further relevant studies of tractor rear wheel slip as a reference.展开更多
基金support by the National Natural Science Foundation of China(51975488 and 51991373)National Key R&D Program of China(2020YFA0711001)Fundamental Research Funds for the Central Universities(2682021CG011).
文摘With the rapid development of semiconductors,the number of materials needed to be polished sharply increases.The material properties vary significantly,posing challenges to chemical mechanical polishing(CMP).Accordingly,the study aimed to classify the material removal mechanism.Based on the CMP and atomic force microscopy results,the six representative metals can be preliminarily classified into two groups,presumably due to different material removal modes.From the tribology perspective,the first group of Cu,Co,and Ni may mainly rely on the mechanical plowing effect.After adding H_(2)O_(2),corrosion can be first enhanced and then suppressed,affecting the surface mechanical strength.Consequently,the material removal rate(MRR)and the surface roughness increase and decrease.By comparison,the second group of Ta,Ru,and Ti may primarily depend on the chemical bonding effect.Adding H_(2)O_(2)can promote oxidation,increasing interfacial chemical bonds.Therefore,the MRR increases,and the surface roughness decreases and levels off.In addition,CMP can be regulated by tuning the synergistic effect of oxidation,complexation,and dissolution for mechanical plowing,while tuning the synergistic effect of oxidation and ionic strength for chemical bonding.The findings provide mechanistic insight into the material removal mechanism in CMP.
基金funding from Space Technology Cell (IIT Kanpur, and Indian Space Research Organisation)
文摘The mechanical,tribological and corrosion protection offered to Mg-9Li-7Al-1Sn and Mg-9Li-5Al-3Sn-1Zn alloys by the epoxy coating containing polyaniline/graphene(PANI/Gr)pigments is undertaken in the current work.PANI/Gr containing coatings were observed to be strongly adherent with a higher scratch hardness(Hs)and plowing hardness(Hp),i.e.Hsof 0.43 GPa,and Hpof 0.61 GPa,respectively when compared to that of neat epoxy coating(Hsof 0.17 GPa,and Hpof 0.40 GPa,respectively).Due to their higher Hsand Hpvalues,PANI/Gr based coatings displayed an enhanced wear resistance(Wear volume,Wv=4.53×10^-3 m^3)than that of neat epoxy coating(Wv=5.15×10^-3 m^3).The corrosion protection efficiency in corrosive environment of 3.5 wt%NaCl solution was obtained to be>99% for PANI/Gr containing coatings when compared to that of neat epoxy coating.The charge-transfer resistance(R(ct))of the PANI/Gr containing coatings were estimated to be>10^6 cm^2,which indicates their highly protective nature when compared to that of neat epoxy coating(R(ct)10^5 Ω cm^2).Hence,PANI/Gr containing coatings can be potentially used for wear resistance and corrosion protection applications in marine environments.
文摘This paper deals with implementation of intelligent simulation configurations for prediction of tractor wheel slip in tillage operations.The effects of numeral variables of forward speed(2,4,and 6 km/h)and plowing depth(10,20,and 30 cm),and nominal variable of tractor driving mode(two-wheel drive(2WD)and four-wheel drive(4WD))on tractor rear wheel slip were intelligently simulated utilizing data mining methodologies of artificial neural network(ANN)and adaptive neuro-fuzzy inference system(ANFIS).Neuro-fuzzy potential of the ANFIS simulation framework against neural ability of the ANN simulation framework was apprised.Results confirmed higher efficiency of the best configuration of the ANFIS simulation framework with satisfactory statistical performance criteria of coefficient of determination(0.981),root mean square error(1.124%),mean absolute percentage error(1.515%),and mean of absolute values of prediction residual errors(1.135%)than that of the ANN simulation framework.Physical perception obtained from the ANFIS simulation results demonstrated that the wheel slip increased nonlinearly with increment of forward speed and plowing depth,while it decreased as tractor driving mode changed from the 2WD to 4WD.Therefore,the best configuration of the ANFIS based intelligent simulation framework implemented in this study can be used for further relevant studies of tractor rear wheel slip as a reference.
