Although the genetic algorithm (GA) has very powerful robustness and fitness, it needs a large size of population and a large number of iterations to reach the optimum result. Especially when GA is used in complex str...Although the genetic algorithm (GA) has very powerful robustness and fitness, it needs a large size of population and a large number of iterations to reach the optimum result. Especially when GA is used in complex structural optimization problems, if the structural reanalysis technique is not adopted, the more the number of finite element analysis (FEA) is, the more the consuming time is. In the conventional structural optimization the number of FEA can be reduced by the structural reanalysis technique based on the approximation techniques and sensitivity analysis. With these techniques, this paper provides a new approximation model-segment approximation model, adopted for the GA application. This segment approximation model can decrease the number of FEA and increase the convergence rate of GA. So it can apparently decrease the computation time of GA. Two examples demonstrate the availability of the new segment approximation model.展开更多
Chemical vapor deposited （CVD） graphene is nanopatterned using a spherical block copolymer etch mask. The use of spherical rather than cylindrical block copolymers allows homogeneous patterning of cm-scale areas wit...Chemical vapor deposited （CVD） graphene is nanopatterned using a spherical block copolymer etch mask. The use of spherical rather than cylindrical block copolymers allows homogeneous patterning of cm-scale areas without any substrate surface treatment. Raman spectroscopy was used to study the con- trolled generation of point defects in the graphene lattice with increasing etching time, confirming that alongside the nanomesh patterning, the nanopatterned CVD graphene presents a high defect density between the mesh holes. The nanopatterned samples showed sensitivities for NO2 of more than one order of magnitude higher than for non-patterned graphene. NO2 concentrations as low as 300 ppt were detected with an ultimate detection limit of tens of ppt. This is the smallest value reported so far for non-UV illuminated graphene chemiresistive NO2 gas sensors. The dramatic improvement in the gas sensitivity is believed to be due to the high adsorption site density, thanks to the combination of edge sites and point defect sites. This work opens the possibility of large area fabrication of nanopatterned graphene with extremely high densities of adsorption sites for sensing applications.展开更多
文摘Although the genetic algorithm (GA) has very powerful robustness and fitness, it needs a large size of population and a large number of iterations to reach the optimum result. Especially when GA is used in complex structural optimization problems, if the structural reanalysis technique is not adopted, the more the number of finite element analysis (FEA) is, the more the consuming time is. In the conventional structural optimization the number of FEA can be reduced by the structural reanalysis technique based on the approximation techniques and sensitivity analysis. With these techniques, this paper provides a new approximation model-segment approximation model, adopted for the GA application. This segment approximation model can decrease the number of FEA and increase the convergence rate of GA. So it can apparently decrease the computation time of GA. Two examples demonstrate the availability of the new segment approximation model.
文摘Chemical vapor deposited （CVD） graphene is nanopatterned using a spherical block copolymer etch mask. The use of spherical rather than cylindrical block copolymers allows homogeneous patterning of cm-scale areas without any substrate surface treatment. Raman spectroscopy was used to study the con- trolled generation of point defects in the graphene lattice with increasing etching time, confirming that alongside the nanomesh patterning, the nanopatterned CVD graphene presents a high defect density between the mesh holes. The nanopatterned samples showed sensitivities for NO2 of more than one order of magnitude higher than for non-patterned graphene. NO2 concentrations as low as 300 ppt were detected with an ultimate detection limit of tens of ppt. This is the smallest value reported so far for non-UV illuminated graphene chemiresistive NO2 gas sensors. The dramatic improvement in the gas sensitivity is believed to be due to the high adsorption site density, thanks to the combination of edge sites and point defect sites. This work opens the possibility of large area fabrication of nanopatterned graphene with extremely high densities of adsorption sites for sensing applications.
