A novel method of controlling the shape memory properties of shape memory polyurethane （SMPU） by addition of micro-phase separation promoters including 1-octadecanol （ODO） and liquid paraffin （LP） is reported. T...A novel method of controlling the shape memory properties of shape memory polyurethane （SMPU） by addition of micro-phase separation promoters including 1-octadecanol （ODO） and liquid paraffin （LP） is reported. The results indicate that the strain recovery temperature and the strain modulus rate （Eg/Er） were increased significantly with addition of small amount of micro-phase separation promoters. Thus it can increase the shape memory fixity rate and other shape memory behaviors of SMPU.展开更多
Sub-micron sized phenolic epoxy resin waterborne particles were prepared by phase inversion emulsification. Micro-phase separation occurred during the curing process at high temperature. The as-prepared samples posses...Sub-micron sized phenolic epoxy resin waterborne particles were prepared by phase inversion emulsification. Micro-phase separation occurred during the curing process at high temperature. The as-prepared samples possessed one glass transition temperature （Tg） and two exothermal processes during DSC heating scannings. After being thermally treated above the exothermal peak temperature, they possessed two glass transition temperatures with the disappearance of exothermal peaks, whilst a core/shell structure was formed. This was likely related with the outward diffusion of reactive oligomers to the outer layer of particles.展开更多
In the process of geologic prospecting and development, it is important to forecast the distribution of gritstone, master the regulation of physical parameter in the reserves mass level. Especially, it is more importa...In the process of geologic prospecting and development, it is important to forecast the distribution of gritstone, master the regulation of physical parameter in the reserves mass level. Especially, it is more important to recognize to rock phase and sedimentary circumstance. In the land level, the study of sedimentary phase and micro-phase is important to prospect and develop. In this paper, an automatic approach based on ANN (Artificial Neural Networks) is proposed to recognize sedimentary phase, the corresponding system is designed after the character of well general curves is considered. Different from the approach extracting feature parameters, the proposed approach can directly process the input curves. The proposed method consists of two steps: The first step is called learning. In this step, the system creates automatically sedimentary micro-phase features by learning from the standard sedimentary micro-phase patterns such as standard electric current phase curves of the well and standard resistance rate curves of the well. The second step is called recognition. In this step, based the results of the learning step, the system classifies automatically by comparing the standard pattern curves of the well to unknown pattern curves of the well. The experiment has demonstrated that the proposed approach is more effective than those approaches used previously.展开更多
Self-organization in thin micro-films has shown potential for the production of microelements with specific structures and functions; however, little is known about its mechanism of formation. A 2-D molecular dynamics...Self-organization in thin micro-films has shown potential for the production of microelements with specific structures and functions; however, little is known about its mechanism of formation. A 2-D molecular dynamics (MD) simulation on this process is carried out in this paper for films between two parallel walls (substrates) under different initial conditions. The films consist of two immiscible components (A and B). The simulation results in alternative columns perpendicular to the walls, which are rich either in A or in B molecules, respectively, apparently owing to their different interactions with the walls. The characteristic breadths of the columns depend on the distance between the two walls. By providing microscopic details of the self-organization processes and the resulted structures, MD simulation proves itself as a unique way for analyzing the dynamics of thin films.展开更多
基金We are grateful to the Natural Science Foundation of Hunan Province(Project no.01JJY33011)for financial support for this work.We also thank Dr.Yuan Li Cai for his assistance.
文摘A novel method of controlling the shape memory properties of shape memory polyurethane （SMPU） by addition of micro-phase separation promoters including 1-octadecanol （ODO） and liquid paraffin （LP） is reported. The results indicate that the strain recovery temperature and the strain modulus rate （Eg/Er） were increased significantly with addition of small amount of micro-phase separation promoters. Thus it can increase the shape memory fixity rate and other shape memory behaviors of SMPU.
基金This work was financially supported by the National Natural Science Foundation of China(No.20104008).
文摘Sub-micron sized phenolic epoxy resin waterborne particles were prepared by phase inversion emulsification. Micro-phase separation occurred during the curing process at high temperature. The as-prepared samples possessed one glass transition temperature （Tg） and two exothermal processes during DSC heating scannings. After being thermally treated above the exothermal peak temperature, they possessed two glass transition temperatures with the disappearance of exothermal peaks, whilst a core/shell structure was formed. This was likely related with the outward diffusion of reactive oligomers to the outer layer of particles.
文摘In the process of geologic prospecting and development, it is important to forecast the distribution of gritstone, master the regulation of physical parameter in the reserves mass level. Especially, it is more important to recognize to rock phase and sedimentary circumstance. In the land level, the study of sedimentary phase and micro-phase is important to prospect and develop. In this paper, an automatic approach based on ANN (Artificial Neural Networks) is proposed to recognize sedimentary phase, the corresponding system is designed after the character of well general curves is considered. Different from the approach extracting feature parameters, the proposed approach can directly process the input curves. The proposed method consists of two steps: The first step is called learning. In this step, the system creates automatically sedimentary micro-phase features by learning from the standard sedimentary micro-phase patterns such as standard electric current phase curves of the well and standard resistance rate curves of the well. The second step is called recognition. In this step, based the results of the learning step, the system classifies automatically by comparing the standard pattern curves of the well to unknown pattern curves of the well. The experiment has demonstrated that the proposed approach is more effective than those approaches used previously.
文摘Self-organization in thin micro-films has shown potential for the production of microelements with specific structures and functions; however, little is known about its mechanism of formation. A 2-D molecular dynamics (MD) simulation on this process is carried out in this paper for films between two parallel walls (substrates) under different initial conditions. The films consist of two immiscible components (A and B). The simulation results in alternative columns perpendicular to the walls, which are rich either in A or in B molecules, respectively, apparently owing to their different interactions with the walls. The characteristic breadths of the columns depend on the distance between the two walls. By providing microscopic details of the self-organization processes and the resulted structures, MD simulation proves itself as a unique way for analyzing the dynamics of thin films.
基金support from the National Science Foundation of China (No.51971249)the Natural Science Foundation of Shandong Province,China (No.ZR2020KE012)the Science and Technology Planning Project of Longkou City,China (No.2021KJJH025).
