Establishing the structure-property relationship in amorphous materials has been a long-term grand challenge due to the lack of a unified description of the degree of disorder.In this work,we develop SPRamNet,a neural...Establishing the structure-property relationship in amorphous materials has been a long-term grand challenge due to the lack of a unified description of the degree of disorder.In this work,we develop SPRamNet,a neural network based machine-learning pipeline that effectively predicts structure-property relationship of amorphous material via global descriptors.Applying SPRamNet on the recently discovered amorphous monolayer carbon,we successfully predict the thermal and electronic properties.More importantly,we reveal that a short range of pair correlation function can readily encode sufficiently rich information of the structure of amorphous material.Utilizing powerful machine learning architectures,the encoded information can be decoded to reconstruct macroscopic properties involving many-body and long-range interactions.Establishing this hidden relationship offers a unified description of the degree of disorder and eliminates the heavy burden of measuring atomic structure,opening a new avenue in studying amorphous materials.展开更多
A kind of amphiphilic functional monomer was selected to modify polyacrylamide （PAM） or partially hydrolyzed polyacrylamide （HPAM）. The relative properties of the modified polyacrylamide （HM-PAM） and modified pa...A kind of amphiphilic functional monomer was selected to modify polyacrylamide （PAM） or partially hydrolyzed polyacrylamide （HPAM）. The relative properties of the modified polyacrylamide （HM-PAM） and modified partially hydrolyzed polyacrylamide （HM-HPAM） such as radius of gyration （Rg）, hydrodynamic radius （RH）, and radial distribution functions （RDFs） have been studied to find the intrinsic relation between the microstructure of the polymer chain and the intrinsic viscosities with changing the amotmt of modified monomers from 1% to 4%. The simulation results show that, compared to HPAM, HM-HPAM has a better performance in increasing viscosity when the percentage of modified monomers is 2% and has a stronger salt tolerance when the modified monomers is 4%. Furthermore, a complex hydrogen bonding network was revealed with the analysis of radial distribution functions （RDFs） and the pair correlation function was used to investigate the diffusivity of Na^＋ and carbon atoms in the COO^- group.展开更多
A new model for self-diffusion coefficients was proposed based oil both the concepts of molecular free volume and activation energy. The unknown parameters of this model were clearly defined and compared with the Chap...A new model for self-diffusion coefficients was proposed based oil both the concepts of molecular free volume and activation energy. The unknown parameters of this model were clearly defined and compared with the Chapman-Enskog model. At the same time a new method for calculating activation energy was devised and applied to the new model. In addition, the free volume was defined by implementing the generic van der Waals equation of state, the radial distribution function of which was obtained by using the Morsali- Goharshadi empirical formula. Under the same conditions, the new model was better than the original free volume model.展开更多
基金supported by the National Key R&D Program of China under Grant No.2021YFA1400500the Strategic Priority Research Program of the Chinese Academy of Sciences under Grant No.XDB33000000+1 种基金the National Natural Science Foundation of China under Grant No.12334003the Beijing Municipal Natural Science Foundation under Grant Nos.JQ22001 and QY23014。
文摘Establishing the structure-property relationship in amorphous materials has been a long-term grand challenge due to the lack of a unified description of the degree of disorder.In this work,we develop SPRamNet,a neural network based machine-learning pipeline that effectively predicts structure-property relationship of amorphous material via global descriptors.Applying SPRamNet on the recently discovered amorphous monolayer carbon,we successfully predict the thermal and electronic properties.More importantly,we reveal that a short range of pair correlation function can readily encode sufficiently rich information of the structure of amorphous material.Utilizing powerful machine learning architectures,the encoded information can be decoded to reconstruct macroscopic properties involving many-body and long-range interactions.Establishing this hidden relationship offers a unified description of the degree of disorder and eliminates the heavy burden of measuring atomic structure,opening a new avenue in studying amorphous materials.
基金financially supported by the National Natural Science Foundation of China(No.20904035)
文摘A kind of amphiphilic functional monomer was selected to modify polyacrylamide （PAM） or partially hydrolyzed polyacrylamide （HPAM）. The relative properties of the modified polyacrylamide （HM-PAM） and modified partially hydrolyzed polyacrylamide （HM-HPAM） such as radius of gyration （Rg）, hydrodynamic radius （RH）, and radial distribution functions （RDFs） have been studied to find the intrinsic relation between the microstructure of the polymer chain and the intrinsic viscosities with changing the amotmt of modified monomers from 1% to 4%. The simulation results show that, compared to HPAM, HM-HPAM has a better performance in increasing viscosity when the percentage of modified monomers is 2% and has a stronger salt tolerance when the modified monomers is 4%. Furthermore, a complex hydrogen bonding network was revealed with the analysis of radial distribution functions （RDFs） and the pair correlation function was used to investigate the diffusivity of Na^＋ and carbon atoms in the COO^- group.
文摘A new model for self-diffusion coefficients was proposed based oil both the concepts of molecular free volume and activation energy. The unknown parameters of this model were clearly defined and compared with the Chapman-Enskog model. At the same time a new method for calculating activation energy was devised and applied to the new model. In addition, the free volume was defined by implementing the generic van der Waals equation of state, the radial distribution function of which was obtained by using the Morsali- Goharshadi empirical formula. Under the same conditions, the new model was better than the original free volume model.
