Binding energies of shallow hydrogenic impurity in a GaAs/GaAlAs quantum dot with spherical confinement, parabolic confinement and rectangular confinement are calculated as a function of dot radius in the influence of...Binding energies of shallow hydrogenic impurity in a GaAs/GaAlAs quantum dot with spherical confinement, parabolic confinement and rectangular confinement are calculated as a function of dot radius in the influence of electric field. The binding energy is calculated following a variational procedure within the effective mass approximation along with the spatial depended dielectric function. A finite confining potential well with depth is determined by the discontinuity of the band gap in the quantum dot and the cladding. It is found that the contribution of spatially dependent screening effects are small for a donor impurity and it is concluded that the rectangulax confinement is better than the parabolic and spherical confinements. These results are compared with the existing literature.展开更多
Consistency between density functional theory calculations and X-ray photoelectron spectroscopy measurements confirms our predications on the undercoordination-induced local bond relaxation and core level shift of alk...Consistency between density functional theory calculations and X-ray photoelectron spectroscopy measurements confirms our predications on the undercoordination-induced local bond relaxation and core level shift of alkali metal,which determine the surface,size and thermal properties of materials.Zone-resolved photoelectron spectroscopyanalysis method and bond order-length-strength theory can be utilized to quantify the physical parameters regarding bonding identities and electronic property of metal surfaces,which allows for the study of the core-electron binding-energy shifts in alkali metals.By employing these methods and first principle calculation in this work,we can obtain the information of bond and atomic cohesive energy of under-coordinated atoms at the alkali metal surface.In addition,the effect of size and temperature towards the binding-energy in the surface region can be seen from the view point of Hamiltonian perturbation by atomic relaxation with atomic bonding.展开更多
Most pharmaceutical formulation developments are complex and ideal formulations are generally obtained after extensive experimentation.Machine learning is increasingly advancing many aspects in modern society and has ...Most pharmaceutical formulation developments are complex and ideal formulations are generally obtained after extensive experimentation.Machine learning is increasingly advancing many aspects in modern society and has achieved significant success in multiple subjects.Current research demonstrated that machine learning can be adopted to build up high-accurate predictive models in drugs/cyclodextrins(CDs)systems.Molecular descriptors of compounds and experimental conditions were employed as inputs,while complexation free energy as outputs.Results showed that the light gradient boosting machine provided significantly improved predictive performance over random forest and deep learning.The mean absolute error was 1.38 kJ/mol and squared correlation coefficient was0.86.The evaluation of relative importance of molecular descriptors further demonstrated the key factors affecting molecular interactions in drugs/CD systems.In the specific ketoprofen-CD systems,machine learning model showed better predictive performance than molecular modeling calculation,while molecular simulation could provide structural,dynamic and energetic information.The integration of machine learning and molecular simulation could produce synergistic effect for interpreting and predicting pharmaceutical formulations.In conclusion,the developed predictive models were able to quickly and accurately predict the solubilizing capacity of CD systems.Current research has taken an important step toward the application of machine learning in pharmaceutical formulation design.展开更多
Acetohydroxyacid synthase(AHAS) is the target enzyme of several classes of herbicides,such as sulfonylureas and imidazolinones.Now many mutant AHASs with herbicide resistance have emerged along with extensive use of h...Acetohydroxyacid synthase(AHAS) is the target enzyme of several classes of herbicides,such as sulfonylureas and imidazolinones.Now many mutant AHASs with herbicide resistance have emerged along with extensive use of herbicides,therefore it is imperative to understand the detailed interaction mechanism and resistance mechanism so as to develop new potent inhibitors for wild-type or resistant AHAS.With the aid of available crystal structures of the Arabidopsis thaliana(At) AHAS-inhibitor complex,molecular dynamics(MD) simulations were used to investigate the interaction and resistance mechanism directly and dynamically at the atomic level.Nanosecond-level MD simulations were performed on six systems consisting of wild-type or W574L mutant AtAHAS in the complex with three sulfonylurea inhibitors,separately,and binding free energy was calculated for each system using the MM-GBSA method.Comprehensive analyses from structural and energetic aspects confirmed the importance of residue W574,and also indicated that W574L mutation might alert the structural charactersistic of the substrate access channel and decrease the binding affinity of inhibitors,which cooperatively weaken the effective channel-blocked effect and finally result in weaker inhibitory effect of inhibitor and corresponding herbicide resistance of W574L mutant.To our knowledge,it is the first report about MD simulations study on the AHAS-related system,which will pave the way to study the interactions between herbicides and wild-type or mutant AHAS dynamically,and decipher the resistance mechanism at the atomic level for better designing new potent anti-resistance herbicides.展开更多
文摘Binding energies of shallow hydrogenic impurity in a GaAs/GaAlAs quantum dot with spherical confinement, parabolic confinement and rectangular confinement are calculated as a function of dot radius in the influence of electric field. The binding energy is calculated following a variational procedure within the effective mass approximation along with the spatial depended dielectric function. A finite confining potential well with depth is determined by the discontinuity of the band gap in the quantum dot and the cladding. It is found that the contribution of spatially dependent screening effects are small for a donor impurity and it is concluded that the rectangulax confinement is better than the parabolic and spherical confinements. These results are compared with the existing literature.
基金supported by the National Natural Science Foundation of China (No.11947205 and No.61504079)the China Postdoctoral Science Foundation (No.2019M663877XB)+2 种基金the Startup Fund for Youngman Research at Shanghai Jiao Tong University (No.19X100040004)The fund from the Chongqing Special Postdoctoral Science Foundation(No.XmT2019021)supported by the center for HPC,Shanghai Jiao Tong University
文摘Consistency between density functional theory calculations and X-ray photoelectron spectroscopy measurements confirms our predications on the undercoordination-induced local bond relaxation and core level shift of alkali metal,which determine the surface,size and thermal properties of materials.Zone-resolved photoelectron spectroscopyanalysis method and bond order-length-strength theory can be utilized to quantify the physical parameters regarding bonding identities and electronic property of metal surfaces,which allows for the study of the core-electron binding-energy shifts in alkali metals.By employing these methods and first principle calculation in this work,we can obtain the information of bond and atomic cohesive energy of under-coordinated atoms at the alkali metal surface.In addition,the effect of size and temperature towards the binding-energy in the surface region can be seen from the view point of Hamiltonian perturbation by atomic relaxation with atomic bonding.
基金supported by the University of Macao Research Grants(MYRG2016-00038ICMS-QRCM and MYRG2016-00040-ICMS-QRCM,Macao,China).
文摘Most pharmaceutical formulation developments are complex and ideal formulations are generally obtained after extensive experimentation.Machine learning is increasingly advancing many aspects in modern society and has achieved significant success in multiple subjects.Current research demonstrated that machine learning can be adopted to build up high-accurate predictive models in drugs/cyclodextrins(CDs)systems.Molecular descriptors of compounds and experimental conditions were employed as inputs,while complexation free energy as outputs.Results showed that the light gradient boosting machine provided significantly improved predictive performance over random forest and deep learning.The mean absolute error was 1.38 kJ/mol and squared correlation coefficient was0.86.The evaluation of relative importance of molecular descriptors further demonstrated the key factors affecting molecular interactions in drugs/CD systems.In the specific ketoprofen-CD systems,machine learning model showed better predictive performance than molecular modeling calculation,while molecular simulation could provide structural,dynamic and energetic information.The integration of machine learning and molecular simulation could produce synergistic effect for interpreting and predicting pharmaceutical formulations.In conclusion,the developed predictive models were able to quickly and accurately predict the solubilizing capacity of CD systems.Current research has taken an important step toward the application of machine learning in pharmaceutical formulation design.
基金supported by the National Natural Science Foundation of China (Grant Nos.20432010, 20421202, and 90713011)the National Key Project for Basic Research (Grant Nos.2008DFA30770 and 2010CB126102)Key Project of Ministry of Education,China (Grant No.104189) and Institute of Scientific Computing (ISC) of Nankai University
文摘Acetohydroxyacid synthase(AHAS) is the target enzyme of several classes of herbicides,such as sulfonylureas and imidazolinones.Now many mutant AHASs with herbicide resistance have emerged along with extensive use of herbicides,therefore it is imperative to understand the detailed interaction mechanism and resistance mechanism so as to develop new potent inhibitors for wild-type or resistant AHAS.With the aid of available crystal structures of the Arabidopsis thaliana(At) AHAS-inhibitor complex,molecular dynamics(MD) simulations were used to investigate the interaction and resistance mechanism directly and dynamically at the atomic level.Nanosecond-level MD simulations were performed on six systems consisting of wild-type or W574L mutant AtAHAS in the complex with three sulfonylurea inhibitors,separately,and binding free energy was calculated for each system using the MM-GBSA method.Comprehensive analyses from structural and energetic aspects confirmed the importance of residue W574,and also indicated that W574L mutation might alert the structural charactersistic of the substrate access channel and decrease the binding affinity of inhibitors,which cooperatively weaken the effective channel-blocked effect and finally result in weaker inhibitory effect of inhibitor and corresponding herbicide resistance of W574L mutant.To our knowledge,it is the first report about MD simulations study on the AHAS-related system,which will pave the way to study the interactions between herbicides and wild-type or mutant AHAS dynamically,and decipher the resistance mechanism at the atomic level for better designing new potent anti-resistance herbicides.
