Machine learning combined with density functional theory(DFT)enables rapid exploration of catalyst descriptors space such as adsorption energy,facilitating rapid and effective catalyst screening.However,there is still...Machine learning combined with density functional theory(DFT)enables rapid exploration of catalyst descriptors space such as adsorption energy,facilitating rapid and effective catalyst screening.However,there is still a lack of models for predicting adsorption energies on oxides,due to the complexity of elemental species and the ambiguous coordination environment.This work proposes an active learning workflow(LeNN)founded on local electronic transfer features(e)and the principle of coordinate rotation invariance.By accurately characterizing the electron transfer to adsorption site atoms and their surrounding geometric structures,LeNN mitigates abrupt feature changes due to different element types and clarifies coordination environments.As a result,it enables the prediction of^(*)H adsorption energy on binary oxide surfaces with a mean absolute error(MAE)below 0.18 eV.Moreover,we incorporate local coverage(θ_(l))and leverage neutral network ensemble to establish an active learning workflow,attaining a prediction MAE below 0.2 eV for 5419 multi-^(*)H adsorption structures.These findings validate the universality and capability of the proposed features in predicting^(*)H adsorption energy on binary oxide surfaces.展开更多
The preparation of xylo-oligosaccharides(XOSs)through hydrolysis of hemicelluloses was studied.The hemicelluloses were isolated from the press lye discharged in the production of viscose,which contained about 30%xylan...The preparation of xylo-oligosaccharides(XOSs)through hydrolysis of hemicelluloses was studied.The hemicelluloses were isolated from the press lye discharged in the production of viscose,which contained about 30%xylan.Then,a factorial experimental design was applied to compare the influences of several factors including the concentrations of sulphuric acid and hemicelluloses,the duration and temperature of the hydrolysis,on the conversion of xylan,and the selectivity for the product–XOSs.The results showed that the hydrolysis duration affects the yield of XOSs to the greatest extent.It is difficult to obtain a high yield of XOSs with sulphuric acid as the hydrolysis catalyst.展开更多
基金supported by the National Natural Science Foundation of China(No.52488201)the Natural Science Basic Research Program of Shaanxi(No.2024JC-YBMS-284)+1 种基金the Key Research and Development Program of Shaanxi(No.2024GHYBXM-02)the Fundamental Research Funds for the Central Universities.
文摘Machine learning combined with density functional theory(DFT)enables rapid exploration of catalyst descriptors space such as adsorption energy,facilitating rapid and effective catalyst screening.However,there is still a lack of models for predicting adsorption energies on oxides,due to the complexity of elemental species and the ambiguous coordination environment.This work proposes an active learning workflow(LeNN)founded on local electronic transfer features(e)and the principle of coordinate rotation invariance.By accurately characterizing the electron transfer to adsorption site atoms and their surrounding geometric structures,LeNN mitigates abrupt feature changes due to different element types and clarifies coordination environments.As a result,it enables the prediction of^(*)H adsorption energy on binary oxide surfaces with a mean absolute error(MAE)below 0.18 eV.Moreover,we incorporate local coverage(θ_(l))and leverage neutral network ensemble to establish an active learning workflow,attaining a prediction MAE below 0.2 eV for 5419 multi-^(*)H adsorption structures.These findings validate the universality and capability of the proposed features in predicting^(*)H adsorption energy on binary oxide surfaces.
基金finically supported by Science and Education Integration Program of Henan University of Technology
文摘The preparation of xylo-oligosaccharides(XOSs)through hydrolysis of hemicelluloses was studied.The hemicelluloses were isolated from the press lye discharged in the production of viscose,which contained about 30%xylan.Then,a factorial experimental design was applied to compare the influences of several factors including the concentrations of sulphuric acid and hemicelluloses,the duration and temperature of the hydrolysis,on the conversion of xylan,and the selectivity for the product–XOSs.The results showed that the hydrolysis duration affects the yield of XOSs to the greatest extent.It is difficult to obtain a high yield of XOSs with sulphuric acid as the hydrolysis catalyst.
