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Theoretical Research On The Synthetic Routes Of The Third Subgroup Endohedral Metallofullerenes Dimerization Materials And Hydrogenated Materials

Posted on:2022-07-04Degree:MasterType:Thesis
Country:ChinaCandidate:L H WangFull Text:PDF
GTID:2481306317954079Subject:Master of Engineering
Abstract/Summary:PDF Full Text Request
Endohedral metallofullerenes(EMFs)have attracted much attention because of its unique structure and application prospects.The surface of EMFs can be modified through functional modification to control its physical and chemical properties.It has been applied to biomedicine,semiconductor materials and quantum computing and information storage et al..At present,the main method for synthesizing EMFs in experiments is the arc discharge method.Because the preparation and separation of EMFs is difficult,and it is hard to produce large amounts of EMFs in experiments.Due to the numerous reaction sites in the EMFs chemical reaction,the complexity of material synthesis increases,so theoretically it is very necessary to design and study the synthesis route of materials.The purpose of this thesis is to theoretically explore the activity and regioselectivity of representative EMFs dimerization and hydrogenation reactions,and predict its active sites through the proposed model,which can guide the experimental synthesis.The main research contents of this paper are as follows:1.Synthesis of dimerization material of EMFs.EMFs are prone to dimerize due to their radical character.EMFs are prone to dimerize due to their radical character.The dimerization shows high selectivity,that is,at each reaction site of many carbon cage isomers,only one or a few dimers were observed in the experiment.In order to explain the regioselectivity of dimerization,we conducted a systematic computational study of the dimerization of a series of experimentally synthesized paramagnetic EMFs,representatively including M@C82(M=Y,Sc,La),La@C72 with adjacent pentagons,and Y2@C80 in triplet state.By exploring possible monomer isomers and all possible dimerization sites for each monomer,we can explain the unique dimer structure of Y@Cs2 observed in the experiment.Therefore,we propose two energetic standards to determine whether a dimer can be formed under certain experimental conditions:the monomer is stable enough,and the dimerization process should have sufficient energy.In addition,we found that the commonly used reaction descriptors(spin density,the?-orbital axis vector,aromaticity,and bond orders)have almost no correlation with the dimerization regioselectivity of EMFs.Therefore,we propose a simple hydride model that can quantitatively predict the relative energy of the dimer,which will provide reliable and effective guidance for the dimerization of EMFs and derivatives.2.Research on the synthesis of empty fullerene C72 and Cs2 hydrogenated materials based on machine learning.We use machine learning to analyze and process a large amount of C72 dihydride data,and finally obtain a multivariable linear regression model with better predictive ability,and then use this model to predict the hydrogenation reaction of the Cs2 system.For the activity of the empty fullerene C72 hydrogenation reaction,the energy obtained by the multivariable linear regression model and the exohedral fullerene stabilization index(XSI)model have a good correlation with the relative energy of the DFT calculated,and both predict the pentagon-pentagon bond of the adj acent five-membered ring has the strongest activity,and the corresponding isomer has the lowest energy,thus verifying that our model is feasible.Although the model cannot accurately predict the most stable isomer of C82,the more stable isomers can still be predicted,and the XSI value has a good correlation with the predicted energy,i.e.Epredict,obtained by machine learning,which further proves that the machine learning model is feasible and effective.Comparing the Schlegel diagrams of the more stable and unstable structures in C72 and C82,we can draw a conclusion:for the more stable isomers,one of the addition sites of the dihydride must be located on the pentagon-hexagon-hexagon junction;for the unstable isomer,the addition sites of the dihydride are located on the hexagon-hexagon-hexagon junction.3.Research on the synthesis of EMFs with embedded atoms of La and Sc hydrogenated materials based on machine learning.We use non-IPR La@C2-C72 dihydride data as a machine learning sample,and finally obtain an optimal model,which predicts that the addition site of the most stable dihydride is not on the pentagon-pentagon bond of the adj acent five-membered ring,but on the bond of six-membered ring.This may be due to the interaction between the metal atoms in the metallofullerene and the carbon cage,resulting in a change in the reactivity of the atoms on the carbon cage.This model can effectively predict the relatively stable structures of La@C2v-C82,for example,the addition site of the most stable dihydride is consistent with the reaction site of the Bingle-Hirsch reaction product La@C2vC82[CH(COOC2H5)]2;and the addition site of the second stable dihydride is the same as that of the Diels-Alder reaction product La@C2v-Cs2Cp*.For Sc@C2v-C82,the machine learning model will no longer be applicable.Because of the difference in metal atom,the predictive ability of the model is greatly reduced.Therefore,the machine learning model of non-IPR La@C2-C72 will only be suitable to those fullerenes containing metallic La atom.In this thesis,by studying the activity and regioselectivity of the dimerization and hydrogenation reactions of EMFs,the chemical nature of the free radical addition will be revealed.This will provide a theoretical basis for the experimental synthesis and regulation of molecules,and deepen the exploration of the properties of this new type of material,thereby enriching the applications of EMFs in biomedicine,molecular devices and quantum information processing.
Keywords/Search Tags:Endohedral metallofullerene, Density functional theory, Reactivity, Regioselectivity, Machine learning
PDF Full Text Request
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