Accurate machine learning models based on small dataset of energetic materials through spatial matrix featurization methods

A large database is desired for machine learning(ML) technology to make accurate predictions of materials physicochemical properties based on their molecular structure.When a large database is not available,the development of proper featurization method based on physicochemical nature of target proprieties can improve the predictive power of ML models with a smaller database.In this work,we show that two new featurization methods,volume occupation spatial matrix and heat contribution spatial matrix,can improve the accuracy in predicting energetic materials' crystal density(ρ_(crystal)) and solid phase enthalpy of formation(H_(f,solid)) using a database containing 451 energetic molecules.Their mean absolute errors are reduced from 0.048 g/cm~3 and 24.67 kcal/mol to 0.035 g/cm~3 and 9.66 kcal/mol,respectively.By leave-one-out-cross-validation,the newly developed ML models can be used to determine the performance of most kinds of energetic materials except cubanes.Our ML models are applied to predict ρ_(crystal) and H_(f,solid) of CHON-based molecules of the 150 million sized PubChem database,and screened out 56 candidates with competitive detonation performance and reasonable chemical structures.With further improvement in future,spatial matrices have the potential of becoming multifunctional ML simulation tools that could provide even better predictions in wider fields of materials science.

The properties of an asymmetric Gaussian potential quantum well qubit in RbCl crystal

With the circumstance of the electron strongly coupled to LO-phonon and using the variational method of Pekar type（VMPT）,we study the eigenenergies and the eigenfunctions（EE） of the ground and the first excited states（GFES） in a RbCl crystal asymmetric Gaussian potential quantum well（AGPQW）.It concludes：（i） Twoenergy-level of the AGPQW may be seen as a qubit.（ii） When the electron located in the superposition state of the two-energy-level system,the time evolution and the coordinate changes of the electron probability density oscillated periodically in the AGPQW with every certain period T0=22.475 fs.（iii） Due to the confinement that is a two dimensional x-y plane symmetric structure in the AGPQW and the asymmetrical Gaussian potential（AGP） in the AGPQW growth direction,the electron probability density presents only one peak configuration located in the coordinate of z 〉 0,whereas it is zero in the range of z 〈 0.（iv） The oscillatory period is a decreasing function of the AGPQW height and the polaron radius,（v） The oscillating period is a decreasing one in the confinement potential R 〈 0.24 nm,whereas it is an increasing one in the confinement potential R 〉 0.24 nm and it takes a minimum value in R = 0.24 nm.