Autoxidation of cycloalkanes(C5–C8) with molecular oxygen under catalyst-free and solvent-free conditions was conducted systematically for the first time, focusing on the autoxidation temperature and product distribu...Autoxidation of cycloalkanes(C5–C8) with molecular oxygen under catalyst-free and solvent-free conditions was conducted systematically for the first time, focusing on the autoxidation temperature and product distribution. The autoxidation of cyclopentane, cyclohexane, cycloheptane and cyclooctane occurs at 120 ℃,130 ℃, 120 ℃, and 105 ℃ respectively, with obvious oxidized products formation. At 140 ℃, 145 ℃, 130 ℃ and 125 ℃, acceptable yields of the oxidized products could be obtained for them, and the oxidized product distributions were investigated in detail. The autoxidation of cycloalkanes follows the pseudo-first-order kinetic model and the apparent activation energies(E_a) for the autoxidation of cyclopentane and cyclohexane are 159.76 kJ·mol^(-1) and 86.75 kJ·mol^(-1) respectively. This study can act as an important reference in screen of suitable reaction temperature and comparison of the performance of various catalysts in the catalytic oxidation of cycloalkanes in the attempt to enhance the oxidized product selectivity.展开更多
In this work,a new method to solve the Reynolds equation including mass-conserving cavitation by using the physics informed neural networks(PINNs)is proposed.The complementarity relationship between the pressure and t...In this work,a new method to solve the Reynolds equation including mass-conserving cavitation by using the physics informed neural networks(PINNs)is proposed.The complementarity relationship between the pressure and the void fraction is used.There are several difficulties in problem solving,and the solutions are provided.Firstly,the difficulty for considering the pressure inequality constraint by PINNs is solved by transferring it into one equality constraint without introducing error.While the void fraction inequality constraint is considered by using the hard constraint with the max-min function.Secondly,to avoid the fluctuation of the boundary value problems,the hard constraint method is also utilized to apply the boundary pressure values and the corresponding functions are provided.Lastly,for avoiding the trivial solution the limitation for the mean value of the void fraction is applied.The results are validated against existing data,and both the incompressible and compressible lubricant are considered.Good agreement can be found for both the domain and domain boundaries.展开更多
基金Supported by the National Natural Science Foundation of China(Grant No.21476270,21306176,21776259,21276006)Scientific Research Launching Foundation of Zhejiang University of Technology(Grant No.G2817101103)
文摘Autoxidation of cycloalkanes(C5–C8) with molecular oxygen under catalyst-free and solvent-free conditions was conducted systematically for the first time, focusing on the autoxidation temperature and product distribution. The autoxidation of cyclopentane, cyclohexane, cycloheptane and cyclooctane occurs at 120 ℃,130 ℃, 120 ℃, and 105 ℃ respectively, with obvious oxidized products formation. At 140 ℃, 145 ℃, 130 ℃ and 125 ℃, acceptable yields of the oxidized products could be obtained for them, and the oxidized product distributions were investigated in detail. The autoxidation of cycloalkanes follows the pseudo-first-order kinetic model and the apparent activation energies(E_a) for the autoxidation of cyclopentane and cyclohexane are 159.76 kJ·mol^(-1) and 86.75 kJ·mol^(-1) respectively. This study can act as an important reference in screen of suitable reaction temperature and comparison of the performance of various catalysts in the catalytic oxidation of cycloalkanes in the attempt to enhance the oxidized product selectivity.
基金the funding from Anhui University of Science and Technology(No.2022yjrc15)the Key Project of National Natural Science Foundation of China(Nos.U21A20125 and U21A20122)+1 种基金the Key Research and Development Projects of Anhui Province(No.2022a05020043)the National Natural Science Foundation of China(Nos.51805410 and 51804007).
文摘In this work,a new method to solve the Reynolds equation including mass-conserving cavitation by using the physics informed neural networks(PINNs)is proposed.The complementarity relationship between the pressure and the void fraction is used.There are several difficulties in problem solving,and the solutions are provided.Firstly,the difficulty for considering the pressure inequality constraint by PINNs is solved by transferring it into one equality constraint without introducing error.While the void fraction inequality constraint is considered by using the hard constraint with the max-min function.Secondly,to avoid the fluctuation of the boundary value problems,the hard constraint method is also utilized to apply the boundary pressure values and the corresponding functions are provided.Lastly,for avoiding the trivial solution the limitation for the mean value of the void fraction is applied.The results are validated against existing data,and both the incompressible and compressible lubricant are considered.Good agreement can be found for both the domain and domain boundaries.