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Modified NiO catalysts with controllable vacancies and dopants are promising for alkene production from oxidative dehydrogenation (ODH) of light alkanes, and a molecular understanding of the modification on elementary reaction steps would facilitate the design of highly efficient catalysts and catalytic processes. In this study, density functional theory (DFT) calculations was used to map out the complete reaction pathways of propane ODH on the NiO (100) surfaces with different modifiers. The results demonstrated that the presence of vacancies (O and Ni) and dopants (Li and Al) alters the electrophilicity of surface oxygen species, which in turn affects the reactivity towards C−H bond activation and the overall catalytic activity and selectivity. The strongly electrophilic O favors a radical mechanism for the first C−H activation on O followed by the second C−H activation on O−O site, whereas weak electrophilic O favors concerted C−H bond breaking over Ni−O site. The C−H bond activation proceeds through a late transition state, characterized by the almost completion of the O−H bond formation. Consequently, the adsorption energy of H adatom on O rather than p‐band center or Bader charge of O has been identified to be an accurate descriptor to predict the activation barrier for C−H breaking (activity) as well as the difference between the activation barriers of propene and CH3CCH3 (selectivity) of ODH.

The trust region (TR) method is an effective algorithm for image reconstruction of electrical impedance tomography (EIT). Aiming at the drawback of the traditional TR method, an improved method named the nonmonotonic and self-adaptive trust region (NSTR) method is proposed in this paper, in which three kinds of modified techniques are shown that help in improving the computational precision and convergence speed of the algorithm. The comparisons with image reconstruction are carried out between the NSTR, Levenberd-Marquardt (LM) and TR methods. Simulation experiment results indicate that for both the LM and TR methods it is difficult to accurately reconstruct concave and multiple boundaries. However the NSTR method cannot only realize accurate reconstruction, but also provide faster convergence speed. A noise simulation test is carried out and results show that the NSTR method also has strong stability in image reconstruction for EIT. This new method presents a feasible and effective way to research on image reconstruction for EIT.

Magnetoacoustic Tomography with Magnetic Induction (MAT-MI) is a hybrid imaging modality proposed to reconstruct the electrical impedance property in biological tissue with high spatial resolution. The tissue in most parts of human body has inhomogeneous acoustic properties, which will significantly affect the propagations of ultrasound waves. And then it leads to potential distortion and blurring of the acoustic source and conductivity images in the reconstruction. The purpose of this paper is to reconstruct both the acoustic source and conductivity distribution in an acoustically heterogeneous medium. And a new algorithm is presented based on the generalized finite element method (GFEM) and inhomogeneous time reversal method. We established an acoustic inhomogeneous model, in which different regions of the model the acoustic signals spread with different speeds. The numerical simulation experiments showed feasibility of the new method. Then we applied the proposed algorithm to reconstruct the conductivity of a gel phantom with our MAT-MI system. The experimental results indicate that the acoustic inhomogeneity of tissues in terms of speed variation can be reconstructed in the process of MAT-MI imaging.

In this paper, aiming at the severely non-linear and ill-posed in electrical impedance tomography (EIT), trust region (TR) method is proposed. The calculation steps of TR method are deduced for solving EIT inverse problem. Simulations for EIT boundary image reconstruction are realized based on the TR method. The effects of different numbers of boundary elements and different conductivity multiples are investigated. The effect of noise is also researched. Simulation results indicate that， stably and precise results of the boundary reconstruction can be obtained by the TR method.