The surface behaviour and catalytic properties of Nd2-XSrXCoO4±Λ mixed oxides

The mixed oxides, Nd2-XSrXCoO4±λ (0.4 ≤ x ≤ 1.2), (λ = non-stochiometric oxygen) with the K2NiF4 structure were prepared by the polyglycol gel method and used as catalysts for NO reduction. The samples were investigated by IR, TPD, TPR, and XRD methods and iodometry and the effects of the coefficient x on the structure and catalytic activity of the samples were studied. The results show that the Nd2-XSrXCoO4±λ mixed oxides have the K2NiF4 structure; other phases are found when x 1.2. The amount of Co3+ and the lattice oxygen in Nd2-XSrXCoO4±λ increase with increasing x. The catalytic activity of Nd2-XSrXCoO4±λ for NO reduction is closely correlated with the concentration of oxygen vacancies and the amount of Co3+.KEY WORDS: A2BO4, Co-containing mixed oxide, NO reduction, Rare-earthBull. Chem. Soc. Ethiop. 2006, 20(2), 201-206

A direct unified wave-particle method for simulating non-equilibrium flows

In this work, the Navier-Stokes (NS) solver is combined with the Direct simulation Monte Carlo (DSMC) solver in a direct way, under the wave-particle formulation [J. Comput. Phys. 401, 108977 (2020)]. Different from the classical domain decomposition method with buffer zone for overlap, in the proposed direct unified wave-particle (DUWP) method, the NS solver is coupled with DSMC solver on the level of algorithm. Automatically, in the rarefied flow regime, the DSMC solver leads the simulation, while the NS solver leads the continuum flow simulation. Thus advantages of accuracy and efficiency are both taken. At internal flow regimes, like the transition flow regime, the method is accurate as well because a kind of mesoscopic modeling is proposed in this work, which gives the DUWP method the multi-scale property. Specifically, as to the collision process, at $t < \tau$, it is supposed that only single collision happens, and the collision term of DSMC is just used. At $t > \tau$, it is derived that $1-\tau/\Delta t$ of particles should experience multiple collisions, which will be absorbed into the wave part and calculated by the NS solver. Then the DSMC and NS solver can be coupled in a direct and simple way, bringing about multi-scale property. The governing equation is derived and named as multi-scale Boltzmann equation. Different from the original wave-particle method, in the proposed DUWP method, the wave-particle formulation is no more restricted by the Boltzmann-BGK type model and the enormous research findings of DSMC and NS solvers can be utilized into much more complicated flows, like the thermochemical non-equilibrium flow. In this work, one-dimensional cases in monatomic argon gas are preliminarily tested, such as shock structures and Sod shock tubes

FACTS: Fully Automatic CT Segmentation of a Hip Joint

Extraction of surface models of a hip joint from CT data is a pre-requisite step for computer assisted diagnosis and planning (CADP) of periacetabular osteotomy (PAO). Most of existing CADP systems are based on manual segmentation, which is time-consuming and hard to achieve reproducible results. In this paper, we present a Fully Automatic CT Segmentation (FACTS) approach to simultaneously extract both pelvic and femoral models. Our approach works by combining fast random forest (RF) regression based landmark detection, multi-atlas based segmentation, with articulated statistical shape model (aSSM) based fitting. The two fundamental contributions of our approach are: (1) an improved fast Gaussian transform (IFGT) is used within the RF regression framework for a fast and accurate landmark detection, which then allows for a fully automatic initialization of the multi-atlas based segmentation; and (2) aSSM based fitting is used to preserve hip joint structure and to avoid penetration between the pelvic and femoral models. Taking manual segmentation as the ground truth, we evaluated the present approach on 30 hip CT images (60 hips) with a 6-fold cross validation. When the present approach was compared to manual segmentation, a mean segmentation accuracy of 0.40, 0.36, and 0.36 mm was found for the pelvis, the left proximal femur, and the right proximal femur, respectively. When the models derived from both segmentations were used to compute the PAO diagnosis parameters, a difference of 2.0 ± 1.5°, 2.1 ± 1.6°, and 3.5 ± 2.3% were found for anteversion, inclination, and acetabular coverage, respectively. The achieved accuracy is regarded as clinically accurate enough for our target applications