An Object-Based Shale Permeability Model: Non-Darcy Gas Flow,Sorption, and Surface Diffusion Effects

Shale samples consist of two major components: organic matter (OM) and inorganic mineral component (iOM). Each component has its distinct pore network topology and morphology, which necessitates generating a model capable of distinguishing the two media. We constructed an object-based model using the OM and iOM composition of shale samples. In the model, we integrated information such as OM population and size distribution, as well as its associated pore-size distribution. For the iOM part, we used mineralogy and pore-size information derived from X-ray diffraction, scanning electron microscopy, and nitrogen sorption measurements. Our proposed model results in millimeter-scale 2D realizations of shale samples by honoring OM and mineral types, their compositions, shapes, and size distributions. The model can capture heterogeneities smaller than 1 mm. We studied the effects of different gas flow processes and found that Knudsen diffusion and gas slippage dominate the flow, but surface diffusion has little impact on total gas flow.     

Removal of iodate from aqueous solution using diatomite/nano titanium dioxide composite as adsorbent

Journal of Radioanalytical and Nuclear Chemistry - Highly deficient strontium cobaltite (SrCoOx), as a new nanomaterial that is thermally treated at low temperature...     

The designing strategies of graphene-based peroxidase mimetic materials

Natural enzymes have been praised highly as ideal catalysts, presumably owing to their remarkable advantages of high efficiency, high selectivity, and mild reaction conditions. The reports of chemical simulation and systematic synthesis of natural enzymes such as peroxidase (POD) are rare because of their complex biological structures. POD represents a large family of oxidoreductases and offers a wide range of applications in many fields of science. Recent advance in the fusion of nanomaterial, catalysis, and biochemistry has inspired the development of artificial enzymes implemented with desired catalytic features of natural enzymes. Herein, we review the redox chemistry of POD and compare its catalytic performance to graphene-based nanomaterials (G-NMs) as POD mimetic nanoenzymes bases on catalytic center, binding site, and carrier function. Based on the viewpoints of stereo chemistry and molecular kinetic and dynamics in heterogeneous system, we evaluate and compare the suitability of different NMs as artificial enzyme constituent. We propose that reevaluates design strategies of graphene-based peroxidase (G-POD) mimetic materials and emphasizes on their selectivity (role as catalytic center, binding site, or carrier) is of uttermost.     

Inference for a change-point problem under a generalised Ornstein–Uhlenbeck setting

Determining accurately when regime and structural changes occur in various time-series data is critical in many social and natural sciences. We develop and show further the equivalence of two consistent estimation techniques in locating the change point under the framework of a generalised version of the one-dimensional Ornstein–Uhlenbeck process. Our methods are based on the least sum of squared error and the maximum log-likelihood approaches. The case where both the existence and the location of the change point are unknown is investigated and an informational methodology is employed to address these issues. Numerical illustrations are presented to assess the methods’ performance.     

Graph-Theoretical Method to the Existence of Stationary Distribution of Stochastic Coupled Systems

In this paper, by linking Fokker–Planck equations with stochastic coupled systems, a new method is provided to investigate the existence of a stationary distribution of stochastic coupled systems. Based on the graph theory and the Lyapunov method, an appropriate Lyapunov function associated with stationary Fokker–Planck equations is constructed. Moreover, a Lyapunov-type theorem and a coefficients-type criterion are obtained to guarantee the existence of a stationary distribution. Furthermore, theoretical results are applied to explore the existence of a stationary distribution of stochastic predator–prey models with dispersal and a sufficient criterion is presented correspondingly. Finally, a numerical example is given to illustrate the effectiveness of our results.     

Self-supported metal sulphide nanocrystals-assembled nanosheets on carbon paper as efficient counter electrodes for quantum-dot-sensitized solar cells

Developing efficient counter electrodes (CEs) and quantum dots made of earth-abundant and non-toxic elements is essential but still challenging for quantum dot-sensitized solar cells (QDSSCs). Here, we report a facile strategy to prepare self-supported and robust CoS₂ and NiS nanocrystals-assembled nanosheets directly grown on carbon paper (MSx NS@CP) as efficient counter electrodes for QDSSCs. Such CEs integrate the merits of fast electron transfer from interconnected conductive scaffold, efficient mass transfer from hierarchically vertical nanosheet on 3D open substrate, as well as abundant highly active catalytic sites from metal sulphide nanocrystal units. As a result, QDDSCs based on such CoS₂ NS@CP and NiS NS@CP CEs achieve a PCE of 8.88% and 7.53%, respectively. The detailed analyses suggest that CoS₂ NS@CP has the highest catalytic activity and shows the lowest charger transfer resistance, leading to the highest PCE. These findings may inspire the design and exploration of other self-supported efficient CEs by integrating highly active catalysts onto 3D conductive networks for efficient QDSSCs.