Manipulating electrokinetic conductance of nanofluidic channel by varying inlet pH of solution

The electrokinetic conductivity of micro-/nanofluidic systems, which strongly depends on the local solution properties (e.g., pH and ionic strength), has wide applications in nanosystems to control the system performance and ion rectification. Accurate and active manipulation of this parameter is proven to be very challenging since, in nanoscale, the ion transport is particularly dominated by the acquired surface charge on the solid–liquid interfaces. In this study, we propose an approach to manipulate the nanochannel electrokinetic conductivity by changing the pH value of the solution at the inlet in order to impose asymmetrical conditions inside nanochannel. The variable surface charge of walls is determined by considering the chemical adsorption on the solid–liquid interface and the electrical double layer interaction. The presented numerical model, which couples Poisson–Nernst–Planck and Navier–Stokes equations, can fully consider the electro-chemo-mechanical transport phenomena and predict the electrokinetic conductivity of nanofluidic channels with good accuracy. Modeling results show that the electrokinetic conductivity of the nanofluidic systems can be regulated by varying the solution pH at the inlet. It is revealed that the stronger electric double layers interaction can enhance the sensitivity of the nanochannel electrokinetic conductance to the inlet pH. This unique behavior of the nanochannel electrokinetic conductivity could broaden potential applications in biomedical, energy, and environmental systems using nanofluidic devices.     

Cold heavy oil production with sand simulation including wormhole propagation and foamy oil behaviour

Cold heavy oil production with sand (CHOPS) is a primary production method used for heavy oil reservoirs with no requirements of external energy consumption. A new model for CHOPS is simulated by incorporating wormhole propagation and foamy oil behaviour mechanisms to evaluate the recovery of an extra-heavy oil reservoir of the Athabasca region. The most critical mechanisms of CHOPS, wormhole propagation and foamy oil behaviour, are captured by using Wang's model for wormhole propagation and Uddin's model of gas exsolution. After 120 months of simulation, 53.38%, 99.76%, and 100% of wormhole propagation were achieved during three time steps of 12, 48, and 60 months, respectively, toward the sides of the studied reservoir section. The propagation was achieved within all directions of the investigated section compatible with the erratic nature of wormhole propagation. Furthermore, the application of Uddin's model was incorporated into production by reducing the fluid viscosity as a result of the foamy oil behaviour. Over 3% of the recovery was achieved at the end of the primary CHOPS phase simulation by taking into account that we modelled the recovery based on highly viscous oil with API 7.5. Finally, the model can provide an improved understanding of the primary CHOPS process by considering its two significant mechanisms.     

Modeling,equilibrium, and demand management for mobility and delivery services in Mobility-as-a-Service ecosystems

Mobility-as-a-Service (MaaS) is an emerging business model integrating various travel modes into a single mobility service accessible on demand. Besides the on-demand mobility services, instant delivery services have increased rapidly and particularly boomed during the coronavirus (COVID-19) pandemic, requiring online orders to be delivered timely. In this study, to deal with the redundant mobility resources and high costs of instant delivery services, we model an MaaS ecosystem that provides mobility and instant delivery services by sharing the same multimodal transport system. We derive a two-class bundle choice user equilibrium (BUE) for mobility and delivery users in the MaaS ecosystems. We propose a bilateral surcharge–reward scheme (BSRS) to manage the integrated mobility and delivery demand in different incentive scenarios. We further formulate a bilevel programming problem to optimize the proposed BSRS, where the upper level problem aims to minimize the total system equilibrium costs of mobility and delivery users, and the lower level problem is the derived two-class BUE with BSRS. We analyze the optimal operational strategies of the BSRS and develop a solution algorithm for the proposed bilevel programming problem based on the system performance under BSRS. Numerical studies conducted with real-world data validate the theoretical analysis, highlight the computational efficiency of the proposed algorithm, and indicate the benefits of the BSRS in managing the integrated mobility and delivery demand and reducing total system equilibrium costs of the MaaS ecosystems.     

Density of Bismuth Boro Zinc Glasses Using Machine Learning Techniques

Journal of Inorganic and Organometallic Polymers and Materials - Machine learning techniques have been employed to predict the glass densities of...     

A numerical study integrated with RSM for hydrothermal and entropy performance of porous jet impingement

The thermohydraulic and thermodynamic performance of porous jet impingement under pressure drop effect has not yet been jointly published. Thus, the novelty of this work computationally along with the response surface methodology (RSM) optimization approach considers the porous jet impingement performance linked with a pressure drop simultaneously. Also, the current study used a novel multiobjective optimum design study for various design parameters, such as porosity (ε), Darcy number (Da), and pore per inch (PPI), under numerical simulation assessment of forced laminar convection of jet impingement with full and partial metal foam. The influence of various base plate thicknesses (t = 0, 1, 2, and 3 mm), various nanofluids (Al₂O₃, CuO, SiO₂, and ZnO), and the metal foam size percentage (W/L = 0, 0.25, 0.5, 0.75, and 1) on the improvement of the thermohydraulic and thermodynamic performance is also simulated. Results indicated that utilizing pure water and a metal foam size (W/L) of 1 along with a base plate thickness of 0 mm produced the preferable thermohydraulic and thermodynamic performance. Furthermore, according to an optimization analysis, the current study's objective for the thermohydraulic and thermodynamic performance of jet impingement can be achieved using the parameters porosity ε = 0.1, Darcy number, Da = 1, and the PPI = 15. Therefore, this investigation integrating computational fluid dynamics and RSM offers considerable innovation and useful reference for the optimum design of a porous jet impingement cooling.     

Multiobjective optimization of free convection through a nonuniform cabinet filled with porous media

In the current study, multiobjective optimization and numerical simulation were used to evaluate free convection through a nonuniform cabinet, which has several technical applications, such as cooling techniques, solar air collectors, and heat sinks. The new aspect of the current study is to compute the maximum free convection within an irregular L-shaped cavity filled with porous media using both computational analysis and response surface methodology (RSM). Moreover, the impacts of constant coefficients, such as aspect ratios of the horizontal (AR_h), vertical (AR_v), and Darcy numbers (Da) on the Nusselt number (Nu_ave), Nusselt number maximization (NNM), the temperature of the surface (Ts), and entropy (S) are studied and discussed to evaluate their effect on the thermal performance. The results showed that when Da, AR_h, and AR_v increase, Nu_ave improves while the Ts and S decline and the largest desirability is achieved at AR_h = 0.9, AR_v = 0.9, and Da = 10⁻¹. Additionally, when compared with the subpar design data, the largest gain in NNM was 26.7 times, while the biggest decreases in surface temperature and entropy were 59% and 97%, respectively. As a result, the combination of the numerical simulation and RSM study produces a novel strategy and insightful suggestions for the ideal cooling L-shaped cabinet design.     

Novel Strategy for Hazardous Cement Bypass Dust Removal: Structural,Optical and Nuclear Radiation Shielding Properties of CBD-Bismuth Borate Glass

Journal of Inorganic and Organometallic Polymers and Materials - Herein, this study introduced a novel strategy for hazardous cement bypass dust (CBD) removal via incorporated it into glassy system...     

Lattice Transformation from 2D to Quasi 1D and Phonon Properties of Exfoliated ZrS2 and ZrSe2

Recent reports on thermal and thermoelectric properties of emerging 2D materials have shown promising results. Among these materials are Zirconium-based chalcogenides such as zirconium disulfide (ZrS₂), zirconium diselenide (ZrSe₂), zirconium trisulfide (ZrS₃), and zirconium triselenide (ZrSe₃). Here, the thermal properties of these materials are investigated using confocal Raman spectroscopy. Two different and distinctive Raman signatures of exfoliated ZrX₂ (where X = S or Se) are observed. For 2D-ZrX₂, Raman modes are in alignment with those reported in literature. However, for quasi 1D-ZrX₂, Raman modes are identical to exfoliated ZrX₃ nanosheets, indicating a major lattice transformation from 2D to quasi-1D. Raman temperature dependence for ZrX₂ are also measured. Most Raman modes exhibit a linear downshift dependence with increasing temperature. However, for 2D-ZrS₂, a blueshift for A1g mode is detected with increasing temperature. Finally, phonon dynamics under optical heating for ZrX₂ are measured. Based on these measurements, the calculated thermal conductivity and the interfacial thermal conductance indicate lower interfacial thermal conductance for quasi 1D-ZrX₂ compared to 2D-ZrX₂, which can be attributed to the phonon confinement in 1D. The results demonstrate exceptional thermal properties for Zirconium-based materials, making them ideal for thermoelectric device applications and future thermal management strategies.