Unleashing the Potential of Sodium-Ion Batteries: Current State and Future Directions for Sustainable Energy Storage

Rechargeable sodium-ion batteries (SIBs) are emerging as a viable alternative to lithium-ion battery (LIB) technology, as their raw materials are economical, geographically abundant (unlike lithium), and less toxic. The matured LIB technology contributes significantly to digital civilization, from mobile electronic devices to zero electric-vehicle emissions. However, with the increasing reliance on renewable energy sources and the anticipated integration of high-energy-density batteries into the grid, concerns have arisen regarding the sustainability of lithium due to its limited availability and consequent price escalations. In this context, SIBs have gained attention as a potential energy storage alternative, benefiting from the abundance of sodium and sharing electrochemical characteristics similar to LIBs. Furthermore, high-entropy chemistry has emerged as a new paradigm, promising to enhance energy density and accelerate advancements in battery technology to meet the growing energy demands. This review uncovers the fundamentals, current progress, and the views on the future of SIB technologies, with a discussion focused on the design of novel materials. The crucial factors, such as morphology, crystal defects, and doping, that can tune electrochemistry, which should inspire young researchers in battery technology to identify and work on challenging research problems, are also reviewed.     

Pricing decisions for three-echelon supply chain with advertising and quality effort-dependent fuzzy demand

Simultaneous influence of market power structure, advertising and quality efforts on the optimal pricing decisions and performance of a multi-echelon supply chain under uncertainty have received scant attention in the literature. We focus on this gap by examining a serial decentralised three-echelon supply chain consisting of a supplier, a manufacturer and a retailer. The uncertainty associated with customer demand, marginal production costs and effort costs is expressed as linguistic or fuzzy variables. We analyse centralised supply chain to obtain all benchmark parameters. We investigate four decentralised supply chain cases through fuzzy game theoretic approach. We compare among three Stackelberg games with various supply chain leaderships and a vertical Nash. Our key findings are as follows. First, the manufacturer puts least quality effort while retailer puts least advertising effort when they act as Stackelberg leader in a three-echelon supply chain. Second, supplier's per unit price is governed by the channel leadership in three-echelon supply chain while retail prices are less affected by the leadership. We investigate the impact of fuzzy degree of quality and advertising sensitivity on optimal profit distribution among agents. We present numerical analysis to illustrate the importance of the derived theoretical results and discuss additional managerial insights.     

Simulation of population balance model-based particulate processes via parallel and distributed computing

Population Balance Models (PBMs), a class of integro partial differential equations, are utilized for simulating dynamics of numerous particulate systems. PBMs describe the time evolutions and distributions of many particulate processes and their efficient and quick simulation are critical for enhanced process control and optimization, especially for real-time applications. However, their intensive computational resource requirement is largely a prohibitive factor in the utility of PBMs for control and optimization. This paper describes how distributed computing systems may be leveraged to execute PBM-based simulations thus achieving time savings, using MATLAB's Distributed Computing Toolbox. A parallel computing algorithm was developed for a three dimensional and four dimensional population balance model with built-in constructs such as SPMD that ran efficiently on a cluster of two quad-core machines linked via a gigabit ethernet cable. Speedup of 6.2 and 5.7 times were achieved with 8 workers, over an un-parallelized code, for a 3 and 4 dimensional PBM respectively. Evaluations on work efficiency and scalability further affirm the algorithms’ respectable performance on larger clusters despite significant memory transfer overheads.     

Energy efficient control of a BTX dividing-wall column

Dividing-wall column (DWC) is considered nowadays the new champion in distillation, as it can bring substantial reduction in the capital invested as well as savings in the operating costs. This work presents the simulation results of energy efficient control and dynamics of a dividing-wall column (DWC). In order to allow a fair comparison of the results with previously published references, the case-study considered here is the industrially relevant ternary separation of the mixture benzene-toluene-xylene (BTX) in a DWC. Rigorous simulations were carried out in Aspen Plus and Aspen Dynamics. Several conventional control structures based on PID control loops (DB/LSV, DV/LSB, LB/DSV, LV/DSB) were used as a control basis. These control structures were enhanced by adding an extra loop controlling the heavy component composition in the top of the prefractionator, by using the liquid split as an additional manipulated variable, thus implicitly achieving minimization of energy requirements. The results of the dynamic simulations show relatively short settling times and low overshooting especially for the DB/LSV and LB/DSV control structures. Moreover, the energy efficient control proposed in this work allows the operation of DWC with minimum energy requirements or maximum purity of products.     

Computational Approaches for Studying the Granular Dynamics of Continuous Blending Processes, 2 – Population Balance and Data‐Based Methods

The application of computationally inexpensive modeling methods for a predictive study of powder mixing is discussed. A multidimensional population balance model is formulated to track the evolution of the distribution of a mixture of particle populations with respect to position and time. Integrating knowledge derived from a discrete element model, this method can be used to predict residence time distribution, mean and relative standard deviation of the API concentration in a continuous mixer. Low‐order statistical models, including response surface methods, kriging, and high‐dimensional model representations are also presented. Their efficiency for design optimization and process design space identification with respect to operating and design variables is illustrated.

     

Dynamic optimization of a dividing-wall column using model predictive control

Dividing-wall column (DWC) is one of the best examples of process intensification, as it can bring significant reduction in the capital invested as well as savings in the operating costs. Conventional ternary separations progressed from the (in-)direct sequences to thermally coupled columns such as Petlyuk configuration, and later to the DWC compact design that integrates the two distillation columns into a single shell. Nevertheless, this integration leads also to changes in the control and operating mode due to the higher number of degrees of freedom.In this work we explore the dynamic optimization and advanced control strategies based on model predictive control (MPC), coupled or not with PID. These structures were enhanced by adding an extra loop controlling the heavy component in the top of the feed side of the column, using the liquid split as manipulated variable, thus implicitly achieving energy minimization. To allow a fair comparison with previously published references, this work considers as a case-study the industrially relevant separation of the mixture benzene–toluene–xylene (BTX) in a DWC.The results show that MPC leads to a significant increase in performance, as compared to previously reported conventional PID controllers within a multi-loop framework. Moreover, the optimization employed by the MPC efficiently accommodates the goal of minimum energy requirements – possible due to the addition of an extra loop – in a transient state. The practical benefits of coupling MPC with PID controllers are also clearly demonstrated.     

Synthesis of magnetic nanocomposite microparticles for binding of chlorinated organics in contaminated water sources

In this work, the development of novel magnetic nanocomposite microparticles (MNMs) via free radical polymerization for their application in the remediation of contaminated water is presented. Acrylated plant-based polyphenols, curcumin multiacrylate (CMA) and quercetin multiacrylate (QMA), were incorporated as functional monomers to create high affinity binding sites for the capture of polychlorinated biphenyls (PCBs), as a model pollutant. The MNMs were characterized by Fourier transform infrared spectroscopy, thermogravimetric analysis, scanning electron microscopy, dynamic light scattering, and UV–visible spectroscopy. The affinity of these novel materials for PCB 126 was evaluated and fitted to the nonlinear Langmuir model to determine binding affinities (K_D). The results suggest the presence of the polyphenolic moieties enhances the binding affinity for PCB 126, with K_D values comparable to that of antibodies. This demonstrates that these nanocomposite materials have promising potential as environmental remediation adsorbents for harmful contaminants.     

Influence of normal contact force model on simulations of spherocylindrical particles

How the choice of elastic normal contact force model affects predictions from discrete element method simulations of spherocylindrical particles is investigated in this article. Three force models were investigated: (1) a Hertzian force model (HFM) which assumes a circular contact area; (2) a linear force model (LFM) with a constant stiffness; and (3) a modified HFM (MFM) that accounts for various contact areas and contact transitions. With the MFM, transitions between contact area types must be accounted for otherwise discontinuities in the contact force can occur. It is found that simple force models (HFM, LFM) can be substituted for more accurate force models if only force data and bulk properties are of interest. However, if more detailed contact information, such as contact area, contact overlap, contact duration, or collision frequency, are needed, for example, in population balance models and transient liquid bridge modeling, then a more accurate force model should be used. © 2018 American Institute of Chemical Engineers AIChE J, 64: 1986–2001, 2018     

Application of inline imaging for monitoring crystallization process in a continuous oscillatory baffled crystallizer

In this study, an in situ imaging system has been analysed to characterize the crystal size, the shape and the number of particles during a continuous crystallization process in a Continuous Oscillatory Baffled Crystallizer (COBC). Two image analysis approaches were examined for particle characterization in the suspension containing both small nuclei and larger grown crystals (nonspherical and irregular in shape). The pattern matching approach, in which the particles are approximated to be spherical, did result in an overestimation of the size. Alternatively, a segmentation‐based algorithm resulted in reliable crystal size and shape characteristics. The laser diffraction analysis in comparison to the image analysis overestimated the particle sizes due to the agglomeration of particles upon filtration and drying. The trend in the particle counts during the start of crystallization process, including nucleation, determined by the image analysis probe was comparable with the one measured by FBRM, highlighting the potential of in situ imaging for process monitoring. © 2018 American Institute of Chemical Engineers AIChE J, 64: 2450–2461, 2018     

Electroless Plating of Copper on Fluorinated Polyimide Films Modified by Plasma Graft Copolymerization and UV‐induced Graft Copolymerization with 4‐Vinylpyridine

Surface modification of two types of fluorinated polyimide (FPI) films, either by plasma polymerization and deposition of 4‐vinylpyridine (4VP) or by UV‐induced graft copolymerization with 4VP under atmospheric conditions, was carried out for adhesion enhancement with the electrolessly deposited copper. X‐ray photoelectron spectroscopy (XPS) and Fourier transform infrared (FTIR) results revealed that the pyridine groups in the plasma polymerized 4VP (pp‐4VP) layer could be preserved to a large extent under proper glow discharge conditions. The grafted 4VP layer with well‐preserved pyridine groups was used not only as the chemisorption sites for the palladium complexes (without the need for prior sensitization by SnCl₂) during the electroless plating of copper, but also as an adhesion promotion layer for the electrolessly deposited copper. The T‐peel adhesion strength of the electrolessly deposited copper with both the 4VP plasma‐polymerized FPI (pp‐4VP‐FPI) film and the 4VP graft‐copolymerized FPI (4VP‐g‐FPI) film was much higher than that of the electrolessly deposited copper with the pristine or the Ar plasma‐treated FPI films. The high adhesion strength between the electrolessly deposited copper and the surface‐modified FPI film was attributed to the fact that the plasma‐polymerized and the UV graft‐copolymerized 4VP chains were covalently tethered on the FPI surfaces, as well as the fact that these grafted 4VP polymer chains were spatially and reactively distributed into the copper matrix.