Virtual Materials Intelligence for Design and Discovery of Advanced Electrocatalysts

Similar to advancements gained from big data in genomics, security, internet of things, and e-commerce, the materials workflow could be made more efficient and prolific through advances in streamlining data sources, autonomous materials synthesis, rapid characterization, big data analytics, and self-learning algorithms. In electrochemical materials science, data sets are large, unstructured/heterogeneous, and difficult to process and analyze from a single data channel or platform. Computer-aided materials design together with advances in data mining, machine learning, and predictive analytics are expected to provide inexpensive and accelerated pathways towards tailor-made functionally optimized energy materials. Fundamental research in the field of electrochemical energy materials focuses primarily on complex interfacial phenomena and kinetic electrocatalytic processes. This perspective article critically assesses AI-driven modeling and computational approaches that are currently applied to those objects. An application-driven materials intelligence platform is introduced, and its functionalities are scrutinized considering the development of electrocatalyst materials for CO₂ conversion as a use case.     

Interactive fuzzy goal programming for a multi-objective closed-loop logistics network

Over the last decade, there has been increased attention to closed-loop logistics networks. Environmental legislation requires companies to be more responsible by collecting used products from customers. Companies can also benefit from savings that are related to recovering and recycling used products. Unlike previous studies, which only consider single products or a single period of time in multi-objective problems, this paper considers a multi-product multi-period closed-loop logistics network with different types of facilities. A?multi-objective mixed-integer nonlinear programming formulation is developed to minimize the total cost, the delivery time of new products, and the collection time of used products. Thus, this model better approximates real-life applications of closed-loop logistics problems. Interactive fuzzy goal programming (IFGP) is applied to solve the model for handling multiple objective problems with conflicting objectives and to address the imprecise nature of decision-makers?? aspiration levels for goals. The results from computational experiments performed here show that by changing the upper or lower bound of each objective function, one can obtain a better final solution of the problem and also can provide more options for decision makers to choose from based on their situation. Finally, the utilization rate of facilities is shown to be an important indicator when designing a logistics network.     

Solving a new stochastic multi-mode p-hub covering location problem considering risk by a novel multi-objective algorithm

In this paper, we develop a novel stochastic multi-objective multi-mode transportation model for hub covering location problem under uncertainty. The transportation time between each pair of nodes is an uncertain parameter and also is influenced by a risk factor in the network. We extend the traditional comprehensive hub location problem by considering two new objective functions. So, our multi-objective model includes (i) minimization of total current investment costs and (ii) minimization of maximum transportation time between each origin–destination pair in the network. Besides, a novel multi-objective imperialist competitive algorithm (MOICA) is proposed to obtain the Pareto-optimal solutions of the problem. The performance of the proposed solution algorithm is compared with two well-known meta-heuristics, namely, non-dominated sorting genetic algorithm (NSGA-II) and Pareto archive evolution strategy (PAES). Computational results show that MOICA outperforms the other meta-heuristics.     

Copolymers: efficient carriers for intelligent nanoparticulate drug targeting and gene therapy

Copolymers are among the most promising substances used in the preparation of drug/gene delivery systems. Different categories of copolymers, including block copolymers, graft copolymers, star copolymers and crosslinked copolymers, are of interest in drug delivery. A variety of nanostructures, including polymeric micelles, polymersomes and hydrogels, have been prepared from copolymers and tested successfully for their drug delivery potential. The most recent area of interest in this field is smart nanostructures, which benefit from the stimuli-responsive properties of copolymeric moieties to achieve novel targeted drug delivery systems. Different copolymer applications in drug/gene delivery using nanotechnology-based approaches with particular emphasis on smart nanoparticles are reviewed.     

Application of particle swarm optimization in chaos synchronization in noisy environment in presence of unknown parameter uncertainty

In this paper, particle swarm optimization (PSO) is applied to synchronize chaotic systems in presence of parameter uncertainties and measurement noise. Particle swarm optimization is an evolutionary algorithm which is introduced by Kennedy and Eberhart. This algorithm is inspired by birds flocking. Optimization algorithms can be applied to control by defining an appropriate cost function that guarantees stability of system. In presence of environment noise and parameter uncertainty, robustness plays a crucial role in succeed of controller. Since PSO needs only rudimentary information about the system, it can be a suitable algorithm for this case. Simulation results confirm that the proposed controller can handle the uncertainty and environment noise without any extra information about them. A comparison with some earlier works is performed during simulations.     

Interaction among a lump,periodic waves,and kink solutions to the fractional generalized CBS‐BK equation

The Hirota bilinear method is prepared for searching the diverse soliton solutions for the fractional generalized Calogero‐Bogoyavlenskii‐Schiff‐Bogoyavlensky‐Konopelchenko (CBS‐BK) equation. Also, the Hirota bilinear method is used to finding the lump and interaction with two stripe soliton solutions. Interaction among lumps, periodic waves, and multi‐kink soliton solutions will be investigated. Also, the solitary wave, periodic wave, and cross‐kink wave solutions will be examined for the fractional gCBS‐BK equation. The graphs for various fractional order α are plotted to contain 3D plot, contour plot, density plot, and 2D plot. We construct the exact lump and interaction among other types solutions, by solving the under‐determined nonlinear system of algebraic equations for the associated parameters. Finally, analysis and graphical simulation are presented to show the dynamical characteristics of our solutions and the interaction behaviors are revealed. The existence conditions are employed to discuss the available got solutions.     

Unsteady flows of inhomogeneous incompressible fluids

In this paper, we study the unsteady motion of inhomogeneous incompressible viscous fluids. We present the results corresponding to Stokes' second problem and for the flow between two parallel plates where one is oscillating.     

The use of Chebyshev cardinal functions for solution of the second‐order one‐dimensional telegraph equation

A numerical technique is presented for the solution of the second order one‐dimensional linear hyperbolic equation. This method uses the Chebyshev cardinal functions. The method consists of expanding the required approximate solution as the elements of Chebyshev cardinal functions. Using the operational matrix of derivative, the problem is reduced to a set of algebraic equations. Some numerical examples are included to demonstrate the validity and applicability of the technique. The method is easy to implement and produces very accurate results. © 2008 Wiley Periodicals, Inc. Numer Methods Partial Differential Eq, 2009