Sodiation Of Hard Carbon: How Separating Enthalpy And Entropy Contributions Can Find Transitions Hidden In The Voltage Profile

Sodium-ion batteries (NIBs) utilize cheaper materials than lithium-ion batteries (LIBs) and can thus be used in larger scale applications. The preferred anode material is hard carbon, because sodium cannot be inserted into graphite. We apply experimental entropy profiling (EP), where the cell temperature is changed under open circuit conditions. EP has been used to characterize LIBs; here, we demonstrate the first application of EP to any NIB material. The voltage versus sodiation fraction curves (voltage profiles) of hard carbon lack clear features, consisting only of a slope and a plateau, making it difficult to clarify the structural features of hard carbon that could optimize cell performance. We find additional features through EP that are masked in the voltage profiles. We fit lattice gas models of hard carbon sodiation to experimental EP and system enthalpy, obtaining: 1. a theoretical maximum capacity, 2. interlayer versus pore filled sodium with state of charge.     

Artificial intelligence for decision support systems in the field of operations research: review and future scope of research

Operations research (OR) has been at the core of decision making since World War II, and today, business interactions on different platforms have changed business dynamics, introducing a high degree of uncertainty. To have a sustainable vision of their business, firms need to have a suitable decision-making process at each stage, including minute details. Our study reviews and investigates the existing research in the field of decision support systems (DSSs) and how artificial intelligence (AI) capabilities have been integrated into OR. The findings of our review show how AI has contributed to decision making in the operations research field. This review presents synergies, differences, and overlaps in AI, DSSs, and OR. Furthermore, a clarification of the literature based on the approaches adopted to develop the DSS is presented along with the underlying theories. The classification has been primarily divided into two categories, i.e. theory building and application-based approaches, along with taxonomies based on the AI, DSS, and OR areas. In this review, past studies were calibrated according to prognostic capability, exploitation of large data sets, number of factors considered, development of learning capability, and validation in the decision-making framework. This paper presents gaps and future research opportunities concerning prediction and learning, decision making and optimization in view of intelligent decision making in today’s era of uncertainty. The theoretical and managerial implications are set forth in the discussion section justifying the research questions.

     

Monoclinic zirconia nanoparticle-catalyzed regioselective synthesis of some novel substituted spirooxindoles through one-pot multicomponent reaction in a ball mill: A step toward green and sustainable chemistry

A highly efficient, green as well as atom economical protocol for the synthesis of substituted spirooxindoles from m-ZrO₂ NPs catalyzed multicomponent reaction of isatin derivatives with ethyl cyanoacetate and 1,3-dicarbonyl compounds in a ball mill has been established. Because of the simple and readily available starting materials, easy operation, and high bioactivity of substituted spirooxindoles, this strategy can be broadly applied to medicinal chemistry. The recyclability of the m-ZrO₂ Nps catalyst is another emphasis of proposed methodology.     

$$\varvec{}$$-Classes in finite groups of conjugate type $$\varvec{(n,1)}$$(n,1)

Two elements in a group G are said to be z-equivalent or to be in the same z-class if their centralizers are conjugate in G. In a recent work, Kulkarni et al. (J. Algebra Appl., 15 (2016) 1650131) proved that a non-abelian p-group G can have at most \(\frac{p^k-1}{p-1} +1\) number of z-classes, where \(|G/Z(G)|=p^k\). Here, we characterize the p-groups of conjugate type (n, 1) attaining this maximal number. As a corollary, we characterize p-groups having prime order commutator subgroup and maximal number of z-classes.     

Solving dual problems using a coevolutionary optimization algorithm

In solving certain optimization problems, the corresponding Lagrangian dual problem is often solved simply because in these problems the dual problem is easier to solve than the original primal problem. Another reason for their solution is the implication of the weak duality theorem which suggests that under certain conditions the optimal dual function value is smaller than or equal to the optimal primal objective value. The dual problem is a special case of a bilevel programming problem involving Lagrange multipliers as upper-level variables and decision variables as lower-level variables. Another interesting aspect of dual problems is that both lower and upper-level optimization problems involve only box constraints and no other equality of inequality constraints. In this paper, we propose a coevolutionary dual optimization (CEDO) algorithm for co-evolving two populations—one involving Lagrange multipliers and other involving decision variables—to find the dual solution. On 11 test problems taken from the optimization literature, we demonstrate the efficacy of CEDO algorithm by comparing it with a couple of nested smooth and nonsmooth algorithms and a couple of previously suggested coevolutionary algorithms. The performance of CEDO algorithm is also compared with two classical methods involving nonsmooth (bundle) optimization methods. As a by-product, we analyze the test problems to find their associated duality gap and classify them into three categories having zero, finite or infinite duality gaps. The development of a coevolutionary approach, revealing the presence or absence of duality gap in a number of commonly-used test problems, and efficacy of the proposed coevolutionary algorithm compared to usual nested smooth and nonsmooth algorithms and other existing coevolutionary approaches remain as the hallmark of the current study.     

A novel PCF design with an ultra-flattened dispersion and low confinement loss by varying tiny air-hole concentration at core and cladding

Optical Review - We propose a highly doped circular photonic crystal fiber (HDC-PCF) in which solid fiber core is surrounded by four layer circular rings consisting of air holes in the cladding....