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Doped carbon allotropes are promising materials for use in a range of applications in energy harvesting and gas adsorption. Synthesis of multifunctional C is however challenging as it requires simultaneous control over surface area, conductivity, chemical nature and loading of heteroatoms in the carbon matrix, usually yielding a material at a time that favours a single application. Pyridinic-N on C-surface, for instance, facilitates oxygen reduction (ORR) and CO 2 capture, whereas more heteroatom enhances capacitance. Here we report on soya derived N-doped carbon having high surface area of 1072 m 2 /g and exhibiting superior performance for all these applications. Supercapacitors made of this material is operable in a wide potential window and possesses specific energy density of 24.3 Wh/kg with 93% capacitive retention beyond 10,000 charge-discharge cycles at a high 10 A/g discharge rate. It also exhibits one of the best performances among bio-derived materials towards ORR with half wave potential of −0.211 V ( vs . SCE) in alkaline solution that involve facile multi-electron transfer at rate determining step. Further at 1 bar pressure, it captures an appreciable 14 wt% CO 2 at 25 °C and 57.7 wt% at −78 °C. [ABSTRACT FROM AUTHOR]

Corncob carbon prepared by means of (KOH) chemical activation method at 600 °C for 1 h is shown as a promising electrode material for supercapacitors. The XRD analysis of the activated corncob carbon shows highly amorphous and disordered structure. The specific surface area and pore volume of the activated carbon are analysed using Brunauer-Emmett-Teller (BET) method. The calculated BET surface area of activated corncob carbon is ∼ 800 m 2 g −1 with micro and mesoporous in nature. The porous nature of the carbon is further confirmed using SEM and HR-TEM analysis. The electrochemical studies in aqueous electrolytes reveal that a high specific capacitance of 390 F g −1 at 0.5 A g −1 current density. The electrochemical performance of activated corncob electrodes is studied in three different ionic liquids, among them the EMIMBF 4 possess good capacitive behaviour and the wide potential window resulted a high energy density of 25 Wh kg −1 and power density of 174 W kg −1 . The supercapacitor device fabricated using the ionic liquid could power a red LED for more than 4 min after upon 10 s charging. The above investigation clearly indicates that the corncob derived carbon materials are promising for applications in supercapacitor. [ABSTRACT FROM AUTHOR]

Scale formation is a serious problem often observed in heat transfer equipments. Barite, calcite and aragonite are some of the major components of scale. Control of scale formation is usually achieved through usage of scale inhibitors/chelating agents. Here we report the effect of ethylene glycol-O,O’-bis(2-aminoethyl)-N,N,N’,N’-tetraacetic acid (EGTA) on the morphology and polymorphism of CaCO3 when synthesized from CaCl2 solution using Na2CO3 at three different temperatures, 60, 80 and 100°C. The samples were characterized using XRD, FTIR and SEM techniques. The details revealed that EGTA stabilizes aragonite more efficiently at 60°C and with raise in temperature formation of calcite is predominant. The study revealed an unusual and novel datura pod like morphology for calcite. [ABSTRACT FROM AUTHOR]

Abstract: This paper discusses space–time tradeoffs associated with algorithms for the problem of detecting negative cost cycles in networks (NCCD). NCCD is one of the more ubiquitous problems in computer science and operations research, with applications ranging from program verification and real-time scheduling to image segmentation and shortest path identification. Typical algorithmic analysis, whether theoretical or empirical, focuses almost exclusively on the running time of the algorithm. However, there exist applications in which space is just as important a parameter as time is. This is especially true when the problem instances are very large, as is the case in program verification. Consequently, an algorithm that minimizes running time while ignoring the space overhead may be impractical. In this paper, we analyze a number of the more common algorithms for NCCD from the perspectives of both time and space, with a view towards providing a space–time tradeoff for the practitioner. All the algorithms discussed in this paper (with the exception of Network Simplex) run in time on a network with m arcs and n vertices; however, their space requirements range from (Stressing Algorithm) to (all the Bellman–Ford and Network Simplex variants). Our empirical results demonstrate that in the cases where space is paramount, the Stressing Algorithm is a useful alternative to the Bellman–Ford variants. [Copyright &y& Elsevier]

Abstract: In this paper, we present a comprehensive empirical analysis of the Vertex Contraction (VC) algorithm for the problem of checking whether a directed graph with positive and negative costs on its edges has a negative cost cycle (NCCD). VC was first presented in [K. Subramani, L. Kovalchick, Contraction versus relaxation: a comparison of two approaches for the negative cost cycle detection problem, in: P.M.A. Sloot et al. (Ed.), Proceedings of the third international conference on computational science (ICCS), Lecture notes in computer science, vol. 2659, Springer-Verlag, 2003, pp. 377–387] and is the only known purely greedy strategy for the NCCD problem. In [K. Subramani, L. Kovalchick, Contraction versus relaxation: a comparison of two approaches for the negative cost cycle detection problem, in: P.M.A. Sloot et al. (Ed.), Proceedings of the third international conference on computational science (ICCS), Lecture notes in computer science, vol. 2659, Springer-Verlag, 2003, pp. 377–387], we compared the performance profiles of a naive implementation of VC and the “standard” Bellman–Ford (BF) algorithm for negative cost cycle detection; we observed that VC performed an order of magnitude better than the BF algorithm. Our experiments were conducted on a range of randomly generated inputs over multiple classes of networks and the results conclusively demonstrated the superiority of VC over a naive implementation of BF. Our observations are surprising given that VC is asymptotically inferior to BF on sparse networks. This paper continues the study of contrasting greedy and dynamic programming (relaxation-based) approaches for the NCCD problem, by comparing sophisticated variants of VC with sophisticated implementations of the BF algorithm. Variants of VC are obtained by employing different heuristics to determine the vertex contraction sequence, in precisely the same manner as variants of BF are obtained by employing different heuristics to determine the edge relaxation sequence. Our experiments indicate that on most classes of networks, there is at least one VC variant with a performance profile that is comparable to the more sophisticated BF implementations. Our results are most surprising for the case of planar networks, where a variant of VC performs almost as well as the best relaxation-based algorithm. One of the principal conclusions of our work is that a simple, greedy approach involving vertex contraction is a good choice on sparse networks. On a more fundamental note, we establish that the selection of an algorithm for the NCCD problem should involve an analysis of the input and the architecture of the computing machine, in order to maximize performance. [Copyright &y& Elsevier]