A mathematical framework for expanding a railway’s theoretical capacity

Analytical techniques for measuring and planning railway capacity expansion activities have been considered in this article. A preliminary mathematical framework involving track duplication and section sub divisions is proposed for this task. In railways these features have a great effect on network performance and for this reason they have been considered. Additional motivations have also arisen from the limitations of prior models that have not included them.

Optimization models for expanding a railway’s theoretical capacity

Changing the topology of a railway network can greatly affect its capacity. Railway networks however can be altered in a multitude of different ways. As each way has significant immediate and long term financial ramifications, it is a difficult task to decide how and where to expand the network. In response some railway capacity expansion models (RCEM) have been developed to help capacity planning activities, and to remove physical bottlenecks in the current railway system. The exact purpose of these models is to decide given a fixed budget, where track duplications and track sub divisions should be made, in order to increase theoretical capacity most. These models are high level and strategic, and this is why increases to the theoretical capacity is concentrated upon. The optimization models have been applied to a case study to demonstrate their application and their worth. The case study evidently shows how automated approaches of this nature could be a formidable alternative to current manual planning techniques and simulation. If the exact effect of track duplications and sub-divisions can be sufficiently approximated, this approach will be very applicable.

Incorporating complex train paths to an analysis of absolute capacity

Railways are an important mode of transportation. They are however large and complex and their construction, management and operation is time consuming and costly. Evidently planning the current and future activities is vital. Part of that planning process is an analysis of capacity. To determine what volume of traffic can be achieved over time, a variety of railway capacity analysis techniques have been created. A generic analytical approach that incorporates more complex train paths however has yet to be provided. This article provides such an approach. This article extends a mathematical model for determining the theoretical capacity of a railway network. The main contribution of this paper is the modelling of more complex train paths whereby each section can be visited many times in the course of a train’s journey. Three variant models are formulated and then demonstrated in a case study. This article’s numerical investigations have successively shown the applicability of the proposed models and how they may be used to gain insights into system performance.

A multi-criteria approach for hospital capacity analysis

Hospitals are critical elements of health care systems and analysing their capacity to do work is a very important topic. To perform a system wide analysis of public hospital resources and capacity, a multi-objective optimization (MOO) approach has been proposed. This approach identifies the theoretical capacity of the entire hospital and facilitates a sensitivity analysis, for example of the patient case mix. It is necessary because the competition for hospital resources, for example between different entities, is highly influential on what work can be done. The MOO approach has been extensively tested on a real life case study and significant worth is shown. In this MOO approach, the epsilon constraint method has been utilized. However, for solving real life applications, with a large number of competing objectives, it was necessary to devise new and improved algorithms. In addition, to identify the best solution, a separable programming approach was developed. Multiple optimal solutions are also obtained via the iterative refinement and re-solution of the model.

MnOx/carbon nanotube/reduced graphene oxide nanohybrids as high-performance supercapacitor electrodes

Nanohybrids consisting of both carbon and pseudocapacitive metal oxides are promising as high-performance electrodes to meet the key energy and power requirements of supercapacitors. However, the development of high-performance nanohybrids with controllable size, density, composition and morphology remains a formidable challenge. Here, we present a simple and robust approach to integrating manganese oxide (MnOx) nanoparticles onto flexible graphite paper using an ultrathin carbon nanotube/reduced graphene oxide (CNT/RGO) supporting layer. Supercapacitor electrodes employing the MnOx/CNT/RGO nanohybrids without any conductive additives or binders yield a specific capacitance of 1070 F g−1 at 10 mV s−1, which is among the highest values reported for a range of hybrid structures and is close to the theoretical capacity of MnOx. Moreover, atmospheric-pressure plasmas are used to functionalize the CNT/RGO supporting layer to improve the adhesion of MnOx nanoparticles, which results in theimproved cycling stability of the nanohybrid electrodes. These results provide information for the utilization of nanohybrids and plasma-related effects to synergistically enhance the performance of supercapacitors and may create new opportunities in areas such as catalysts, photosynthesis and electrochemical sensors

High Lithium Storage in Mixed Crystallographic Phase Nanotubes of Titania and Carbon-Titania

Morphology and electrochemical performance of mixed crystallographic phase titania nanotubes for prospective application as anode in rechargeable lithium ion batteries are discussed. Hydrothermally grown nanotubes of titania (TiO2) and carbon-titania (C-TiO2) comprise a mixture of both anatase and TiO2 (B) crystallographic phases. The first cycle capacity (at Current rate = 10 mAg(-1)) for bare TiO2 nanotubes was 355 mAhg(-1) (approximately 1.06 Li), which is higher than both the theoretical capacity (335 mAhg(-1)) and the reported values for pure anatase and TiO2 (B) nanotubes. Higher capacity is attributed to it combination of the presence of mixed crystallographic phases of titania and trivial size effects. The surface area of bare TiO2 nanotubes was very high at 340 m(2) g(-1). C-TiO2 nanotubes showed a slightly lower first-cycle specific capacity of 307 mAhg(-1), but the irreversible capacity loss in the first cycle decreased by half compared to bare TiO2 nanotubes. The C-TiO2 nanotubes also showed a better rate capability, that is, higher capacities compared to bare TiO2 nanotubes in the Current range 0.1-2 Ag-1. Enhanced rate capability in the case of C-TiO2 is attributed to the efficient percolation of electrons as well its to the decrease in the anatase phase.

Dual yolk-shell structure of carbon and silica-coated silicon for high-performance lithium-ion batteries

Silicon batteries have attracted much attention in recent years due to their high theoretical capacity, although a rapid capacity fade is normally observed, attributed mainly to volume expansion during lithiation. Here, we report for the first time successful synthesis of Si/void/SiO2/void/C nanostructures. The synthesis strategy only involves selective etching of SiO2 in Si/SiO2/C structures with hydrofluoric acid solution. Compared with reported results, such novel structures include a hard SiO2-coated layer, a conductive carbon-coated layer, and two internal void spaces. In the structures, the carbon can enhance conductivity, the SiO2 layer has mechanically strong qualities, and the two internal void spaces can confine and accommodate volume expansion of silicon during lithiation. Therefore, these specially designed dual yolk-shell structures exhibit a stable and high capacity of 956 mA h g−1 after 430 cycles with capacity retention of 83%, while the capacity of Si/C core-shell structures rapidly decreases in the first ten cycles under the same experimental conditions. The novel dual yolk-shell structures developed for Si can also be extended to other battery materials that undergo large volume changes.

A Low-Complexity Near-ML Performance Achieving Algorithm for Large MIMO Detection

In this paper, we present a low-complexity, near maximum-likelihood (ML) performance achieving detector for large MIMO systems having tens of transmit and receive antennas. Such large MIMO systems are of interest because of the high spectral efficiencies possible in such systems. The proposed detection algorithm, termed as multistage likelihood-ascent search (M-LAS) algorithm, is rooted in Hopfield neural networks, and is shown to possess excellent performance as well as complexity attributes. In terms of performance, in a 64 x 64 V-BLAST system with 4-QAM, the proposed algorithm achieves an uncoded BER of 10(-3) at an SNR of just about 1 dB away from AWGN-only SISO performance given by Q(root SNR). In terms of coded BER, with a rate-3/4 turbo code at a spectral efficiency of 96 bps/Hz the algorithm performs close to within about 4.5 dB from theoretical capacity, which is remarkable in terms of both high spectral efficiency as well as nearness to theoretical capacity. Our simulation results show that the above performance is achieved with a complexity of just O(NtNt) per symbol, where N-t and N-tau denote the number of transmit and receive antennas.

Low-Complexity Near-MAP Decoding of Large Non-Orthogonal STBCs Using PDA

Non-orthogonal space-time block codes (STBC) from cyclic division algebras (CDA) are attractive because they can simultaneously achieve both high spectral efficiencies (same spectral efficiency as in V-BLAST for a given number of transmit antennas) as well as full transmit diversity. Decoding of non-orthogonal STBCs with hundreds of dimensions has been a challenge. In this paper, we present a probabilistic data association (PDA) based algorithm for decoding non-orthogonal STBCs with large dimensions. Our simulation results show that the proposed PDA-based algorithm achieves near SISO AWGN uncoded BER as well as near-capacity coded BER (within 5 dB of the theoretical capacity) for large non-orthogonal STBCs from CDA. We study the effect of spatial correlation on the BER, and show that the performance loss due to spatial correlation can be alleviated by providing more receive spatial dimensions. We report good BER performance when a training-based iterative decoding/channel estimation is used (instead of assuming perfect channel knowledge) in channels with large coherence times. A comparison of the performances of the PDA algorithm and the likelihood ascent search (LAS) algorithm (reported in our recent work) is also presented.

New rock salt-related oxides Li3M2RuO6 (M=Co, Ni): Synthesis, structure, magnetism and electrochemistry

We describe the synthesis, crystal structure, magnetic and electrochemical characterization of new rock salt-related oxides of formula, Li3M2RuO6 (M=Co, Ni). The M=Co oxide adopts the LiCoO2 (R-3m) structure, where sheets of LiO6 and (Co-2/Ru)O-6 octahedra are alternately stacked along the c-direction. The M=Ni oxide also adopts a similar layered structure related to Li2TiO3, where partial mixing of Li and Ni/Ru atoms lowers the symmetry to monoclinic (C2/c). Magnetic susceptibility measurements reveal that in Li3Co2RuO6, the oxidation states of transition metal ions are Co3+ (S=0), Co2+ (S=1/2) and Ru4+ (S=1), all of them in low-spin configuration and at 10 K, the material orders antiferromagnetically. Analogous Li3Ni2RuO6 presents a ferrimagnetic behavior with a Curie temperature of 100 K. The differences in the magnetic behavior have been explained in terms of differences in the crystal structure. Electrochemical studies correlate well with both magnetic properties and crystal structure. Li-transition metal intermixing may be at the origin of the more impeded oxidation of Li3Ni2RuO6 when compared to Li3CO2RuO6. Interestingly high first charge capacities (between ca. 160 and 180 mAh g(-1)) corresponding to ca. 2/3 of theoretical capacity are reached albeit, in both cases, capacity retention and cyclability are not satisfactory enough to consider these materials as alternatives to LiCoO2. (C) 2013 Elsevier Inc. All rights reserved.

Lithium metal borate (LiMBO3) family of insertion materials for Li-ion batteries: a sneak peak

Rechargeable lithium-ion battery remains the leading electrochemical energy-storage device, albeit demanding steady effort of design and development of superior cathode materials. Polyanionic framework compounds are widely explored in search for such cathode contenders. Here, lithium metal borate (LiMBO3) forms a unique class of insertion materials having the lowest weight polyanion (i. e., BO33-), thus offering the highest possible theoretical capacity (ca. 220 mAh/g). Since the first report in 2001, LiMBO3 has rather slow progress in comparison to other polyanionic cathode systems based on PO4, SO4, and SiO4. The current review gives a sneak peak to the progress on LiMBO3 cathode systems in the last 15 years highlighting their salient features and impediments in cathode implementation. The synthesis and structural aspects of borate family are described along with the critical analysis of the electrochemical performance of borate family of insertion materials.

Insight into the limited electrochemical activity of NaVP2O7

Recently, LiVP2O7 has been investigated as a possible high-voltage substitute for Li2FeP2O7. However, its Na-equivalent, NaVP2O7, as an economic replacement for Li2FeP2O7 has not yet been well understood. Here, for the first time, we report the feasibility of NaVP2O7 as a 3.4 V cathode material for Na-ion batteries. Having a theoretical capacity of 108 mA h g(-1), it shows an initial discharge capacity of 38.4 mA h g(-1) at 1/20C (1C = 108 mA g(-1)) in the voltage range of 2.5-4.0 V. Our study suggests that part of the sodium ions in the lattice structure exist as structural stabilizers and bring lattice distortion upon desodiation. This study also shows that the title compound, NaVP2O7, suffers from high intrinsic internal resistance, which limits the phase transition kinetics between pristine NaVP2O7 and desodiated Na1-xVP2O7.

Nanostructured materials for Lithium-ion battery technology

The Li-ion battery has for several years been at the forefront of powering an ever-increasing number of modem consumer electronic devices such as laptops, tablet PCs, cell phones, portable music players etc., while in more recent times, has also been sought to power a range of emerging electric and hybrid-electric vehicle classes. Given their extreme popularity, a number of features which define the performance of the Li-ion battery have become a target of improvement and have garnered tremendous research effort over the past two decades. Features such as battery capacity, voltage, lifetime, rate performance, together with important implications such as safety, environmental benignity and cost have all attracted attention. Although properties such as cell voltage and theoretical capacity are bound by the selection of electrode materials which constitute its interior, other performance makers of the Li-ion battery such as actual capacity, lifetime and rate performance may be improved by tailoring such materials with characteristics favourable to Li+ intercalation. One such tailoring route involves shrinking of the constituent electrode materials to that of the nanoscale, where the ultra-small diameters may bestow favourable Li+ intercalation properties while providing a necessary mechanical robustness during routine electrochemical operation. The work detailed in this thesis describes a range of synthetic routes taken in nanostructuring a selection of choice Li-ion positive electrode candidates, together with a review of their respective Li-ion performances. Chapter one of this thesis serves to highlight a number of key advancements which have been made and detailed in the literature over recent years pertaining to the use of nanostructured materials in Li-ion technology. Chapter two provides an overview of the experimental conditions and techniques employed in the synthesis and electrochemical characterisation of the as-prepared electrode materials constituting this doctoral thesis. Chapter three details the synthesis of small-diameter V2O5 and V2O5/TiO2 nanocomposite structures prepared by a novel carbon nanocage templating method using liquid precursors. Chapter four details a hydrothermal synthesis and characterisation of nanostructured β-LiVOPO4 powders together with an overview of their Li+ insertion properties while chapter five focuses on supercritical fluid synthesis as one technique in the tailoring of FeF2 and CoF2 powders having potentially appealing Li-ion 'conversion' properties. Finally, chapter six summarises the overall conclusions drawn from the results presented in this thesis, coupled with an indication of potential future work which may be explored upon the materials described in this work.

Tubular Organization of SnO₂ Nanocrystallites for Improved Lithium Ion Battery Anode Performance

Porous tin oxide nanotubes were obtained by vacuum infiltration of tin oxide nanoparticles into porous aluminum oxide membranes, followed by calcination. The porous tin oxide nanotube arrays so prepared were characterized by FE-SEM, TEM, HRTEM, and XRD. The nanotubes are open-ended, highly ordered with uniform cross-sections, diameters and wall thickness. The tin oxide nanotubes were evaluated as a substitute anode material for the lithium ion batteries. The tin oxide nanotube anode could be charged and discharged repeatedly, retaining a specific capacity of 525 mAh/g after 80 cycles. This capacity is significantly higher than the theoretical capacity of commercial graphite anode (372 mAh/g) and the cyclability is outstanding for a tin based electrode. The cyclability and capacities of the tin oxide nanotubes were also higher than their building blocks of solid tin oxide nanoparticles. A few factors accounting for the good cycling performance and high capacity of tin oxide nanotubes are suggested.

Microwave-assisted hydrothermal synthesis of magnetite nanoparticles with potential use as anode in lithium ion batteries

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)