Pareto-optimality solution recommendation using a multi-objective artificial wolf-pack algorithm

In practical applications, multi-objective optimisation is one of the most challenging problems that engineers face. For this, Pareto-optimality is the most widely adopted concept, which is a set of optimal trade-offs between conflicting objectives without committing to a recommendation for decision-making. In this paper, a fast approach to Pareto-optimal solution recommendation is developed. It recommends an optimal ranking for decision-makers using a Pareto reliability index. Further, a mean average precision and a mean standard deviation are utilised to gauge the trend of the evolutionary process. A multi-objective artificial wolf-pack algorithm is thus developed to handle the multi-objective problem using a non-dominated sorting method (MAWNS). This is tested in a case study, where the MAWNS is employed as an optimiser for a widely adopted standard test problem, ZDT6. The results show that the proposed method works valuably for the multi-objective optimisations

Robust design for the lower extremity exoskeleton under a stochastic terrain by mimicking wolf pack behaviors

While kinematics analysis plays an important role in studying human limb motions, existing methods (namely, direct and inverse kinematics) have their deficiencies. To improve, this paper develops a robust design method using artificial intelligence and applies it to the lower extremity exoskeleton design under a stochastic terrain. An inverse kinematic model is first built considering the impact on human's comfort from the stochastic terrain. Then, a robust design model is constructed based on the inverse kinematic model, where the design framework mimics wolf pack behaviors and the robust design problem is thus solved for keeping probabilistic consistency between the exoskeleton and its wearer. A case study validates the effectiveness of the developed robust method and algorithm, which ensures walking comfort under the stochastic terrain within the validity of simulations

Carbon nanocages with nanographene shell for high-rate lithium ion batteries

Carbon nanocages with a nanographene shell have been prepared by catalytic decomposition of p-xylene on a MgO supported Co and Mo catalyst in supercritical CO2 at a pressure of 10.34 MPa and temperatures ranging from 650 to 750 °C. The electrochemical performance of these carbon nanocages as anodes for lithium ion batteries has been evaluated by galvanostatic cycling. The carbon nanocages prepared at a temperature of 750 °C exhibited relatively high reversible capacities, superior rate performance and excellent cycling life. The advanced performance of the carbon nanocages prepared at 750 °C is ascribed to their unique structural features: (1) nanographene shells and the good inter-cage contact ensuring fast electron transportation, (2) a porous network formed by fine pores in the carbon shell and the void space among the cages facilitating the penetration of the electrolyte and ions within the electrode, (3) thin carbon shells shortening the diffusion distance of Li ions, and (4) the high specific surface area providing a large number of active sites for charge-transfer reactions. These carbon nanocages are promising candidates for application in lithium ion batteries

A supercritical-fluid method for growing carbon nanotubes

Large‐scale generation of multiwalled carbon nanotubes (MCNTs) is efficiently achieved through a supercritical fluid technique employing carbon dioxide as the carbon source. Nanotubes with diameters ranging from 10 to 20 nm and lengths of several tens of micrometers are synthesized (see figure). The supercritical‐fluid‐grown nanotubes also exhibit field‐emission characteristics similar to MCNTs grown by chemical‐vapor deposition

Growth of carbon nanotubes from heterometallic palladium and copper catalysts

Bamboo-structured carbon nanotubes (BCNTs) were synthesized with MgO-supported Pd and Cu catalysts, doped with either Mo or W, by the catalytic chemical vapor decomposition of methane. No nanotubes were observed to grow from the catalysts in the absence of the dopant metals. Additionally, the level of dopant in the catalysts was found to strongly affect the morphology of carbon produced. Amorphous carbon was generated on a 10 wt % Cu/5 wt % W (2:1) catalyst, while BCNTs were produced on 20 wt % Cu/5 wt % W (4:1) and a 30 wt % Cu/5 wt % W (6:1) catalysts. A pure Pd catalyst produced carbon nanofibres (CNFs), while BCNTs were able to grow from Pd/Mo catalysts. Density functional theory simulations show that the composite Cu/W and Pd/Mo bimetallic particles which generated BCNTs have similar binding energies to carbon, and comparable to metals such as Fe, Co, and Ni which are traditionally used to grow CNTs by chemical vapor deposition

Supercritical fluid synthesis of magnetic hexagonal nanoplatelets of magnetite

A supercritical fluid technique was used to prepare hexagonal nanoplatelets of magnetite. Ferrocene was used as the Fe source, and sc-CO2 acted as both a solvent and oxygen source in the process. Powder X-ray diffraction, transmission electron microscopy, X-ray photoelectron spectroscopy, and magnetic measurements were used to characterize the products. It was found that the morphology and structure of the product strongly depended on the reaction conditions

Nitrogen-doped carbon nanotubes: growth, mechanism and structure

Nitrogen‐doped bamboo‐structured carbon nanotubes have been successfully grown using a series of cobalt/molybdenum catalysts. The morphology and structure of the nanotubes were analysed by transmission electron microscopy and Raman spectroscopy. The level of nitrogen doping, as determined by X‐ray photoelectron spectroscopy, was found to range between 0.5 to 2.5 at. %. The growth of bamboo‐structured nanotubes in the presence of nitrogen, in preference to single‐walled and multi‐walled nanotubes, was due to the greater binding energy of nitrogen for cobalt in the catalyst compared to the binding strength of carbon to cobalt, as determined by density functional theory

Supercritical fluid growth of porous carbon nanocages

Carbon nanocages, with remarkably large mesoporous volumes, have been synthesized by the deposition of p-xylene over a Co/Mo catalyst in supercritical carbon dioxide. Nanocages with diameters ranging between 10 and 60 nm were synthesized at temperatures between 650 and 750 °C. The surface area and pore volume of the nanocages produced was found to depend on the reaction temperature and pressure employed. In particular, carbon nanocages with a pore volume of up to 5.8 cm3 g-1 and a BET surface area of 1240 m2 g-1 were readily synthesized at a temperature of 650 °C and a pressure of 10.34 MPa. The high pore volume and surface area of the carbon nanocages synthesized makes them ideal materials for use as inert adsorbents and catalytic supports

Copper/molybdenum nanocomposite particles as catalysts for the growth of bamboo-structured carbon nanotubes

Bamboo-structured carbon nanotubes (BCNTs), with mean diameters of 20 nm, have been synthesized on MgO-supported Cu and Mo catalysts by the catalytic chemical vapor deposition of methane. BCNTs could only be generated using a combination of Cu and Mo catalysts. No BCNTs were produced from either individual Cu or Mo catalysts. In combination, Mo was found to be essential for cracking the methane precursor, while Cu was required for BCNT formation. Energy dispersive X-ray analysis of the individual particles at the tips of the nanotubes suggest that Cu and Mo are present as a “composite” nanoparticle catalyst after growth. First-principles modeling has been used to describe the interaction of the Cu/Mo catalyst with the nanotubes, suggesting that the catalyst binds with the same energy as traditional catalysts such as Fe, Ni, and Co