University of Wollongong

About: University of Wollongong is a education organization based out in Wollongong, New South Wales, Australia. It is known for research contribution in the topics: Population & Graphene. The organization has 15674 authors who have published 46658 publications receiving 1197471 citations. The organization is also known as: UOW & Wollongong University.

Self-Healing Hydrogels

Abstract: Over the past few years, there has been a great deal of interest in the development of hydrogel materials with tunable structural, mechanical, and rheological properties, which exhibit rapid and autonomous self-healing and self-recovery for utilization in a broad range of applications, from soft robotics to tissue engineering. However, self-healing hydrogels generally either possess mechanically robust or rapid self-healing properties but not both. Hence, the development of a mechanically robust hydrogel material with autonomous self-healing on the time scale of seconds is yet to be fully realized. Here, the current advances in the development of autonomous self-healing hydrogels are reviewed. Specifically, methods to test self-healing efficiencies and recoveries, mechanisms of autonomous self-healing, and mechanically robust hydrogels are presented. The trends indicate that hydrogels that self-heal better also achieve self-healing faster, as compared to gels that only partially self-heal. Recommendations to guide future development of self-healing hydrogels are offered and the potential relevance of self-healing hydrogels to the exciting research areas of 3D/4D printing, soft robotics, and assisted health technologies is highlighted.

Preparation and Electrochemical Properties of SnO2 Nanowires for Application in Lithium-Ion Batteries

Abstract: One-dimensional (1D) nanostructured materials have received considerable attention for advanced functional systems as well as extensive applications owing to their attractive electronic, optical, and thermal properties. In lithium-ion-battery science, recent research has focused on nanoscale electrode materials to improve electrochemical performance. The high surface-to-volume ratio and excellent surface activities of 1D nanostructured materials have stimulated great interest in their development for the next generation of power sources. Materials based on tin oxide have been proposed as alternative anode materials with high-energy densities and stable capacity retention in lithium-ion batteries. Various SnO2-based materials have displayed extraordinary electrochemical behavior such that the initial irreversible capacity induced by Li2O formation and the abrupt capacity fading caused by volume variation could be effectively reduced when in nanoscale form. From this point of view, SnO2 nanowires can also be suggested as a promising anode material because the nanowire structure is of special interest with predictions of unique electronic and structural properties. Furthermore, the nanowires can be easily synthesized by a thermal evaporation method. However, in its current form, this method of manufacture of SnO2 nanowires has several limitations: it is inappropriate for mass production as high synthesis temperatures are required and there are difficulties in the elimination of metal catalysts that could act as impurities or defects. This results in reversible capacity loss or poor cyclic performance during electrochemical reactions. 12] The critical issues relating to SnO2 nanowires as anode materials for lithium-ion batteries are how to avoid the deteriorative effects of catalysts and how to increase production. Herein, we report on the preparation and electrochemical performance of self-catalysis-grown SnO2 nanowires to determine their potential use as an anode material for lithium-ion batteries. SnO2 nanowires have been synthesized by thermal evaporation combined with a self-catalyzed growth procedure by using a ball-milled evaporation material to increase production at lower temperature and prevent the undesirable effects of conventional catalysts on electrochemical performance. The self-catalysis-grown SnO2 nanowires show higher initial coulombic efficiency and an improved cyclic retention compared with those of SnO2 powder and SnO2 nanowires produced by Au-assisted growth. The self-catalysis growth method, which uses a ball-milled mixture of SnO and Sn powder as an evaporation source, is appropriate for obtaining SnO2 nanowires with high purity. The deposited products on the Si substrates contain almost 100% of the SnO2 nanowires formed. Observation with scanning electron microscopy (SEM) clearly shows a general view of randomly aligned SnO2 nanowires with diameters of 200–500 nm and lengths extending to several tens of micrometers (Figure 1a). Sn droplets at the tips of nanowires were observed and confirmed by energy dispersive X-ray (EDX)

Asymmetric Supercapacitors Using 3D Nanoporous Carbon and Cobalt Oxide Electrodes Synthesized from a Single Metal-Organic Framework.

Abstract: Nanoporous carbon and nanoporous cobalt oxide (Co3O4) materials have been selectively prepared from a single metal–organic framework (MOF) (zeolitic imidazolate framework, ZIF-67) by optimizing the annealing conditions. The resulting ZIF-derived carbon possesses highly graphitic walls and a high specific surface area of 350 m2·g–1, while the resulting ZIF-derived nanoporous Co3O4 possesses a high specific surface area of 148 m2·g–1 with much less carbon content (1.7 at%). When nanoporous carbon and nanoporous Co3O4 were tested as electrode materials for supercapacitor application, they showed high capacitance values (272 and 504 F·g–1, respectively, at a scan rate of 5 mV·s–1). To further demonstrate the advantages of our ZIF-derived nanoporous materials, symmetric (SSCs) and asymmetric supercapacitors (ASCs) were also fabricated using nanoporous carbon and nanoporous Co3O4 electrodes. Improved capacitance performance was successfully realized for the ASC (Co3O4//carbon), better than those of the SSCs bas...

Computational Intelligence: An Introduction

Abstract: The Artificial Intelligence field continues to be plagued by what can only be described as ‘bold promises for the future syndrome’, often perpetrated by researchers who should know better. While impartial assessment can point to concrete contributions over the past 50 years (such as automated theorem proving, games strategies, the LISP and Prolog high-level computer languages, Automatic Speech Recognition, Natural Language Processing, mobile robot path planning, unmanned vehicles, humanoid robots, data mining, and more), the more cynical argue that AI has witnessed more than its fair share of ‘unmitigated disasters’ during this time – see, for example [3,58,107,125,186]. The general public becomes rapidly jaded with such ‘bold predictions’ that fail to live up to their original hype, and which ultimately render the zealots’ promises as counter-productive.