Local Electrical Stress-Induced Doping and Formation of 2D Monolayer Graphene P-N Junction

We demonstrated doping in 2D monolayer graphene via local electrical stressing. The doping, confirmed by the resistance-voltage transfer characteristics of the graphene system, is observed to continuously tunable from N-type to P-type as the electrical stressing level (voltage) increases. Two major physical mechanisms are proposed to interpret the observed phenomena: modifications of surface chemistry for N-type doping (at low-level stressing) and thermally-activated charge transfer from graphene to SiO2 substrate for P-type doping (at high-level stressing). The formation of P-N junction on 2D graphene monolayer is demonstrated with complementary doping based on locally applied electrical stressing.Comment: 12 pages, 4 figure

Ionic Liquids for High Performance Solid-state Lithium Metal Batteries

The quest for high energy storages has driven the growth of high-performance lithium metal batteries, but this has also raised serious safety concerns. In response, ionic liquids (ILs) have become a popular choice due to their high ionic conductivity, non-flammability, and ability to facilitate the formation of stable solid electrolyte interphase (SEI) layer. Understanding the challenges faced by lithium metal batteries and the role of ILs in them is vital to improving their performance. This study examines how ILs affect key factors such as ionic conductivity, Li⁺ ion transference number, electrochemical stability window, and the lithium metal anode/electrolyte interface. It also investigates the use of ILs with different types of cathodes, such as, including LiFePO4 (LFP), LiNi0.6Co0.2Mn0.2O2 (NCM622), LiNi0.8Co0.1Mn0.1O2 (NCM811), and LiCoO2 (LCO). A comparative study was made on the development of ionic liquid involved solid-state electrolyte to achieve high performance solid-state lithium metal batteries. Three key aspects are addressed in this thesis: Firstly, an ionic liquid was injected into metal-organic framework (MOF-5) nanomaterials to improve the poly(ethylene oxide) (PEO) solid electrolyte and enhance the performance of solid- state lithium batteries. The results show that the formed nano-wetted interface structure can greatly improve the interface stability, reduce the interface impedance, and inhibit the Li dendrite growth. The MOF structure accelerates the transport of lithium ions by ion confinement effect on anions inn the IL and large-size cations, thereby improving the lithium transference number. As a consequence, the overall performance of solid solid-state Li metal battery has been improved. Secondly, using electrospun polyacrylonitrile PAN membranes, the ionic liquid and liquid electrolyte monomers are combined and in situ polymerized to form a polymer electrolyte. In this system, the decomposition of the ionic liquid is involved in the formation of the solid electrolyte interface ( SEI mem brane. Through analysis at different current densities of the Li symmetric cell , it was found that the ionic liquid can significantly suppress the formation and growth of lithium dendrites. Moreover, due to the increased lithium affinity of the ionic liqui d, Li ion transport is accelerated, resulting in a high lithium transference number, which improves conductivity and allows the battery performing within a wide temperature range. Additionally, L i F e P O 4 /Li batteries can run steadily for 100 0 cycles at high rate of 2 C. T hirdly, through the combined action of fluorine containing additives and ionic liquids, the in situ formed polymer lithium battery can operate stably at high voltage. Analysis has shown that the SEI membrane in this system is rich in LiF, whi ch effectively increases interface stability. The ionic liquid enhances the electrochemical window of the polymer electrolyte, allowing this system to match high voltage cathodes. Moreover, IL is beneficial to improve the interfacial contact and provide st able components for the interfacial layer. Results show that at room temperature, the NCM811/cell can perform at 1C, and the LCO/Li cell has good cycling performance at 4.45 V, increasing the battery energy capacity. This project contributes to the understanding of the application of ionic liquids in solid state electrolytes, the knowledge of which can be used to design the solid state electrolyte. The chemical compositions of the SEI layers formed on the surface of Li anode from this experimental work also provide valuable data that can be used in the future studiesThesis (Ph.D.) -- University of Adelaide, School of Chemical Engineering and Advanced Materials, 202

Tribological properties of calcium carbonate powders modified with Tween 40 as lubricant additives

In this experiment, nanometer calcium carbonate was prepared by metathesis method. The nanometer calcium carbonate was modified by non-ionic surfactant-tween 40. The nanometer calcium carbonate before and after modification was analyzed and characterized by various methods. Scanning electron microscope (SEM) result show the size of the unmodified nano-calcium carbonate is about 200-400nm, while the particle size of the modified particles is about 200 nanometers. Contact angle indicate that CаCO₃ powders become hydrophobic after modified. Moreover the friction and wear properties of Tween 40-CаCO₃ as lubricant additives in rapeseed oil were evaluated with a four-ball friction and wear tester. Tween 40-CаCO₃ could improve the anti-wear and friction reducing capacities of rapeseed oil can conclude from the friction results. X-ray photoelectron spectroscope of worn steel surfaces indicated that an absorption film containing rapeseed oil and 40-CаCO₃ was formed

Induction of accurate and interpretable fuzzy rules from preliminary crisp representation

This paper proposes a novel approach for building transparent knowledge-based systems by generating accurate and interpretable fuzzy rules. The learning mechanism reported here induces fuzzy rules via making use of only predefined fuzzy labels that reflect prescribed notations and domain expertise, thereby ensuring transparency in the knowledge model adopted for problem solving. It works by mapping every coarsely learned crisp production rule in the knowledge base onto a set of potentially useful fuzzy rules, which serves as an initial step towards an intuitive technique for similarity-based rule generalisation. This is followed by a procedure that locally selects a compact subset of the emerging fuzzy rules, so that the resulting subset collectively generalises the underlying original crisp rule. The outcome of this local procedure forms the input to a global genetic search process, which seeks for a trade-off between accuracy and complexity of the eventually induced fuzzy rule base while maintaining transparency. Systematic experimental results are provided to demonstrate that the induced fuzzy knowledge base is of high performance and interpretabilitypublishersversionPeer reviewe

Exploiting Data Reliability and Fuzzy Clustering for Journal Ranking

This is the author accepted manuscript. The final version is available from IEEE Computational Intelligence Society via http://dx.doi.org/10.1109/TFUZZ.2016.2612265Journal impact indicators are widely accepted as possible measurements of academic journal quality. However, much debate has recently surrounded their use, and alternative journal impact evaluation techniques are desirable. Aggregation of multiple indicators offers a promising method to produce a more robust ranking result, avoiding the possible bias caused by the use of a single impact indicator. In this paper, fuzzy aggregation and fuzzy clustering, especially the Ordered Weighted Averaging (OWA) operators are exploited to aggregate the quality scores of academic journals that are obtained from different impact indicators. Also, a novel method for linguistic term-based fuzzy cluster grouping is proposed to rank academic journals. The work allows for the construction of distinctive fuzzy clusters of academic journals on the basis of their performance with respect to different journal impact indicators, which may be subsequently combined via the use of the OWA operators. Journals are ranked in relation to their memberships in the resulting combined fuzzy clusters. In particular, the nearest-neighbour guided aggregation operators are adopted to characterise the reliability of the indicators, and the fuzzy clustering mechanism is utilised to enhance the interpretability of the underlying ranking procedure. The ranking results of academic journals from six subjects are systematically compared with the outlet ranking used by the Excellence in Research for Australia (ERA), demonstrating the significant potential of the proposed approach.publishersversionPeer reviewe