Prefacedoi: 10.1088/1757-899X/647/1/011001pmid: N/A
2019 4th International Conference on Advanced Materials Research and Manufacturing Technologies (AMRMT 2019) was held in Oxford, UK during Aug. 8-11, 2019. AMRMT 2019 was organized by Hong Kong Society of Mechanical Engineers, supported by South China University of Technology and St Anne’s College, University of Oxford. The conference provides a useful and wide platform both for display the latest research and for exchange of research results and thoughts in Materials Research and Manufacturing Technologies and other topics. The participants of the conference were from almost every part of the world, with background of either academia or industry, even well-known enterprise. The success and prosperity of the conference is reflected high level of the papers received.The proceedings are a compilation of the accepted papers and represent an interesting outcome of the conference. This book covers 2 chapters: Materials Science; Manufacturing Technologies.We would like to acknowledge all of those who supported AMRMT 2019. Each individual and institutional help were very important for the success of this conference. Especially we would like to thank the organizing committee for their valuable advices in the organization and helpful peer review of the papers.We sincerely hope that AMRMT 2019 will be a forum for excellent discussions that will put forward new ideas and promote collaborative researches. We are sure that the proceedings will serve as an important research source of references and the knowledge, which will lead to not only scientific and engineering progress but also other new products and processes.Roderick Smith, Imperial College, UKAlan Kin-Tak Lau, Swinburne University of Technology, Australia
Peer review statementdoi: 10.1088/1757-899X/647/1/011003pmid: N/A
All papers published in this volume of IOP Conference Series: Materials Science and Engineering have been peer reviewed through processes administered by the proceedings Editors. Reviews were conducted by expert referees to the professional and scientific standards expected of a proceedings journal published by IOP Publishing.
Thermal Loading Effect During Machining of Borosilicate Glass Using ECDM ProcessArya, R K; Dvivedi, A
doi: 10.1088/1757-899X/647/1/012001pmid: N/A
Glass has unique properties for micro fluidic, MEMS and optical applications. However, poor machinability of glass materials limit its applications. ECDM process is one of the most utilized micro machining process for fabrication of glass micro products. In ECDM thermal energy of discharges utilizes to provide thermal loading for removal of material. However, controlled thermal loading requires for machining of glass materials owing to its poor thermal conductivity. High thermal stresses may develop at high thermal loading, which leads to uncontrolled facture of glass material. Therefore, a thorough discussion is needed to understand the effect of thermal loading on glass materials. In this study, the experiments are conducted to investigate the thermal loading effect on borosilicate glass during ECDM process. Also, an analytical model is developed to estimate the induced thermal stress during ECDM process. Theses thermal stresses are discussed during drilling of micro hole on work material. After discussion three zones are identified for machining of borosilicate glass using ECDM process, wherein zone-II (i.e. from 44 V to 52 V applied voltage) is identified for safe machining.
Improvement in Machined Surface with the use of Powder and Magnetic Field Assisted on Machining Aluminium 6061 Alloy with EDMRouniyar, Arun Kumar; Shandilya, Pragya
doi: 10.1088/1757-899X/647/1/012002pmid: N/A
Surface characteristics are the major challenges faced by the manufacturing industry when materials are machined with electrical discharge machining. Magnetic Field assisted powder mixed electrical discharge machining (MFAPM-EDM) is hybrid machining process which has shown the good potential of improving the surface characteristics. In this present paper, machining of aluminium 6061 alloy was carried out with aluminium powder mixed in EDM oil and in presence of magnetic field using EDM process Magnetic field, spark on duration, spark off duration, pulse current and powder concentration were selected as variable machining parameters and surface roughness as a response. Box-Behnken design approach based on response surface methodology was used for performing the experiments. In the present analysis, current was observed as the most significant parameter followed by spark on duration, powder concentration and magnetic field on surface roughness. Improvement in surface roughness with lesser voids and craters were observed under the influence of magnetic field and aluminium powder mixed in EDM oil.
Preparation of Carbon Encapsulated Magnetic FeCo Alloy Nanoparticles Supported on Carbon Nanotubes for Enhanced Microwave AbsorptionYuan, Guanming; Su, Yong; Cui, Zhengwei; Dong, Zhijun; Li, Xuanke
doi: 10.1088/1757-899X/647/1/012003pmid: N/A
A mixture of multi-walled carbon nanotubes in an ethanol solution of Fe(NO3)3.9H2O and Co(NO3)2.6H2O, were used to prepare an Fe2O3-CoO catalyst supported on carbon nanotubes by a supercritical fluid drying method. The carbon encapsulated FeCo nanoparticles were prepared by the catalytic decomposition of methane over the catalyst at 850°C for 30 mins. The morphology and microstructure of the catalyst and carbon encapsulated nanoparticles (CEP) were characterized by XRD, FESEM, EDS and TEM analyses. The electromagnetic characteristics and microwave absorption properties of the CEP product were also studied. Results show that the CEP product possesses high complex permittivity and good permeability in the microwave frequency range from 2 to 18 GHz. The maximum absorption peak was observed at 9.44 GHz for a large reflection loss (R) of 13.3 dB, with a band width of 7.4 GHz and 2.56 GHz, at R <- 5 dB and R <- 10 dB, respectively.
Using Deep Neural Networks to Predict the Tensile Property of Ceramic Matrix Composites Based on Incomplete Small DatasetXiang, GAO; Guanghui, LI; Rong, TAN; Leijiang, YAO
doi: 10.1088/1757-899X/647/1/012004pmid: N/A
It has been a hot spot in the area of material science that how to design an experiment to produce a kind of ceramic matrix composites (CMCs) which possesses ideal performances. An approach is to build models with data from previous experiments recorded in published papers and predict the experiment parameters needed by the ideal CMCs. According to the database of CMCs funded by the National Material Genome Engineering, 8 factors were considered to affect the tensile property of CMCs, which were the basis, the reinforcement fiber type, the reinforcement fiber volume content, the perform type, the porosity, the interface type, the interface thickness and the density. Among the data we collected from papers, however, only few of pieces contained all the 8 factors, most were incomplete, some of them even lacked multiple factors. This paper’s work mainly researched how to take advantage of the incomplete data to build an effective model to predict the tensile property of CMCs. We proposed a model to predict the tensile property of CMCs based on a 1-D convolution neural network (CNN), the training data of which were all from papers. To decrease the influences of the incompleteness of data, we tried several methods to process the missing data, such as the mean imputation, the K-Means clustering imputation, the Hot-Deck Imputation and the regression imputation. The results showed that the regression imputation with a dual-hidden-layer feedforward network performed better and improved the performance of the CNN tensile property prediction model.
A Novel Coupler Design and Analysis with Shielding Material Tests for a CPT System of Electric Vehicles Based on Electromagnetic Resonant CouplingDuan, J; Wang, W
doi: 10.1088/1757-899X/647/1/012005pmid: N/A
In this paper, a contactless power transfer (CPT) system using a novel geometrically enhanced energy transfer coupler with three different shielding materials has been built and analysed, along with the evaluations from aspects of electromagnetics and RMS power transmitting based on electromagnetic resonant coupling. A CPT system design improvement with the proposed H-shape ferromagnetic cores and the combined semi-enclosed passive electromagnetic shielding methods have been investigated in terms of generated electromagnetic field characteristics, system power transfer ratings, system efficiency optimization and performances of shielding materials. The results have shown that, across the range of operating frequency of the CPT system, aluminium shielding as a metallic material method could deliver better overall CPT system performance than other two ferromagnetic materials, steel 1010 and ferrite. In addition, the coupler prototype design limitations, misalignment tolerance and the passive shielding design considerations including distance between windings and inner surfaces of shielding shells have been discussed.
Modeling the Electrical Conductivity of Ni1-xFex-SDC Composite Anode by Using PSO-SVRTang, J. L; Yang, R. F
doi: 10.1088/1757-899X/647/1/012006pmid: N/A
Studies have shown that numerous indexes affecting the electrical conductivity of Solid Oxide Fuel Cell (SOFC) anode. In order to improve performance of SOFC, it is advantageous to have a model with which one can modeling the electrical conductivity at different operating conditions. In this study, a model utilizing support vector regression (SVR) approach combined with particle swarm optimization (PSO), was proposed to modeling the electrical conductivity of Ni1-xFex(0⩽x⩽0.25)-Ce0.85Sm0.15O2-δ(SDC) composite anode. The test result by PSO-SVR show that the root mean square error (RMSE) of test samples is 3.79, mean absolute percentage error (MAPE) of test samples is 0.82%, multiplecorrelation correlation coefficients (R2) of test samples is 1.00, which is satisfied with the engineering demand. The result of this investigation provides that PSO-SVR is an effective tool for modeling the electrical conductivity of Ni1-xFex-SDC composite anode.
Mechanism and Research on Preparation of AlN Powder by Carbon Thermal Reduction MethodWang, L Y; Zhang, N
doi: 10.1088/1757-899X/647/1/012007pmid: N/A
The alumina and activated carbon used as raw materials were prepared by chemical precipitation method. The uniformed aluminum nitride precursor was synthesized by mechanical mixing process. The effects of nitride temperature and time on the diameter of the particle were studied in detail. Ultrafined aluminum nitride powder was prepared by carbon-thermal reduction method. The results show that the precursor has better activity and nitride reaction proceeds rapidly. The complete conversion can be got at 1600°C for 2h. After calcination, it can be seen from the XRD graph that the powder with uniform size distribution has high AlN content.