Papers by Keyword: Material Science

Abstract: Machine learning (ML) has recently made a major contribution to the fields of Material Science (MS). In this study, ML algorithms are used to learn atoms types over structural geometrical data of anatase TiO₂ nanoparticles produced at different temperature levels with the density-functional tight-binding method (DFTB). Especially for this work, Random Forest (RF), Decision Trees (DT), K-Nearest Neighbor (KNN), Naïve Bayes (NB), which are among the most popular ML algorithms, were run to learn titanium (Ti) and oxygen (O) atoms. RF outperforms other algorithms, almost succeeding in learning this skewed data set close to perfect. The use of ML algorithms with datasets compatible with its mathematical design increases their learning performance. Therefore, we find it remarkable that a certain type of ML algorithm performs almost perfectly. Because it can help material scientists predict the behavior and structural and electronic properties of atoms at different temperatures.

Abstract: This study used 700 children under the age of 11 as the research target for materials science introduces disaster prevention and mitigation education. The purpose of this study is to training and popularize the scientific knowledge literacy of disaster prevention, and to design disaster prevention and mitigation education through the diversity of material science. This study will carry out the learning outcome experiment of scientific concept and spontaneous concept into the disaster prevention science popularization education. Hope to study through teacher training courses, life science practice activities and digital learning application experiments. The study integrates material science disaster prevention course and campus science education, and 15 material science experiments were planned to be applied to the evaluation of the learning outcome of disaster prevention and mitigation experiments. Before the experiment, teachers were guided by disaster prevention science education, and after 12-year-old children relayed the principles of science, they assisted 6 to 11-year-old students to operate materials science experiments and analyze the learning outcome. Through simple teaching design and multi-level pre-teaching can effective promotion 36.5% of student's interest in material science used in the field of disaster prevention and mitigation, and by 73% of student aged 9 to 11, they can be more effectively improved the strategy and purpose of disaster prevention and mitigation education by dictation of their disaster prevention and mitigation education related to family, peers and living environment.

Abstract: This chapter provides information in the area of vegetable fiber-reinforced polymer composites. It includes discussion about definition and classification of the composites and their constituents, composite manufacturing process and current application in different industrial sectors. Factors affecting the fiber/matrix interfacial adhesion and physic-chemical and mechanical properties of vegetable fiber-reinforced polymer composites are also revealed. The aim is to show for both academy and industry the viability on the use of vegetable fibers as reinforcement in polymer materials, because it offers many advantages and high potential in terms of unlimited availability, lightweight, reasonable cost, acceptable mechanical properties, and socio-economic and environmental benefits.

Abstract: The functional requirements of lower extremity paediatric prostheses in developing regions and the materials used in the manufacture thereof is presented in this paper. Specific advantages and disadvantages of materials used in relation to the African paediatric amputee are highlighted. The paper examines the critical issues for which further research and development is needed into material and manufacture tailoring to meet the functional requirements of a paediatric prosthetic. The applicability of light metal alloys in meeting these requirements is emphasised.

Abstract: The potential to control the final properties, as measured by density, strength and microstructure, of press-and-sintered titanium and master alloy Ti-6Al-4V is investigated by designing and evaluating bimodal particle size distributions of the relevant powders. Ratios of 1/3, 2/3 and 1/1 by volume of coarse to fine powders, as determined by particle size peaks, were blended from -200 and -100 mesh commercially pure titanium powders and -200 mesh 60Al-40V master alloy powder, in the case of Ti-6Al-4V. The powder blends were uniaxially compacted at 350, 400 and 450 MPa, and the green specimens were sintered under high vacuum for two hours at 1300°C. The results support theoretical prediction of green and sintered density based on the ratio of the volume percentage of coarse to fine powder; green density increases as the ratio of coarse powder increases for both the pure and alloy titanium, while the sinter density similarly decreases for the pure titanium. Microstructural observations of the sintered specimens show that the pore size decreases, and the pore shape becomes more rounded, as the ratio of fine powder increases. In order to extend the study to find the optimal packing ratio, and potentially the optimal blend for densification, further refinement of the initial powder particle size distributions is needed.

Abstract: The aim of the paper is to demonstrate, how artificial intelligence methods, especially genetic ones, naturally combine with problems of material science. On the example of modelling a function showing how carbon concentration in steel changes its hardness it was shown how modern artificial intelligence methods can easily be adapted for solving problems of modern science. The paper presents the possibility of applying genetic programming to model properties of the steel.

Abstract: The equipment for plasma processing with specific area of application – production of building materials – is proposed. For the proposed equipment the examination of possibilities is carried out. It was shown that plasma processing significantly affects the components of concrete – portland cement, fine filler (silica) and water. The treatment of portland cement leads to crystalline hydrate shell destruction and removal of chemically bound water. This, in turn, leads to the increase of strength by 15-20%. Plasma processing significantly changes the state of the fine filler. The total surface area of such a filler decreases due to flash-off effects. In Raman spectra all strong peaks of crystalline quartz disappear, and amorphization of quartz takes place after processing. If both cement and fine filler are processed than strength can be increased by 30%. By means of plasma processing of water it is possible not only to enlarge the strength of mortar, but also to increase the rate of curing. The improvement of properties is probably due to changes of hydration completeness in case of activated water.

Abstract: In material science the simultaneous application of theoretical examination, experimental and numerical studies are often required. This is especially true for modern composite materials with extra inter-boundary nanoscale layers. Thickness of layers is usually about tens of nanometers, while diameters of particles of filler are about several hundreds of nanometers. Thus, during the theoretical study and numerical experiments the size and properties of inter-boundary layer must be taken into account. The proper choice of the model is the key factor for the adequate results of simulation. In the present work we have derived such a model. The system under investigation – disperse-filled composite material with inter-boundary layers of different properties – is represented by particle system; these classes of models can be characterized by high generality. Initial equation for the law of motion is sequentially extended with terms which account for different phenomena – conservative binary interaction, non-conservative interaction with environment, interaction with planar boundaries and non-conservative particle-particle interaction via inter-boundary layer. The reduction of the law of motion to the system of ordinary differential equations had opened the possibility for utilization of the vast majority of numerical algorithms for the prediction of the structural properties of nanomodified sulfur-based composite.

Abstract: Nowadays, reducing energy consumption, using clean resources and the aim of creating net-zero building are going to be more and more important. It seems that use of recombinant materials may be a way to reach a more energy efficient architecture. There are considerable advances in development of new material, while the use of these materials is limited in architecture. Regarding to hypothesis of the research, identification of new materials, their performance and their properties, which cause decrease in energy consumption may be helpful for development a more energy efficient architecture. The results of the paper show that architects may incorporate recombinant material to reach energy efficient buildings, however they can play a crucial role in saving natural energy resources through adoption of recombinant materials in architecture and planning

Abstract: Escalating the operational actions in construction demands the development of building materials with improved properties. Today, the nanomodified and nanostructured materials (also called nanocomposites) attract great attention of the scientists all over the world. The successful development of nanocomposites requires simultaneous application of theoretical examination, experimental investigations and numerical studies. In the present work we provide short review of the simulation methods involving particle systems as a materials model and also discuss several results obtained during numerical studies of building materials by means of using such methods. It is noted that neither the single mathematical model, nor the only one simulation method can be used for modeling of building material at all levels of scale (from macroscopic down to nanoscale). However, some models and numerical methods are still quite general. Thus, they can be utilized for modeling a very wide range of phenomena from compaction process at macroscopic level to reinforcement regularities at micro-and nanoscale. The obtained results both offers the insight into regularities of structure forming process and allow to reduce time and cost of the design.