scholarly journals Functional Materials Development from Kitchen Waste

2012 ◽  
Vol 16 ◽  
pp. 70-74 ◽  
Author(s):  
Fushen Zhang ◽  
Qianfang Wu
2019 ◽  
Vol 8 (4) ◽  
pp. 22 ◽  
Author(s):  
Matthias Steinbacher ◽  
Gabriela Alexe ◽  
Michael Baune ◽  
Ilya Bobrov ◽  
Ingmar Bösing ◽  
...  

The development of novel structural materials with increasing mechanical requirements is a very resource-intense process if conventional methods are used. While there are high-throughput methods for the development of functional materials, this is not the case for structural materials. Their mechanical properties are determined by their microstructure, so that increased sample volumes are needed. Furthermore, new short-time characterization techniques are required for individual samples which do not necessarily measure the desired material properties, but descriptors which can later be mapped on material properties. While universal micro-hardness testing is being commonly used, it is limited in its capability to measure sample volumes which contain a characteristic microstructure. We propose to use alternative and fast deformation techniques for spherical micro-samples in combination with classical characterization techniques such as XRD, DSC or micro magnetic methods, which deliver descriptors for the microstructural state.


Author(s):  
Huaiwei Shi ◽  
Teng Zhou

Abstract Functional materials are widely used in chemical industry in order to reduce the process cost while simultaneously increase the product quality. Considering their significant effects, systematic methods for the optimal selection and design of materials are essential. The conventional synthesis-and-test method for materials development is inefficient and costly. Additionally, the performance of the resulting materials is usually limited by the designer’s expertise. During the past few decades, computational methods have been significantly developed and they now become a very important tool for the optimal design of functional materials for various chemical processes. This article selectively focuses on two important process functional materials, namely heterogeneous catalyst and gas separation agent. Theoretical methods and representative works for computational screening and design of these materials are reviewed.


2015 ◽  
Vol 6 (10) ◽  
pp. 5347-5365 ◽  
Author(s):  
Zujin Zhao ◽  
Bairong He ◽  
Ben Zhong Tang

Recent advances in the structure–property relationship decipherment and luminescent functional materials development of AIE-active siloles are reviewed.


2021 ◽  
Author(s):  
MD Rajbanul Akhond ◽  
Ahmed Sharif

Bio-composites have diverse functional demands for many structural, electrical, electronic, and medical applications. An expansion of the composite functionality is achieved by manipulating the material and design scheme. Smart selection of matrix-reinforcement combinations will lead to applications that have never even been considered. Research holds a huge potential to create a wide variety of usable materials by mixing different fillers and modifying the parameters. Apart from selecting the polymer and the filler, the engineer will have to understand the compatibility of the polymer and the filler, dispersion, and bonding behavior making the design of polymer nanocomposite a rather complex system. In this chapter, we have tried to display different functional materials development pursuit.


2019 ◽  
Vol 5 (1) ◽  
Author(s):  
Yuma Iwasaki ◽  
Ryohto Sawada ◽  
Valentin Stanev ◽  
Masahiko Ishida ◽  
Akihiro Kirihara ◽  
...  

Abstract Machine learning is becoming a valuable tool for scientific discovery. Particularly attractive is the application of machine learning methods to the field of materials development, which enables innovations by discovering new and better functional materials. To apply machine learning to actual materials development, close collaboration between scientists and machine learning tools is necessary. However, such collaboration has been so far impeded by the black box nature of many machine learning algorithms. It is often difficult for scientists to interpret the data-driven models from the viewpoint of material science and physics. Here, we demonstrate the development of spin-driven thermoelectric materials with anomalous Nernst effect by using an interpretable machine learning method called factorized asymptotic Bayesian inference hierarchical mixture of experts (FAB/HMEs). Based on prior knowledge of material science and physics, we were able to extract from the interpretable machine learning some surprising correlations and new knowledge about spin-driven thermoelectric materials. Guided by this, we carried out an actual material synthesis that led to the identification of a novel spin-driven thermoelectric material. This material shows the largest thermopower to date.


2012 ◽  
Vol 27 (1) ◽  
pp. 18-23 ◽  
Author(s):  
Myriam Le Normand ◽  
Ulrica Edlund ◽  
Bjarne Holmbom ◽  
Monica Ek

Abstract Non-cellulosic polysaccharides (NCP) from bark offer large potential as a class of natural raw materials for functional materials development and production of biochemicals. We have elaborated a process for sequential extraction of NCP from industrial Norway spruce bark using an accelerated solvent extraction (ASE) with water at 100 to 160°C. Carbohydrates, Klason lignin and ash content as well as size-exclusion chromatography (SEC) analyses were performed for all hot-water extracts. NCP were mainly composed of glucose, arabinose and galacturonic acid units which revealed the presence of starch, arabinose-rich hemicelluloses and pectins. In total, the industrial bark of Norway spruce contained up to 20% of NCP which were extracted with pressurized hot water. NCP were mainly extractable at 140°C and started to undergo degradation at higher temperature.


Author(s):  
Tongyan Yu ◽  
Fei Ji ◽  
Daichuan Huang ◽  
Ya Gao ◽  
Zhaoping Shi ◽  
...  

Given the importance of pyrroles in pharmaceuticals, agrochemicals and functional materials, development of efficient strategies for their construction continues to be the hot area. Here, we present a novel BF3·Et2O...


2004 ◽  
Vol 14 (14) ◽  
pp. 2176-2188 ◽  
Author(s):  
Horst Böttcher ◽  
Ulrich Soltmann ◽  
Michael Mertig ◽  
Wolfgang Pompe

Author(s):  
Yoichi Ishida ◽  
Hideki Ichinose ◽  
Yutaka Takahashi ◽  
Jin-yeh Wang

Layered materials draw attention in recent years in response to the world-wide drive to discover new functional materials. High-Tc superconducting oxide is one example. Internal interfaces in such layered materials differ significantly from those of cubic metals. They are often parallel to the layer of the neighboring crystals in sintered samples(layer plane boundary), while periodically ordered interfaces with the two neighboring crystals in mirror symmetry to each other are relatively rare. Consequently, the atomistic features of the interface differ significantly from those of cubic metals. In this paper grain boundaries in sintered high-Tc superconducting oxides, joined interfaces between engineering ceramics with metals, and polytype interfaces in vapor-deposited bicrystal are examined to collect atomic information of the interfaces in layered materials. The analysis proved that they are not neccessarily more complicated than that of simple grain boundaries in cubic metals. The interfaces are majorly layer plane type which is parallel to the compound layer. Secondly, chemical information is often available, which helps the interpretation of the interface atomic structure.


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