Recent advances on high performance machining of aerospace materials and composites using vegetable oil-based Metal Working Fluids

2021 ◽  
pp. 127459
Author(s):  
K.C. Wickramasinghe ◽  
Hiroyuki Sasahara ◽  
E.A. Rahim ◽  
G.I.P. Perera
2011 ◽  
Vol 115 (8) ◽  
pp. 3410-3415 ◽  
Author(s):  
J. Samuel ◽  
J. Rafiee ◽  
P. Dhiman ◽  
Z.-Z. Yu ◽  
N. Koratkar

2021 ◽  
Vol 3 (1) ◽  
Author(s):  
Yanting Han ◽  
Jinlian Hu ◽  
Gang Sun

Abstract During nature evolution process, living organisms have gradually adapted to the environment and been adept in synthesizing high performance structural materials at mild conditions by using fairly simple building elements. The skin, as the largest organ of animals, is such a representative example. Conferred by its intricate organization where collagen fibers are arranged in a randomly interwoven network, skin collagen (SC), defined as a biomass derived from skin by removing non-collagen components displays remarkable performance with combinations of mechanical properties, chemical-reactivity and biocompatibility, which far surpasses those of synthetic materials. At present, the application of SC in medical field has been largely studied, and there have been many reviews summarizing these efforts. However, the generalized view on the aspects of SC as smart materials in non-medical fields is still lacking, although SC has shown great potential in terms of its intrinsic properties and functionality. Hence, this review will provide a comprehensive summary that integrated the recent advances in SC, including its preparation method, structure, reactivity, and functionality, as well as applications, particularly in the promising area of smart materials. Graphical abstract


Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4425
Author(s):  
Ana María Pineda-Reyes ◽  
María R. Herrera-Rivera ◽  
Hugo Rojas-Chávez ◽  
Heriberto Cruz-Martínez ◽  
Dora I. Medina

Monitoring and detecting carbon monoxide (CO) are critical because this gas is toxic and harmful to the ecosystem. In this respect, designing high-performance gas sensors for CO detection is necessary. Zinc oxide-based materials are promising for use as CO sensors, owing to their good sensing response, electrical performance, cost-effectiveness, long-term stability, low power consumption, ease of manufacturing, chemical stability, and non-toxicity. Nevertheless, further progress in gas sensing requires improving the selectivity and sensitivity, and lowering the operating temperature. Recently, different strategies have been implemented to improve the sensitivity and selectivity of ZnO to CO, highlighting the doping of ZnO. Many studies concluded that doped ZnO demonstrates better sensing properties than those of undoped ZnO in detecting CO. Therefore, in this review, we analyze and discuss, in detail, the recent advances in doped ZnO for CO sensing applications. First, experimental studies on ZnO doped with transition metals, boron group elements, and alkaline earth metals as CO sensors are comprehensively reviewed. We then focused on analyzing theoretical and combined experimental–theoretical studies. Finally, we present the conclusions and some perspectives for future investigations in the context of advancements in CO sensing using doped ZnO, which include room-temperature gas sensing.


2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Mehdi Srifi ◽  
Ahmed Oussous ◽  
Ayoub Ait Lahcen ◽  
Salma Mouline

AbstractVarious recommender systems (RSs) have been developed over recent years, and many of them have concentrated on English content. Thus, the majority of RSs from the literature were compared on English content. However, the research investigations about RSs when using contents in other languages such as Arabic are minimal. The researchers still neglect the field of Arabic RSs. Therefore, we aim through this study to fill this research gap by leveraging the benefit of recent advances in the English RSs field. Our main goal is to investigate recent RSs in an Arabic context. For that, we firstly selected five state-of-the-art RSs devoted originally to English content, and then we empirically evaluated their performance on Arabic content. As a result of this work, we first build four publicly available large-scale Arabic datasets for recommendation purposes. Second, various text preprocessing techniques have been provided for preparing the constructed datasets. Third, our investigation derived well-argued conclusions about the usage of modern RSs in the Arabic context. The experimental results proved that these systems ensure high performance when applied to Arabic content.


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