The inherent disadvantages of traditional nonflexible aerogels, such as high fragility and moisture sensitivity, severely restrict their applications. To address these issues, different techniques have been used to incorporate the flexibility in aerogel materials; hence, the term "flexible aerogels" was introduced. In the case of introducing flexibility, the organic part is induced with the inorganic part (flexible hybrid aerogels). Additionally, some more modern research is also available in the fabrication of hybrid flexible aerogels (based on organic-organic), the combination of two organic polymers. Moreover, a new type (single-component flexible aerogels) are quite a new category composed of only single materials; this category is very limited, charming to make the flexible aerogels pure from single polymers. The present review is composed of modern techniques and studies available to fabricate hybrid and single-component flexible aerogels. Their synthesis, factors affecting their parameters, and limitations associated with them are explained deeply. Moreover, a comparative analysis of drying methods and their effectiveness in the development of structures are described in detail. The further sections explain their properties and characterization methods. Eventually, their applications in a variety of multifunctional fields are covered. This article will support to introduce the roadmap pointing to a future direction in the production of the single-component flexible aerogel materials and their applications.

• Publikační typ
• časopisecké články MeSH

This paper introduces a novel technique to evaluate comfort properties of zinc oxide nanoparticles (ZnO NPs) coated woven fabrics. The proposed technique combines artificial neural network (ANN) and golden eagle optimizer (GEO) to ameliorate the training process of ANN. Neural networks are state-of-the-art machine learning models used for optimal state prediction of complex problems. Recent studies showed that the use of metaheuristic algorithms improve the prediction accuracy of ANN. GEO is the most advanced methaheurstic algorithm inspired by golden eagles and their intelligence for hunting by tuning their speed according to spiral trajectory. From application point of view, this study is a very first attempt where GEO is applied along with ANN to improve the training process of ANN for any textiles and composites application. Furthermore, the proposed algorithm ANN with GEO (ANN-GEO) was applied to map out the complex input-output conditions for optimal results. Coated amount of ZnO NPs, fabric mass and fabric thickness were selected as input variables and comfort properties were evaluated as output results. The obtained results reveal that ANN-GEO model provides high performance accuracy than standard ANN model, ANN models trained with latest metaheuristic algorithms including particle swarm optimizer and crow search optimizer, and conventional multiple linear regression.

• MeSH
• Accipitridae * MeSH
• algoritmy MeSH
• neuronové sítě MeSH
• oxid zinečnatý * MeSH
• propylaminy MeSH
• sulfidy MeSH
• textilie MeSH
• zvířata MeSH
• Check Tag
• zvířata MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• Názvy látek
• 1-(4-methylthiophenyl)-2-aminopropane MeSH Prohlížeč
• oxid zinečnatý * MeSH
• propylaminy MeSH
• sulfidy MeSH

In this study, an artificial neural network (ANN) is used for the prediction of tensile strength of nano titanium dioxide (TiO2) coated cotton. The coating process was performed by ultraviolet (UV) radiations. Later on, a backpropagation ANN algorithm trained with Bayesian regularization was applied to predict the tensile strength. For a comparative study, ANN results were compared with traditional methods including multiple linear regression (MLR) and polynomial regression analysis (PRA). The input conditions for the experiment were dosage of TiO2, UV irradiation time and temperature of the system. Simulation results elucidated that ANN model provides high performance accuracy than MLR and PRA. In addition, statistical analysis was also performed to check the significance of this study. The results show a strong correlation between predicted and measured tensile strength of nano TiO2-coated cotton with small error values.

• Klíčová slova
• artificial neural network, tensile strength, titanium dioxide nanoparticles,
• Publikační typ
• časopisecké články MeSH

The term aerogel is used for unique solid-state structures composed of three-dimensional (3D) interconnected networks filled with a huge amount of air. These air-filled pores enhance the physicochemical properties and the structural characteristics in macroscale as well as integrate typical characteristics of aerogels, e.g., low density, high porosity and some specific properties of their constituents. These characteristics equip aerogels for highly sensitive and highly selective sensing and energy materials, e.g., biosensors, gas sensors, pressure and strain sensors, supercapacitors, catalysts and ion batteries, etc. In recent years, considerable research efforts are devoted towards the applications of aerogels and promising results have been achieved and reported. In this thematic issue, ground-breaking and recent advances in the field of biomedical, energy and sensing are presented and discussed in detail. In addition, some other perspectives and recent challenges for the synthesis of high performance and low-cost aerogels and their applications are also summarized.

• Klíčová slova
• aerogels, catalysts, porous materials, sensors, silica aerogels,
• Publikační typ
• časopisecké články MeSH
• přehledy MeSH