Nano Hybrids and Composites Vol. 34

Erscheinungsjahr 2022
ISBN: 978-3-0357-1808-9
Verlag: Trans Tech Publications

Buch, Englisch, 98 Seiten, Format (B × H): 170 mm x 240 mm, Gewicht: 310 g

This volume represents research results and engineering solutions in area of Nanomaterials, Semiconductor, Thin Film, Nanocoating, Metal-Organic Framework, Composite, Microwave Absorber, Density Functional Theory, Alloy, Lithium, Solid Electrolyte, Polymer

Autoren/Hrsg.

Singhal, Subhash C.

Wang, Zhi Xin

Fachgebiete

• Technische Wissenschaften Maschinenbau | Werkstoffkunde Technische Mechanik | Werkstoffkunde Materialwissenschaft: Biomaterialien, Nanomaterialien, Kohlenstoff
• Technische Wissenschaften Maschinenbau | Werkstoffkunde Technische Mechanik | Werkstoffkunde Materialwissenschaft: Elektronik, Optik
• Technische Wissenschaften Technik Allgemein Nanotechnologie
• Technische Wissenschaften Maschinenbau | Werkstoffkunde Technische Mechanik | Werkstoffkunde Materialwissenschaft: Verbundwerkstoffe

Inhaltsverzeichnis

Preface
Chapter 1: Materials for Energy Storage
Optimized Lithium-Indium Chloride Solid Electrolyte for High Energy All-Solid-State Batteries
MXenes Composites as the Protective Layer for Li Metal Electrodes
Chapter 2: Composite Materials
Synthesis of Titanium-Based Composites by Pulsed Methods
The Co-Poly(Urethane-Imide) Heat Resistant Thermoplastic Elastomers
Microstructure Evolution at High Temperatures for Co-MOF-74 as High-Efficiency Electromagnetic Absorbers
Bond Behaviour of Treated Natural Fibre in Concrete
Chapter 3: Multifunctional Materials
Fabrication of Fluorite and Perovskite Functional Films by Solution Spray Pyrolysis
Controllable Modification and Synthesis of Intelligent Nanomaterials: A Brief Review
Preparation and Cavilation Erosion Resistance of High Strength Nanocoating Cylinder Liner
Chapter 4: Computational Materials Science
Bandgap Modulation of the C2N-h2D Nanomaterials under Elastic Strains
First-Principal Investigation of Lattice Constants of Si1-xGex, Si1-xSnx and Ge1-xSnx
The Investigation of Lattice Properties for Group-IV Sigesn Ternary Alloy: By Using Machine Learning Method