**3-D Metal - Non-Metal Matrix**

*Lourduraj Stephen's* chapter has involved research to improve performance of 3-D metal-non-metal matrixes obtained through nano-technologically induced skeletal

**V**

optimization problems.

**2D-2D Metal - Non-Metal Matrix**

reinforcement. Recently varied metal/non-metal matrixes are fabricated with distinctive features such as super-porosity, non-biodegradability, flexible shape/size, and great surface area viable for superior applicability. In this regard, the author has controlled morphology of 3-D nanotitania to yield 7.7 nm dimension particles being smaller than commercially offered nanotitania of 25 nm ranges. This chapter gives an overview of titanium dioxide nano-crystalline material with particular porosity, pore-size distribution, and nature of pores being modified via in-situ synthetic conditions. The author has optimized certain preparative parameters in the making of 3-D nanotitania films apt to deliver superior performances in optical, structural, and electrical fields alongside photo-anode usage in solar cells due to native photo-

*Marta Michalska-Domańska's* chapter describes the surface-sensitive enhancement of Raman scattering by molecules being adsorbed onto nanostructures and how enhancement is sufficiently able to detect even a single molecule. Surface-enhanced Raman spectroscopy (SERS) strategically offers broad applicability in various fields, yet native progress is limited due to substrates used in SERS and their impeding characters such as less sensitivity, stability and repeatability with high reproducibility. Commercially available SERS substrates have an enhancement factor in

over the substrate's morphology at the nano-scale. In this overview, the author has summarized certain anodic oxides derived nano-composite substrates to be used in SERS analytical technique. The preferred substrates for SERS analysis must have unique features such as homogeneous nano-structures, large surface areas, and self-cleaning to perform analysis with utmost accuracy and precision. The author has exposed many challenges involved in improvement of SERS substrates besides focusing on minimizing native drawbacks. Nowadays porous anodic oxides are obtained through cheap and scalable methodologies; this chapter cited some progressive SERS substrates and briefly compared these with conventional substrates.

*Thankam Sreekumar Rajesh's* chapter investigated Al2O3-40% TiO2 powder blend for atmospheric plasma spray coating onto SS316 stainless steel to be used in manufacturing of jigs, guides, shafts, and fixtures. They utilize the teaching learning-based optimization (TLBO) algorithm to optimize input parameters and to find the best output parameters beside conducted confirmation tests, which gave the same values as predicted without significant error. Three levels L18 orthogonal array (OA) design of experiments (DoE) is applied to conduct this research study. The main input parameters measured included: nozzle distance, substrate speed, arc-current, carrier gas flow, and coating powder flow and the output parameters involved were: coating thickness, micro-hardness surface roughness, abrasion rate, and % porosity. Further mathematical models were made for each output parameter. Analytical hierarchy process was used to get weights for unit output parameters with generated objective and combined objective functions through the TLBO algorithm (global optimum values of input parameters and all the output parameters obtained simultaneously). The TLBO algorithm is easy and helpful to solve many multi-objective

The research group of *K. Bhuvaneswari* intercalated organic matrixes such as 2-D graphitic carbon nitrides (g-C3N4) into LDHs to get a blend of organic matrixes being used as a photo-catalyst for degradation of methylene-blue dye from aqueous

besides possessing partial durability by virtue of little control

electric/photovoltaic significance.

–107

the range of 105

reinforcement. Recently varied metal/non-metal matrixes are fabricated with distinctive features such as super-porosity, non-biodegradability, flexible shape/size, and great surface area viable for superior applicability. In this regard, the author has controlled morphology of 3-D nanotitania to yield 7.7 nm dimension particles being smaller than commercially offered nanotitania of 25 nm ranges. This chapter gives an overview of titanium dioxide nano-crystalline material with particular porosity, pore-size distribution, and nature of pores being modified via in-situ synthetic conditions. The author has optimized certain preparative parameters in the making of 3-D nanotitania films apt to deliver superior performances in optical, structural, and electrical fields alongside photo-anode usage in solar cells due to native photoelectric/photovoltaic significance.

*Marta Michalska-Domańska's* chapter describes the surface-sensitive enhancement of Raman scattering by molecules being adsorbed onto nanostructures and how enhancement is sufficiently able to detect even a single molecule. Surface-enhanced Raman spectroscopy (SERS) strategically offers broad applicability in various fields, yet native progress is limited due to substrates used in SERS and their impeding characters such as less sensitivity, stability and repeatability with high reproducibility. Commercially available SERS substrates have an enhancement factor in the range of 105 –107 besides possessing partial durability by virtue of little control over the substrate's morphology at the nano-scale. In this overview, the author has summarized certain anodic oxides derived nano-composite substrates to be used in SERS analytical technique. The preferred substrates for SERS analysis must have unique features such as homogeneous nano-structures, large surface areas, and self-cleaning to perform analysis with utmost accuracy and precision. The author has exposed many challenges involved in improvement of SERS substrates besides focusing on minimizing native drawbacks. Nowadays porous anodic oxides are obtained through cheap and scalable methodologies; this chapter cited some progressive SERS substrates and briefly compared these with conventional substrates.

*Thankam Sreekumar Rajesh's* chapter investigated Al2O3-40% TiO2 powder blend for atmospheric plasma spray coating onto SS316 stainless steel to be used in manufacturing of jigs, guides, shafts, and fixtures. They utilize the teaching learning-based optimization (TLBO) algorithm to optimize input parameters and to find the best output parameters beside conducted confirmation tests, which gave the same values as predicted without significant error. Three levels L18 orthogonal array (OA) design of experiments (DoE) is applied to conduct this research study. The main input parameters measured included: nozzle distance, substrate speed, arc-current, carrier gas flow, and coating powder flow and the output parameters involved were: coating thickness, micro-hardness surface roughness, abrasion rate, and % porosity. Further mathematical models were made for each output parameter. Analytical hierarchy process was used to get weights for unit output parameters with generated objective and combined objective functions through the TLBO algorithm (global optimum values of input parameters and all the output parameters obtained simultaneously). The TLBO algorithm is easy and helpful to solve many multi-objective optimization problems.
