Optical properties of Si/SiO<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" id="d1e459" altimg="si1.svg"><mml:msub><mml:mrow/><mml:mrow><mml:mn>2</mml:mn></mml:mrow></mml:msub></mml:math> nano structured films induced by laser plasma ionization deposition

Abed, Meisam Moghareh; Gaspari, F.; Kiani, Amirkianoosh

doi:10.1016/j.optcom.2020.125297

Cited by 6 publications

(2 citation statements)

References 22 publications

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“…Figure 4c and d enlarges the mastoid, and it can be found that there are a small amount of nanoparticles on the surface. These micro-/nanoparticles are formed by injection and sputtering in laser texturing [22].…”

Section: Resultsmentioning

confidence: 99%

Effect of stabilizing heat treatment on condensation heat transfer performance of laser micro-/nano-textured copper surface

et al. 2020

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The surface reforming method of metal superhydrophobic surface usually utilizes organic matter, which has the problems of serious environmental pollution, high thermal resistance, low processing efficiency, as well as easy to fall off. According to the application requirements of steam condensation heat transfer on copper surface, a laser micro-/nano-texturing technology assisted by green post-processing method is proposed in this study. In this technology, a nanosecond laser was used to texture the surface of pure copper, which will undergo heat treatment to prepare a superhydrophobic surface with micro-/nano-level structures. Scanning electron microscopy and X-ray photoelectron spectroscopy were used to analyze the microstructure changes. A contact angle tester was used to measure the wettability of the surfaces and surface Gibbs energy. Furthermore, steam condensation system was set up to assess surface heat transfer performance. The results show that the laser micro-/nano-textured copper surface has a superhydrophilic contact angle of 4°; after heat treatment, it reaches 161°and became a superhydrophobic surface. As the heat treatment promotes fully oxidation of the textured copper surface, the surface energy is greatly reduced. Due to the formation of nanoscale CuO ''clusters'' transferred from laser-textured Cu 2 O by heat treatment, the superhydrophobic surface blocks the growth of condensate droplets and increases the condensation heat transfer coefficient by 4 times to 730.4 W m -2 K -1 . It provides a green nonchemical treatment method for heat transfer applications of copper alloy components in the fields of energy, chemical engineering, refrigeration, microelectronics, and batteries.

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Section: Resultsmentioning

confidence: 99%

Effect of stabilizing heat treatment on condensation heat transfer performance of laser micro-/nano-textured copper surface

et al. 2020

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“…Further, the fast response time of 100 μs for a 3% change in index modulation, as compared to conventional devices which have a response in a ms timescale, signifies the tremendous potential of silicon thin films in telecommunications applications. One dimensional (1-D) fibrous elements, in the form of thin films, have been proven to exhibit exceptional sensing properties, as their porous structures result in a large surface contact area 5,6 .…”

Section: Introductionmentioning

confidence: 99%

Hybrid artificial neural networks and analytical model for prediction of optical constants and bandgap energy of 3D nanonetwork silicon structures

Joshi¹,

Micro²,

Kiani³

2021

OEA

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The aim of this study is to develop a reliable method to determine optical constants for 3D-nanonetwork Si thin films manufactured using a pulsed-laser ablation technique that can be applied to other materials synthesized by this technique. An analytical method was introduced to calculate optical constants from reflectance and transmittance spectra. Optical band gaps for this novel material and other important insights on the physical properties were derived from the optical constants. The existing optimization methods described in the literature were found to be complex and prone to errors while determining optical constants of opaque materials where only reflectance data is available. A supervised Deep Learning Algorithm was developed to accurately predict optical constants from the reflectance spectrum alone. The hybrid method introduced in this study was proved to be effective with an accuracy of 95%.

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Emissivity study of nanofibro-porous Si/SiO2 structures synthesized by picosecond pulse deposition at varied laser scanning speeds and repetition rates

Abed

Kiani

2020

Results in Materials

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Optical properties of Si/SiO2 nano structured films induced by laser plasma ionization deposition

Cited by 6 publications

References 22 publications

Effect of stabilizing heat treatment on condensation heat transfer performance of laser micro-/nano-textured copper surface

Effect of stabilizing heat treatment on condensation heat transfer performance of laser micro-/nano-textured copper surface

Hybrid artificial neural networks and analytical model for prediction of optical constants and bandgap energy of 3D nanonetwork silicon structures

Emissivity study of nanofibro-porous Si/SiO2 structures synthesized by picosecond pulse deposition at varied laser scanning speeds and repetition rates

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