In this work, the experimental investigations were piloted to study the influence of hybrid nanoparticles containing SiO2 and CeO2 nanoparticles on thermo-physical characteristics of the paraffin-based phase change material (PCM). Initially, the hybrid nanoparticles were prepared by blending equal mass of SiO2 and CeO2 nanoparticles. The hybrid-nano/paraffin (HnP) samples were prepared by cautiously dispersing 0, 0.5, 1.0, and 2.0 percentage mass of hybrid nanoparticles inside the paraffin, respectively. The synthesized samples were examined under different instruments such as field emission scanning electron microscope (FESEM), Fourier transform infrared spectrometer (FTIR), differential scanning calorimetry (DSC), thermogravimetric analyzer (TGA), and thermal properties analyzer to ascertain the influence of hybrid nanoparticles on thermo-physical characteristics of the prepared samples. The obtained experimental results proved that the hybrid nanoparticles were uniformly diffused in the paraffin matrix without affecting the chemical arrangement of paraffin molecules. Prominently, the relative thermal stability and relative thermal conductivity of the paraffin were synergistically enriched up to 115.49% and 165.56%, respectively, when dispersing hybrid nanoparticles within paraffin. Furthermore, the hybrid nanoparticles appropriately amended the melting and crystallization point of the paraffin to reduce its supercooling, and the maximum reduction in supercooling was ascertained as 35.81%. The comprehensive studies indicated that the paraffin diffused with SiO2 and CeO2 hybrid nanoparticles at 1.0 mass percentage would yield a better outcome compared to the next higher mass fractions without much diminishing the latent heat of paraffin. Hence, it is recommended to utilize the hybrid-nano/paraffin with 1.0 mass fraction of the aforementioned hybrid nanoparticles for effectively augmenting the thermal energy capacity of low-temperature solar thermal systems.

https://www.mdpi.com/1996-1073/13/19/5079/pdf

Characterization of Hybrid-nano/Paraffin Organic Phase Change Material for Thermal Energy Storage Applications in Solar Thermal Systems

A comprehensive study on thermal storage characteristics of nano-CeO2 embedded phase change material and its influence on the performance of evacuated tube solar water heater

This work explores the opportunities to address the setback in thermal energy storage of solar-based water heaters by uniting it with a suitable hybrid-nano composite phase change material (HNCPCM)...

Investigations on an evacuated tube solar water heater using hybrid-nano based organic phase change material

Investigating a single slope solar still with a nano-phase change material

Thermal management of metal roof building using phase change material (PCM)

Experimental and Theoretical Investigations on Thermal Conductivity of the Paraffin Wax using CuO Nanoparticles

Investigating thermal properties of Nanoparticle Dispersed Paraffin (NDP) as phase change material for thermal energy storage

IoT which is briefly known as the Internet of Things, it is one of the few main resources that transmutes everything by making day to day life easier through monitoring and controlling of the smart objects that are interlinked to each other. They exist from households, e-healthcare, industrial cars, and smart cities to wearable's, farming, transportation, smart control systems, etc. All of these IoT device's implementation is mounting in extensive quantity of data. Therefore, processing these annually generated data are increasing alongside. They carry comfort in human lives; however, they are easily prone towards diverse threats like safety encounters in subtle surroundings (e-health and smart home) and other areas by posing as a threat for IoT in approaching times. Henceforward, we meticulously review the safety necessities, threats, attack vector challenges that are relevant to IoT systems. Based off breach breakdown, we conclude to a suitable solution. Through the tremendous growth of DDoS attacks and IoT botnets in recent times, IoT safety is the utmost troubled issues in a network safety field. A whole lot of safety methods came to be projected on these new evolving issues of IoT malware, but they still lack in dealing with them. E.g. Zero-Day Attacks. Here the extent of an innovative tactic for malware detection method like using the machine learning techniques can be used towards contending DDoS Attacks (Zero-Day) and mirai effects that develops an uncluttered task securing IoT network devices. These days we benefit from IoT technologies, however, newer safety difficulties arise as new IoT systems are introduced. Most of IoT systems that are linked in Net have trivial safety measures, therefore smart homes are exceedingly susceptible towards comprisable attacks. These threats include generic CIA attacks and IoT botnets. The study discovers botnet recognition by testing with an administered machine learning with deranged dataset which contains cordial data usually assorted in slight volumes of malicious data. Here the established classifiers are able to identify distinct malicious action from normal action in a minor IoT dataset network and collective traffic attacks. 

M. Nithish

Papers

Experimental and Theoretical Investigations on Thermal Conductivity of the Paraffin Wax using CuO Nanoparticles

Investigating thermal properties of Nanoparticle Dispersed Paraffin (NDP) as phase change material for thermal energy storage

A unified predictability for bot attack on IoT devices and its platforms