Cutting fluid corrosion inhibitors from inorganic to organic: Progress and applications

Li, Haogang; Zhang, Yanbin; Li, Changhe; Zhou, Zongming; Nie, Xiaolin; Chen, Yun; Cao, Huajun; Liu, Bo; Zhang, Naiqing; Said, Zafar; Debnath, Sujan; Jamil, Muhammad; Ali, Hafız Muhammad; Sharma, Shubham

doi:10.1007/s11814-021-1057-0

Cited by 115 publications

(17 citation statements)

References 125 publications

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“…In1 and In5 samples showed a decrease in water transfer compared to the reference sample of 9% and 12%, respectively, and other samples showed a decrease in water transmissibility of about 55 to 65%. Therefore, it can be said that the use of inhibitors has a significant effect on corrosion resistance [ 48 , 49 ].…”

Section: Resultsmentioning

confidence: 99%

The Effect of Eco-Friendly Inhibitors on the Corrosion Properties of Concrete Reinforcement in Harsh Environments

et al. 2022

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In the present research, the synergistic effect of Arabic and guar gum inhibitors on the corrosion efficiency of concrete reinforcement was investigated. Thus, eight types of Arabic and guar gum combinations with 100, 250, 500, 750, and 1000 ppm were added to the steel reinforcement for 1, 7, 28, 48, and 72 days. The corrosion behavior of the samples was investigated by the electrochemical impedance (EIS) test. Water transmissibility, electrical resistivity, and compressive strength of concrete were also studied. The results showed that adding inhibitors generally increased the compressive strength of concrete. It was also found that water transmissibility was reduced by the addition of inhibitors. The electrical resistivity of the samples increased slightly with increasing time up to 72 days. EIS and Tafel results have demonstrated that Arabic and guar gums are effective inhibitors for reinforced concrete structures. Furthermore, scanning electron microscopy (SEM) and Fourier transform infrared spectroscopy (FTIR) utilized to analyze the samples indicated that inhibitor grain size was enhanced by enhancing the concentration of the inhibitor combination, showing that the guar and Arabic inhibitor combinations were properly absorbed on the reinforcement surface. Results showed that a sample with 250 ppm Arabic gum and 250 ppm guar gum having a properly distributed inhibitor combination on the reinforcement surface creates a desirable cathode current.

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Section: Resultsmentioning

confidence: 99%

The Effect of Eco-Friendly Inhibitors on the Corrosion Properties of Concrete Reinforcement in Harsh Environments

et al. 2022

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“…The heat transfer in a heat exchanger device or equipment is dependent on the characteristics of the heat transfer fluid; therefore, precise measurement and forecasting of nanofluid’s thermophysical characteristics are important . However, numerous factors impact the thermophysical characteristics of a nanofluid, including nanoparticle type, concentration, shape, size, shape, temperature, rate of shear, preparation method, kind of base fluid, flow condition, and so on.…”

Section: Machine Learning For Thermophysical Propertiesmentioning

confidence: 99%

Recent Advances in Machine Learning Research for Nanofluid-Based Heat Transfer in Renewable Energy System

Sharma¹,

Said

Kumar³

et al. 2022

Energy Fuels

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222

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Nanofluids have gained significant popularity in the field of sustainable and renewable energy systems. The heat transfer capacity of the working fluid has a huge impact on the efficiency of the renewable energy system. The addition of a small amount of high thermal conductivity solid nanoparticles to a base fluid improves heat transfer. Even though a large amount of research data is available in the literature, some results are contradictory. Many influencing factors, as well as nonlinearity and refutations, make nanofluid research highly challenging and obstruct its potentially valuable uses. On the other hand, data-driven machine learning techniques would be very useful in nanofluid research for forecasting thermophysical features and heat transfer rate, identifying the most influential factors, and assessing the efficiencies of different renewable energy systems. The primary aim of this review study is to look at the features and applications of different machine learning techniques employed in the nanofluid-based renewable energy system, as well as to reveal new developments in machine learning research. A variety of modern machine learning algorithms for nanofluid-based heat transfer studies in renewable and sustainable energy systems are examined, along with their advantages and disadvantages. Artificial neural networks-based model prediction using contemporary commercial software is simple to develop and the most popular. The prognostic capacity may be further improved by combining a marine predator algorithm, genetic algorithm, swarm intelligence optimization, and other intelligent optimization approaches. In addition to the well-known neural networks and fuzzy- and gene-based machine learning techniques, newer ensemble machine learning techniques such as Boosted regression techniques, K-means, K-nearest neighbor (KNN), CatBoost, and XGBoost are gaining popularity due to their improved architectures and adaptabilities to diverse data types. The regularly used neural networks and fuzzy-based algorithms are mostly black-box methods, with the user having little or no understanding of how they function. This is the reason for concern, and ethical artificial intelligence is required.

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“…machining shaft parts and high hardness materials [131]. Drilling time for stainless steel is approximately 30% shorter with laser assisted drilling than with conventional drilling [132][133][134][135][136][137][138][139][140][141][142][143][144][145].…”

Section: Lam Advantagesmentioning

confidence: 99%

State of the art review on the sustainable dry machining of advanced materials for multifaceted engineering applications: progressive advancements and directions for future prospects

Singh

Gill²,

Dogra³

et al. 2022

Mater. Res. Express

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In this article, the comprehensive review on the application, and indeed, a comparative analysis on dry machining of different types of materials (Inconel, steel, aluminum, cast iron, magnesium and advanced materials) used in machining (turning, drilling and milling operations) were carried out in the light of utmost works published in the literature. The work describes the scientific findings of the past twenty years, including sustainable methods (surface texture, solid lubricants, vibration-assisted machining, laser-assisted machining), tool coatings, and geometry of tools. Vibration-assisted machining is another direction that researchers have investigated without the use of cutting coolants, where the complete disposal of coolants is not possible. Various researchers have carried out rigorous experimental work on milling, drilling, and turning operations under dry conditions to machine numerous materials. A significant proportion of experimental data about tool wear, tool wear machining, surface quality, surface integrity, etc., has been analyzed under dry conditions. However, the critical analysis of dry machining for different conventional machining operations for a variety of industrial materials is still lacking for establishing dry machining as a sustainable process for industrial applications. Thus, the critical analysis of various machining parameters and their consequences on tool wear and the surface quality of machined work was carried out in this work. Finally, scientific recommendations based on critical findings were proposed for industrial implementation of dry machining.

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Cutting fluid corrosion inhibitors from inorganic to organic: Progress and applications

Cited by 115 publications

References 125 publications

The Effect of Eco-Friendly Inhibitors on the Corrosion Properties of Concrete Reinforcement in Harsh Environments

The Effect of Eco-Friendly Inhibitors on the Corrosion Properties of Concrete Reinforcement in Harsh Environments

Recent Advances in Machine Learning Research for Nanofluid-Based Heat Transfer in Renewable Energy System

State of the art review on the sustainable dry machining of advanced materials for multifaceted engineering applications: progressive advancements and directions for future prospects

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