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The purpose of this study is to develop black pigmented ceramic stoneware bodies that integrate various aspects of material composition and color potential. Recent research has explored black pigmented calcium aluminosilicate glass (BPCG), a specialized material known for its unique properties, which holds promise for transforming the color capabilities of traditional ceramics.

In this investigation, initially composite ceramic sample (B-1) was prepared by milling process prior to sieve analysis to attain the particle size within 44 microns. Microanalysis and morphology and thermography were studied by energy-dispersive X-ray spectroscopy, scanning electron microscope and thermogravimetric analysis and found Sample-B-1 received attractive properties like firing shrinkage, porosity, bulk density and firing strength along with good pyro-plastic properties at various temperatures like 950°C, 1050°C, 1000°C and 1180°C. Furthermore, BPCG-assisted pigmented ceramic composites were synthesized with B-1 matrix. CIE lab investigation of the attributed composites (C-series) within selective soaking range of 5–20 min was performed, and the investigation found that prominent black hue appeared (L: 24.09, a*: −0.17, b*: −0.49) for C-10 containing appeared phases of Di-Co-Silicide (26%), Ni-Chromite, Stilpnomelane (rich in iron) as obtained by X-ray diffraction studies.

Ceramic material played a significant role in the realms of art and craft, as well as in technology. The artistic facet reveals concepts or ornamentation, while the craft echoes both traditional and functional appeal. Technology, on the other hand, involves the logical implementation behind the creation.

This C-10 Sample comprised the lower percentage of mullite which attributed that the BPCG homogeneously mixed in the matrix of base (B-1) and appeared as spinal staff. Therefore, BPCG was a potential candidate for ceramic metallization, and this traditional metallization processes often faced some challenges like uniformity and mixing in the ceramic composite domain practices. This study aimed to open up new avenues for artistic decoration and bridging the gap between traditional craftsmanship and modern technology. Furthermore, BPCG’s role in color assessment through shocking techniques added an exciting concept for the ceramic practitioners, designers or ceramic educators.

The purpose of this paper is to develop a concept and design to cast Al alloys/metal matrix composites (MMCs) by continuous casting process. The various steps involved in the evolution of the design have been reported and discussed in this study.

On the basis of developed design concept, initial prototype design has been prepared in this study. The casting process's melt flow pattern was studied via computer simulation, and the resulting changes were implemented in the original design. The single-phase fluid flow pattern through bottom feeding technique is studied. The equipment was fabricated based on computer simulation and water modelling studies. Finally, validation was performed for the preparation of Al alloys/ MMCs after parameter optimisation. The results were observed in the optical metallography to confirm the alloying and Al MMC preparation.

The developed continuous casting process with bottom feeding technique for the addition of constituent particles shows more efficiency in comparison to the existing batch processes. The final manufactured setup demonstrates effective Al alloy/MMC production as the basis for final fabrication has been accomplished by both computer simulation and water model test. In addition, the microstructure exhibits homogeneous distribution, validating the reliability of the setup.

Integrating continuous casting with continuous reinforcement or master alloy addition is novel in this area. The constraints that batch production had that have been rectified will also lower the contemporary cost of production.

As the global community increasingly directs its attention towards sustainable urban development, integrating artificial intelligence (AI) into circular economy (CE) management within smart cities has become a potent strategy. This study aims to examine the potential influence of AI-based technologies on optimizing resources and minimizing waste, which constitute critical components of the principles underpinning the CE. The focus is mainly on applying these technologies within smart city environments. Artificial Intelligence can significantly enhance the processes of gathering, analyzing and decision-making by integrating internet of things (IoT) sensors, data analytics, machine learning algorithms and predictive analytics. This chapter explores the potential of AI in predicting trends, optimizing circular supply chains, improving waste management and recycling practices, facilitating sustainable product design, fostering citizen engagement and aiding policy development. The current research presents a comprehensive examination of the interrelated connection between the principles of CE and the advanced technology of AI. Doing so contributes significantly to our holistic comprehension of how these advancements might collectively influence the development of a more sustainable and resilient future for urban populations.

It's no longer a secret that a hassle-free life and better human development index are only possible in smart cities with appropriate and efficient deployment of artificial intelligence (AI)-based technologies where the best results of data analysis are being used. Technology is becoming more productive using circular economy while employing all the dimensions of AI where integration of results is being incorporated as an outcome of data analysis received from different segments i.e., Traffic Management, Public Safety, and Movement, Security and surveillance, Waste Management Systems, or the Energy Management, etc. This chapter specifically talks about areas where AI is facing challenges in the implementation and administration of smart cities while covering the intrinsic challenges faced in specialized domains such as Public Sanitation, Virtual Parking Management, Traffic Congestion, Security Surveillance, and many more discussed as case study relating to the functioning of the circular economy. In the last, we have summarized the impact of AI on the CE and its future scope where AI can play a better role in increased productivity, increased efficiency, robust safety and finally economic benefit for long-term stable economic stability, development and inclusive growth.