Molybdenum is a critical raw material for advanced alloys and the chemical industry; however, its supply is increasingly constrained by geopolitical and resource limitations. An efficient recycling of molybdenum from secondary resources is therefore essential to mitigate the supply risk and promote maximum utilization of resources. In this study, a low-energy hydrometallurgical process is proposed for the recovery of molybdenum from spent iron-molybdate catalysts, integrating ammoniacal leaching with anti-solvent crystallization. Conventional leaching using ammonia solution alone achieved less than 90% efficiency and required a high ammonia concentration of 5.0 mol/L. This consumption was significantly reduced to only 2.0 mol/L by employing an ammonia-ammonium solution. The required NH4OH-(NH4)2SO4 ratio was optimized to achieve selective molybdenum dissolution that resulted in 92% leaching efficiency while limiting iron co-dissolution to below 5%. The residual iron, governed by the quasi-equilibrium of iron pentaamine complexation, was effectively supressed through controlled settling of the leachate. Subsequently, ethanol-assisted anti-solvent crystallization, performed at an aqueous-to-organic volumetric ratio of 1:2, enabled the direct recovery of high-purity (NH4)6Mo7O24(H2O)4 with 95% yield under ambient conditions. This work demonstrates a scalable and resource-efficient strategy for molybdenum recovery through integrating the selective leaching approach with low-energy crystallization technique.

Rapid population growth and shifts in lifestyles have significantly increased plastic production and disposal, resulting in a major environmental chal-lenge. The persistence of plastic waste, due to its non-biodegradable nature and large volume, has become a critical concern. Recycling plastic waste into valuable prod-ucts offers a more sustainable solution compared to traditional disposal methods, effectively addressing waste management issues while also enhancing economic value. One promising approach is the use of green concrete, a sustainable composite material that incorporates natural and waste-derived substances as substitutes for conventional cement and aggregates, that may be a key contributor to carbon dioxide emissions and shows the great interest in developing green concrete using readily available natural and waste materials. This chapter explores studies on cement-based materials that integrate recycled plastic waste into concrete. It also examines the potential applications of machine learning and artificial intelligence in predicting the mechanical properties of plastic-infused concrete, such as workability; reduced density; and achieving compressive, tensile, and flexural strengths within accept-able limits. It is suggested that incorporating plastic waste into construction not only promotes sustainability but also helps to mitigate environmental pollution.

Plastics are extensively used across various sectors, including agricul-ture, industries, construction, and daily life, owing to their low cost and excellent corrosion resistance. However, this widespread use has led to a significant accu-mulation of plastics released into the environment, coupled with growing concerns about its potential harm to biota has made plastic waste an escalating issue world-wide. Under environmental stress, plastics break down into micro-and nano-plastics (MNPs), which vary in size, shape, morphology, and composition. Despite growing concerns, research on effective methods for collecting and separating MNPs remains limited. This chapter outlines the sampling procedures for MNPs from both envi-ronmental and biological sources. It then explores the methods for extracting and separating MNPs, followed by an in-depth examination of the techniques used to identify and quantify these particles. Finally, the review discusses the need for stan-dardized and harmonized approaches for the separation, extraction, and identification of MNPs, aiming to provide a framework for advancing pollution monitoring and risk assessment of MNPs in the future.