Preparation of Viscose Fibres Stripped of Reactive Dyes and Wrinkle-Free Crosslinked Cotton Textile Finish

The chemical recycling of cellulosic fibres may represent a next-generation fibre–fibre recycling system for cotton textiles, though remaining challenges include how to accommodate fibre blends, dyes, wrinkle-free finishes, and other impurities from finishing. These challenges may disrupt the regeneration process steps and reduce the fibre quality. This study examines the impact on regenerated viscose fibre properties of a novel alkaline/acid bleaching sequence to strip reactive dyes and dimethyloldihydroxyethyleneureas (DMDHEU) wrinkle-free finish from cotton textiles. Potentially, such a bleaching sequence could advantageously be integrated into the viscose process, reducing the costs and environmental impact of the product. The study investigates the spinning performance and mechanical properties (e.g., tenacity and elongation) of the regenerated viscose fibres. The alkaline/acid bleaching sequence was found to strip the reactive dye and DMDHEU wrinkle-free finish from the cotton fabric, so the resulting pulp could successfully be spun into viscose fibres, though the mechanical properties of these fibres were worse than those of commercial viscose fibres. This study finds that reactive dyes and DMDHEU wrinkle-free finish affect the viscose dope quality and the regeneration performance. The results might lead to progress in overcoming quality challenges in cellulosic chemical recycling.     

Cyclodextrin-based supramolecular assemblies: a versatile toolbox for the preparation of functional porous materials

The discovery of ordered mesoporous materials in 1992 by Mobil Oil Corporation scientists has opened great opportunities for new applications in many emerging fields such as heterogeneous catalysis, biocatalysis, energy conversion, biosensors, photocatalytic devices and environmental technologies. Porous materials are grouped by the International Union of Pure and Applied Chemistry (IUPAC) into three classes according to their pore diameter: microporous (<?2 nm), mesoporous (2–50 nm) and macroporous (>?50 nm). One of the most versatile methods for the preparation of those materials is the soft template approach which combines the sol–gel process with molecular self-assembly. While the micelles formed by ionic or nonionic surfactants, as well as amphiphilic polymers, have been extensively used as templates, the supramolecular assemblies formed between cyclodextrins and block copolymers have been less investigated, despite their large chemical and structural diversity. This review article focuses mainly on nanostructured porous inorganic materials derived from cyclodextrins or cyclodextrin-based assemblies. More than 100 references are described and discussed, in which we look both at their synthesis and characterization, as well as their applications in the emerging fields of heterogeneous catalysis and photocatalysis. A special attention is paid to the evaluation of the critical parameters that need to be controlled for improving their (photo) catalytic performances.     

Sampling strategies in the assessment of long‐term exposures to toxic substances in air

The decision to mitigate exposures from vapor intrusion (VI) is typically based on limited data from 24‐hour air samples. It is well documented that these data do not accurately represent long‐term average exposures linked to adverse health effects. Limited decision guidance is currently available to determine the most appropriate sampling strategy, considering the cost of sampling alternatives along with the economic consequences of exposure‐related health effects. We present a decision model that introduces economic and statistical considerations in evaluating alternative VI sampling methods. The model characterizes the best sampling method by factoring economic and health consequences of exposure, the variability of exposure, the cost of sampling and mitigation, and the likelihood of false‐negatives and false‐positives. Decision‐makers can use results to select the sample size that maximizes net benefit. Conceptual and mathematical models are presented linking biological, statistical, and economic considerations to assess the cost and effectiveness of different sampling strategies. The model relates an average exposure concentration, determined statistically, to abatement costs and to the monetary value of health deterioration. The value of the information provided by different strategies is calculated and used to select the optimum sampling method. Simulations show that longer‐term sampling methods tend to be more accurate and cost‐effective than short‐term samples. The ideal sampling strategy shows significant seasonal variation (it is typically optimal to use longer samples in the winter) and also varies significantly with the stringency of regulatory standards. Longer‐term sample collection provides a more accurate representation of average VI exposure and reduces the likelihood of type I and type II errors. This reduces expected costs of mitigation and exposure (e.g., health consequences, legal and regulatory penalties), which in some cases can be quite significant. The model herein shows how these savings are balanced against the additional costs of longer‐term sampling.     

Methyl methacrylate (MMA) and alumina recovery from waste artificial marble powder pyrolysis

Journal of Material Cycles and Waste Management - Owing to various advantages of artificial marble compared to natural marble, its application has been rising exponentially, which has resulted in...     

Promoting e-mobility in India: challenges,framework, and future roadmap

The purpose of the research is to identify the critical challenges that are impeding the adoption of e-mobility in India. It also aims to give a roadmap how to address these challenges while taking into considerations concerns of all the relevant stakeholders. Based on an in-depth literature review, an exploratory research design is employed to delve deep into various aspects of e-mobility. This is followed by a three-phase Delphi technique to identify and rate the e-mobility challenges in the Indian context. The study successfully identifies four different categories of challenges and proposes integrative framework for e-mobility. Further, the research goes on to lay out the future roadmap for mass adoption of electric vehicles (EVs) in India. The research is novel in terms of presenting a holistic viewpoint on e-mobility in India. Its originality lies in identifying the major inhibitors obstructing EVs adoption in India and then suggesting the roadmap how to overcome these impediments for mass adoption of e-mobility.