Retraction notice to "Recent breakthroughs on the development of electrodeionization systems for toxic pollutants removal from water environment" [Environ. Res. 241 (2024) 117549].

This article has been retracted: please see Elsevier Policy on Article Withdrawal (https://www.elsevier.com/locate/withdrawalpolicy).

Adsorption and storage of hydrogen- A computational model approach.

Due to the imperative global energy transition crisis, hydrogen storage and adsorption technologies are becoming popular with the growing hydrogen economy. Recently, complex hydrides have been one of the most reliable materials for storing and transporting hydrogen gas to various fuel cells to generate clean energy with zero carbon emissions. With the ever-increasing carbon emissions, it is necessary to substitute the current energy sources with green hydrogen-based efficient energy-integrated systems.

Recent breakthroughs on the development of electrodeionization systems for toxic pollutants removal from water environment.

Since ecosystems are becoming inherently polluted, long-term contaminant removal methods are required. Electrodeionization, in particular, has recently been demonstrated as an effective approach for eliminating ionic compounds from contaminated water sources. Being a more environmentally friendly technology is most likely the main reason for its eminence.

Recent developments on advanced oxidation processes for degradation of pollutants from wastewater with focus on antibiotics and organic dyes.

The existence of various pollutants in water environment contributes to global pollution and poses significant threats to humans, wildlife, and other living beings. The emergence of an effective, realistic, cost-effective, and environmentally acceptable technique to treat wastewater generated from different sectors is critical for reducing pollutant accumulation in the environment. The electrochemical advanced oxidation method is a productive technology for treating hazardous effluents because of its potential benefits such as lack of secondary pollutant and high oxidation efficiency.

Protein nanofibrils as versatile and sustainable adsorbents for an effective removal of heavy metals from wastewater: A review.

Water is a valuable natural resource, which plays a crucial role in ecological survival as well as economic progress. However, the water quality has deteriorated in recent years as a result of urbanization, industrialization and human activities due to the uncontrolled release of industrial wastes, which can be extremely carcinogenic and non-degradable, in air, water and soil bodies. Such wastes showed the presence of organic and inorganic pollutants in high dosages.

Sustainable adsorbents for the removal of pharmaceuticals from wastewater: A review.

Over the previous three decades, the worldwide use of pharmaceuticals has surged by more than 2.5 times. Although being considered essential to save many lives, pharmaceuticals have also emerged as a large source of complex environmental contaminants in recent decades.

Modeling of carbon dioxide fixation by microalgae using hybrid artificial intelligence (AI) and fuzzy logic (FL) methods and optimization by genetic algorithm (GA).

In this study, we are reporting a novel prediction model for forecasting the carbon dioxide (CO) fixation of microalgae which is based on the hybrid approach of adaptive neuro-fuzzy inference system (ANFIS) and genetic algorithm (GA). The CO fixation rate of various algal strains was collected and the cultivation conditions of the microalgae such as temperature, pH, CO %, and amount of nitrogen and phosphorous (mg/L) were taken as the input variables, while the CO fixation rate was taken as the output variable. The optimization of ANFIS parameters and the formation of the optimized fuzzy model structure were performed by genetic algorithm (GA) using MATLAB in order to achieve optimum prediction capability and industrial applicability.

Growth of MWCNTs from Azadirachta indica oil for optimization of chromium(VI) removal efficiency using machine learning approach.

The main objective of the present study is to develop artificial neural networks (ANN) to predict the adsorption efficiency of multi-walled carbon nanotubes (MWCNTs) on Cr(VI) removal. Polydisperse MWCNTs were synthesized at 750 °C on alumina supported Fe-Co-Mo catalyst using CVD (chemical vapor deposition)-assisted spray pyrolysis of Azadirachta indica (Neem) oil under inert Argon (Ar) atmosphere. Growth of MCWNTs with inner diameters between 9 and 14 nm was corroborated by scanning electron microscopy (SEM), high resolution transmission electron microscopy (HRTEM), X-ray diffraction analysis (XRD), and Raman spectral evidence assessments.

Fluorescent carbon dots driven from ayurvedic medicinal plants for cancer cell imaging and phototherapy.

Ayurveda based nanomaterials are recently conceptualized phenomena for biomedical applications especially for imaging and treatment of in vitro cancer cell. Wide range florescent (blue to red emission) quantum dots are versatile materials for imaging and sensing applications. Various procedures and precursors of fluorescent carbon quantum dots (CQDs) are well established and documented in the literature.