Impacts of Linear Alkylbenzene (LABs) on ecosystems: Detection, fate and remediation.

This review article provides a thorough examination of an interaction between linear alkylbenzenes (LABs) and ecosystems. The review covers various aspects of LABs' impact on ecosystems, focusing on detection and treatment strategies to mitigate ecological consequences. It delves into LABs' role as molecular markers for sewage pollution, their physicochemical properties contributing to persistence, and their effects on aquatic and terrestrial organisms, including disruptions to endocrine systems.

Metal nanoparticles entrapment in chitosan-carbon black composite hydrogel towards sustainable environmental solutions.

A catalytic system has been developed, utilizing metal nanoparticles confined within a chitosan‑carbon black composite hydrogel (M-CH/CB), aimed at improving ease of use and recovery in catalytic processes. The M-CH/CBs were characterized by XPS, XRD, SEM, and EDX, the M-CH/CB system demonstrated exceptional catalytic activity in producing hydrogen gas (H) from water and methanol, and in reducing several hazardous materials including 2-nitrophenol (2-NP), 4-nitrophenol (4-NP), 2,6-dinitrophenol (2,6-DNP), acridine orange (ArO), methyl orange (MO), congo red (CR), methylene blue (MB), and potassium ferricyanide (PFC). Among the tested nanocatalysts, CH/CB showed the highest efficiency for H₂ production, while Fe-CH/CB excelled in contaminant reduction (7.

Unraveling current breakthroughs in phytochemical therapeutics: A systematic review.

, also known as the Kulim tree or Garlic tree, has been consumed by the local communities in Southeast Asia as traditional spice using its old leaves, stem bark, and seeds. The locals also used Kulim tree parts as conventional alternative to treat many diseases such as hemorrhoids, leprosy, diabetes, and diarrhea. However, there was limited scientific evidence to support these traditional claims.

Machine learning based-model to predict catalytic performance on removal of hazardous nitrophenols and azo dyes pollutants from wastewater.

To maintain human health and purity of drinking water, it is crucial to eliminate harmful chemicals such as nitrophenols and azo dyes, considering their natural presence in the surroundings. In this particular research study, the application of machine learning techniques was employed in order to make an estimation of the performance of reduction catalysis in the context of ecologically detrimental nitrophenols and azo dyes contaminants. The catalyst utilized in the experiment was Ag@CMC, which proved to be highly effective in eliminating various contaminants found in water, like 4-nitrophenol (4-NP).

Catalytic innovations: Improving wastewater treatment and hydrogen generation technologies.

The effective reduction of hazardous organic pollutants in wastewater is a pressing global concern, necessitating the development of advanced treatment technologies. Pollutants such as nitrophenols and dyes, which pose significant risks to both human and aquatic health, making their reduction particularly crucial. Despite the existence of various methods to eliminate these pollutants, they are not without limitations.