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Chromium

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Efficient remediation of different concentrations of Cr-contaminated soils by nano zero-valent iron modified with carboxymethyl cellulose and biochar.

Journal of environmental sciences (China)
Nano zero-valent iron (nZVI) is widely used in soil remediation due to its high reactivity. However, the easy agglomeration, poor antioxidant ability and passivation layer of Fe-Cr coprecipitates of nZVI have limited its application scale in Cr-conta...

Efficient reduction of Cr(VI) by guava (Psidium guajava) leaf extract and its mitigation effect on Cr toxicity in rice seedlings.

Journal of environmental sciences (China)
Hexavalent chromium (Cr(VI)) is a toxic element that has negative impacts on crop growth and yield. Using plant extracts to convert toxic Cr(VI) into less toxic Cr(III) may be a more favorable option compared to chemical reducing agents. In this stud...

Nanoisland SERS-Substrates for Specific Detection and Quantification of Influenza A Virus.

Biosensors
Surface-enhanced Raman spectroscopy (SERS)-based aptasensors for virus determination have attracted a lot of interest recently. This approach provides both specificity due to an aptamer component and a low limit of detection due to signal enhancement...

NanoRobotic Structures with Embedded Actuation via Ion Induced Folding.

Advanced materials (Deerfield Beach, Fla.)
4D structures are tridimensional structures with time-varying abilities that provide high versatility, sophisticated designs, and a broad spectrum of actuation and sensing possibilities. The downsizing of these structures below 100 μm opens up except...

Machine learning-assisted chromium speciation using a single-well ratiometric fluorescent nanoprobe.

Chemosphere
Chromium is widely recognized as a significant pollutant discharged into the environment by various industrial activities. The toxicity of this element is dependent on its oxidation state, making speciation analysis crucial for monitoring the quality...

Prediction of Cr(VI) and As(V) adsorption on goethite using hybrid surface complexation-machine learning model.

Water research
This study aimed to develop surface complexation modeling-machine learning (SCM-ML) hybrid model for chromate and arsenate adsorption on goethite. The feasibility of two SCM-ML hybrid modeling approaches was investigated. Firstly, we attempted to uti...

Enhanced biodegradation of phenol under Cr(VI) stress by microbial collaboration and potential application of machine learning for phenol biodegradation.

Water science and technology : a journal of the International Association on Water Pollution Research
Cr(VI) and phenol commonly coexist in wastewater, posing a great threat to the environment and human health. However, it is still a challenge for microorganisms to degrade phenol under high Cr(VI) stress. In this study, the phenol-degrading strain Z...

Biosorption of cobalt and chromium from wastewater using manganese dioxide and iron oxide nanoparticles loaded on cellulose-based biochar: Modeling and optimization with machine learning (artificial neural network).

International journal of biological macromolecules
In this study, two nanomaterials with excellent adsorption capacities were developed to remove heavy metals efficiently from wastewater. Manganese dioxide MnO nanoparticles and iron oxide FeO nanoparticles were successfully synthesized using cassava ...

Hidden threats beneath: uncovering the bio-accessible hazards of chromite-asbestos mine waste and their impacts on rice components via multi-machine learning algorithm.

Environmental geochemistry and health
The chromite-asbestos mining leaves behind tonnes of toxic waste, contaminating nearby agricultural fields with potentially toxic elements (PTEs). Over time, wind and water erosion spread these pollutants, severely impacting the ecosystem, food chain...