ArticleMaterials (Basel, Switzerland)2018
Removal of Crystal Violet by Using Reduced-Graphene-Oxide-Supported Bimetallic Fe/Ni Nanoparticles (rGO/Fe/Ni): Application of Artificial Intelligence Modeling for the Optimization Process.
Article in Materials (Basel, Switzerland), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
5 citing papers in PubMed, 46 citations in OpenAlex.
- Modeling the Electrochemical Synthesis of Zinc Oxide Nanoparticles Using Artificial Neural Networks.Materials (Basel, Switzerland) · 2025Article
- Enhanced removal of tetrabromobisphenolA (TBBPA) from e-waste by Fe-S nanoparticles and Fe-S/CuS nanocomposite with response surface methodology (RSM).Scientific reports · 2024Article
- Binary Dye Removal from Simulated Wastewater Using Reduced Graphene Oxide Loaded with Fe-Cu Bimetallic Nanocomposites Combined with an Artificial Neural Network.Materials (Basel, Switzerland) · 2021Article
- Selective Removal of Malachite Green Dye from Aqueous Solutions by Supported Liquid Membrane Technology.International journal of environmental research and public health · 2019Article
- Preparation of a Highly Porous Carbon Material Based on Quinoa Husk and Its Application for Removal of Dyes by Adsorption.Materials (Basel, Switzerland) · 2018Article
Corrections and comments
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Reduced-graphene-oxide-supported bimetallic Fe/Ni nanoparticles were synthesized in this study for the removal of crystal violet (CV) dye from aqueous solutions. This material was characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM) coupled with energy dispersive spectroscopy (EDS), Raman spectroscopy, N₂-sorption, and X-ray photoelectron spectroscopy (XPS). The influence of independent parameters (namely, initial dye concentration, initial pH, contact time, and temperature) on the removal efficiency were investigated via Box⁻Behnken design (BBD). Artificial intelligence (i.e., artificial neural network, genetic algorithm, and particle swarm optimization) was used to optimize and predict the optimum conditions and obtain the maximum removal efficiency. The zero point of charge (pH
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.