Found: 13
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Highly efficient removal of ionic dyes in aqueous solutions using magnetic 3D reduced graphene oxide aerogel supported nano zero-valent iron.
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- Environmental Engineering Research, 2024, v. 29, n. 1, p. 1, doi. 10.4491/eer.2023.149
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- Article
Flight Experiment Validation of Altitude Measurement Performance of MOSIR on Tianwen-1 Orbiter.
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- Remote Sensing, 2021, v. 13, n. 24, p. 5049, doi. 10.3390/rs13245049
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- Article
The Mars Orbiter Subsurface Investigation Radar (MOSIR) on China's Tianwen-1 Mission.
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- Space Science Reviews, 2021, v. 217, n. 1, p. 1, doi. 10.1007/s11214-020-00786-4
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- Article
Artificial Intelligence Based Optimization for the Se(IV) Removal from Aqueous Solution by Reduced Graphene Oxide-Supported Nanoscale Zero-Valent Iron Composites.
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- Materials (1996-1944), 2018, v. 11, n. 3, p. 428, doi. 10.3390/ma11030428
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- Article
Modeling of Malachite Green Removal from Aqueous Solutions by Nanoscale Zerovalent Zinc Using Artificial Neural Network.
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- Applied Sciences (2076-3417), 2018, v. 8, n. 1, p. 3, doi. 10.3390/app8010003
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- Article
Heavy Metal Pollution and Ecological Assessment around the Jinsha Coal-Fired Power Plant (China).
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- International Journal of Environmental Research & Public Health, 2017, v. 14, n. 12, p. 1589, doi. 10.3390/ijerph14121589
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- Article
Studies on Organic Matter and Heavy Metals in Soils around the Coal-fired Power Plant in Jinsha.
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- Meteorological & Environmental Research, 2017, v. 8, n. 6, p. 56, doi. 10.19547/j.issn2152-3940.2017.06.012
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- Article
Optimizing Low-Concentration Mercury Removal from Aqueous Solutions by Reduced Graphene Oxide-Supported Fe<sub>3</sub>O<sub>4</sub> Composites with the Aid of an Artificial Neural Network and Genetic Algorithm.
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- Materials (1996-1944), 2017, v. 10, n. 11, p. 1279, doi. 10.3390/ma10111279
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- Article
Addendum: Shi, X.D.; Ruan, W.Q.; Hu, J.W.; Fan, M.Y.; Cao, R.S.; Wei, X.H. Optimizing the Removal of Rhodamine B in Aqueous Solutions by Reduced Graphene Oxide-Supported Nanoscale Zerovalent Iron (nZVI/rGO) Using an Artificial Neural Network-Genetic Algorithm (ANN-GA). Nanomaterials 2017, 7, 134.
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- 2017
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- Correction Notice
Optimizing the Removal of Rhodamine B in Aqueous Solutions by Reduced Graphene Oxide-Supported Nanoscale Zerovalent Iron (nZVI/rGO) Using an Artificial Neural Network-Genetic Algorithm (ANN-GA).
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- Nanomaterials (2079-4991), 2017, v. 7, n. 6, p. 134, doi. 10.3390/nano7060134
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- Article
Artificial Neural Network Modeling and Genetic Algorithm Optimization for Cadmium Removal from Aqueous Solutions by Reduced Graphene Oxide-Supported Nanoscale Zero-Valent Iron (nZVI/rGO) Composites.
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- Materials (1996-1944), 2017, v. 10, n. 5, p. 544, doi. 10.3390/ma10050544
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- Article
Nanoscale zero-valent metals: a review of synthesis, characterization, and applications to environmental remediation.
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- Environmental Science & Pollution Research, 2016, v. 23, n. 18, p. 17880, doi. 10.1007/s11356-016-6626-0
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- Article
Synthesis and Characterization of Reduced Graphene Oxide-Supported Nanoscale Zero-Valent Iron (nZVI/rGO) Composites Used for Pb(II) Removal.
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- Materials (1996-1944), 2016, v. 9, n. 8, p. 687, doi. 10.3390/ma9080687
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- Article