A deep learning neural network approach for predicting the factors influencing heavy-metal adsorption by clay minerals.
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- Clay Minerals, 2022, v. 57, n. 1, p. 70, doi. 10.1180/clm.2022.20
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- Publication type:
- Article
Works matching IS 00098558 AND DT 2022 AND VI 57 AND IP 1
Results: 7
1
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Engineering clay minerals to manage the functions of soils.
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- Clay Minerals, 2022, v. 57, n. 1, p. 51, doi. 10.1180/clm.2022.19
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- Article
3
Adsorption of crystal violet on kaolinite clay: kinetic and equilibrium study using non-linear models.
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- Clay Minerals, 2022, v. 57, n. 1, p. 41, doi. 10.1180/clm.2022.18
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- Article
4
Assessing trace-element mobility during alteration of rhyolite tephra from the Dinaride Lake System using glass-phase and clay-separate laser ablation inductively coupled plasma mass spectrometry.
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- Clay Minerals, 2022, v. 57, n. 1, p. 1, doi. 10.1180/clm.2022.12
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- Article
5
Mineral stabilities in soils: how minerals can feed the world and mitigate climate change.
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- Clay Minerals, 2022, v. 57, n. 1, p. 31, doi. 10.1180/clm.2022.17
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- Publication type:
- Article
6
Removal of ivermectin from aqueous media using commercial, bentonite-based organophilic clay as an adsorbent.
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- Clay Minerals, 2022, v. 57, n. 1, p. 21, doi. 10.1180/clm.2022.16
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- Publication type:
- Article
7
Efficient removal of crystal violet from solution by montmorillonite modified with docosyl-trimethylammonium chloride and sodium dodecyl sulfate: modelling, kinetics and equilibrium studies.
- Published in:
- Clay Minerals, 2022, v. 57, n. 1, p. 7, doi. 10.1180/clm.2022.15
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- Publication type:
- Article