Preparation and application of metal-modified biochar in the purification of micro-polystyrene polluted aqueous environment

Journal of Environmental Management, Год журнала: 2023, Номер 347, С. 119158 - 119158

Опубликована: Окт. 5, 2023

Язык: Английский

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A review of microbial responses to biochar addition in anaerobic digestion system: Community, cellular and genetic level findings

Bioresource Technology, Год журнала: 2023, Номер 391, С. 129929 - 129929

Опубликована: Ноя. 2, 2023

Язык: Английский

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Tree-structured parzen estimator optimized-automated machine learning assisted by meta–analysis for predicting biochar–driven N2O mitigation effect in constructed wetlands

Journal of Environmental Management, Год журнала: 2024, Номер 354, С. 120335 - 120335

Опубликована: Фев. 17, 2024

Язык: Английский

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Biochar design for antibiotics adsorption based on a hybrid machine-learning-based optimization framework

Separation and Purification Technology, Год журнала: 2024, Номер 348, С. 127666 - 127666

Опубликована: Апрель 27, 2024

Язык: Английский

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Electron transfer-mediated peroxymonosulfate activation through monoatomic Fe–pyridinic N4 moiety in biochar-based catalyst for electron-rich pollutants degradation in groundwater

Chemical Engineering Journal, Год журнала: 2024, Номер 492, С. 152158 - 152158

Опубликована: Май 11, 2024

Язык: Английский

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Discovery of an End-to-End Pattern for Contaminant-Oriented Advanced Oxidation Processes Catalyzed by Biochar with Explainable Machine Learning

Environmental Science & Technology, Год журнала: 2024, Номер unknown

Опубликована: Авг. 20, 2024

The utilization of biochar-catalyzed peroxymonosulfate in advanced oxidation processes (BC-PMS AOPs) is widely acknowledged as an effective and economical method for mitigating emerging contaminants (ECs). Especially, state-of-the-art machine learning (ML) technology has been employed to accurately predict the reaction rate constants EC degradation BC-PMS AOPs, primarily focusing on three aspects: performance prediction, operating condition optimization, mechanism interpretation. However, its real application specific optimization targeting different ECs seldom considered, hindering realization contaminant-oriented AOPs. Herein, we propose a hierarchical ML pipeline achieve end-to-end (E2E) pattern addressing this issue. First, overall XGB model, trained with comprehensive data set, can perform well predicting additionally providing basis further analysis various ECs. Then, submodels clusters offer strategies selection optimum option AOPs HOMO-LUMO gaps, thus forming E2E This study not only increases our understanding but also successfully bridges gap between model development environmental application.

Язык: Английский

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Engineering defects in heterogeneous catalytic persulfates for water purification: An overlooked role?

Coordination Chemistry Reviews, Год журнала: 2024, Номер 507, С. 215749 - 215749

Опубликована: Март 8, 2024

Язык: Английский

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Machine learning-driven optimization and application of bimetallic catalysts in peroxymonosulfate activation for degradation of fluoroquinolone antibiotics

Chemical Engineering Journal, Год журнала: 2024, Номер 486, С. 150297 - 150297

Опубликована: Март 11, 2024

Язык: Английский

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LIGNOCELLULOSIC BIOMASS FOR BIOCHAR PRODUCTION: A GREEN INITIATIVE ON BIOWASTE CONVERSION FOR PHARMACEUTICAL AND OTHER EMERGING POLLUTANT REMOVAL

Chemosphere, Год журнала: 2024, Номер 360, С. 142312 - 142312

Опубликована: Май 16, 2024

Язык: Английский

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Triggering nanoconfinement effect in advanced oxidation processes (AOPs) for boosted degradation of organic contaminants: A review

Chemical Engineering Journal, Год журнала: 2024, Номер 503, С. 158428 - 158428

Опубликована: Дек. 9, 2024

Язык: Английский

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