Unveiling the potential of machine learning in cost-effective degradation of pharmaceutically active compounds: A stirred photo-reactor study-Reference-Cited by-同舟云学术

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Unveiling the potential of machine learning in cost-effective degradation of pharmaceutically active compounds: A stirred photo-reactor study

Published:2024-06 Issue: Volume:358 Page:142222
ISSN:0045-6535
Container-title:Chemosphere
language:en
Short-container-title:Chemosphere

Author:

Acosta-Angulo B.,Lara-Ramos J.,Niño-Vargas A.,Diaz-Angulo J.,Benavides-Guerrero J.,Bhattacharya A.,Cloutier S.,Machuca-Martínez F.

Funder

Minciencias

University of the Valley

Publisher

Elsevier BV

Reference86 articles.

1. Mechanistic model and optimization of the diclofenac degradation kinetic for ozonation processes intensification;Acosta-Angulo;Water,2021

2. An optical and energy absorption analysis of the solar compound parabolic collector photoreactor (CPCP): the impact of the radiation distribution on its optimization;Acosta-Herazo;Chem. Eng. J.,2020

3. An Imperative Style, High-Performance Deep Learning Library;Adam,2019

4. Bulk production of porous TiO2 nanowires by unique solvo-plasma oxidation approach for combating biotic and abiotic water contaminants;Afreen;J. Mater. Sci. Mater. Electron.,2021

5. Atkins' Physical Chemistry;Atkins,2018

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