A novel interpretable machine learning model approach for the prediction of TiO2 photocatalytic degradation of air contaminants

to related objects

Location: Deutsche Nationalbibliothek Frankfurt am Main

Extent: 1 Online-Ressource.

Language: Englisch

Bibliographic citation: A novel interpretable machine learning model approach for the prediction of TiO2 photocatalytic degradation of air contaminants ; volume:14 ; number:1 ; day:6 ; month:6 ; year:2024 ; pages:1-15 ; date:12.2024
Scientific reports ; 14, Heft 1 (6.6.2024), 1-15, 12.2024

Creator: Schossler, Rodrigo Teixeira
Ojo, Samuel
Jiang, Zhuoying
Hu, Jiajie
Yu, Xiong

Contributor: SpringerLink (Online service)

DOI: 10.1038/s41598-024-62450-z

URN: urn:nbn:de:101:1-2408132107434.079065081927

Rights: Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.

Last update: 14.08.2025, 10:50 AM CEST

Data provider

This object is provided by:
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.

Show original at data provider

Associated

Schossler, Rodrigo Teixeira
Ojo, Samuel
Jiang, Zhuoying
Hu, Jiajie
Yu, Xiong
SpringerLink (Online service)

Other Objects (12)

Evaluation of machine learning models for predicting TiO2 photocatalytic degradation of air contaminants

Publisher Correction: Evaluation of machine learning models for predicting TiO2 photocatalytic degradation of air contaminants

Photocatalytic activity of P-doped TiO2 photocatalyst

Optical and photocatalytic properties of TiO2 nanoplumes

Influence of ThO2 on the photocatalytic activity of TiO2

Investigation of photocatalytic degradation of phenol by Fe(III)-doped TiO2 and TiO2 nanoparticles

Hochschulschrift

Synthesis of TiO2 based nanoparticles for photocatalytic applications

Photocatalytic degradation of Metronidazole with illuminated TiO2 nanoparticles

Fundamental studies of photocatalytic CO2 reduction on TiO2

Photocatalytic oxidation of phenol red onto nanocrystalline TiO2 particles

Bandgap reduction of photocatalytic TiO2 nanotube by Cu doping

Modeling TiO2: insights into photocatalytic material properties and reactions

Evaluation of machine learning models for predicting TiO2 photocatalytic degradation of air contaminants

Publisher Correction: Evaluation of machine learning models for predicting TiO2 photocatalytic degradation of air contaminants

Photocatalytic activity of P-doped TiO2 photocatalyst

Optical and photocatalytic properties of TiO2 nanoplumes

Influence of ThO2 on the photocatalytic activity of TiO2

Investigation of photocatalytic degradation of phenol by Fe(III)-doped TiO2 and TiO2 nanoparticles

Hochschulschrift

Synthesis of TiO2 based nanoparticles for photocatalytic applications

Photocatalytic degradation of Metronidazole with illuminated TiO2 nanoparticles

Fundamental studies of photocatalytic CO2 reduction on TiO2

Photocatalytic oxidation of phenol red onto nanocrystalline TiO2 particles

Bandgap reduction of photocatalytic TiO2 nanotube by Cu doping

Modeling TiO2: insights into photocatalytic material properties and reactions

Evaluation of machine learning models for predicting TiO2 photocatalytic degradation of air contaminants

Publisher Correction: Evaluation of machine learning models for predicting TiO2 photocatalytic degradation of air contaminants

Photocatalytic activity of P-doped TiO2 photocatalyst

Optical and photocatalytic properties of TiO2 nanoplumes

Influence of ThO2 on the photocatalytic activity of TiO2

Investigation of photocatalytic degradation of phenol by Fe(III)-doped TiO2 and TiO2 nanoparticles

Hochschulschrift

Synthesis of TiO2 based nanoparticles for photocatalytic applications

Photocatalytic degradation of Metronidazole with illuminated TiO2 nanoparticles

Fundamental studies of photocatalytic CO2 reduction on TiO2

Photocatalytic oxidation of phenol red onto nanocrystalline TiO2 particles

Bandgap reduction of photocatalytic TiO2 nanotube by Cu doping

Modeling TiO2: insights into photocatalytic material properties and reactions

Cultural heritage institutions wishing to register will find more information here.

Fields marked * need to be filled in.

Username*

Please enter your username

Email*

Please enter your email address

Please do not fill this field

First name

Last name

Password*

Please enter your password

Confirm password*

Please enter the same password

I have read the terms of use and the privacy policy for the collection of personal data and accept them. *

This field is required.

I would like to subscribe to the newsletter of the Deutsche Digitale Bibliothek. See newsletter subscription info.

Account created

Your "My DDB" account has been successfully created. Before you can log in to your account, you must click the confirmation link in the message we just sent to the email address you provided.

A novel interpretable machine learning model approach for the prediction of TiO2 photocatalytic degradation of air contaminants

Object Details

References and Relationships

Contributors, Places and Time

Further information

Data provider

Associated

Other Objects (12)

Evaluation of machine learning models for predicting TiO2 photocatalytic degradation of air contaminants

Publisher Correction: Evaluation of machine learning models for predicting TiO2 photocatalytic degradation of air contaminants

Photocatalytic activity of P-doped TiO2 photocatalyst

Optical and photocatalytic properties of TiO2 nanoplumes

Influence of ThO2 on the photocatalytic activity of TiO2

Investigation of photocatalytic degradation of phenol by Fe(III)-doped TiO2 and TiO2 nanoparticles

Synthesis of TiO2 based nanoparticles for photocatalytic applications

Photocatalytic degradation of Metronidazole with illuminated TiO2 nanoparticles

Fundamental studies of photocatalytic CO2 reduction on TiO2

Photocatalytic oxidation of phenol red onto nanocrystalline TiO2 particles

Bandgap reduction of photocatalytic TiO2 nanotube by Cu doping

Modeling TiO2: insights into photocatalytic material properties and reactions

Evaluation of machine learning models for predicting TiO2 photocatalytic degradation of air contaminants

Publisher Correction: Evaluation of machine learning models for predicting TiO2 photocatalytic degradation of air contaminants

Photocatalytic activity of P-doped TiO2 photocatalyst

Optical and photocatalytic properties of TiO2 nanoplumes

Influence of ThO2 on the photocatalytic activity of TiO2

Investigation of photocatalytic degradation of phenol by Fe(III)-doped TiO2 and TiO2 nanoparticles

Synthesis of TiO2 based nanoparticles for photocatalytic applications

Photocatalytic degradation of Metronidazole with illuminated TiO2 nanoparticles

Fundamental studies of photocatalytic CO2 reduction on TiO2

Photocatalytic oxidation of phenol red onto nanocrystalline TiO2 particles

Bandgap reduction of photocatalytic TiO2 nanotube by Cu doping

Modeling TiO2: insights into photocatalytic material properties and reactions

Evaluation of machine learning models for predicting TiO2 photocatalytic degradation of air contaminants

Publisher Correction: Evaluation of machine learning models for predicting TiO2 photocatalytic degradation of air contaminants

Photocatalytic activity of P-doped TiO2 photocatalyst

Optical and photocatalytic properties of TiO2 nanoplumes

Influence of ThO2 on the photocatalytic activity of TiO2

Investigation of photocatalytic degradation of phenol by Fe(III)-doped TiO2 and TiO2 nanoparticles

Synthesis of TiO2 based nanoparticles for photocatalytic applications

Photocatalytic degradation of Metronidazole with illuminated TiO2 nanoparticles

Fundamental studies of photocatalytic CO2 reduction on TiO2

Photocatalytic oxidation of phenol red onto nanocrystalline TiO2 particles

Bandgap reduction of photocatalytic TiO2 nanotube by Cu doping

Modeling TiO2: insights into photocatalytic material properties and reactions

Related objects

Reset password