Van Krevelen diagrams based on machine learning visualize feedstock-product relationships in thermal conversion processes

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27650%2F23%3A10254087" target="_blank" >RIV/61989100:27650/23:10254087 - isvavai.cz</a>

Result on the web

<a href="https://www.nature.com/articles/s42004-023-01077-z" target="_blank" >https://www.nature.com/articles/s42004-023-01077-z</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1038/s42004-023-01077-z" target="_blank" >10.1038/s42004-023-01077-z</a>

Result language

angličtina

Original language name

Van Krevelen diagrams based on machine learning visualize feedstock-product relationships in thermal conversion processes

Original language description

Feedstock properties play a crucial role in thermal conversion processes, where understanding the influence of these properties on treatment performance is essential for optimizing both feedstock selection and the overall process. In this study, a series of van Krevelen diagrams were generated to illustrate the impact of H/C and O/C ratios of feedstock on the products obtained from six commonly used thermal conversion techniques: torrefaction, hydrothermal carbonization, hydrothermal liquefaction, hydrothermal gasification, pyrolysis, and gasification. Machine learning methods were employed, utilizing data, methods, and results from corresponding studies in this field. Furthermore, the reliability of the constructed van Krevelen diagrams was analyzed to assess their dependability. The van Krevelen diagrams developed in this work systematically provide visual representations of the relationships between feedstock and products in thermal conversion processes, thereby aiding in optimizing the selection of feedstock and the choice of thermal conversion technique

Czech name

—

Czech description

—

Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

10200 - Computer and information sciences

Project

—

Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2023

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Communications Chemistry

ISSN

2399-3669

e-ISSN

2399-3669

Volume of the periodical

6

Issue of the periodical within the volume

1

Country of publishing house

DE - GERMANY

Number of pages

10

Pages from-to

—

UT code for WoS article

001122502600001

EID of the result in the Scopus database

2-s2.0-85179331588