Journalartikel - Wissenschaftlicher Artikel | 2024 | Peer reviewed

Syngas Composition Analysis for Waste to Methanol Production : (Techno-Economic Assessment Using Machine Learning and Aspen Plus)

Autor*innen

Timilsina, Manish Sharma ; Chaudhary, Yuvraj ; Shah, Aman Kumar ; Lohani, Sunil Prasad ; Bhandari, Ramchandra ; Uprety, Bibek

Zeitschrift

Renewable energy

DOI

10.1016/j.renene.2024.120574

Weitere Details

Sprache

englisch

Darstellungsform

Text

Band

228

Artikelnummer

120574

Schlüsselwörter

Aspen Plus , Economic Analysis , Gasification , Machine Learning , Methanol , Syngas Composition

Zitierstile

Timilsina, M. S., Chaudhary, Y., Shah, A. K., Lohani, S. P., Bhandari, R., & Uprety, B. (2024). Syngas Composition Analysis for Waste to Methanol Production. Renewable Energy, 228, 120574. doi:10.1016/j.renene.2024.120574

In die Zwischenablage kopieren

Timilsina, M.S., Chaudhary, Y., Shah, A.K., Lohani, S.P., Bhandari, R. and Uprety, B., 2024. Syngas Composition Analysis for Waste to Methanol Production. Renewable energy, 228, p.120574.

In die Zwischenablage kopieren

Timilsina, Manish Sharma u. a. 2024. Syngas Composition Analysis for Waste to Methanol Production. Renewable energy 228, 120574.

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Zitierstile

In die Zwischenablage kopieren

Timilsina, M.S., Chaudhary, Y., Shah, A.K., Lohani, S.P., Bhandari, R. and Uprety, B., 2024. Syngas Composition Analysis for Waste to Methanol Production. Renewable energy, 228, p.120574.

In die Zwischenablage kopieren

Timilsina, Manish Sharma u. a. 2024. Syngas Composition Analysis for Waste to Methanol Production. Renewable energy 228, 120574.

In die Zwischenablage kopieren

Download
RDF/XML-Format
JSON-LD-Format
Turtle-Format
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American Psychological Association 6th edition (DOI)

Anglia Ruskin University - Harvard

Gesellschaft für Bildung und Forschung in Europa - Harvard