Identification of amino acids with sensitive nanoporous MoS2: towards machine learning-based prediction
- Location
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Deutsche Nationalbibliothek Frankfurt am Main
- ISSN
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2397-7132
- Extent
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Online-Ressource
- Language
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Englisch
- Notes
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online resource.
- Bibliographic citation
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Identification of amino acids with sensitive nanoporous MoS2: towards machine learning-based prediction ; volume:2 ; number:1 ; day:24 ; month:5 ; year:2018 ; pages:1-9 ; date:12.2018
npj 2D materials and applications ; 2, Heft 1 (24.5.2018), 1-9, 12.2018
- Classification
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Ingenieurwissenschaften und Maschinenbau
- Creator
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Barati Farimani, Amir
- Contributor
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Heiranian, Mohammad
Aluru, Narayana R.
SpringerLink (Online service)
- DOI
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10.1038/s41699-018-0060-8
- URN
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urn:nbn:de:101:1-2018072707364675303845
- Rights
-
Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
-
15.08.2025, 7:35 AM CEST
Data provider
This object is provided by:
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Associated
- Barati Farimani, Amir
- Heiranian, Mohammad
- Aluru, Narayana R.
- SpringerLink (Online service)
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Ferromagnetism in freestanding MoS2 nanosheets
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Transport in Nanoporous Solids
Ordered arrays of nanoporous silicon nanopillars and silicon nanopillars with nanoporous shells
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Adsorption of chlorophenols from aqueous solution over amino-modified ordered nanoporous silica materials
Nanoporous materials
Zeolites as nanoporous, gas-sensitive materials for in situ monitoring of DeNOx-SCR
All-printed highly sensitive 2D MoS2 based multi-reagent immunosensor for smartphone based point-of-care diagnosis
Molecular Simulation of MoS2 Exfoliation
Photoconductivities in MoS2 Nanoflake Photoconductors
Covalent Patterning of 2D MoS2
Ferromagnetism in freestanding MoS2 nanosheets
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