61 a 70 de 3.464 Resultados
7 nov. 2024 -
Surface functionalization of graphene oxide with tannic acid: Covalent vs non-covalent approaches
Imagen PNG - 11,4 KB -
MD5: b0111c78a3c32781508afeff52b04266
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7 nov. 2024 -
Surface functionalization of graphene oxide with tannic acid: Covalent vs non-covalent approaches
Imagen PNG - 60,0 KB -
MD5: dc73361d1ddbad946ecea7cd1d01b3b5
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7 nov. 2024 -
Surface functionalization of graphene oxide with tannic acid: Covalent vs non-covalent approaches
Imagen PNG - 52,8 KB -
MD5: 9c6146d12d84184e9e98683c81627d3c
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7 nov. 2024 -
Surface functionalization of graphene oxide with tannic acid: Covalent vs non-covalent approaches
Imagen PNG - 31,0 KB -
MD5: 76f2ef76df8d517064b895d9c990b523
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7 nov. 2024 -
Surface functionalization of graphene oxide with tannic acid: Covalent vs non-covalent approaches
Imagen PNG - 27,4 KB -
MD5: c533e87aca5c016cf6fad9602f83e92f
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7 nov. 2024 -
Surface functionalization of graphene oxide with tannic acid: Covalent vs non-covalent approaches
Texto plano - 6,3 KB -
MD5: eb750a640d66c666986ba7d13045d750
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7 nov. 2024 -
Surface functionalization of graphene oxide with tannic acid: Covalent vs non-covalent approaches
Texto plano - 476 B -
MD5: 40c9c714ea7fb9971032504b2a115830
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7 nov. 2024 -
Surface functionalization of graphene oxide with tannic acid: Covalent vs non-covalent approaches
Texto plano - 564 B -
MD5: 937f7de865c4e641438c805066a190b5
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5 nov. 2024
Diez-Pascual, Ana María; Champa-Bujaico, Elisabeth; Garcia Díaz, Pilar; Sesini, Valentina; G. Mosquera, Marta E., 2024, "Machine learning algorithms to optimize the properties of bio-based poly(butylene succinate-co- butylene adipate) nanocomposites with carbon nanotubes", https://doi.org/10.21950/AN5SP2, e-cienciaDatos, V1
In this project, a simple, cost-effective and scalable solution to improve the mechanical properties of poly(butylene succinate-co- butylene adipate) (PBSA) is reported by using functionalized single-walled carbon nanotubes (SWCNTs). Different SWCNT percentages w/w (0.15, 0.25, 0... |
Imagen PNG - 49,6 KB -
MD5: 4331f12f2289f9df5efc2faa269dc4e0
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