Graph Machine Based-QSAR Approach for Modeling Thermodynamic Properties of Amines: Application to CO2 Capture in Postcombustion (Record no. 187933)

MARC details
000 -LEADER
fixed length control field 02348nab a2200253 4500
008 - CÓDIGOS DE INFORMACIÓN DE LONGITUD FIJA - INFORMACIÓN GENERAL
Campo de control de longitud fija 260224s2013 xxu ing
041 ## - IDIOMA
Idioma Inglés
245 00 - TITULO
Título Graph Machine Based-QSAR Approach for Modeling Thermodynamic Properties of Amines: Application to CO2 Capture in Postcombustion
260 ## - PUBLICACION, DISTRIBUCION, ETC
Lugar de publicación, distribución, etc.
Nombre de publicador, distribuidor, etc.
Fecha de publicación, distribución, etc. ene./feb. 2013
270 ## - FECHA DE CARGA
Fecha de carga 21/10/2013 ; 21/10/2013
300 ## - DESCRIPCION FISICA
Otra extensión 17 p. ; 469-486
520 ## - RESUMEN, ETC
Resumen Transcripción del resumen del autor: Amine scrubbing is usually considered as the most efficient technology for CO2 mitigation through postcombustion Carbon Capture and Storage (CCS). However, optimization of the amine structure to improve the solvent properties requires to sample a large number of possible candidates and hence to gather a large amount of experimental data. In this context, the use of QSAR (Quantitative Structure Activity Relationship) statistical modeling is a powerful tool as it performs a mapping of a set of input vectors (i.e. the characteristics or the properties of the molecules under consideration) to a set of output vectors (i.e. their targeted properties). In this work, we used a high throughput screening experimental device to measure CO2 solubility data on a set of 46 amine aqueous solutions. Absorption isotherms are represented using a thermodynamic model based on two thermodynamic constants, pKa* and pKc* , accounting for the main chemical reactions occurring in the liquid phase between amine and CO2. Then, we used a statistical approach named Graph Machines at the same time to cluster the molecules and to model the variation of the acidity constant pKa* as a function of the molecular structure. The originality of our approach is the use of graphs to represent molecules in multidimensional spaces and simultaneously construct predictive models of their physicochemical properties based on these graphs. This approach is applied in this paper to predict the thermodynamic properties of a set of 5 new molecules.
581 ## - ESTADO DE COLECCIÓN
Estado de colección 1
773 0# - CORRECCIÓN
Título Oil and Gas Science and Technology
Partes relacionadas 68
942 ## - DESC. DE MATERIAL
Tipo de item KOHA Artículo de Revista
100 1# - RESPONSABLE PERSONAL
Apellido, Nombre Porcheron, F.
9 (RLIN) 53530
100 1# - RESPONSABLE PERSONAL
Apellido, Nombre Jacquin, M.
9 (RLIN) 53531
100 1# - RESPONSABLE PERSONAL
Apellido, Nombre El Hadri, N.
9 (RLIN) 53532
100 1# - RESPONSABLE PERSONAL
Apellido, Nombre Saldana, D.A.
9 (RLIN) 53533
100 1# - RESPONSABLE PERSONAL
Apellido, Nombre Goulon, A.
9 (RLIN) 53534
100 1# - RESPONSABLE PERSONAL
Apellido, Nombre Faraj, A.
9 (RLIN) 12310
Holdings
Biblioteca propietaria Biblioteca actual Fecha de adquisición Inventario Total de préstamos Inventario Fecha de carga Tipo de item KOHA
Biblioteca Alejandro Angel Bulgheroni Biblioteca Alejandro Angel Bulgheroni 06/03/2026 200060087   200060087 06/03/2026 Artículo de Revista


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