ADITIVOS FUNCIONALIZADOS BIOBASADOS PARA LA MEJORA DE LA COMPATIBILIDAD EN MATERIALES COMPUESTOS HIBRIDOS
PID2021-122708OB-C31
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Nombre agencia financiadora Agencia Estatal de Investigación
Acrónimo agencia financiadora AEI
Programa Programa Estatal para Impulsar la Investigación Científico-Técnica y su Transferencia
Subprograma Subprograma Estatal de Generación de Conocimiento
Convocatoria Proyectos de I+D+I (Generación de Conocimiento y Retos Investigación)
Año convocatoria 2021
Unidad de gestión Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023
Centro beneficiario UNIVERSIDAD DE ALCALA
Identificador persistente http://dx.doi.org/10.13039/501100011033
Publicaciones
Found(s) 5 result(s)
Found(s) 1 page(s)
Found(s) 1 page(s)
Titanium-catalyzed synthesis of polymyrcene and polyanethol and application as sustainable additives for poly(lactic acid)
e_Buah Biblioteca Digital Universidad de Alcalá
- Vinueza Vaca, Joan Martín|||0000-0002-0885-6394
- Franco-Mateo, Emma
- Sessini, Valentina|||0000-0003-1205-4586
- González Mosquera, Marta Elena|||0000-0003-2248-3050
- Souza Egipsy, Virginia
- Ramos, Javier
- Vega, Juan F
- Jiménez Pindado, Gerardo Javier|||0000-0002-7057-4750
- Tabernero Magro, María Vanessa|||0000-0003-1054-1663
The replacement of fossil-derived plastics with those obtained from bio-based resources, which present suitable performance to be employed as commodity plastics is currently an important field of research, given the urgent need to transition from a fossil-based to a more sustainable economy. In this context, this work is focused on the application of a catalytic system based on silsesquioxane-cyclopentadienyl titanium complexes for the preparation of bio-based polymers, which can be used as additives to improve the poor material properties of a biodegradable polymer such as poly(lactic acid) (PLA). These titanium complexes, when activated with methylaluminoxane or with triflate salts, are shown to be capable of the polymerization of two bio-based monomers: myrcene and anethole. It is notable that polymerizations with these two distinct monomers take place through different mechanisms. The resulting polymyrcene (PMy) and polyanethol (PAN) have been applied as modifiers for PLA. Binary blends of PMy and PLA exhibited a considerable decrease in Tg and the promotion of PLA crystallization for a PMy content below 15 wt%. The mechanical properties of the PLA/PMy blends also displayed plasticization, with a decrease in the elastic modulus and enhanced plasticity, which resulted in less fragile systems compared to pure PLA. Morphological analysis has indicated a partially miscible, phase-separated system with micron-sized domains. In contrast, PAN completely inhibited PLA crystallization and the PLA/PAN blends were immiscible, but well-dispersed, a phase-separated system was obtained in solvent-casting film preparation with very small PAN domains. The blends showed higher tensile modulus than pure PLA and an absence of plastic behaviour, resulting in more fragile systems upon the addition of PAN to PLA., Ministerio de Ciencia e Innovación, Agencia Estatal de Investigación, Universidad de Alcalá
Machine learning algorithms to optimize the properties of bio-based poly (butylene succinate-co-butylene adipate) nanocomposites with carbon nanotubes
e_Buah Biblioteca Digital Universidad de Alcalá
- Champa Bujaico, Elizabeth
- Díez Pascual, Ana María|||0000-0001-7405-2354
- García Díaz, María Del Pilar|||0000-0002-5361-6947
- Sessini , Valentina|||0000-0003-1205-4586
- González Mosquera, Marta Elena|||0000-0003-2248-3050
19 p., Poly[(butylene succinate)-co-adipate] (PBSA)-based materials are gathering much attention in the packaging industry, agriculture, and other fields owed to their biocompatibility and biodegradability. Nonetheless, poor thermal and mechanical properties of biodegradable polymers, such as PBSA, have hampered their wide-spread use. Herein, a simple, cost-effective and scalable solution to improve the mechanical properties of PBSA is reported by using functionalized single-walled carbon nanotubes (SWCNTs). Different SWCNT loadings have been incorporated in the PBSA matrix via simple solution casting, and the ultrasonication conditions have been optimized to attain a homogenous SWCNT dispersion. The nanocomposites have been characterized in detail by scanning electron microscopy (SEM), Infrared spectroscopy, thermogravimetric analysis (TGA), differential scanning calorimetry (DSC), tensile and impact strength tests. Unprecedented increments in stiffness were found at low nanotube loadings, ascribed to the outstanding reinforcing capability of the SWCNTs combined with their superior modulus and strong interfacial adhesion with the matrix via H-bonding, polar and CH? interactions. Further, four machine learning (ML) algorithms, Polynomial Regression (PR), Support Vector Machines for Regression (SVR), Gradient Boosting (GB) and Artificial Neural Network (ANN), were applied to predict their mechanical properties. The algorithms performance was assessed using analytical parameters such as the coeff icient of determination (R 2 ), the mean square error (MSE) and the mean absolute error (MAE). The developed models exhibited strong performance, achieving R 2 values ranging from 0.69 to 0.99 across the evaluated properties. The results corroborate that even when the same prediction model is used, its performance varies depending on the physical property to be predicted. Thus, SVR, GB, PR, and ANN were found to be the most effective for estimating the Young?s modulus, tensile strength, elongation at break and impact strength, respectively. This research holds great potential for advancing the field of modelling the mechanical properties of polymeric nanocomposites and their practical applications in various industries such as food, pharmaceutical and biomedicine. The development of accurate models for predicting nanocomposite properties would cheapen, simplify and systematize their design and production processes, resulting in improved final products and more efficient development procedures., Universidad del Alcalá, Ministerio de Ciencia e Innovación
Insight into the melt-processed polylimonene oxide/polylactic acid blends
Digital.CSIC. Repositorio Institucional del CSIC
- Palenzuela, Miguel
- Vega, Juan Francisco
- Souza-Egipsy, Virginia
- Ramos, Javier
- Rentero, Christian
- Sessini, Valentina
- Mosquera, Marta E.G.
8 pags., 7 figs. 2 tabs., In this work, the polymerization of limonene oxide (LO) has been optimized at room temperature with two different aluminium-based catalysts [AlMeX{2,6-(CHPh2)2-4-tBu-C6H2O}] (X = Me (1), Cl (2)). A fully bio-based ether, polylimonene oxide (PLO), has been synthesized with low molecular weight and good thermal stability, being a potential sustainable polymeric additive for other bio-based and biodegradable polymers such as polylactic acid (PLA). Hence, we have explored its ability to influence the thermal, mechanical and morphological properties of PLA by preparing their blends by melt processing. The addition of a low amount of PLO led to a nearly 10 °C decrease in the PLA glass transition temperature. Moreover, a decrease in the PLA melting temperature and the degree of crystallinity was observed. Interestingly, a remarkable increase in the flexibility of PLA-based films was noticed. All the results point to the existence of strong interactions between the components, suggesting their partial miscibility., The authors would like to thank the Comunidad de Madrid (EPU-INV/2020/001) and the Ministerio de Ciencia e Innovación (Spain) through the projects TED2021-130871B-C22, PID2021-122708OB-C31, PID2019-107710 GB-I00, and RYC2021-033921-I for their financial support. BIOPHYM Service at the IEM-CSIC and POLYMAT (Rheology Lab) are acknowledged for granting the use of their facilities. This project has received funding from
the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 754382, GOT ENERGY TALENT., Peer reviewed
the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 754382, GOT ENERGY TALENT., Peer reviewed
DOI: http://hdl.handle.net/10261/346446, https://api.elsevier.com/content/abstract/scopus_id/85168844641
Titanium-catalyzed synthesis of polymyrcene and polyanethol and application as sustainable additives for poly(lactic acid)
Digital.CSIC. Repositorio Institucional del CSIC
- Vinueza-Vaca, J.
- Franco-Mateo, Emma
- Sessini, V.
- Mosquera, Marta E.G.
- Souza-Egipsy, Virginia
- Ramos, Javier
- Vega, Juan Francisco
- Jiménez, Gerardo
- Tabernero, Vanessa
12 pags., 11 figs., 4 tabs., The replacement of fossil-derived plastics with those obtained from bio-based resources, which present suitable performance to be employed as commodity plastics is currently an important field of research, given the urgent need to transition from a fossil-based to a more sustainable economy. In this context, this work is focused on the application of a catalytic system based on silsesquioxane-cyclopentadienyl titanium complexes for the preparation of bio-based polymers, which can be used as additives to improve the poor material properties of a biodegradable polymer such as poly(lactic acid) (PLA). These titanium complexes, when activated with methylaluminoxane or with triflate salts, are shown to be capable of the polymerization of two bio-based monomers: myrcene and anethole. It is notable that polymerizations with these two distinct monomers take place through different mechanisms. The resulting polymyrcene (PMy) and polyanethol (PAN) have been applied as modifiers for PLA. Binary blends of PMy and PLA exhibited a considerable decrease in T and the promotion of PLA crystallization for a PMy content below 15 wt%. The mechanical properties of the PLA/PMy blends also displayed plasticization, with a decrease in the elastic modulus and enhanced plasticity, which resulted in less fragile systems compared to pure PLA. Morphological analysis has indicated a partially miscible, phase-separated system with micron-sized domains. In contrast, PAN completely inhibited PLA crystallization and the PLA/PAN blends were immiscible, but well-dispersed, a phase-separated system was obtained in solvent-casting film preparation with very small PAN domains. The blends showed higher tensile modulus than pure PLA and an absence of plastic behaviour, resulting in more fragile systems upon the addition of PAN to PLA., The authors would like to thank the financial support from the Ministerio de Ciencia e Innovacion and Agencia Estatal de Investigacion (Spain) through the project PID2021-122708OB-C31, PID2019-107710GB-I00, TED2021-130871B–C22, and RYC2021-033921-I, Project UAHAE-2017-2. J.M.V. thanks the Universidad de Alcala for FPI-572765 Predoctoral Fellowship and the PIUAH21/CC-028 project. The TEMBIOPHYM Service at the IEM-CSIC is acknowledged for granting the
use of the facilities
use of the facilities
Machine learning algorithms to optimize the properties of bio-based poly(butylene succinate-co- butylene adipate) nanocomposites with carbon nanotubes
e-cienciaDatos, Repositorio de Datos del Consorcio Madroño
- Diez-Pascual, Ana María
- Champa-Bujaico, Elisabeth
- Garcia Díaz, Pilar
- Sesini, Valentina
- G. Mosquera, Marta E.
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, 0.5, 0.65, 0.75, 0.85 and 1.0) have been incorporated in the PBSA matrix via simple solution casting, and the ultrasonication conditions, namely amplitude (A) and time (t) have been optimized to attain a homogenous SWCNT dispersion. The nanocomposites have been characterized in detail by scanning electron microscopy (SEM), Infrared spectroscopy, thermogravimetric analysis (TGA), differential scanning calorimetry (DSC), tensile and impact strength tests. Unprecedented increments in stiffness, up to 114 % for the nanocomposite with 0.65 wt% content,were found. Further, four machine learning (ML) algorithms were applied to predict their mechanical properties and very good correlation was attained.