El texto del Buscón, de Quevedo

Sin resume

Francisco de Quevedo, La vida del Buscón. Edición, estudio y notas de Fernando Cabo Aseguinolaza. Real Academia Española, Madrid, s.a. [2011], xii + 465 pp.

Se reseña el libro:La vida del Buscón. Edición, estudio y notas de Fernando Cabo Aseguinolaza

Enmiendas ideológicas al Buscón

En este trabajo se repasan algunos de los problemas generales que plantea la lectura e interpretación del Buscón. Aunque no existen datos inequívocos sobre la fecha de redacción de esta obra, Jauralde defiende una redacción única en torno a 1604 y afirma que no existe «ni un solo testimonio ni directo ni indirecto de que Quevedo retocara mínimamente el Buscón». En su opinión, la originalidad de esta pieza quevediana frente al Lazarillo y el Guzmán consiste «en una actitud más ideológica que formal». Después de repasar el proceso de transmisión del texto, analiza otros aspectos como su adscripción al género picaresco, su estructura, el ritmo narrativo y las diversas interpretaciones críticas que la obra ha suscitado. This article tries to examine some problems arisen by the reading and interpretation of Quevedo's El Buscón. Although we lack indisputable information about the date in which this work was written, Jauralde believes that the work was written around 1604 and assures that there is not a direct testimony nor indirect proving that Quevedo revised El Buscón later. In his opinion, «the originality of this work compared with El Lazarillo or El Guzmán de Alfarache rests on the ideologic attitude more than on a formal one». After summarizing the process of transmission of the text, he analyses other aspects such as its being in the picaresque genre, its structure, the narrative rithm and the different critic inerpretations that El Buscón has received

Forces and currents in carbon nanostructures: Are we imaging atoms?

First-principles calculations show that the rich variety of image patterns found in carbon nanostructures with the atomic force and scanning tunneling microscopes can be rationalized in terms of the chemical reactivity of the tip and the distance range explored in the experiments. For weakly reactive tips, the Pauli repulsion dominates the atomic contrast and force maxima are expected on low electronic density positions as the hollow site. With reactive tips, the interaction is strong enough to change locally the hybridization of the carbon atoms, making it possible to observe atomic resolution in both the attractive and the repulsive regime although with inverted contrast. Regarding STM images, we show that in the near-contact regime, due to current saturation, bright spots correspond to hollow positions instead of atomic sites, providing an explanation for the most common hexagonal pattern found in the experimentsWe acknowledge the support of Projects No. 202/09/0545 and No. 204/10/0952 (GAĈR), No. M100100904 (GAAV), No. MAT2008-02929-NAN, No. MAT2008-02939-E, No. MAT2008-01497, and No. CSD2007-41 (MICINN, Spain), a JAE-doc contract (CSIC), and the Ramón y Cajal Program (MICINN)

Molecular Identification from AFM Images Using the IUPAC Nomenclature and Attribute Multimodal Recurrent Neural Networks

Spectroscopic methods like nuclear magnetic resonance, mass spectrometry, X-ray diffraction, and UV/visible spectroscopies applied to molecular ensembles have so far been the workhorse for molecular identification. Here, we propose a radically different chemical characterization approach, based on the ability of noncontact atomic force microscopy with metal tips functionalized with a CO molecule at the tip apex (referred as HRAFM) to resolve the internal structure of individual molecules. Our work demonstrates that a stack of constant-height HR-AFM images carries enough chemical information for a complete identification (structure and composition) of quasiplanar organic molecules, and that this information can be retrieved using machine learning techniques that are able to disentangle the contribution of chemical composition, bond topology, and internal torsion of the molecule to the HR-AFM contrast. In particular, we exploit multimodal recurrent neural networks (M-RNN) that combine convolutional neural networks for image analysis and recurrent neural networks to deal with language processing, to formulate the molecular identification as an imaging captioning problem. The algorithm is trained using a data set which contains almost 700,000 molecules and 165 million theoretical AFM images to produce as final output the IUPAC name of the imaged molecule. Our extensive test with theoretical images and a few experimental ones shows the potential of deep learning algorithms in the automatic identification of molecular compounds by AFM. This achievement supports the development of on-surface synthesis and overcomes some limitations of spectroscopic methods in traditional solution-based synthesisWe would like to acknowledge support from the Comunidad de Madrid Industrial Doctorate programme 2017 under reference number IND2017/IND7793 and from Quasar Science Resources S.L. P.P. and R.P. acknowledge support from the Spanish Ministry of Science and Innovation, through project PID2020-115864RB-I00 and the “María de Maeztu” Programme for Units of Excellence in R&D (CEX2018-000805-M). C.R.-M. acknowledges financial support by the Ramón y Cajal program of the Spanish Ministry of Science and Innovation (ref. RYC2021-031176-I). Computer time provided by the Red Española de Supercomputación (RES) at the Finisterrae II Supercomputer is also acknowledge

Substrate-induced enhancement of the chemical reactivity in metal-supported graphene

Graphene is commonly regarded as an inert material. However, it is well known that the presence of defects or substitutional hetero-atoms confers graphene promising catalytic properties. In this work, we use first-principles calculations to show that it is also possible to enhance the chemical reactivity of a graphene layer by simply growing it on an appropriate substrate. Our comprehensive study demonstrates that, in strongly interacting substrates like Rh(111), graphene adopts highly rippled structures that exhibit areas with distinctive chemical behaviors. According to the local coupling with the substrate, we find areas with markedly different adsorption, dissociation and diffusion pathways for both molecular and atomic oxygen, including a significant change in the nature of the adsorbed molecular and dissociated states, and a dramatic reduction (∼60%) of the O2dissociation energy barrier with respect to free-standing graphene. Our results show that the graphene-metal interaction represents an additional and powerful handle to tailor the graphene chemical properties with potential applications to nano patterning, graphene functionalization and sensing devicesWe thank the financial support from the Spanish MINECO (projects MAT2014-54484-P, MDM-2014-0377, MAT2016-77852-C2-2-R (AEI/FEDER, UE) and MAT2017-83273-R (AEI/FEDER,UE)). Computer time provided by the Spanish Supercomputer Network (RES) at the Magerit (CesViMa, Madrid) and Altamira (IFCA, Santander) supercomputers. CRM is grateful to the FPI-UAM graduate scholarship program and to Fundación Universia for financial suppor