The nature of the observed free-electron-like state in a PTCDA monolayer on Ag(111)

A free-electron like band has recently been observed in a monolayer of PTCDA (3,4,9,10-perylene tetracarboxylic dianhydride) molecules on Ag(111) by two-photon photoemission [Schwalb et al., Phys. Rev. Lett. 101, 146801 (2008)] and scanning tunneling spectroscopy [Temirov et al., Nature 444, 350 (2006)]. Using density functional theory calculations, we find that the observed free-electron like band originates from the Shockley surface state band being dramatically shifted up in energy by the interaction with the adsorbed molecules while it acquires also a substantial admixture with a molecular band

The nature of highly anisotropic free-electron-like states in a glycinate monolayer on Cu(100)

The free-electron-like state observed in a scanning tunneling spectroscopy study of a chiral p(2x4) monolayer of glycinate ions on the Cu(100) surface [K. Kanazawa et al, J. Am. Chem. Soc. 129, 740 (2007)] is shown from density functional theory calculations to originate from a Cu Shockley surface state at the surface Brillouin zone boundary of the clean surface with highly anisotropic dispersion. The presence of the glycinate ions on the surface causes a dramatically enhanced tunneling into this surface state that is otherwise not observed in tunneling on the bare surface

Cost-effectiveness of a European preventive cardiology programme in primary care: A Markov modelling approach

This is an open-access article distributed under the terms of the Creative Commons Attribution Non-commercial License, which permits use, distribution, and reproduction in any medium, provided the original work is properly cited, the use is non commercial and is otherwise in compliance with the license.OBJECTIVE: To investigate the longer-term cost-effectiveness of a nurse-coordinated preventive cardiology programme for primary prevention of cardiovascular disease (CVD) compared to routine practice from a health service perspective. DESIGN: A matched, paired cluster-randomised controlled trial. SETTING: Six pairs of general practices in six countries. PARTICIPANTS: 1019 patients were randomised to the EUROACTION intervention programme and 1005 patients to usual care (UC) and who completed the 1-year follow-up. OUTCOME MEASURES: Evidence on health outcomes and costs was based on patient-level data from the study, which had a 1-year follow-up period. Future risk of CVD events was modelled, using published risk models based on patient characteristics. An individual-level Markov model for each patient was used to extrapolate beyond the end of the trial, which was populated with data from published sources. We used an 11-year time horizon and investigated the impact on the cost-effectiveness of varying the duration of the effect of the intervention beyond the end of the trial. Results are expressed as incremental cost per quality-adjusted life-year gained. RESULTS: Unadjusted results found the intervention to be more costly and also more effective than UC. However, after adjusting for differences in age, gender, country and baseline risk factors, the intervention was dominated by UC, but this analysis was not able to take into account the lifestyle changes in terms of diet and physical activity. CONCLUSIONS: Although the EUROACTION study achieved healthier lifestyle changes and improvements in management of blood pressure and lipids for patients at high risk of CVD, compared to UC, it was not possible to show, using available risk equations which do not incorporate diet and physical activity, that the intervention reduced longer-term cardiovascular risk cost-effectively. Whether or not an intervention such as that offered by EUROACTION is cost-effective requires a longer-term trial with major cardiovascular events as the outcome.This study is sponsored solely by AstraZeneca through the provision of an unconditional educational grant

Inferring energy-composition relationships with Bayesian optimization enhances exploration of inorganic materials

Computational exploration of the compositional spaces of materials can provide guidance for synthetic research and thus accelerate the discovery of novel materials. Most approaches employ high-throughput sampling and focus on reducing the time for energy evaluation for individual compositions, often at the cost of accuracy. Here, we present an alternative approach focusing on effective sampling of the compositional space. The learning algorithm PhaseBO optimizes the stoichiometry of the potential target material while improving the probability of and accelerating its discovery without compromising the accuracy of energy evaluation

Visible Light Photo-oxidation of Model Pollutants Using CaCu3Ti4O12: An Experimental and Theoretical Study of Optical Properties, Electronic Structure, and Selectivity

[Image: see text] Charge transfer between metal ions occupying distinct crystallographic sublattices in an ordered material is a strategy to confer visible light absorption on complex oxides to generate potentially catalytically active electron and hole charge carriers. CaCu(3)Ti(4)O(12) has distinct octahedral Ti(4+) and square planar Cu(2+) sites and is thus a candidate material for this approach. The sol−gel synthesis of high surface area CaCu(3)Ti(4)O(12) and investigation of its optical absorption and photocatalytic reactivity with model pollutants are reported. Two gaps of 2.21 and 1.39 eV are observed in the visible region. These absorptions are explained by LSDA+U electronic structure calculations, including electron correlation on the Cu sites, as arising from transitions from a Cu-hybridized O 2p-derived valence band to localized empty states on Cu (attributed to the isolation of CuO(4) units within the structure of CaCu(3)Ti(4)O(12)) and to a Ti-based conduction band. The resulting charge carriers produce selective visible light photodegradation of 4-chlorophenol (monitored by mass spectrometry) by Pt-loaded CaCu(3)Ti(4)O(12) which is attributed to the chemical nature of the photogenerated charge carriers and has a quantum yield comparable with commercial visible light photocatalysts

Conformational control of structure and guest uptake by a tripeptide-based porous material

Chemical processes often rely on the selective sorting and transformation of molecules according to their size, shape and chemical functionality. For example, porous materials such as zeolites achieve the required selectivity through the constrained pore dimensions of a single structure.1 In contrast, proteins function by navigating between multiple metastable structures using bond rotations of the polypeptide,2,3 where each structure lies in one of the minima of a conformational energy landscape and can be selected according to the chemistry of the molecules interacting with the protein.3 Here we show that rotation about covalent bonds in a peptide linker can change a flexible metal-organic framework (MOF) to afford nine distinct crystal structures, revealing a conformational energy landscape characterised by multiple structural minima. The uptake of small molecule guests by the MOF can be chemically triggered by inducing peptide conformational change. This change transforms the material from a minimum on the landscape that is inactive for guest sorption to an active one. Chemical control of the conformation of a flexible organic linker offers a route to modify the pore geometry and internal surface chemistry and thus the function of open-framework materials

Element selection for functional materials discovery by integrated machine learning of atomic contributions to properties

At the high level, the fundamental differences between materials originate from the unique nature of the constituent chemical elements. Before specific differences emerge according to the precise ratios of elements (composition) in a given crystal structure (phase), the material can be represented by its phase field defined simply as the set of the constituent chemical elements. Classification of the materials at the level of their phase fields can accelerate materials discovery by selecting the elemental combinations that are likely to produce desirable functional properties in synthetically accessible materials. Here, we demonstrate that classification of the materials phase field with respect to the maximum expected value of a target functional property can be combined with the ranking of the materials synthetic accessibility. This end-to-end machine learning approach (PhaseSelect) first derives the atomic characteristics from the compositional environments in all computationally and experimentally explored materials and then employs these characteristics to classify the phase field by their merit. PhaseSelect can quantify the materials potential at the level of the periodic table, which we demonstrate with significant accuracy for three avenues of materials applications: high-temperature superconducting, high-temperature magnetic and targetted energy band gap materials

Computationally Assisted Identification of Functional Inorganic Materials

Modules of Desire Using computational methods to design materials with specific properties has found some limited success. Dyer et al. (p. 847 , published online 11 April) have devised a method, based on extended module materials assembly, that combines chemical intuition and ab initio calculations starting from fragments or modules of structure types that show the desired functionality. The method was tested by identifying materials suitable for a solid oxide fuel cell cathode. </jats:p

STM fingerprint of molecule–adatom interactions in a self-assembled metal–organic surface coordination network on Cu(111)

7 páginas, 5 figuras, 3 tablas.-- El pdf del artículo es la versión pre-print.A novel approach of identifying metal atoms within a metal–organic surface coordination network using scanning tunnelling microscopy (STM) is presented. The Cu adatoms coordinated in the porous surface network of 1,3,8,10-tetraazaperopyrene (TAPP) molecules on a Cu(111) surface give rise to a characteristic electronic resonance in STM experiments. Using density functional theory calculations, we provide strong evidence that this resonance is a fingerprint of the interaction between the molecules and the Cu adatoms. We also show that the bonding of the Cu adatoms to the organic exodentate ligands is characterised by both the mixing of the nitrogen lone-pair orbitals of TAPP with states on the Cu adatoms and the partial filling of the lowest unoccupied molecular orbital (LUMO) of the TAPP molecule. Furthermore, the key interactions determining the surface unit cell of the network are discussed.This work was financially supported by the European Union through the Marie Curie Research Training Network PRAIRIES (MRTN-CT-2006-035810). Support from the Swiss National Science Foundation, the National Center of Competence in Research (NCCR) ‘‘Nanoscale Science’’ and the Wolfermann Naegeli Stiftung is also acknowledged. MP is also grateful for support from the Swedish Research Council (VR).Peer reviewe