Breakdown of the adiabatic Born-Oppenheimer approximation in graphene

The adiabatic Born-Oppenheimer approximation (ABO) has been the standard ansatz to describe the interaction between electrons and nuclei since the early days of quantum mechanics. ABO assumes that the lighter electrons adjust adiabatically to the motion of the heavier nuclei, remaining at any time in their instantaneous ground state. ABO is well justified when the energy gap between ground and excited electronic states is larger than the energy scale of the nuclear motion. In metals, the gap is zero and phenomena beyond ABO (such as phonon-mediated superconductivity or phonon-induced renormalization of the electronic properties) occur. The use of ABO to describe lattice motion in metals is, therefore, questionable. In spite of this, ABO has proved effective for the accurate determination of chemical reactions, molecular dynamics and phonon frequencies in a wide range of metallic systems. Here, we show that ABO fails in graphene. Graphene, recently discovered in the free state, is a zero-bandgap semiconductor that becomes a metal if the Fermi energy is tuned applying a gate voltage, Vg. This induces a stiffening of the Raman G peak that cannot be described within ABO.     

In situ observations of catalyst dynamics during surface-bound carbon nanotube nucleation

We present atomic-scale, video-rate environmental transmission electron microscopy and in situ time-resolved X-ray photoelectron spectroscopy of surface-bound catalytic chemical vapor deposition of single-walled carbon nanotubes and nanofibers. We observe that transition metal catalyst nanoparticles on SiOx support show crystalline lattice fringe contrast and high deformability before and during nanotube formation. A single-walled carbon nanotube nucleates by lift-off of a carbon cap. Cap stabilization and nanotube growth involve the dynamic reshaping of the catalyst nanocrystal itself. For a carbon nanofiber, the graphene layer stacking is determined by the successive elongation and contraction of the catalyst nanoparticle at its tip.     

Topologically controlled growth of magnetic-metal-functionalized semiconductor oxide nanorods

Colloidal semiconductor-magnetic hybrid nanocrystals with topologically controlled composition are fabricated by heterogeneous nucleation of spherical epsilon-Co domains onto anatase TiO2 nanorods. The latter can be selectively decorated at either their tips or at multiple locations along their longitudinal sidewalls, forming lattice-matched heterointerfaces regardless of the metal deposition sites. The possibility of switching between either heterostructure growth modes arises from the facet-dependent chemical reactivity of the oxide seeds, which is governed mainly by selective adhesion of the surfactants rather than by small differences in misfit-induced interfacial strain at the relevant junction points.     

An empirical approach to compare the performance of heterogeneous academic fields

In this paper, we propose a ‘scaling’ approach to compare the scientific performance of Italian heterogeneous academic disciplines. This method is based on the idea that, after eliminating the percentages of ‘silent’ researchers, the distribution of bibliometric parameters of the different academic fields can be superimposed and collapse into a unique master curve by a single scaling parameter. By using data on the scientific production of around 2,500 scholars of the university of Rome ‘La Sapienza’ from the Web of Science from 2004 to 2008, we (i) demonstrate the existence of a master curve, (ii) determine the scaling factors that work like rates of substitution to compare the scientific production across different academic fields on a common ground, (iii) show that the master bibliometric distribution follows a log-normal law and (iv) illustrate the relevance of the proposed approach for research assessment and allocation of competitive funding at the university level.     

Synthesis, characterization and antimicrobial activity of conjugates based on fluoroquinolon-type antibiotics and gelatin

Different fluoroquinolon-type antibiotics were conjugated to gelatin with the aim to synthesize biomacromolecules with antimicrobial properties. The covalent linkage of the antibiotic was performed by a radical process involving the residues in the side chains of gelatin able to undergo oxidative modifications. The conjugation of antibiotic moieties onto the protein structure was confirmed by FT-IR, UV–Vis, fluorescence, and calorimetric analyses. Biocompatibility tests were performed on human bone marrow mesenchymal stromal cells and the antibacterial properties of bioactive polymers were investigated by appropriate tests against Klebsiella pneumoniae and Escherichia coli. With regard to the tests conducted in the presence of E. coli, a minimum inhibitory concentration (MIC) ranging from 0.05 to 0.40 μg mL^?1 was recorded, while in the presence of K. pneumoniae this concentration varies from 0.10 to 1.60 μg mL^?1. In all the conjugates, the drug moieties retain their biological activity and the MIC values are lower than the resistance parameters of fluoroquinolon-type antibiotics versus Enterobacteriacae. The collected data suggest a broad range of applications, from biomedical to pharmaceutical and food science for all conjugates.     

Using normative ethics for building a good evaluation of research practices: towards the assessment of researcher’s virtues

This paper is an attempt of using co-citation analysis to sort out and to analyze the development and evolution of a latest hot area, open innovation from the perspective of network embedding. A dataset of 1437 records published between 1990 and 2019 is collected from Web of Science database. The empirical results show the latest hot topics in the open innovation study focus on innovation performance and value creation. In addition, we make a new interpretation of open innovation from four aspects: innovation and entrepreneurship, resource acquisition, knowledge sharing and innovation performance, then combines the importance of network embedding to the innovation and development of enterprises, and proposes the future research direction of open innovation. Our research in this paper is helpful to systematically sort out the knowledge context of open innovation, which is of great significance to the construction and development of open innovation knowledge system. The conclusions and implications in this paper will be particularly illuminating for both academic research and enterprises’ practice application.

     

A comparison of three multidisciplinarity indices based on the diversity of Scopus subject areas of authors’ documents,their bibliography and their citing papers

Scientometrics - In this paper, we compare the distribution of Elsevier Scopus subject areas of authors’ documents, their bibliographical references and their citing documents. We compute the...     

Uncertainty in health risk analysis

This paper discuss several quantitative issues that arise in the analysis of health risks, beginning with principles such as de minimis and zero-risk. The paper also provides a probabilistic definition of risk in terms of hazard, context, consequence, magnitude, and uncertainty. The example relies on this definition to investigate, through sensitivity analysis, the effect that uncertainty has on the results obtained. The results, from a case study based on waterborne total arsenic, show that the choice of dose—response functions causes more uncertainty than any other component of risk analysis. Chemical carcinogenesis provides the basis for discussing inability to know as well as uncertainty. The conclusion is that risk analysis keeps uncertainty and inability to know separate; through this function, it provides a much needed method to present information to decision makers and the public.     

Robust Bayesian analysis given priors on partition sets

Summary In a Bayesian analysis, suppose that probability measures may be specified over the subsets partitioning the parameter space Ω, in such a way that they can be combined to form a unique prior measure, defined over all Ω, according to some weights. Should the weights be uncertain, then the class Г of all the probability measures compatible with such uncertainty is specified instead. Situations in which such a class Г is justified are presented and, in these cases, established and quite recent techniques in the field of robust Bayesian analysis are applied to Г. Bounds on posterior expectations are computed, as the prior measure varies in Г, whilst concentration functions and coefficients of divergence are considered when interest lies with comparing functional forms of measures in Г.