11 research outputs found
Low-coverage heteroepitaxial growth with interfacial mixing
We investigate the influence of intermixing on heteroepitaxial growth
dynamics, using a two-dimensional point island model, expected to be a good
approximation in the early stages of epitaxy. In this model, which we explore
both analytically and numerically, every deposited B atom diffuses on the
surface with diffusion constant , and can exchange with any A atom
of the substrate at constant rate. There is no exchange back, and emerging
atoms diffuse on the surface with diffusion constant . When any two
diffusing atoms meet, they nucleate a point island. The islands neither diffuse
nor break, and grow by capturing other diffusing atoms. The model leads to an
island density governed by the diffusion of one of the species at low
temperature, and by the diffusion of the other at high temperature. We show
that these limit behaviors, as well as intermediate ones, all belong to the
same universality class, described by a scaling law. We also show that the
island-size distribution is self-similarly described by a dynamic scaling law
in the limits where only one diffusion constant is relevant to the dynamics,
and that this law is affected when both and play a
role.Comment: 16 pages, 6 figure
Converting genetic network oscillations into somite spatial pattern
In most vertebrate species, the body axis is generated by the formation of
repeated transient structures called somites. This spatial periodicity in
somitogenesis has been related to the temporally sustained oscillations in
certain mRNAs and their associated gene products in the cells forming the
presomatic mesoderm. The mechanism underlying these oscillations have been
identified as due to the delays involved in the synthesis of mRNA and
translation into protein molecules [J. Lewis, Current Biol. {\bf 13}, 1398
(2003)]. In addition, in the zebrafish embryo intercellular Notch signalling
couples these oscillators and a longitudinal positional information signal in
the form of an Fgf8 gradient exists that could be used to transform these
coupled temporal oscillations into the observed spatial periodicity of somites.
Here we consider a simple model based on this known biology and study its
consequences for somitogenesis. Comparison is made with the known properties of
somite formation in the zebrafish embryo . We also study the effects of
localized Fgf8 perturbations on somite patterning.Comment: 7 pages, 7 figure
The Naming Game in Social Networks: Community Formation and Consensus Engineering
We study the dynamics of the Naming Game [Baronchelli et al., (2006) J. Stat.
Mech.: Theory Exp. P06014] in empirical social networks. This stylized
agent-based model captures essential features of agreement dynamics in a
network of autonomous agents, corresponding to the development of shared
classification schemes in a network of artificial agents or opinion spreading
and social dynamics in social networks. Our study focuses on the impact that
communities in the underlying social graphs have on the outcome of the
agreement process. We find that networks with strong community structure hinder
the system from reaching global agreement; the evolution of the Naming Game in
these networks maintains clusters of coexisting opinions indefinitely. Further,
we investigate agent-based network strategies to facilitate convergence to
global consensus.Comment: The original publication is available at
http://www.springerlink.com/content/70370l311m1u0ng3
Opinion dynamics: models, extensions and external effects
Recently, social phenomena have received a lot of attention not only from
social scientists, but also from physicists, mathematicians and computer
scientists, in the emerging interdisciplinary field of complex system science.
Opinion dynamics is one of the processes studied, since opinions are the
drivers of human behaviour, and play a crucial role in many global challenges
that our complex world and societies are facing: global financial crises,
global pandemics, growth of cities, urbanisation and migration patterns, and
last but not least important, climate change and environmental sustainability
and protection. Opinion formation is a complex process affected by the
interplay of different elements, including the individual predisposition, the
influence of positive and negative peer interaction (social networks playing a
crucial role in this respect), the information each individual is exposed to,
and many others. Several models inspired from those in use in physics have been
developed to encompass many of these elements, and to allow for the
identification of the mechanisms involved in the opinion formation process and
the understanding of their role, with the practical aim of simulating opinion
formation and spreading under various conditions. These modelling schemes range
from binary simple models such as the voter model, to multi-dimensional
continuous approaches. Here, we provide a review of recent methods, focusing on
models employing both peer interaction and external information, and
emphasising the role that less studied mechanisms, such as disagreement, has in
driving the opinion dynamics. [...]Comment: 42 pages, 6 figure
Enhanced light emission in Si-nanoclusters arrays
An array of silicon nanoclusters aimed at producing light emission upon injection of electrons and holes from external sources is studied by Monte Carlo simulations. The conditions for obtaining a significant charge accumulation in the emitting nanoclusters are investigated as a function of array geometry and applied electric fields. It is found that if a stationary state, reached for an applied field F 0, is suddenly perturbed by a field F 1≫F 0, a significant increase in electron-hole pairs population can be obtained with respect to the case of a single field of constant intensity F 1, leading to enhanced light emission when the conductivity of the array is above 6×10 -10  [ Ω cm] -1 . The excess population thus created gets fully recombined on the time scale of milliseconds, suggesting a device that can produce enhanced light emission in the range of kilohertz. Copyright EDP Sciences/Società Italiana di Fisica/Springer-Verlag 200685.60.Jb Light-emitting devices, 05.10.Ln Monte Carlo methods, 73.63.-b Electronic transport in nanoscale materials and structures,
Effects of Coulomb interaction on charge transport in a silicon-based nanocluster array
The effects of Coulomb interaction on charge transport in a model of light emission from an array of silicon nanoclusters are studied by Monte Carlo simulations. The array is sandwiched between a p-type and an n-type doped silicon crystals and electrons and holes are driven into the array by an applied electric field. Radiative recombinations of electrons and holes take place near the center of the array producing the emission of red light, and the total emission power is approximately proportional to the current injected into the system. It is found that the carrier-carrier interaction plays a crucial role in charge transport. Specifically, the self-interaction of charges inside each nanocluster is found to be the dominant interaction term for the semiclassical Hamiltonian considered. In addition, it drastically limits the current in the device giving rise to a strong non-linear relation between current and density of free carriers in the doped silicon crystals. Copyright EDP Sciences/Società Italiana di Fisica/Springer-Verlag 2005
Evolutionary Developmental Biology and the Limits of Philosophical Accounts of Mechanistic Explanation
Abstract Evolutionary developmental biology (evo-devo) is considered a ‘mechanistic science, ’ in that it causally explains morphological evolution in terms of changes in developmental mechanisms. Evo-devo is also an interdisciplinary and integrative approach, as its explanations use contributions from many fields and pertain to different levels of organismal organization. Philosophical accounts of mechanistic explanation are currently highly prominent, and have been particularly able to capture the integrative nature of multifield and multilevel explanations. However, I argue that evo-devo demonstrates the need for a broadened philosophical conception of mechanisms and mechanistic explanation. Mechanistic explanation (in terms of the qualitative interactions of the structural parts of a whole) has been developed as an alternative to the traditional idea of explanation as derivation from laws or quantitative principles. Against the picture promoted by Carl Craver, that mathematical models describe but do not explain, my discussion of cases from the strand of evo-devo which is concerned with developmental processes points to qualitative phenomena where quantitative mathematical models are an indispensable part of the explanation. While philosophical accounts have focused on the actual organization and operation of mechanisms, properties of developmental mechanisms that are about how a mechanism reacts to modifications are of major evolutionary significance, including robustness, phenotypic plasticity, and modularity. A philosophical conception of mechanisms is needed that takes into account quantitative changes, transient entities and the generation of novel types of entities, feedback loops and complex interaction networks, emergent properties, and, in particular, functional-dynamical aspects of mechanisms, including functional (as opposed to structural) organization and distributed, system-wide phenomena. I conclude with general remarks on philosophical accounts of explanation