The lowest energy configurations of Cn(n =< 55) clusters are obtained using the energy mini- mization technique with the conjugate gradient (CG) method where a modified Brenner potential is invoked to describe the carbon and hydrocarbon interaction. We found that the ground state configuration consists of a single ring for small number of C atoms and multi-ring structures are found with increasing n, which can be in planar, bowl-like or cap-like form. Contrary to previous predictions, the binding energy Eb does not show even-odd oscillations and only small jumps are found in the Eb(n) curve as a consequence of specific types of edges or equivalently the number of secondary atoms. We found that hydrogenation of the edge atoms may change the ground state configuration of the nanocluster. In both cases we determined the magic clusters. Special attention is paid to trigonal and hexagonal shaped carbon clusters and to clusters having a graphene-like configuration. Trigonal clusters are never the ground state, while hexagonal shaped clusters are only the ground state when they have zigzag edges.Comment: Accepted for publication in Phys. Rev.

Chemisorption of hydrogen on graphene is studied using atomistic simulations with the second generation of reactive empirical bond order Brenner inter-atomic potential. The lowest energy adsorption sites and the most important metastable sites are determined. The H concentration is varied from a single H atom, to clusters of H atoms up to full coverage. We found that when two or more H atoms are present, the most stable configurations of H chemisorption on a single graphene layer are ortho hydrogen pairs adsorbed on one side or on both sides of the graphene sheet. The latter has the highest hydrogen binding energy. The next stable configuration is the ortho-para pair combination, and then para hydrogen pairs. The structural changes of graphene caused by chemisorbed hydrogen are discussed and are compared with existing experimental data and other theoretical calculations. The obtained results will be useful for nanoengineering of graphene by hydrogenation and for hydrogen storage. ‫٭‬ Corresponding author. Fax: +32 3 2653204. E-mail: Abdiravuf.Dzhurakhalov@ua.ac.be a http://webbook.nist.gov/chemistry/ b http://srdata.nist.gov/cccbdb/

Both even-and odd-numbered neutral carbon clusters C n (n = 2-10) are systematically studied using the energy minimization method and the modified Brenner potential for the carboncarbon interactions. Many stable configurations were found and several new isomers are predicted. For the lowest energy stable configurations we obtained their binding energies and bond lengths. We found that for n ≤ 5 the linear isomer is the most stable one while for n > 5 the monocyclic isomer becomes the most stable. The latter was found to be regular for all studied clusters. The dependence of the binding energy for linear and cyclic clusters versus the cluster size n (n = 2-10) is found to be in good agreement with several previous calculations, in particular with ab initio calculations as well as with experimental data for n = 2-5. PACS number(s): 36.40.Mr, 61.46.Bc, 81.05.Uw Corresponding author: A.A. Dzhurakhalov, Abdiravuf.Dzhurakhalov@ua.ac.be Fax: +32-3-2653542

Modelling and simulation are increasingly used as tools in the study of plant growth and developmental processes. By formulating experimentally obtained knowledge as a system of interacting mathematical equations, it becomes feasible for biologists to gain a mechanistic understanding of the complex behaviour of biological systems. In this review, the modelling tools that are currently available and the progress that has been made to model plant development, based on experimental knowledge, are described. In terms of implementation, it is argued that, for the modelling of plant organ growth, the cellular level should form the cornerstone. It integrates the output of molecular regulatory networks to two processes, cell division and cell expansion, that drive growth and development of the organ. In turn, these cellular processes are controlled at the molecular level by hormone signalling. Therefore, combining a cellular modelling framework with regulatory modules for the regulation of cell division, expansion, and hormone signalling could form the basis of a functional organ growth simulation model. The current state of progress towards this aim is that the regulation of the cell cycle and hormone transport have been modelled extensively and these modules could be integrated. However, much less progress has been made on the modelling of cell expansion, which urgently needs to be addressed. A limitation of the current generation models is that they are largely qualitative. The possibilities to characterize existing and future models more quantitatively will be discussed. Together with experimental methods to measure crucial model parameters, these modelling techniques provide a basis to develop a Systems Biology approach to gain a fundamental insight into the relationship between gene function and whole organ behaviour.

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Motivation: Computational modeling of plant developmental processes is becoming increasingly important. Cellular resolution plant tissue simulators have been developed, yet they are typically describing physiological processes in an isolated way, strongly delimited in space and time.Results: With plant systems biology moving toward an integrative perspective on development we have built the Virtual Plant Tissue (VPTissue) package to couple functional modules or models in the same framework and across different frameworks. Multiple levels of model integration and coordination enable combining existing and new models from different sources, with diverse options in terms of input/output. Besides the core simulator the toolset also comprises a tissue editor for manipulating tissue geometry and cell, wall, and node attributes in an interactive manner. A parameter exploration tool is available to study parameter dependence of simulation results by distributing calculations over multiple systems.Availability: Virtual Plant Tissue is available as open source (EUPL license) on Bitbucket (https://bitbucket.org/vptissue/vptissue). The project has a website https://vptissue.bitbucket.io.

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