Computation
http://mdpi.com/journal/computation
Latest open access articles published in Computation at http://mdpi.com/journal/computation<![CDATA[Computation, Vol. 3, Pages 114-127: Evolution by Pervasive Gene Fusion in Antibiotic Resistance and Antibiotic Synthesizing Genes]]>
http://mdpi.com/2079-3197/3/2/114
Phylogenetic (tree-based) approaches to understanding evolutionary history are unable to incorporate convergent evolutionary events where two genes merge into one. In this study, as exemplars of what can be achieved when a tree is not assumed a priori, we have analysed the evolutionary histories of polyketide synthase genes and antibiotic resistance genes and have shown that their history is replete with convergent events as well as divergent events. We demonstrate that the overall histories of these genes more closely resembles the remodelling that might be seen with the children’s toy Lego, than the standard model of the phylogenetic tree. This work demonstrates further that genes can act as public goods, available for re-use and incorporation into other genetic goods.Computation2015-03-2632Article10.3390/computation30201141141272079-31972015-03-26doi: 10.3390/computation3020114Orla ColemanRuth HoganNicole McGoldrickNiamh RuddenJames McInerney<![CDATA[Computation, Vol. 3, Pages 99-113: Evolutionary Dynamics in Gene Networks and Inference Algorithms]]>
http://mdpi.com/2079-3197/3/1/99
Dynamical interactions among sets of genes (and their products) regulate developmental processes and some dynamical diseases, like cancer. Gene regulatory networks (GRNs) are directed networks that define interactions (links) among different genes/proteins involved in such processes. Genetic regulation can be modified during the time course of the process, which may imply changes in the nodes activity that leads the system from a specific state to a different one at a later time (dynamics). How the GRN modifies its topology, to properly drive a developmental process, and how this regulation was acquired across evolution are questions that the evolutionary dynamics of gene networks tackles. In the present work we review important methodology in the field and highlight the combination of these methods with evolutionary algorithms. In recent years, this combination has become a powerful tool to fit models with the increasingly available experimental data.Computation2015-03-1331Review10.3390/computation3010099991132079-31972015-03-13doi: 10.3390/computation3010099Daniel Aguilar-HidalgoMaría LemosAntonio Córdoba<![CDATA[Computation, Vol. 3, Pages 72-98: Use of CMEIAS Image Analysis Software to Accurately Compute Attributes of Cell Size, Morphology, Spatial Aggregation and Color Segmentation that Signify in Situ Ecophysiological Adaptations in Microbial Biofilm Communities]]>
http://mdpi.com/2079-3197/3/1/72
In this review, we describe computational features of computer-assisted microscopy that are unique to the Center for Microbial Ecology Image Analysis System (CMEIAS) software, and examples illustrating how they can be used to gain ecophysiological insights into microbial adaptations occurring at micrometer spatial scales directly relevant to individual cells occupying their ecological niches in situ. These features include algorithms that accurately measure (1) microbial cell length relevant to avoidance of protozoan bacteriovory; (2) microbial biovolume body mass relevant to allometric scaling and local apportionment of growth-supporting nutrient resources; (3) pattern recognition rules for morphotype classification of diverse microbial communities relevant to their enhanced fitness for success in the particular habitat; (4) spatial patterns of coaggregation that reveal the local intensity of cooperative vs. competitive adaptations in colonization behavior relevant to microbial biofilm ecology; and (5) object segmentation of complex color images to differentiate target microbes reporting successful cell-cell communication. These unique computational features contribute to the CMEIAS mission of developing accurate and freely accessible tools of image bioinformatics that strengthen microscopy-based approaches for understanding microbial ecology at single-cell resolution.Computation2015-03-0931Review10.3390/computation301007272982079-31972015-03-09doi: 10.3390/computation3010072Frank DazzoBrighid Niccum<![CDATA[Computation, Vol. 3, Pages 58-71: Visual Simulation of Soil-Microbial System Using GPGPU Technology]]>
http://mdpi.com/2079-3197/3/1/58
General Purpose (use of) Graphics Processing Units (GPGPU) is a promising technology for simulation upscaling; in particular for bottom–up modelling approaches seeking to translate micro-scale system processes to macro-scale properties. Many existing simulations of soil ecosystems do not recover the emergent system scale properties and this may be a consequence of “missing” information at finer scales. Interpretation of model output can be challenging and we advocate the “built-in” visual simulation afforded by GPGPU implementations. We apply this GPGPU approach to a reaction–diffusion soil ecosystem model with the intent of linking micro (micron) and core (cm) spatial scales to investigate how microbes respond to changing environments and the consequences on soil respiration. The performance is evaluated in terms of computational speed up, spatial upscaling and visual feedback. We conclude that a GPGPU approach can significantly improve computational efficiency and offers the potential added benefit of visual immediacy. For massive spatial domains distribution over GPU devices may still be required.Computation2015-02-2731Article10.3390/computation301005858712079-31972015-02-27doi: 10.3390/computation3010058Ruth FalconerAlasdair Houston<![CDATA[Computation, Vol. 3, Pages 29-57: A Review of Two Multiscale Methods for the Simulation of Macromolecular Assemblies: Multiscale Perturbation and Multiscale Factorization]]>
http://mdpi.com/2079-3197/3/1/29
Many mesoscopic N-atom systems derive their structural and dynamical properties from processes coupled across multiple scales in space and time. That is, they simultaneously deform or display collective behaviors, while experiencing atomic scale vibrations and collisions. Due to the large number of atoms involved and the need to simulate over long time periods of biological interest, traditional computational tools, like molecular dynamics, are often infeasible for such systems. Hence, in the current review article, we present and discuss two recent multiscale methods, stemming from the N-atom formulation and an underlying scale separation, that can be used to study such systems in a friction-dominated regime: multiscale perturbation theory and multiscale factorization. These novel analytic foundations provide a self-consistent approach to yield accurate and feasible long-time simulations with atomic detail for a variety of multiscale phenomena, such as viral structural transitions and macromolecular self-assembly. As such, the accuracy and efficiency of the associated algorithms are demonstrated for a few representative biological systems, including satellite tobacco mosaic virus (STMV) and lactoferrin.Computation2015-02-0531Article10.3390/computation301002929572079-31972015-02-05doi: 10.3390/computation3010029Stephen PankavichPeter Ortoleva<![CDATA[Computation, Vol. 3, Pages 2-28: Computational Studies of the Intestinal Host-Microbiota Interactome]]>
http://mdpi.com/2079-3197/3/1/2
A large and growing body of research implicates aberrant immune response and compositional shifts of the intestinal microbiota in the pathogenesis of many intestinal disorders. The molecular and physical interaction between the host and the microbiota, known as the host-microbiota interactome, is one of the key drivers in the pathophysiology of many of these disorders. This host-microbiota interactome is a set of dynamic and complex processes, and needs to be treated as a distinct entity and subject for study. Disentangling this complex web of interactions will require novel approaches, using a combination of data-driven bioinformatics with knowledge-driven computational modeling. This review describes the computational approaches for investigating the host-microbiota interactome, with emphasis on the human intestinal tract and innate immunity, and highlights open challenges and existing gaps in the computation methodology for advancing our knowledge about this important facet of human health.Computation2015-01-1431Review10.3390/computation30100022282079-31972015-01-14doi: 10.3390/computation3010002Scott ChristleyChase CockrellGary An<![CDATA[Computation, Vol. 3, Pages 1: Acknowledgement to Reviewers of Computation in 2014]]>
http://mdpi.com/2079-3197/3/1/1
The editors of Computation would like to express their sincere gratitude to the following reviewers for assessing manuscripts in 2014:[...]Computation2015-01-0931Editorial10.3390/computation3010001112079-31972015-01-09doi: 10.3390/computation3010001 Computation Editorial Office<![CDATA[Computation, Vol. 2, Pages 246-257: SBMLSimulator: A Java Tool for Model Simulation and Parameter Estimation in Systems Biology]]>
http://mdpi.com/2079-3197/2/4/246
The identification of suitable model parameters for biochemical reactions has been recognized as a quite difficult endeavor. Parameter values from literature or experiments can often not directly be combined in complex reaction systems. Nature-inspired optimization techniques can find appropriate sets of parameters that calibrate a model to experimentally obtained time series data. We present SBMLsimulator, a tool that combines the Systems Biology Simulation Core Library for dynamic simulation of biochemical models with the heuristic optimization framework EvA2. SBMLsimulator provides an intuitive graphical user interface with various options as well as a fully-featured command-line interface for large-scale and script-based model simulation and calibration. In a parameter estimation study based on a published model and artificial data we demonstrate the capability of SBMLsimulator to identify parameters. SBMLsimulator is useful for both, the interactive simulation and exploration of the parameter space and for the large-scale model calibration and estimation of uncertain parameter values.Computation2014-12-1824Article10.3390/computation20402462462572079-31972014-12-18doi: 10.3390/computation2040246Alexander DörrRoland KellerAndreas ZellAndreas Dräger<![CDATA[Computation, Vol. 2, Pages 221-245: Computational and Statistical Analyses of Insertional Polymorphic Endogenous Retroviruses in a Non-Model Organism]]>
http://mdpi.com/2079-3197/2/4/221
Endogenous retroviruses (ERVs) are a class of transposable elements found in all vertebrate genomes that contribute substantially to genomic functional and structural diversity. A host species acquires an ERV when an exogenous retrovirus infects a germ cell of an individual and becomes part of the genome inherited by viable progeny. ERVs that colonized ancestral lineages are fixed in contemporary species. However, in some extant species, ERV colonization is ongoing, which results in variation in ERV frequency in the population. To study the consequences of ERV colonization of a host genome, methods are needed to assign each ERV to a location in a species’ genome and determine which individuals have acquired each ERV by descent. Because well annotated reference genomes are not widely available for all species, de novo clustering approaches provide an alternative to reference mapping that are insensitive to differences between query and reference and that are amenable to mobile element studies in both model and non-model organisms. However, there is substantial uncertainty in both identifying ERV genomic position and assigning each unique ERV integration site to individuals in a population. We present an analysis suitable for detecting ERV integration sites in species without the need for a reference genome. Our approach is based on improved de novo clustering methods and statistical models that take the uncertainty of assignment into account and yield a probability matrix of shared ERV integration sites among individuals. We demonstrate that polymorphic integrations of a recently identified endogenous retrovirus in deer reflect contemporary relationships among individuals and populations.Computation2014-11-2824Article10.3390/computation20402212212452079-31972014-11-28doi: 10.3390/computation2040221Le BaoDaniel EllederRaunaq MalhotraMichael DeGiorgioTheodora MaravegiasLindsay HorvathLaura CarrelColin GillinTomáš HronHelena FábryováDavid HunterMary Poss<![CDATA[Computation, Vol. 2, Pages 199-220: Computation of the Likelihood in Biallelic Diffusion Models Using Orthogonal Polynomials]]>
http://mdpi.com/2079-3197/2/4/199
In population genetics, parameters describing forces such as mutation, migration and drift are generally inferred from molecular data. Lately, approximate methods based on simulations and summary statistics have been widely applied for such inference, even though these methods waste information. In contrast, probabilistic methods of inference can be shown to be optimal, if their assumptions are met. In genomic regions where recombination rates are high relative to mutation rates, polymorphic nucleotide sites can be assumed to evolve independently from each other. The distribution of allele frequencies at a large number of such sites has been called “allele-frequency spectrum” or “site-frequency spectrum” (SFS). Conditional on the allelic proportions, the likelihoods of such data can be modeled as binomial. A simple model representing the evolution of allelic proportions is the biallelic mutation-drift or mutation-directional selection-drift diffusion model. With series of orthogonal polynomials, specifically Jacobi and Gegenbauer polynomials, or the related spheroidal wave function, the diffusion equations can be solved efficiently. In the neutral case, the product of the binomial likelihoods with the sum of such polynomials leads to finite series of polynomials, i.e., relatively simple equations, from which the exact likelihoods can be calculated. In this article, the use of orthogonal polynomials for inferring population genetic parameters is investigated.Computation2014-11-1424Review10.3390/computation20401991992202079-31972014-11-14doi: 10.3390/computation2040199Claus Vogl<![CDATA[Computation, Vol. 2, Pages 182-198: Incongruencies in Vaccinia Virus Phylogenetic Trees]]>
http://mdpi.com/2079-3197/2/4/182
Over the years, as more complete poxvirus genomes have been sequenced, phylogenetic studies of these viruses have become more prevalent. In general, the results show similar relationships between the poxvirus species; however, some inconsistencies are notable. Previous analyses of the viral genomes contained within the vaccinia virus (VACV)-Dryvax vaccine revealed that their phylogenetic relationships were sometimes clouded by low bootstrapping confidence. To analyze the VACV-Dryvax genomes in detail, a new tool-set was developed and integrated into the Base-By-Base bioinformatics software package. Analyses showed that fewer unique positions were present in each VACV-Dryvax genome than expected. A series of patterns, each containing several single nucleotide polymorphisms (SNPs) were identified that were counter to the results of the phylogenetic analysis. The VACV genomes were found to contain short DNA sequence blocks that matched more distantly related clades. Additionally, similar non-conforming SNP patterns were observed in (1) the variola virus clade; (2) some cowpox clades; and (3) VACV-CVA, the direct ancestor of VACV-MVA. Thus, traces of past recombination events are common in the various orthopoxvirus clades, including those associated with smallpox and cowpox viruses.Computation2014-10-1424Article10.3390/computation20401821821982079-31972014-10-14doi: 10.3390/computation2040182Chad SmithsonSamantha KampmanBenjamin HetmanChris Upton<![CDATA[Computation, Vol. 2, Pages 159-181: Multiscale Modeling of the Early CD8 T-Cell Immune Response in Lymph Nodes: An Integrative Study]]>
http://mdpi.com/2079-3197/2/4/159
CD8 T-cells are critical in controlling infection by intracellular pathogens. Upon encountering antigen presenting cells, T-cell receptor activation promotes the differentiation of naïve CD8 T-cells into strongly proliferating activated and effector stages. We propose a 2D-multiscale computational model to study the maturation of CD8 T-cells in a lymph node controlled by their molecular profile. A novel molecular pathway is presented and converted into an ordinary differential equation model, coupled with a cellular Potts model to describe cell-cell interactions. Key molecular players such as activated IL2 receptor and Tbet levels control the differentiation from naïve into activated and effector stages, respectively, while caspases and Fas-Fas ligand interactions control cell apoptosis. Coupling this molecular model to the cellular scale successfully reproduces qualitatively the evolution of total CD8 T-cell counts observed in mice lymph node, between Day 3 and 5.5 post-infection. Furthermore, this model allows us to make testable predictions of the evolution of the different CD8 T-cell stages.Computation2014-09-2924Article10.3390/computation20401591591812079-31972014-09-29doi: 10.3390/computation2040159Sotiris ProkopiouLoic BarbarrouxSamuel BernardJulien MafilleYann LeverrierChristophe ArpinJacqueline MarvelOlivier GandrillonFabien Crauste<![CDATA[Computation, Vol. 2, Pages 131-158: Computational Models of the NF-KB Signalling Pathway]]>
http://mdpi.com/2079-3197/2/4/131
In this review article, we discuss the current state of computational modelling of the nuclear factor-kappa B (NF-ΚB) signalling pathway. NF-ΚB is a transcription factor, which is ubiquitous within cells and controls a number of immune responses, including inflammation and apoptosis. The NF-ΚB signalling pathway is tightly regulated, commencing with activation at the cell membrane, signal transduction through various components within the cytoplasm, translocation of NF-ΚB into the nucleus and, finally, the transcription of various genes relating to the innate and adaptive immune responses. There have been a number of computational (mathematical) models developed of the signalling pathway over the past decade. This review describes how these approaches have helped advance our understanding of NF-ΚB control.Computation2014-09-2924Review10.3390/computation20401311311582079-31972014-09-29doi: 10.3390/computation2040131Richard WilliamsJon TimmisEva Qwarnstrom<![CDATA[Computation, Vol. 2, Pages 112-130: On Mechanistic Modeling of Gene Content Evolution: Birth-Death Models and Mechanisms of Gene Birth and Gene Retention]]>
http://mdpi.com/2079-3197/2/3/112
Characterizing the mechanisms of duplicate gene retention using phylogenetic methods requires models that are consistent with different biological processes. The interplay between complex biological processes and necessarily simpler statistical models leads to a complex modeling problem. A discussion of the relationship between biological processes, existing models for duplicate gene retention and data is presented. Existing models are then extended in deriving two new birth/death models for phylogenetic application in a gene tree/species tree reconciliation framework to enable probabilistic inference of the mechanisms from model parameterization. The goal of this work is to synthesize a detailed discussion of modeling duplicate genes to address biological questions, moving from previous work to future trajectories with the aim of generating better models and better inference.Computation2014-08-2823Article10.3390/computation20301121121302079-31972014-08-28doi: 10.3390/computation2030112Ashley TeufelJing ZhaoMalgorzata O'ReillyLiang LiuDavid Liberles<![CDATA[Computation, Vol. 2, Pages 102-111: Investigation of the Ergopeptide Epimerization Process]]>
http://mdpi.com/2079-3197/2/3/102
Ergopeptides, like ergocornine and a-ergocryptine, exist in an S- and in an R-configuration. Kinetic experiments imply that certain configurations are preferred depending on the solvent. The experimental methods are explained in this article. Furthermore, computational methods are used to understand this configurational preference. Standard quantum chemical methods can predict the favored configurations by using minimum energy calculations on the potential energy landscape. However, the explicit role of the solvent is not revealed by this type of methods. In order to better understand its influence, classical mechanical molecular simulations are applied. It appears from our research that “folding” the ergopeptide molecules into an intermediate state (between the S- and the R-configuration) is mechanically hindered for the preferred configurations.Computation2014-08-0823Article10.3390/computation20301021021112079-31972014-08-08doi: 10.3390/computation2030102Karsten AndraeStefan MerkelVedat DurmazKonstantin FackeldeyRobert KöppenMarcus WeberMatthias Koch<![CDATA[Computation, Vol. 2, Pages 83-101: Cultural Collapse and System Survival Due to Environmental Modification]]>
http://mdpi.com/2079-3197/2/3/83
We consider a simple mathematical approach to the rise and fall of societies based on population growth and its effects on the environment, both beneficial and detrimental. We find that in any simple model of population dynamics with environmental coupling, stable cultures are impossible. Populations inevitably grow or decline exponentially. Further, if the parameters defining a civilisation are allowed to evolve towards an evolutionarily stable state, the only possible solutions are those where each culture ultimately declines. However, computer simulation with multiple competing cultures show that while each eventually collapses, some are always extant and the system is robust. In this broad class of models, individual death is a requirement for system survival.Computation2014-07-2923Article10.3390/computation2030083831012079-31972014-07-29doi: 10.3390/computation2030083Graeme AcklandAdrien HenryAlexander WilliamsMorrel Cohen<![CDATA[Computation, Vol. 2, Pages 61-82: Universal Dimensions of Meaning Derived from Semantic Relations among Words and Senses: Mereological Completeness vs. Ontological Generality]]>
http://mdpi.com/2079-3197/2/3/61
A key to semantic analysis is a precise and practically useful definition of meaning that is general for all domains of knowledge. We previously introduced the notion of weak semantic map: a metric space allocating concepts along their most general (universal) semantic characteristics while at the same time ignoring other, domain-specific aspects of their meanings. Here we address questions of the number, quality, and mutual independence of the weak semantic dimensions. Specifically, we employ semantic relationships not previously used for weak semantic mapping, such as holonymy/meronymy (“is-part/member-of”), and we compare maps constructed from word senses to those constructed from words. We show that the “completeness” dimension derived from the holonym/meronym relation is independent of, and practically orthogonal to, the “abstractness” dimension derived from the hypernym-hyponym (“is-a”) relation, while both dimensions are orthogonal to the maps derived from synonymy and antonymy. Interestingly, the choice of using relations among words vs. senses implies a non-trivial trade-off between rich and unambiguous information due to homonymy and polysemy. The practical utility of the new and prior dimensions is illustrated by the automated evaluation of different kinds of documents. Residual analysis of available linguistic resources, such as WordNet, suggests that the number of universal semantic dimensions representable in natural language may be finite. Their complete characterization, as well as the extension of results to non-linguistic materials, remains an open challenge.Computation2014-07-1523Article10.3390/computation203006161822079-31972014-07-15doi: 10.3390/computation2030061Alexei SamsonovichGiorgio Ascoli<![CDATA[Computation, Vol. 2, Pages 47-60: Can the Thermodynamic Hodgkin-Huxley Model of Voltage-Dependent Conductance Extrapolate for Temperature?]]>
http://mdpi.com/2079-3197/2/2/47
Hodgkin and Huxley (H-H) fitted their model of voltage-dependent conductances to experimental data using empirical functions of voltage. The thermodynamic H-H model of voltage dependent conductances is more physically plausible, as it constrains and parameterises its empirical fit by assuming that ion channel transition rates depend exponentially on a free energy barrier that in turn, linearly or non-linearly, depends on voltage. The original H-H model contains no explicit temperature terms and requires Q10 factors to describe data at different temperatures. The thermodynamic H-H model does have explicit terms for temperature. Do these endow the model with extrapolation for temperature? We utilised voltage clamp data for a voltage-gated K+ current, recorded at three different temperatures. The thermodynamic H-H model’s free parameters were fitted (Marquardt-Levenberg algorithm) to a data set recorded at one (or more) temperature(s). Then we assessed whether it could describe another data set, recorded at a different temperature, with these same free parameter values and its temperature terms set to the new temperature. We found that it could not.Computation2014-05-1422Article10.3390/computation202004747602079-31972014-05-14doi: 10.3390/computation2020047Michael Forrest<![CDATA[Computation, Vol. 2, Pages 23-46: A 3-D Model of a Perennial Ryegrass Primary Cell Wall and Its Enzymatic Degradation]]>
http://mdpi.com/2079-3197/2/2/23
We have developed a novel 3-D, agent-based model of cell-wall digestion to improve our understanding of ruminal cell-wall digestion. It offers a capability to study cell walls and their enzymatic modification, by providing a representation of cellulose microfibrils and non-cellulosic polysaccharides and by simulating their spatial and catalytic interactions with enzymes. One can vary cell-wall composition and the types and numbers of enzyme molecules, allowing the model to be applied to a range of systems where cell walls are degraded and to the modification of cell walls by endogenous enzymes. As a proof of principle, we have modelled the wall of a mesophyll cell from the leaf of perennial ryegrass and then simulated its enzymatic degradation. This is a primary, non-lignified cell wall and the model includes cellulose, hemicelluloses (glucuronoarabinoxylans, 1,3;1,4-β-glucans, and xyloglucans) and pectin. These polymers are represented at the level of constituent monosaccharides, and assembled to form a 3-D, meso-scale representation of the molecular structure of the cell wall. The composition of the cell wall can be parameterised to represent different walls in different cell types and taxa. The model can contain arbitrary combinations of different enzymes. It simulates their random diffusion through the polymer networks taking collisions into account, allowing steric hindrance from cell-wall polymers to be modelled. Steric considerations are included when target bonds are encountered, and breakdown products resulting from enzymatic activity are predicted.Computation2014-05-0522Article10.3390/computation202002323462079-31972014-05-05doi: 10.3390/computation2020023Indrakumar VetharaniamWilliam KellyGraeme AttwoodPhilip Harris<![CDATA[Computation, Vol. 2, Pages 12-22: Ab Initio Research on a New Type of Half-Metallic Double Perovskites, A2CrMO6 (A = IVA Group Elements; M = Mo, Re and W)]]>
http://mdpi.com/2079-3197/2/1/12
The research based on density functional theory was carried out using generalized gradient approximation (GGA) for full-structural optimization and the addition of the correlation effect (GGA + U (Coulomb parameter)) in a double perovskite structure, A2BB’O6. According to the similar valance electrons between IIA(s2) and IVA(p2), IVA group elements instead of alkaline-earth elements settled on the A-site ion position with fixed BB' combinations as CrM (M = Mo, Re and W). The ferrimagnetic half-metallic (HM-FiM) properties can be attributed to the p-d hybridization between the Crd-Mp and the double exchange. All the compounds can be half-metallic (HM) materials, except Si2CrMoO6, Ge2CrMo and Ge2CrReO6, because the strong-correlation correction should be considered. For M = W, only A = Sn and Pb are possible candidates as HM materials. Nevertheless, an examination of the structural stability is needed, because Si, Ge, Sn and Pb are quite different from Sr. All compounds are stable, except for the Si-based double perovskite structure.Computation2014-03-2121Article10.3390/computation201001212222079-31972014-03-21doi: 10.3390/computation2010012Yun-Ping LiuHuei-Ru FuhYin-Kuo Wang<![CDATA[Computation, Vol. 2, Pages 1-11: Linear Scaling Solution of the Time-Dependent Self-Consistent-Field Equations]]>
http://mdpi.com/2079-3197/2/1/1
A new approach to solving the Time-Dependent Self-Consistent-Field equations is developed based on the double quotient formulation of Tsiper 2001 (J. Phys. B). Dual channel, quasi-independent non-linear optimization of these quotients is found to yield convergence rates approaching those of the best case (single channel) Tamm-Dancoff approximation. This formulation is variational with respect to matrix truncation, admitting linear scaling solution of the matrix-eigenvalue problem, which is demonstrated for bulk excitons in the polyphenylene vinylene oligomer and the (4,3) carbon nanotube segment.Computation2014-03-1421Letter10.3390/computation20100011112079-31972014-03-14doi: 10.3390/computation2010001Matt Challacombe<![CDATA[Computation, Vol. 1, Pages 31-45: Second-Row Transition-Metal Doping of (ZniSi), i = 12, 16 Nanoclusters: Structural and Magnetic Properties]]>
http://mdpi.com/2079-3197/1/3/31
TM@ZniSi nanoclusters have been characterized by means of the Density Functional Theory, in which Transition Metal (TM) stands from Y to Cd, and i = 12 and 16. These two nanoclusters have been chosen owing to their highly spheroidal shape which allow for favored endohedral structures as compared to other nanoclusters. Doping with TM is chosen due to their magnetic properties. In similar cluster-assembled materials, these magnetic properties are related to the Transition Metal-Transition Metal (TM-TM) distances. At this point, endohedral doping presents a clear advantage over substitutional or exohedral doping, since in the cluster-assembled materials, these TM would occupy the well-fixed center of the cluster, providing in this way a better TM-TM distance control to experimentalists. In addition to endohedral compounds, surface structures and the TS’s connecting both isomers have been characterized. In this way the kinetic and thermal stability of endohedral nanoclusters is predicted. We anticipate that silver and cadmium endohedrally doped nanoclusters have the longest life-times. This is due to the weak interaction of these metals with the cage, in contrast to the remaining cases where the TM covalently bond to a region of the cage. The open-shell electronic structure of Ag provides magnetic properties to Ag@ZniSi clusters. Therefore, we have further characterized (Ag@Zn12S12)2 and (Ag@Zn16S16)2 dimers both in the ferromagnetic and antiferromagnetic state, in order to calculate the corresponding magnetic exchange coupling constant, J.Computation2013-11-1413Article10.3390/computation103003131452079-31972013-11-14doi: 10.3390/computation1030031Elisa Jimenez-IzalJon MatxainMario PirisJesus Ugalde<![CDATA[Computation, Vol. 1, Pages 27-30: Computation: A New Open Access Journal of Computational Chemistry, Computational Biology and Computational Engineering]]>
http://mdpi.com/2079-3197/1/2/27
Computation (ISSN 2079-3197; http://www.mdpi.com/journal/computation) is an international scientific open access journal focusing on fundamental work in the field of computational science and engineering. Computational science has become essential in many research areas by contributing to solving complex problems in fundamental science all the way to engineering. The very broad range of application domains suggests structuring this journal into three sections, which are briefly characterized below. In each section a further focusing will be provided by occasionally organizing special issues on topics of high interests, collecting papers on fundamental work in the field. More applied papers should be submitted to their corresponding specialist journals. To help us achieve our goal with this journal, we have an excellent editorial board to advise us on the exciting current and future trends in computation from methodology to application. We very much look forward to hearing all about the research going on across the world. [...]Computation2013-09-0412Editorial10.3390/computation102002727302079-31972013-09-04doi: 10.3390/computation1020027Karlheinz SchwarzRainer BreitlingChristian Allen<![CDATA[Computation, Vol. 1, Pages 16-26: Structural Features That Stabilize ZnO Clusters: An Electronic Structure Approach]]>
http://mdpi.com/2079-3197/1/1/16
We show that a simple approach to building small computationally inexpensive clusters offers insights on specific structural motifs that stabilize the electronic structure of ZnO. All-electron calculations on ZniOi needle (i = 6, 9, 12, 15, and 18) and plate (i = 9 and 18) clusters within the density functional theory (DFT) formalism show a higher stability for ZnO needles that increases with length. Puckering of the rings to achieve a more wurtzite-like structure destabilizes the needles, although this destabilization is reduced by going to infinite needles (calculated using periodic boundary conditions). Calculations of density of states (DOS) curves and band gaps for finite clusters and infinite needles highlight opportunities for band-gap tuning through kinetic control of nanocrystal growth.Computation2013-05-3111Article10.3390/computation101001616262079-31972013-05-31doi: 10.3390/computation1010016Csaba SzakacsErika Merschrod S.Kristin Poduska<![CDATA[Computation, Vol. 1, Pages 1-15: Effect of Isotopic Substitution on Elementary Processes in Dye-Sensitized Solar Cells: Deuterated Amino-Phenyl Acid Dyes on TiO2]]>
http://mdpi.com/2079-3197/1/1/1
We present the first computational study of the effects of isotopic substitution on the operation of dye-sensitized solar cells. Ab initio molecular dynamics is used to study the effect of deuteration on light absorption, dye adsorption dynamics, the averaged over vibrations driving force to injection (∆Gi) and regeneration (∆Gr), as well as on promotion of electron back-donation in dyes NK1 (2E,4E-2-cyano-5-(4-dimethylaminophenyl)penta-2,4-dienoic acid) and NK7 (2E,4E-2-cyano-5-(4-diphenylaminophenyl)penta-2,4-dienoic acid) adsorbed in monodentate molecular and bidentate bridging dissociative configurations on the anatase (101) surface of TiO2. Deuteration causes a red shift of the absorption spectrum of the dye/TiO2 complex by about 5% (dozens of nm), which can noticeably affect the overlap with the solar spectrum in real cells. The dynamics effect on the driving force to injection and recombination (the difference between the averaged &lt;∆Gi,r&gt; and ∆Gi,requil at the equilibrium configuration) is strong, yet there is surprisingly little isotopic effect: the average driving force to injection &lt;∆Gi&gt; and to regeneration &lt;∆Gr&gt; changes by only about 10 meV upon deuteration. The nuclear dynamics enhance recombination to the dye ground state due to the approach of the electron-donating group to TiO2, yet this effect is similar for deuterated and non-deuterated dyes. We conclude that the nuclear dynamics of the C-H(D) bonds, mostly affected by deuteration, might not be important for the operation of photoelectrochemical cells based on organic dyes. As the expectation value of the ground state energy is higher than its optimum geometry value (by up to 0.1 eV in the present case), nuclear motions will affect dye regeneration by recently proposed redox shuttle-dye combinations operating at low driving forces.Computation2013-03-1111Article10.3390/computation10100011152079-31972013-03-11doi: 10.3390/computation1010001Sergei ManzhosHiroshi SegawaKoichi Yamashita