Exploration of Reaction Pathways and Chemical Transformation Networks

For the investigation of chemical reaction networks, the identification of all relevant intermediates and elementary reactions is mandatory. Many algorithmic approaches exist that perform explorations efficiently and automatedly. These approaches differ in their application range, the level of completeness of the exploration, as well as the amount of heuristics and human intervention required. Here, we describe and compare the different approaches based on these criteria. Future directions leveraging the strengths of chemical heuristics, human interaction, and physical rigor are discussed.Comment: 48 pages, 4 figure

Interplay of gas and ice during cloud evolution

During the evolution of diffuse clouds to molecular clouds, gas-phase molecules freeze out on surfaces of small dust particles to form ices. On dust surfaces, water is the main constituent of the icy mantle in which a complex chemistry is taking place. We aim to study the formation pathways and the composition of the ices throughout the evolution of diffuse clouds. For this purpose, we use time-dependent rate equations to calculate the molecular abundances in both gas phase and on solid surfaces (onto dust grains). We fully consider the gas-dust interplay by including the details of freeze-out, chemical and thermal desorption, as well as the most important photo-processes on grain surfaces. The difference in binding energies of chemical species on bare and icy surfaces is also incorporated into our equations. Using the numerical code FLASH, we perform a hydrodynamical simulation of a gravitationally bound diffuse cloud and follow its contraction. We find that while the dust grains are still bare, water formation is enhanced by grain surface chemistry which is subsequently released into the gas phase, enriching the molecular medium. The CO molecules, on the other hand, tend to freeze out gradually on bare grains. This causes CO to be well mixed and strongly present within the first ice layer. Once one monolayer of water ice has formed, the binding energy of the grain surface changes significantly and an immediate and strong depletion of gas-phase water and CO molecules occur. While hydrogenation converts solid CO into formaldehyde (H$_2$CO) and methanol (CH$_3$OH), water ice becomes the main constituent of the icy grains. Inside molecular clumps formaldehyde is more abundant than water and methanol in the gas phase owing its presence in part to chemical desorption.Comment: 19 pages, 10 figures, 9 tables, 23 equations. Accepted for publication Astronomy & Astrophysics. In version 3: Language edit, added gas-phase reaction tables, title has change

COEL: A Web-based Chemistry Simulation Framework

The chemical reaction network (CRN) is a widely used formalism to describe macroscopic behavior of chemical systems. Available tools for CRN modelling and simulation require local access, installation, and often involve local file storage, which is susceptible to loss, lacks searchable structure, and does not support concurrency. Furthermore, simulations are often single-threaded, and user interfaces are non-trivial to use. Therefore there are significant hurdles to conducting efficient and collaborative chemical research. In this paper, we introduce a new enterprise chemistry simulation framework, COEL, which addresses these issues. COEL is the first web-based framework of its kind. A visually pleasing and intuitive user interface, simulations that run on a large computational grid, reliable database storage, and transactional services make COEL ideal for collaborative research and education. COEL's most prominent features include ODE-based simulations of chemical reaction networks and multicompartment reaction networks, with rich options for user interactions with those networks. COEL provides DNA-strand displacement transformations and visualization (and is to our knowledge the first CRN framework to do so), GA optimization of rate constants, expression validation, an application-wide plotting engine, and SBML/Octave/Matlab export. We also present an overview of the underlying software and technologies employed and describe the main architectural decisions driving our development. COEL is available at http://coel-sim.org for selected research teams only. We plan to provide a part of COEL's functionality to the general public in the near future.Comment: 23 pages, 12 figures, 1 tabl

Modelling CO formation in the turbulent interstellar medium

We present results from high-resolution three-dimensional simulations of turbulent interstellar gas that self-consistently follow its coupled thermal, chemical and dynamical evolution, with a particular focus on the formation and destruction of H2 and CO. We quantify the formation timescales for H2 and CO in physical conditions corresponding to those found in nearby giant molecular clouds, and show that both species form rapidly, with chemical timescales that are comparable to the dynamical timescale of the gas. We also investigate the spatial distributions of H2 and CO, and how they relate to the underlying gas distribution. We show that H2 is a good tracer of the gas distribution, but that the relationship between CO abundance and gas density is more complex. The CO abundance is not well-correlated with either the gas number density n or the visual extinction A_V: both have a large influence on the CO abundance, but the inhomogeneous nature of the density field produced by the turbulence means that n and A_V are only poorly correlated. There is a large scatter in A_V, and hence CO abundance, for gas with any particular density, and similarly a large scatter in density and CO abundance for gas with any particular visual extinction. This will have important consequences for the interpretation of the CO emission observed from real molecular clouds. Finally, we also examine the temperature structure of the simulated gas. We show that the molecular gas is not isothermal. Most of it has a temperature in the range of 10--20 K, but there is also a significant fraction of warmer gas, located in low-extinction regions where photoelectric heating remains effective.Comment: 37 pages, 15 figures; minor revisions, matches version accepted by MNRA

Design and Development of Software Tools for Bio-PEPA

This paper surveys the design of software tools for the Bio-PEPA process algebra. Bio-PEPA is a high-level language for modelling biological systems such as metabolic pathways and other biochemical reaction networks. Through providing tools for this modelling language we hope to allow easier use of a range of simulators and model-checkers thereby freeing the modeller from the responsibility of developing a custom simulator for the problem of interest. Further, by providing mappings to a range of different analysis tools the Bio-PEPA language allows modellers to compare analysis results which have been computed using independent numerical analysers, which enhances the reliability and robustness of the results computed.

Hardware acceleration of reaction-diffusion systems:a guide to optimisation of pattern formation algorithms using OpenACC

Reaction Diffusion Systems (RDS) have widespread applications in computational ecology, biology, computer graphics and the visual arts. For the former applications a major barrier to the development of effective simulation models is their computational complexity - it takes a great deal of processing power to simulate enough replicates such that reliable conclusions can be drawn. Optimizing the computation is thus highly desirable in order to obtain more results with less resources. Existing optimizations of RDS tend to be low-level and GPGPU based. Here we apply the higher-level OpenACC framework to two case studies: a simple RDS to learn the ‘workings’ of OpenACC and a more realistic and complex example. Our results show that simple parallelization directives and minimal data transfer can produce a useful performance improvement. The relative simplicity of porting OpenACC code between heterogeneous hardware is a key benefit to the scientific computing community in terms of speed-up and portability

Quantifying the implicit process flow abstraction in SBGN-PD diagrams with Bio-PEPA

For a long time biologists have used visual representations of biochemical networks to gain a quick overview of important structural properties. Recently SBGN, the Systems Biology Graphical Notation, has been developed to standardise the way in which such graphical maps are drawn in order to facilitate the exchange of information. Its qualitative Process Diagrams (SBGN-PD) are based on an implicit Process Flow Abstraction (PFA) that can also be used to construct quantitative representations, which can be used for automated analyses of the system. Here we explicitly describe the PFA that underpins SBGN-PD and define attributes for SBGN-PD glyphs that make it possible to capture the quantitative details of a biochemical reaction network. We implemented SBGNtext2BioPEPA, a tool that demonstrates how such quantitative details can be used to automatically generate working Bio-PEPA code from a textual representation of SBGN-PD that we developed. Bio-PEPA is a process algebra that was designed for implementing quantitative models of concurrent biochemical reaction systems. We use this approach to compute the expected delay between input and output using deterministic and stochastic simulations of the MAPK signal transduction cascade. The scheme developed here is general and can be easily adapted to other output formalisms

Approximations for modelling CO chemistry in GMCs: a comparison of approaches

We examine several different simplified approaches for modelling the chemistry of CO in three-dimensional numerical simulations of turbulent molecular clouds. We compare the different models both by looking at the behaviour of integrated quantities such as the mean CO fraction or the cloud-averaged CO-to-H2 conversion factor, and also by studying the detailed distribution of CO as a function of gas density and visual extinction. In addition, we examine the extent to which the density and temperature distributions depend on our choice of chemical model. We find that all of the models predict the same density PDF and also agree very well on the form of the temperature PDF for temperatures T > 30 K, although at lower temperatures, some differences become apparent. All of the models also predict the same CO-to-H2 conversion factor, to within a factor of a few. However, when we look more closely at the details of the CO distribution, we find larger differences. The more complex models tend to produce less CO and more atomic carbon than the simpler models, suggesting that the C/CO ratio may be a useful observational tool for determining which model best fits the observational data. Nevertheless, the fact that these chemical differences do not appear to have a strong effect on the density or temperature distributions of the gas suggests that the dynamical behaviour of the molecular clouds on large scales is not particularly sensitive to how accurately the small-scale chemistry is modelled.Comment: 18 pages, 10 figures. Minor revisions, including the addition of a comparison of simulated and observed C/CO ratios. Accepted by MNRA