Welcome from the Computational Modelling Group

A picture showing several members of the CoMo Group

Welcome to the website of the CoMo Group. We develop and apply modern numerical methods to problems arising in Chemical Engineering. The overall aim is to shorten the development period from research bench to the industrial production stage by providing insight into the underlying physics and supporting the scale-up of processes to industrial level.

The group currently consists of 18 members from various backgrounds. We are keen to collaborate with people from both within industry and academia, so please get in touch if you think you have common interests.

The group's research divides naturally into two inter-related branches. The first of these is research into mathematical methods, which consists of the development of stochastic particle methods, computational fluid dynamics and quantum chemistry. The other branch consists of research into applications, using the methods we have developed in addition to well established techniques. The main application areas are reactive flow, combustion, engine modelling, extraction, nano particle synthesis and dynamics. This research is sponsored on various levels by the UK, EU, and industry.

Markus Kraft's Signature
Markus Kraft - Head of the CoMo Group

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Preprint 230 published

04 June 2019
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Preprint 230, "OntoPowerSys: A Power Systems Ontology for Cross Domain Interactions in an Eco Industrial Park", has been published!

Abstract

Knowledge management in multi-domain, heterogeneous industrial networks like an Eco Industrial Park (EIP) is a challenging task. In the present paper, an ontology based management system has been proposed for tackling this challenge. It focuses on the power systems domain and provides a framework for integrating this knowledge with other domains of an EIP. The proposed ontology, OntoPowSys is expressed using a Description Logics (DL) syntax and OWL2 language was used to make it alive. It is then used as a part of the Knowledge Management System (KMS) in a virtual EIP called the J-Park Simulator (JPS). The advantages of the proposed approach are demonstrated by conducting two case studies on the JPS. The first case study illustrates the application of Optimum Power Flow (OPF) in the electrical network of the JPS. The second case study plays an important role in understanding the cross domain interactions between chemical and electrical engineering domains in a biodiesel plant of the JPS. These case studies are available as web services on the JPS website. The results showcase the advantages of using ontologies in the development of decision support tools. These tools are capable of taking into account contextual information on top of data during their decision making process. They are also able to exchange knowledge across different domains without the need for a communication interface.

Preprint 229 published

21 May 2019
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Preprint 229, "Sphere Encapsulated Monte Carlo: Obtaining minimum energy configurations of large aromatic systems", has been published!

Abstract

In this paper, we introduce a simple global minimisation approach that is able to find minimum energy configurations of clusters containing aromatic molecules. The translational and rotational perturbations required in Monte Carlo-based methods often lead to unrealistic configurations within which two or more molecular rings intersect, causing many of the computational steps to be rejected and the optimisation process to be inefficient. Here we develop a modification of the basin-hopping global optimisation procedure tailored to tackle problems with intersecting molecular rings. Termed the Sphere Encapsulated Monte Carlo (SEMC) method, this method introduces sphere-based rearrangement and minimisation steps at each iteration and its performance is shown through the exploration of potential energy landscapes of polycyclic aromatic hydrocarbon (PAH) clusters, systems of interest in combustion and astrophysics research. The SEMC method provides clusters that are accurate to 5% mean difference of the minimum energy at a 10-fold speed up compared to previous work using advanced molecular dynamics simulations. Importantly, the SEMC method captures key structural characteristics and molecule size partitioning trends as measured by the molecular radial distances and coordination numbers. The advantages of the SEMC method are further highlighted in its application to previously unstudied heterogeneous PAH clusters.

PhD position in Aerosol Science

13 February 2019
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The EPSRC Centre for Doctoral Training in Aerosol Science is offering a number of fully-funded PhD studentships. Students will spend their first 7 months at the University of Bristol taking courses in aerosol science before moving on to their final university placement. Within this CDT, a placement on the topic "Modelling the plasma synthesis of graphene" is available at the Computational Modelling Group.

Plasma synthesis offers a potential route for the bulk synthesis of graphene. Advantages include avoiding the need for a catalyst (thus avoiding the use of rare-earth metals) and the ability to operate at atmospheric pressures (which reduces the cost and complexity of the process), both of which potentially make the process easier to scale up than other manufacturing routes. However, there remains a lack of understanding of how the process variables, such as temperature, affect the quality of the product. The choice of process conditions and reactants is critical to avoid undesirable defects in the carbon structure.

The purpose of this project is to develop a model to explain the processes controlling graphene plasma synthesis. During the project the student will:

  • Extend existing Kinetic Monte Carlo models for the growth of carbonaceous nanomaterials to test different hypotheses to explain the observations made in graphene experiments.
  • Estimate thermodynamic data and rate constants using Density Functional Theory (DFT) calculations.
  • Expand current understanding of the chemistry of polycyclic aromatic hydrocarbons and their role in the graphene, carbon nanotube and carbonaceous particles chemistry.
The models will be developed using data from experiments that investigated the quality and yield of graphene as a function of process conditions and choice of chemical precursor.

CoMo group open to Feodor Lynen Research Fellows

23 January 2019
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In 2016, Prof. Markus Kraft was awarded the Friedrich Wilhelm Bessel Award and is therefore eligible to host Feodor Lynen Research Fellows sponsored by the Alexander von Humboldt Foundation. The Feodor Lynen Research Fellowship covers the salary and travel expenses of researchers from Germany to work at the host institution for 6-24 months. In addition, the fellowship enables the successful candidate to apply for alumni sponsorship from the Humboldt Foundation after the end of the fellowship and become part of their international network of academics.

If you are interested in working at the University of Cambridge and in joining the CoMo group as a post-doctoral researcher, please check your eligibility on the official Feodor Lynen Research Fellowship website and familiarise yourself with the application procedure. You will need to write a research proposal that aligns with your professional expertise. The topic might be of computational or experimental nature but should lie within the research areas of the CoMo group.