Dr Vitaliy Kurlin: mathematics & computer science

MIF++ is the cross-departmental network of MIF collaborators at the University of Liverpool

• Vision of the MIF++ network : facilitate the collaboration with the MIF.
• Style of network seminars and who is welcome to participate and contribute.
• Network seminars : once per month on average, between 11-13 with lunch from 12.

Vision of the MIF++ network : facilitate the collaboration with the MIF

• The Materials Innovation Factory (MIF) is the £82M research institute, which was officially opened in 2018.
• The vision is to provide collaborative opportunities for colleagues from other departments in the University of Liverpool.
• The MIF++ network runs 2-hour seminars that include a presentation combined with lunch and informal discussions.
• The lunch is free and should be well-deserved, so it comes one hour after the start to make all discussions easier.
• The aim is to connect colleagues, who are experts from different areas and would like to start a joint project.

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Style of network seminars and who is welcome to participate and contribute

• An initial presentation should be self-contained and understandable to non-experts, aim at first year undergraduates. A computer projector is available and everyone can use a couple of white boards for extra explanations during the seminar.
• A chemist (in a broad sense including chemical engineering and physical chemistry) could first explain basic concepts and then introduce a real problem, where computational methods can potentially help, and describe the state-of-the-art.
• A computational expert (computer science, mathematics, electrical engineering) could similarly start from basic concepts and explain their methods on toy examples, also describe types of real data that can be processed by their methods.
• All colleagues in the University of Liverpool are welcome to participate and give a talk. We expect different audiences depending on a talk, say for a group of about 20 people. If you wish to come, please e-mail me for catering purposes.

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Network seminars (in the reverse chronological order) : 2020 | 2019

• • 3 February 2020 : Prof Uwe Grimm (Open University Maths).
  • Time : 11-13 (lunch and discussion from about 12).
  • Location : the boardroom on the ground floor in the MIF.
  • Title. An introduction to aperiodically ordered systems and their diffraction.
  • Abstract. The talk will present an introductory overview on aperiodically ordered systems obtained from cut and project or inflation methods. The key methods and results will be illustrated by means of examples and pictures, leaving aside much of the mathematical details. For cut and project sets, the diffraction is well understood, and the general result and its application to examples will be discussed. In contrast, inflation systems are still only partially understood, and paradigms with different spectral type are presented. Finally, I will briefly discuss recent results on the Fourier transform of Rauzy fractals and the point spectrum of unimodular Pisot inflation tilings, which uses both the inflation and the projection structure.

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• • 13 December 2019 : Dr Tom Hasell (Liverpool Chemistry).
  • Time : 11-13 (lunch and discussion from about 12).
  • Location : the 3rd floor meeting room in the MIF.
  • Title. Making polymers from elemental sulfur
  • Abstract. Sulfur is an industrial by-product, removed as an impurity in oil-refining. This has led to vast unwanted stockpiles of sulfur, and resulted in low bulk prices. Sulfur is therefore a promising alternative feedstock to carbon for polymeric materials. Sulfur normally exists as S8 rings – a small molecule with poor physical properties. On heating, these sulfur rings can open and polymerise to form long chains. However, because of the reversibility of sulfur bonds, these polymers are not stable, and decompose back to S8 over time, even at room temperature. Inverse vulcanisation has made possible the production of high sulfur polymers, stabilised against depolymerisation by crosslinking [1]. These high sulfur-materials show excellent potential as low cost water filters to remove mercury [2-4]. Heavy metal contamination exists in the waste streams of many industries, and mercury is of particular concern for human health. Alternative crosslinkers for inverse vulcanisation, from industrial by-products or bio-renewable sources, can be used to reduce the cost and improve the properties of the resultant polymers [4,5]. Polymers made from sulfur also have many other intriguing properties and applications in optics, electronics, insulation, and antimicrobial materials. We recently reported a catalytic route that reduces the required reaction time, temperature, and by-products – and allows otherwise unreactive crosslinkers to be used [6].
    [1] Nat. Chem. 2013, 5, 518–524. [2] Chem. Commun., 2016, 52, 5383 - 5386. [3] J. Mater. Chem. A. 2017,5, 11682-11692 [4] J. Mater. Chem. A., 2017, 5, 18603 [5] Chem.-Eur. J. 2019, 25, 10433-10440 [6] Nat. Commun. 2019, 10, 647
• • 4 November 2019 : Dr Linjiang Chen (Liverpool Chemistry).
  • Time : 11-13 (lunch and discussion from about 12).
  • Location : the 3rd floor meeting room in the MIF.
  • Title. Functional materials discovery: ‘Seeing’ structures and functions?
  • Abstract. We have recently demonstrated a strategy for how new, functional molecular materials can be discovered. By carrying out a priori prediction of both the crystal structure and its functional properties, energy–structure–function (ESF) maps are created to aid researchers, without computational expertise, in realizing several remarkable porous materials promising for different possible applications.
    As large-scale computational screening studies become routinely carried out, new opportunities have arisen for accelerating materials discovery by taking advantage of the availability of big data. It, however, remains a challenge to properly understand and use the vast amount of data generated by simulations. In my talk, I will show how we use computation to accelerate serendipitous discovery of new functional materials, as well as the prowess of data-driven machineries becoming available. I will outline our current focuses on and approaches to the following topics:
    1. 1. ESF mapping to identify synthetic targets with desired functional properties;
    2. 2. Interactive visualization of high-dimensional structure–property relationships;
    3. 3. Smart navigation of the ESF space with machine learning.
• • 21 October 2019 : Mr Georg Osang (IST Austria Computational Geometry).
  • Time : 11-13 (lunch and discussion from about 12).
  • Location : the boardroom on the ground floor in the MIF.
  • Title. The Multi-cover Persistence of Euclidean Balls
  • Abstract. Persistent homology has become a popular tool to analyse various kinds of data, in particular in material sciences. Specifically, persistence of discrete point sets has recently been used to analyse sphere packing data, to shed light on structures arising in sphere packings at different packing densities. We generalize this notion and introduce higher-order persistence of discrete point sets. We address computational challenges and show how this notion can deal with noisy point samples. In the setting of sphere packings we show that this notion can also capture a wider variety of local structures, and in particular can distinguish between the hexagonal close packing and the face centered cubic lattice packing, two structures know to have optimal packing density in 3 dimensions.
• • 1 July 2019 : Dr John Claridge (Liverpool Chemistry).
  • Time : 11-13 (lunch and discussion from about 12).
  • Location : the 3rd floor meeting room in the MIF.
  • Title : Challenges and opportunities in condensed matter science.
  • Abstract. Solid state chemistry, is the study of the synthesis, structure and properties of solid state materials and particularly how these are related to each other. It is obviously closely linked to condensed matter physics, mineralogy, crystallography, ceramics, metallurgy, materials science and electronics. We'll begin with some simple illustrations of these relationships, before looking at how structural/crystallographic methods have advanced in order to both characterise and describe the materials we can now make, and where I believe there are limitations in our current tools and understanding, with examples taken from my own work and more generally, and why they are important.
• • 13 May 2019 : Dr Vanessa Robins (ANU Applied Mathematics).
  • Time : 11-12.15 (with lunch at VGM from 12.30).
  • Location : the boardroom on the ground floor in the MIF.
  • Title : An introduction to the mathematical description and computational enumeration of periodic tilings and nets.
  • Abstract. Periodic tilings and nets are simplified models of atomic arrangements in crystals. Systematic methods for describing and enumerating possible crystal structures are based on factoring out either the translational periodicity or the full crystallographic symmetry. The mathematical version of “factoring out” gives us an object called an orbifold. I will explain how orbifolds encapsulate the essential elements of a crystallographic group and provide an effective basis for the enumeration of hypothetical crystalline structures. The presentation will be informal and largely based on pictures and examples, hopefully accessible to non-specialists.
• • 29 April 2019 : Dr Vladimir Gusev (Liverpool Computer Science).
  • Time : 11-13 (lunch and discussion from about 12).
  • Location : the boardroom on the ground floor in the MIF.
  • Title : New approaches to the crystal structure prediction
• • 1 April 2019 : Dr Chris Collins (Liverpool Chemistry).
  • Time : 11-13 (lunch and discussion from about 12).
  • Location : the boardroom on the ground floor in the MIF.
  • Title : Computationally driven materials discovery
  • Abstract. In the previous seminar by Dr D. Antypov, we discussed the general concepts of energy calculations and crystal structure prediction (CSP). In this session are to discuss how CSP is used in practice in the search for new inorganic materials. We present how the use of ‘probe’ structures accelerates the experimental exploration of composition space. A probe structure is a hypothetical crystal structure for a given composition, it need not be the ground state. However, it needs to be complex enough that it can contain enough co-ordination chemistry to produce an energy which is representative of potential single phases. When probe structures are generated across a range of compositions we can then construct the convex hull, and look for minima – regions of compositional space in which new compounds are likely to be found. We will discuss the methods for creating probe structures. The development of a method is split into two streams: how can we best represent crystal structures in a computer? And how can we search through the possible configuration space? We will then present our latest codes developed for probe structure prediction (Monte Carlo – Extended Module Materials Assembly (MC-EMMA[1]) and the Flexible Unit Structure Engine (FUSE[2]), along with example phase fields computed using them and show how probe structure generation for composition prediction is a powerful, predictive tool to accelerate the discovery of materials.
    1. C. Collins, M. S. Dyer, M. J. Pitcher, G. F. S. Whitehead, M. Zanella, P. Mandal, J. B. Claridge, G. R. Darling and M. J. Rosseinsky, Nature, 2017, 546, 280-284.
    2. C. Collins, G. R. Darling and M. J. Rosseinsky, Faraday Discussions, 2018, 211, 117-131.
• • 11 March 2019 : Dr Dmytro Antypov (Liverpool Chemistry).
  • Time : 11-13 (lunch and discussion from about 12).
  • Location : the 3rd floor meeting room in the MIF.
  • Title : Introduction to crystal structure prediction
  • Abstract. Crystalline solids such as metal oxides and perovskites are functional materials used in solar cells, batteries and many other devices. These materials are often composed from 3, 4 or 5 different chemical elements arranged in a periodic three dimensional structure. Such chemical diversity on the one hand allows for fine-tuning of material properties but on the other hand makes the identification and synthesis of stable compounds difficult. To accelerate the design of such materials we use computation to predict the combinations of the constituent chemical elements that will lead to stable crystalline structures. In this talk I will explain how this chemistry problem is formalised to have a tractable computational solution and show some examples.
• • 25 February 2019 : Dr Phillip Maffettone (Liverpool Chemistry).
  • Time : 11-13 (lunch and discussion from about 12).
  • Location : the 3rd floor meeting room in the MIF.
  • Title : Describing solids, and challenges for high-throughput analysis.
  • Abstract. The talk will introduce reciprocal space and the reciprocal lattice as the inverse of the direct lattice, building on the previous introduction describing periodic structures. The reciprocal lattice plays a fundamental role in understanding wave mechanics in crystalline materials, and is implemented in most analytical studies of materials through the theory of diffraction. These concepts will be presented with a focus on their experimental utility, necessary limitations, and potential implications for high-throughput automation. In particular, we will explore the question: When can we meaningfully invert the diffraction pattern and the pair-wise information it contains, and how can we automate this inversion?
• • 11 February 2019 : Dr Mike Gaultois (Liverpool Chemistry).
  • Time : 11-13 (lunch and discussion from about 12).
  • Location : the 3rd floor meeting room in the MIF.
  • Title : Searching for new magnetic materials.
  • Abstract. Magnetic materials have fascinated humans since the antiquity, but only recently since the 1800's with the work of Oersted and Maxwell did we begin to develop a deeper understanding of magnetism. Magnetic materials are now involved in many technological applications, many of which are limited by the material performance. One area of enquiry is the search for materials that can make hard permanent magnets, and another area of enquiry is the search for materials that conduct electricity without resistance (i.e., superconductors). This discussion is interested in exploring how we can best computationally predict (through first principles, or otherwise) the magnetic properties of a given material. We will describe what others have done to search for new materials using machine learning techniques, and discuss potential areas of interaction between MIF++ where advances can be made.
• • 28 January 2019 : Dr Vitaliy Kurlin (Liverpool Computer Science).
  • Time : 11-13 (lunch and discussion from about 12).
  • Location : the boardroom on the ground floor in the MIF.
  • Title : Mathematical challenges for solid crystalline materials.
  • Abstract. The talk will introduce periodic structures that model all solid crystalline materials, for example molecular crystals, covalent organic frameworks and inorganic crystals based on isolated atoms or ions. The key problems of materials discovery will be stated in mathematical terms: what structures should be equivalent and how to quantify a similarity between crystals. We will discuss several requirements for potentials solutions that should work for real crystals.

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