Knowledge Led Structure Prediction for Nanostructures

Lead Research Organisation: University College London
Department Name: Chemistry

Abstract

Nanoparticles are key to a wide range of day-to-day technological applications, including petrochemical catalysis, biomedical imaging, optoelectronics, paints, inks, coatings, and nanomedicine. To develop and optimise such applications, one needs a good understanding of the atomic structures of the involved nanoparticles that is difficult to obtain from experiment alone. Similar structural models are relevant to understanding the toxicology and environmental effects of nanoparticles and their role in astrochemistry. We will develop a linked nanoscale structure prediction code (WASP@N) and web-interfaced database aimed at generating and archiving such structural models of nanostructures. This combination will provide a fast and efficient way of predicting the atomic structure of both fundamentally new systems that have never been studied before and known systems embedded in a realistic environment; e.g. in solution, in the pores or on the surface of a material, and/or with an organic capping agent, rather than isolated in a vacuum. The latter is crucial for understanding nanoparticles in many industrial processes (e.g. liquid phase nanoparticle catalysis, inks, coatings) and, for instance, nanotoxicology, but has not been done routinely before due to additional computational cost of including the environment. We strongly believe that the combination of new algorithmic approaches to be included in WASP@N and access to all low energy structures for the particles in vacuum in the cluster structure database will make predicting the atomic structure of nanoparticles insolution, for example, much more efficient and a standard technique in the repertoire of the applied computational chemist. The cluster structure database, finally, will also be useful as a stand-alone resource for experimental and computational chemists, chemical engineers, physicists, electronic engineers and toxicologists looking for information on the structure of materials on the nanoscale.

Planned Impact

Nanoparticles are used in a wide range of day-to-day technological applications relevant to the UK economy, including petrochemical catalysis, biomedical imaging, optoelectronics, paints, inks, coatings, and nanomedicine. To develop and optimise such applications, good structural models of nanoparticles are required.

Apart from technological applications, the same models are also crucial when trying to understand and evaluate the environmental and toxicological properties of nanoparticles. Nanoparticles, both naturally occurring and manmade, play an active role in the chemistry of the upper atmosphere and hence influence the environment both in terms of the ozone (layer) destruction and climate. Due to the increasing technological usage of nanoparticles, there is need for a good understanding of nanoparticle toxicology beyond that arising from their chemical composition.

We will provide interested academic, industrial and governmental parties with both new tools to develop structural models of nanoparticles themselves and the opportunity to find models previously developed by others in a web-database we will operate. We will provide unique functionalities, for example, for generating structural models of nanoparticles in the presence of solvent, relevant to both many industrial processes and toxicological and environmental systems. The database and the validation of the data included in it, means we will provide a trusted data source regarding nanoparticles structures and properties to the academic, industrial and governmental community.

Further impact on the UK knowledge economy from the work arises through the exposure of students of the Molecular Modelling and Materials Science Engineering Doctorate centre at UCL and advanced undergraduates at Birmingham and UCL to the underlying philosophy and the developed tools and databases.

Publications

10 25 50
 
Description The overall objective is to enable new science by the development of a standard, software and database for small inorganic nanoparticles, or nanoclusters. The funding has allowed us to develop the first version of a searchable web-database for storing atomic structures of inorganic nanoclusters - which is already accessible to the general public (we have an automated registration process, and currently over 100 registered users (cf. 36 two years ago)). The database is installed on the head node of a dedicated computer resource based at UCL. From our webpage users can: (a) check whether their predicted atomic structure for a particular compound and size is a previously unknown low-energy configuration; (b) upload data that has been published; (c) search and analyse data stored in the database; and (d) download atomic structures for use in further studies. One key aspect is the development of a standard set of atomic structures, which all predictions can be tagged (the available nodes used to refine uploaded atomic structures and to compute its energy using our chosen standard settings so that atomic structures and energies can be compared). Algorithms for comparing atomic structures have also been developed and installed into software connected to the database. Although the funding has ended, the database is still live and the quantity of data increasing. To date there are approximately 800 structures within the database.
Exploitation Route The software and database development initiated in this project aligns itself with the Physical Sciences, Energy, Engineering and Manufacturing the Future themes of EPSRC. There are strong links to EPSRC research areas: Catalysis, Computational and Theoretical Chemistry, Condensed Matter and Electronic Structure, Energy Storage, Materials for Energy Applications, Particle Technology, Functional Ceramics and Inorganics, and Solar Energy; all research areas earmarked either to maintain or grow in the recent capability reshaping exercise. Nanostructures are key to an enormous wealth of important technological applications (e.g. petrochemical catalysts, battery materials, security inks, biomedical imaging, nanomedicine). Development and optimisation of such applications without good structural models of nanoparticles is extremely difficult, as one is limited to serendipity. Similar structural models will be of use in understanding the toxicity of nanoparticles, an important issue with the increasing technological use of nano-structured materials and their environmental effects. We will provide interested academic, industrial and governmental parties both with new tools to develop structural models of nanoparticles and the opportunity to find models previously developed by others in our web-database. We will provide unique functionalities - for example, to generate structural models of nanoparticles in the presence of a solvent, to gain insight in industrial processes, toxicity and environmental systems. Finally, the proposed work also links to Directed Assembly of Extended Structures with Targeted Properties and Nanoscale Design of Functional Materials grand challenges, both of which would greatly benefit from a proper understanding of the atomistic and electronic structure of nanostructured materials.
The software and database developed in this project will have three types of academic beneficiaries. These will benefit academic groups using computational methods to elucidate the physico-chemical processes occurring at the nano-scale. Externally, UK academic beneficiaries would include the groups whose research typically starts with known atomic structures. A second group of beneficiaries consists of experimental groups working with nanoparticles that need structural models to interpret their results or to guide the direction of their efforts. Finally, the new functionalities/ algorithms developed in our software will be of interest to the wider global optimisation community, working on other materials/systems.
Sectors Chemicals,Digital/Communication/Information Technologies (including Software),Education,Electronics,Energy,Environment,Manufacturing, including Industrial Biotechology,Pharmaceuticals and Medical Biotechnology,Security and Diplomacy

URL https://hive.chem.ucl.ac.uk/
 
Description Findings will help academia and industry in their work to predict properties - based on atomic and electronic level of theory - of materials. This project has two components: the development of a database of atomic structures for inorganic nanoclusters and the software that will be able to exploit this database. The starting point for modelling at the atomic scale is of course the initial atomic coordinates. For crystals, the atomic structure is readily obtainable from diffraction experiments. For small sized nanoparticles, or nanoclusters, obtaining atomic structure from experiments is currently not possible. The expense of predicting atomic structures is dependent on the number of atoms and, for any reasonably sized system, computationally demanding, if not impossible. Therefore, the database of atomic structures already published would be an invaluable aid for computational scientist. The solutions used in the automated software that will access and update the database will also aid the development of other client-server codes (which need not be in the field of Materials Modelling). In fact, the experienced gained by the PI on the development, exploitation as well as practical aspects of the database (ownership of data, access control, liability, etc) has resulted in the PI becoming a member of the ERC's European Materials Modeling Council (EMMC), which is developing plans for connecting industry to the wealth of materials modelling knowledge (software and generated data). The methodology implemented within developed software and the results on the prediction of atomic structure and properties of nanoparticles from the use of the developed software will be of use to the wider computational physics and chemistry community, as well as provide guidance to experimental design.
Sector Chemicals,Digital/Communication/Information Technologies (including Software),Education,Energy,Environment
Impact Types Economic,Policy & public services

 
Description DTA
Amount £60,000 (GBP)
Organisation University College London 
Sector Academic/University
Country United Kingdom
Start 09/2015 
End 08/2018
 
Title WASP@N website database for nanoclusters 
Description Database, website interface and additional software developed in collaboration with our partners. Website interface enables users (including general public) to access the database of predicted atomic structures for nanoclusters that have been published (has an associated DOI). Before registering, a user can try and find whether their newly predicted atomic structure is already in the database. Once registered, a user can access the search page as well as upload their own published data. The additional software computes properties and makes links between data entries based on either connectivity or after energy refinement. 
Type Of Material Database/Collection of data 
Year Produced 2015 
Provided To Others? Yes  
Impact Access to the research database is currently only through the website interface. The website went live 2015. Impact, with regards to users of this site is expected to increase with time (we are only now beginning to advertise its existence). Number of registered users: last year 10, now this is 36. Community of researchers who predict atomic structures can benefit from using this site to check whether (or not) their predictions are new and better than previous results (without registering) AND to make their published predicted atomic structures more visible and available to the wider community by uploading their data (once registered). Community of researchers who investigate properties and interaction of nanoclusters with different environments require initial atomic structures may obtain these starting atomic structures from this site. To date, top countries for the number of unique visits were: 271 from the UK, 153 from Russia, 58 from the USA and 30 from Germany; accessed from 630 computers, 64 mobiles and 5 tablet devices. 
URL https://hive.chem.ucl.ac.uk/
 
Title KLMC 
Description KLMC, or more specifically the Knowledge Led Master Code, was created with the desire to: automate many tasks traditionally performed by the user of a range of third party codes; enable a multistage approach where the KLMC code learns on the fly and refines input files that are submitted for new calculations - hence the name knowledge led; and be able to exploit massively parallel computer platforms for a more general set of applications that may require statistical sampling. The KLMC code is witten in Fortran90 and uses MPI to simultaneously exploit more than one processor. KLMC has a number of modules, primarily aimed at predicting the atomic structure using global optimisation schemes (e.g. Basin Hopping (BH), Genetic Algorithm (GA), ...). First show case examples for a particular module include: employment of BH to predict the structures of LaF3 nanoclusters ; prediction of surface reconstruction; employment of employment of GA to predict the structures of ionic, covalent and metallic nanoclusters; and prediction of surface free energies. 
Type Of Technology Software 
Year Produced 2017 
Impact Software is currently being employed in a number of research projects based in academic institutions in the UK, Spain, South Africa and India. It is also being employed in the training given to postgraduate students enrolled on the Masters degree course that is run in the Molecular Modelling and Materials Science Centre for Doctoral Training (UCL). 
URL http://www.ucl.ac.uk/klmc/Software/