Computational optimisation of photoactive dye pairs for designing novel, highly efficient dye-sensitised solar cells.

Lead Research Organisation: UNIVERSITY OF CAMBRIDGE
Department Name: Physics

Abstract

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Planned Impact

Computing, data and communications infrastructure have transformed modern life. They all require software, security and trained personnel to work effectively and it has become common to use the term e-Infrastructure to refer to the whole of this interconnected ecosystem. E-Infrastructure has become a major contributor to advances in science and technology and it is clear that no industry will be able to compete internationally unless it exploits e-Infrastructure at highest level. The proposed EPSRC Centre for Doctoral Training in Computational Methods for Materials Science is focused on the development of new functionality in existing software, and even entirely new codes that will address challenges in materials that cannot presently be addressed. The UK is making large capital investments in e-Infrastructure but these investments will only achieve a fraction of their potential impact unless investments are also made in software development. The CDT will primarily focus on software development for materials science, which is itself, of course, extremely broad. However, the training provided in numerical methods, modern software development techniques and the exposure to present and emerging computational hardware means that the students will have the skilled set to work in any area of software after their PhDs. Given the universally acknowledge lack of highly trained personnel in software development one of our most important impacts will be in providing nearly 80 people who can apply this training in industry, including the very large number of UK software-based SMEs, or academia. The emphasis of the training and subsequent research project in the CDT is on development of innovative new methods for materials modelling and these will have impact in both academia and industry in further expanding the capability of materials simulation and the range of phenomena and processes that can be simulated and/or the amount of information that can be extracted from experiments. Thus we expect the CDT to have a significant impact across a very broad spectrum of disciplines.

Studentship Projects

Project Reference Relationship Related To Start End Student Name
NE/W503204/1 31/03/2021 30/03/2022
1948653 Studentship NE/W503204/1 30/09/2017 30/03/2022 Leon Devereux
 
Description The feasibility of a computational modelling pipeline designed to rapidly screen specialised solar cell materials has been confirmed. These materials are dye molecules for dye-sensitised solar cells (DSCs) - they are the primary light-harvesting component of such cells. The pipeline developed matches two complementary dyes together, that each absorb a different range of wavelengths, such that the net absorption is maximised across the solar spectrum.
Computationally demanding calculations on leading dye pairs in their working environment have been carried out using density functional theory (DFT, a quantum-mechanical modelling technique). These have yielded important descriptors of the dyes' electronic properties, which can be used to predict the power conversion efficiency of a DSC they are used in. Research into the most accurate and general model to perform this prediction is ongoing, alongside experimental fabrication of these cells to test predictions (experimental tests are done in collaboration with research group members at the Rutherford Appleton Laboratory, Oxfordshire).
The standard technique to calculate absorption properties (called linear response time-dependent density functional theory, LR TD-DFT) is too computationally costly when applied to the very large model photoelectrode systems. An alternative technique called real-time time-dependent DFT, that uses a different scheme to obtain the same information, was also trialled on these systems. Whilst more efficient than the linear-response variant, it was ultimately deemed unfeasible in computational cost as well. Smaller dye-pair models are thus used to compute the key absorption information and used in the prediction methods above.
Exploitation Route It is hoped that the steps towards a full computational prediction pipeline for complementary dye pairs will enable much faster design of new, optimised dyes, inspired by computational drug design. This award is ongoing, and so in the remaining time following, it is planned that machine-learning based tools will be investigated to assist in this computer-aided molecular engineering of new dyes.
Sectors Electronics

Energy

Environment
 
Description ANSTO collaboration for experimental and computational studies on adsorbed dye conformations in dye-sensitised solar cells 
Organisation Australian Nuclear Science and Technology Organisation
Country Australia 
Sector Public 
PI Contribution Performed density functional theory calculations to obtain structures of select dye molecules, used in dye-sensitised solar cells, once bound to a titanium dioxide surface in multiple binding conformations.
Collaborator Contribution Carried out experimental characterisation techniques on the select dye layers bound to titanium dioxide (including x-ray reflectometry, infrared spectroscopy) and comparing consistency of computed structures with these results.
Impact The results elucidate the nature of preferred binding conformations of the studied dyes. Understanding this at the molecular level is critical when designing further variants of such dyes to optimise their performance in dye-sensitised solar cells. A manuscript for publication is currently being prepared.
Start Year 2019
 
Description Argonne Leadership Computing Facility allocation of computational resources 
Organisation Argonne National Laboratory
Country United States 
Sector Public 
PI Contribution Feedback on computational performance (e.g. parallelisation efficiency) of the Theta, Mira and Cooley supercomputer clusters when carrying out density functional theory calculations.
Collaborator Contribution Permitted use of the high-performance computing resources of the Theta, Mira (until Jan 2020) and Cooley supercomputer clusters, under the banner of the Argonne Data Science Programme. These have been used to carry out all the computationally demanding DFT modelling within the project thus far.
Impact See "Key Findings" section for the award entitled "Computational optimisation of photoactive dye pairs for designing novel, highly efficient dye-sensitized solar cells".
Start Year 2018