Automated IR reaction Monitoring and data Analysis tools for mechanistic eXamination (AIRMAX): A high throughput flow array for use in reaction discovery


   Department of Chemistry

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  Prof J M Lynam, Prof I J S Fairlamb, Dr Jessica Hargreaves  No more applications being accepted  Competition Funded PhD Project (Students Worldwide)

About the Project

Background

Developments in chemical science are underpinned by modern analytical techniques which provide insight into molecular composition and dynamics. The understanding of structure and dynamics provided by these methods enables new reaction pathways to be discovered so that molecules of societal importance (e.g., pharmaceuticals, agrochemicals, and materials) can be prepared in an efficient and environmentally friendly manner. One of the bottlenecks in the modern analytical methods which provide this information is that they require high levels of interaction from an experienced user who needs to prepare samples, acquire and analyse the resulting data. This is a highly time-consuming processes but developments in automation and data analysis methods could transform the way chemical analysis is performed. This project aims to achieve this through the implementation of a new automated platform to acquire infra-red spectra and then use advanced data analysis methods to deconvolute the rich structural and dynamic information embedded within the datasets.

Objectives

The fundamental aim of this project is to create the automation tools needed to monitor, analyse, and optimise synthetic chemical transformations using IR spectroscopy. In this project we will develop automation tools supported by digital chemistry to monitor exemplar reactions by changing continuous and discrete reaction variables. To achieve this, we have designed and implemented a new sampling and analysis system which allows for automated sampling of samples for IR spectroscopic analysis. Three objectives have been identified to achieve the over-arching aim of the project and to exploit the new system in acquisition of IR spectra.

The first objective of the project will be to design and develop automated IR experiments on timescale from picoseconds through to hours. This will then be enriched by automated data analysis routines to interrogate the spectroscopic data so that reaction profiles can be understood. Finally, the methods will be to develop self-optimising systems so that the best conditions to perform a reaction can be found in an automated fashion.

Experimental Approach

This project will develop automation tools supported by digital chemistry to monitor exemplar reactions by changing continuous and discrete reaction variables. IR spectroscopy is an ideal tool to achieve this as it contains a multitude of valuable information by reporting on all vibrationally allowed changes in a chemical system. IR is complementary to NMR, but arguably carries richer data as every molecule has a unique signature in the spectrum. If spectral changes can be quickly characterised and processed then unique mechanistic insight can be obtained. Furthermore, the rapid IR timescale means that temporal changes enable us to monitor and characterise starting materials, transient species, intermediates and products. When enriched with modern data deconvolution tools and complementary DFT calculations, the data-rich IR spectra of complex reactions mixtures provide the information to profoundly change mechanistic investigations.

Novelty

The novelty of this programme lies in the combination of developing new automated sampling methods, with in-line data analysis and modern data deconvolution tools. This combination promises to provide a significant revolution on how mechanistic insight into catalytic reactions are obtained and analysed.

Training

This project will be suitable for a student interested in applying digital chemistry and automated methods for data acquisition and analysis. They will receive training in a wide range of skills of relevance to laboratory automation, including the development of automated sampling methods, programming, state-of-the-art spectroscopy, design of experiments and methods for data deconvolution and analysis. These are skills in high demand in chemical science.

What is ALBERT?

Doctoral Training in Autonomous Robotic Systems for Laboratory Experiments 

A cohort of students will be part of a mini, pilot Centre for Doctoral Training (CDT) focused on developing the science, engineering, and socio-technology that underpins building robots required for laboratory automation, e.g. in chemistry and related sciences. The first cohort began their PhD projects in 2023, and the second cohort in 2024. Albert represents an autonomous robot that conducts laboratory experiments that are cleaner, greener, safer, and cheaper than anything achievable with today's conventional techniques and technologies. Developing Albert offers significant socio-technical problems for science, engineering, social sciences, and the humanities.

You will follow our core cohort-based training programme to support the development of scientific, transferable and employability skills, as well as training on specific techniques and equipment. Training includes employability and professionalism, graduate teaching assistant training and guidance on writing papers. https://www.york.ac.uk/chemistry/postgraduate/training/idtc/idtctraining/

There will be opportunities for networking and sharing your work both within and beyond the University. Funding is provided to enable you to attend conferences and external training. The department also runs a varied and comprehensive seminar programme.

Equality and Diversity

The Department of Chemistry holds an Athena SWAN Gold Award and is committed to supporting equality and diversity for all staff and students. The Department strives to provide a working environment which allows all staff and students to contribute fully, to flourish, and to excel: https://www.york.ac.uk/chemistry/ed/

As part of our commitment to Equality and Diversity, and Widening Participation, we are working with the YCEDE project (https://ycede.ac.uk/) to improve the number of under-represented groups participating in doctoral study.  

Entry requirements 

You should hold or expect to achieve the equivalent of at least a UK upper second class degree in Chemistry or a relevant related subject. Check the entry requirements for your country: https://www.york.ac.uk/study/international/your-country/

English language requirements: https://www.york.ac.uk/study/postgraduate-research/apply/international/english/

For more information about the project, click on the supervisor's name above to email them. 

For more information about the application process or funding, please click on email institution.

Submit an online PhD in Chemistry application: https://www.york.ac.uk/study/postgraduate/courses/apply?course=DRPCHESCHE3

Please select CDT Autonomous Robotic Systems for Lab Experiments from the drop down menu for How will your studies be funded?

The start date of the PhD will be 16 September 2024


Chemistry (6) Mathematics (25)

Funding Notes

This project is part of the EPSRC ALBERT Doctoral Training Programme. Appointed candidates will be fully-funded for 3.5 years. The funding includes:
Tax-free annual UKRI stipend (£18,622 full time for 2023/24) tuition fees (at the home or overseas rate) plus generous research training and support grant (RTSG).
International students are welcome to apply for this project, however the number of awards we can make to international applicants are limited
Not all projects will be funded; a limited number of strong candidates will be appointed via a competitive process.

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