This PhD opportunity is part of the Centre of Doctoral Training in Autonomous Robotic Systems for Laboratory Experiments (Albert). It is focused on developing the science, engineering, and socio-technology that underpins building robots required for laboratory automation. Albert will contribute to the development of autonomous robots that conduct laboratory experiments that are cleaner, greener, safer, and cheaper than anything achievable with today's conventional techniques and technologies. Albert research will tackle significant socio-technical problems for science, engineering, social sciences, and the humanities. The YorRobots Executive and the Institute for Safe Autonomy will provide international leadership for this research area. The students will be provided with a rich research environment offering world-class labs and training opportunities.
Challenge: Chemical reactions have become increasingly complex, demanding a deeper understanding of diverse reactants, kinetics, and reaction pathways. Multistep reactions, intricate intermediates, and non-linear kinetics are just a few of the complexities that researchers face . Understanding and optimizing these multifaceted processes for the discovery of novel materials is a bottleneck in fields ranging from pharmaceuticals to materials science.
However, the traditional laboratory setup, while invaluable, often faces limitations when dealing with the intricacies of modern chemistry. This is where the concept of robotic labs comes into play, offering an innovative solution to the challenges of reaction complexity and automated synthesis. Automated systems offer precision, high throughput, and consistent execution. However, the conventional automation systems often lack the adaptability and decision-making capabilities required to manage the diverse spectrum of complex chemical processes. Reacting to changing conditions and unexpected variations is a challenge .
Proposal: AI driven robotic labs, a novel paradigm in chemical research, represent a promising solution. These labs integrate advanced robotics, artificial intelligence, and adaptive sensors within a modular and adaptable workspace.
This 3 year PhD programme will investigate the following hypotheses: AI driven Robotics and AI would scale up the discovery of novel chemistry in a sustainable manner.
Objectives: The following objectives will be investigated:
Objective 1: Literature review and down selection of chemistry candidates (6 months): This task would involve an extensive literature review that would look into various chemical and medicinal journals to find a range of potential chemical candidates that are disparate enough but also within the constraints of a physical robotic lab equipment . The idea is that the down selected candidates would be capable of testing the scalability of the automated framework that would be developed.
Objective 2: Development of a virtual robotic lab (9 months): This will involve searching for potential software that can be applied in developing digital copies of physical chemistry equipment. This will enable us to model the limitations of current lab equipment and operate the physical equipment within those constraints.
Objective 3: Development of AI and Optimisation algorithms (9 months): This task will involve the development of and application of population based many-objectives algorithms. The challenge here would be integrating the constraints of physical equipment into the population based algorithms. Another challenge is converting the multiple objectives in the chemical space into a form that the optimisation algorithms would work upon. This work will build upon many-objective algorithm development that is being carried out in Computer Science.
Objective 4: Development and integration with Physical Robotic Equipment (12 months): This task would involve understanding the physical robotic equipment in the laboratory and investigating ways by which they can be adapted to work with the developed flexible automation framework. This work would also involve integrating PC controlled hardware (e.g labview cards) towards controlling various hardware in the lab.