Machine-Learning-Driven Synthesis of the Next Generation Carbon Dots with Tunable Fluorescence/Band-Gap

Inorganic quantum dots exhibit interesting fluorescent and semiconductor properties and are currently explored in biological applications as bioimaging agents or in solar panels/photocatalytic processes, as well as in electronics displays. However, they are based on toxic metals (e.g. Cd, Pb), complicated synthetic processes and exhibit low stability when stored under normal atmospheric conditions. Biomass-derived carbon dots (CDs) have emerged as promising and sustainable candidates to inorganic quantum dots. Yet there remains grand challenges in the field, despite great progress made in the development of novel and sustainable carbon dots, in the engineering of their band gap to fit different requirements for visible light adsorption, as well as producing them with tunable fluorescent properties and high quantum yields. To address these challenges and produce carbon dots with tunable fluorescence and band gap, we propose to correlate reaction parameters in the preparation process of carbon dots to explore structure-properties relationship and potential applications. There is a plethora of experimental data (already existing in Titirici's lab and wider literature) on the synthesis and properties of CDs, so we will apply machine learning (ML) for screening of high-performance materials, first to select diverse conditions under which to synthesise the CDs, and then to weight the importance of synthesis variables and to optimise the desired properties. In this project we will demonstrate how ML-based techniques can offer insights into the successful prediction, optimisation, and acceleration of CDs' synthesis processes and properties leading to emerging applications. A regression ML model on hydrothermally-synthesised CDs from various biomass precursors will be established to reveal the relationship between various synthesis parameters and experimental outcomes as well as enhancing the process-related properties such as the fluorescent quantum yield (QY) and tunable bandgap. The synthesis will first be done in batch, and then ultimately transferred to a flow reactor incorporating advanced process analytical technology (PAT), which will be used to characterise the carbon dots in-situ and tune their properties using computer control, supervised by the ML algorithm.

Academic impact:
Recent advances in data science and digital technology have a disruptive effect on the way synthetic chemistry is practiced. Competence in computing and data analysis has become increasingly important in preparing chemistry students for careers in industry and academic research.

The CDT cohort will receive interdisciplinary training in an excellent research environment, supported by state-of-the-art bespoke facilities, in areas that are currently under-represented in UK Chemistry graduate programmes. The CDT assembles a team of 74 Academics across several disciplines (Chemistry, Chemical Engineering, Bioengineering, Maths and Computing, and pharmaceutical manufacturing sciences), further supported by 16 industrial stakeholders, to deliver the interdisciplinary training necessary to transform synthetic chemistry into a data-centric science, including: the latest developments in lab automation, the use of new reaction platforms, greater incorporation of in-situ analytics to build an understanding of the fundamental reaction pathways, as well as scaling-up for manufacturing.

All of the research data generated by the CDT will be captured (by the use of a common Electronic Lab Notebook) and made openly accessible after an embargo period. Over time, this will provide a valuable resource for the future development of synthetic chemistry.

Industrial and Economic Impact:
Synthetic chemistry is a critical scientific discipline that underpins the UK's manufacturing industry. The Chemicals and Pharmaceutical industries are projected to generate a demand for up to 77,000 graduate recruits between 2015-2025. As the manufacturing industry becomes more digitised (Industry 4.0), training needs to evolve to deliver a new generation of highly-skilled workers to protect the manufacturing sector in the UK. By expanding the traditional skill sets of a synthetic chemist, we will produce highly-qualified personnel who are more resilient to future challenges. This CDT will produce synthetic chemists with skills in automation and data-management skills that are highly prized by employers, which will maintain the UK's world-leading expertise and competitiveness and encourage inward investment.

This CDT will improve the job-readiness of our graduate students, by embedding industrial partners in our training programme, including the delivery of training material, lecture courses, case studies, and offers of industrial placements. Students will be able to exercise their broadened fundamental knowledge to a wide range of applied and industrial problems and enhance their job prospects.

Societal:
The World's population was estimated to be 7.4 billion in August 2016; the UN estimated that it will further increase to 11.2 billion in the year 2100. This population growth will inevitably place pressure on the world's finite natural resources. Novel molecules with improved effectiveness and safety will supersede current pharmaceuticals, agrochemicals, and fine chemicals used in the fabrication of new materials.

Recent news highlights the need for certain materials (such as plastics) to be manufactured and recycled in a sustainable manner, and yet their commercial viability of next-generation manufacturing processes will depend on their cost-effectiveness and the speed which they can be developed. The CDT graduates will act as ambassadors of the chemical science, engaging directly with the Learned Societies, local council, general public (including educational activities), as well as politicians and policymakers, to champion the importance of the chemical science in solving global challenges.