iDMT Lecture Series | 10th October 2023 3pm

Pfizer Lecture Theatre, Yusuf Hamied Department of Chemistry, University of Cambridge

For the October 2023 session of the iDMT Lecture Series, we are pleased to be hosting a double-feature focused on Laboratory Automation with contributions from Dr Nicholas Jose from Accelerated Materials on “Modular automation of reactors” and Aniket Chitre from the Sustainable Reaction Engineering Group, Department of Chemical Engineering & Biotechnology on “pHbot: Self-Driven Robot for pH Adjustment of Viscous Formulations via Physics-informed-ML”. All are welcome to attend.

Modular automation of reactors | Dr Nicholas Jose | Accelerated Materials Ltd.

Reactor technologies can be a limiting factor in discovery, scale-up and manufacturing. Automation can greatly increase R&D throughput by decreasing manual labour, increasing quality of data and enabling the integration of AI; however, the actual process of automating reactors often requires costly equipment, time and engineering expertise. In this work we present the use of FLAB. FLAB is a flexible, python-based framework for developing laboratory automation applications. In this talk, Nicholas will explore the trials and tribulations of reactor automation in several case studies in academia and industry at the iDMT, and share key insights into the automation process.

pHbot: Self-Driven Robot for pH Adjustment of Viscous Formulations via Physics-informed-ML | Aniket Chitre | University of Cambridge Department of Chemical Engineering & Biotechnology 

pH adjustment is crucial for many industrial products, yet this step is typically performed by manual trial-and-error. A particularly industrially relevant yet challenging titration is that of adjusting viscous liquid formulations using weak, polyprotic titrants (usually citric acid). Handling of viscous, non-Newtonian formulations, with such polyprotic acids preferred for their chelation and buffering effects make a robotic solution challenging. We present a self-driving pH robot integrated with physics-informed learning; this hybrid physical-ML model enables automated titration with weak-strong acid/base pairs. To deal with the high viscosities of these formulations, we developed specific automated mixing and cleaning protocols. We hit the target pH within two to five iterations over 250 distinct formulations in labscale small-batch (~ 10 mL and 12 samples) titrations. In the interest of scaling up to match industrial processes, we also demonstrate that our hybrid algorithm works at ~25x scale-up. The method is general, and we open-source our algorithm and designs

Recordings of past iDMT Lecture Series talks are available to iDMT Network Members, contact the iDMT team to find out more.

iDMT Facilities | ChemSpeed

This system can be used, for example, to setup plates for High Throughput Experimentation as a tool to efficiently and accurately load well plates with different solids. The Chemspeed has the ability to handle solids (crystalline or powder) without prior knowledge of density. A specific recent use case within the iDMT has been the dispensing of sodium azide in a non-standard, glass plate, with a 96-well plate being loaded in approximately 1h30. Using the Chemspeed enabled safer and repeatable operation and avoided the need for an aqueous stock solution which was detrimental to the reaction.

Visit our website to find out more about the iDMT's facilities. For the opportunity to work with us, get in touch with the iDMT team.

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