10.5258/SOTON/AI3SD0209
Lapkin, Alexei A.
Alexei A.
Lapkin
University of Cambridge
AI3SD video: development of a full stack for digital R&D in chemistry and chemical process development
University of Southampton
2022
video
Frey, Jeremy
Jeremy
Frey
https://orcid.org/0000-0003-0842-4302
University of Southampton
Kanza, Samantha
Samantha
Kanza
https://orcid.org/0000-0002-4831-9489
University of Southampton
Niranjan, Mahesan
Mahesan
Niranjan
https://orcid.org/0000-0001-7021-140X
University of Southampton
2022
https://youtu.be/DXArgm5VtRo
Creative Commons Attribution 4.0 International
In order to enable seamless access to AI tools in research, it is necessary to transform how our laboratories are equipped. AI requires access to data, and it takes too long to gain access and to clean up datasets. Our experimental hardware is not wired and is not accessible to algorithms. What is required is a development of data architecture that enables access to experimental and literature data both to a uman in the middle and fully algorithmic research tasks. In this talk I'll present our joint effort with the group of Prof Markus Kraft to implement knowledge graph for ML workflow in chemical synthesis development, and the work @ iDMT centre in Cambridge on expanding this to a fully digital R in molecular sciences.
Engineering and Physical Sciences Research Council
https://doi.org/10.13039/501100000266
EP/S000356/1
Artificial and Augmented Intelligence for Automated Scientific Discovery