AI3SD video: development of a full stack for digital R&D in chemistry and chemical process development
AI3SD video: development of a full stack for digital R&D in chemistry and chemical process development
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 ‘human 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&D in molecular sciences.
Lapkin, Alexei A.
e5550045-9bdc-4cca-873a-16c2f37a64c8
Frey, Jeremy G.
ba60c559-c4af-44f1-87e6-ce69819bf23f
Kanza, Samantha
b73bcf34-3ff8-4691-bd09-aa657dcff420
Niranjan, Mahesan
5cbaeea8-7288-4b55-a89c-c43d212ddd4f
3 March 2022
Lapkin, Alexei A.
e5550045-9bdc-4cca-873a-16c2f37a64c8
Frey, Jeremy G.
ba60c559-c4af-44f1-87e6-ce69819bf23f
Kanza, Samantha
b73bcf34-3ff8-4691-bd09-aa657dcff420
Niranjan, Mahesan
5cbaeea8-7288-4b55-a89c-c43d212ddd4f
Lapkin, Alexei A.
(2022)
AI3SD video: development of a full stack for digital R&D in chemistry and chemical process development.
Frey, Jeremy G., Kanza, Samantha and Niranjan, Mahesan
(eds.)
AI4SD Network+ Conference, Chilworth Manor , Southampton, United Kingdom.
01 - 03 Mar 2022.
(doi:10.5258/SOTON/AI3SD0209).
Record type:
Conference or Workshop Item
(Other)
Abstract
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 ‘human 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&D in molecular sciences.
Video
ai4sd_march_2022_day_3_AlexeiLapkin
- Version of Record
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Published date: 3 March 2022
Additional Information:
Alexei Lapkin graduated with an MChem from Novosibirsk State University, specialising in membrane gas separation. He then worked at Boreskov Institute of Catalysis prior to moving to the University of Bath where he was employed as a research officer, which allowed him to complete his PhD in the area of multiphase membrane catalysis.
Venue - Dates:
AI4SD Network+ Conference, Chilworth Manor , Southampton, United Kingdom, 2022-03-01 - 2022-03-03
Identifiers
Local EPrints ID: 469294
URI: http://eprints.soton.ac.uk/id/eprint/469294
PURE UUID: 39b2fa61-df62-4090-b8d3-535706bc7232
Catalogue record
Date deposited: 13 Sep 2022 16:35
Last modified: 17 Mar 2024 03:51
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Contributors
Author:
Alexei A. Lapkin
Editor:
Mahesan Niranjan
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