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AI-DRIVEN MOBILE ROBOTS TEAM UP TO TACKLE CHEMICAL SYNTHESIS


RESEARCHERS DEVELOP MOBILE ROBOTS THAT USE AI TO CARRY OUT CHEMICAL SYNTHESIS
RESEARCH

Date: November 6, 2024 Source: University of Liverpool Summary: Researchers have
developed AI-driven mobile robots that can carry out chemical synthesis research
with extraordinary efficiency. Researchers show how mobile robots that use AI
logic to make decisions were able to perform exploratory chemistry research
tasks to the same level as humans, but much faster. Share:
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FULL STORY

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Researchers at the University of Liverpool have developed AI-driven mobile
robots that can carry out chemical synthesis research with axtraordinairy
efficiency.

In a study publishing in the journal Nature, researchers show how mobile robots
that use AI logic to make decisions were able to perform exploratory chemistry
research tasks to the same level as humans, but much faster.

The 1.75-meter-tall mobile robots were designed by the Liverpool team to tackle
three primary problems in exploratory chemistry: performing the reactions,
analysing the products, and deciding what to do next based on the data.

The two robots performed these tasks in a cooperative manner as they addressed
problems in three different areas of chemical synthesis -- structural
diversification chemistry (relevant to drug discovery), supramolecular
host-guest chemistry, and photochemical synthesis.



The results found that with the AI function the mobile robots made the same or
similar decisions as a human researcher but these decisions were made on a far
quicker timescale than a human, which could take hours.

Professor Andrew Cooper from the University of Liverpool's Department of
Chemistry and Materials Innovation Factory, who led the project explained:

"Chemical synthesis research is time consuming and expensive, both in the
physical experiments and the decisions about what experiments to do next so
using intelligent robots provides a way to accelerate this process.



"When people think about robots and chemistry automation, they tend to think
about mixing solutions, heating reactions, and so forth. That's part of it, but
the decision making can be at least as time consuming. This is particularly true
for exploratory chemistry, where you're not sure of the outcome. It involves
subtle, contextual decisions about whether something is interesting or not,
based on multiple datasets. It's a time-consuming task for research chemists but
a tough problem for AI."

Decision-making is a key problem in exploratory chemistry. For example, a
researcher might run several trial reactions and then decide to scale up only
the ones that give good reaction yields, or interesting products. This is hard
for AI to do as the question of whether something is 'interesting' and worth
pursuing can have multiple contexts, such as novelty of the reaction product, or
the cost and complexity of the synthetic route.

Dr Sriram Vijayakrishnan, a former University of Liverpool PhD student and the
Postdoctoral Researcher with the Department of Chemistry who led the synthesis
work, explained: "When I did my PhD, I did many of the chemical reactions by
hand. Often, collecting and figuring out the analytical data took just as long
as setting up the experiments. This data analysis problem becomes even more
severe when you start to automate the chemistry. You can end up drowning in
data."



"We tackled this here by building an AI logic for the robots. This processes
analytical datasets to make an autonomous decision -- for example, whether to
proceed to the next step in the reaction. This decision is basically
instantaneous, so if the robot does the analysis at 3:00 am, then it will have
decided by 3:01 am which reactions to progress. By contrast, it might take a
chemist hours to go through the same datasets."

Professor Cooper added: "The robots have less contextual breadth than a trained
researcher so in its current form, it won't have a "Eureka!" moment. But for the
tasks that we gave it here, the AI logic made more or less the same decisions as
a synthetic chemist across these three different chemistry problems, and it
makes these decisions in the blink of an eye. There is also huge scope to expand
the contextual understanding of the AI, for example by using large language
models to link it directly to relevant scientific literature."

In the future, the Liverpool team wants to use this technology to discover
chemical reactions that are relevant to pharmaceutical drug synthesis, as well
as new materials for applications such as carbon dioxide capture.

Two mobile robots were used in this study, but there is no limit to the size of
the robot teams that could be used. Hence, this approach could scale to the
largest industrial laboratories.


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--------------------------------------------------------------------------------

Story Source:

Materials provided by University of Liverpool. Note: Content may be edited for
style and length.

--------------------------------------------------------------------------------

Journal Reference:

 1. Tianwei Dai, Sriram Vijayakrishnan, Filip T. Szczypiński, Jean-François
    Ayme, Ehsan Simaei, Thomas Fellowes, Rob Clowes, Lyubomir Kotopanov, Caitlin
    E. Shields, Zhengxue Zhou, John W. Ward, Andrew I. Cooper. Autonomous mobile
    robots for exploratory synthetic chemistry. Nature, 2024; DOI:
    10.1038/s41586-024-08173-7

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University of Liverpool. "AI-driven mobile robots team up to tackle chemical
synthesis." ScienceDaily. ScienceDaily, 6 November 2024. <www.sciencedaily.com/
releases/2024/11/241106132220.htm>.
University of Liverpool. (2024, November 6). AI-driven mobile robots team up to
tackle chemical synthesis. ScienceDaily. Retrieved November 7, 2024 from
www.sciencedaily.com/releases/2024/11/241106132220.htm
University of Liverpool. "AI-driven mobile robots team up to tackle chemical
synthesis." ScienceDaily. www.sciencedaily.com/releases/2024/11/241106132220.htm
(accessed November 7, 2024).





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Share this page ...
AI-driven mobile robots team up to tackle chemical synthesis
https://www.sciencedaily.com/releases/2024/11/241106132220.htm
Researchers have developed AI-driven mobile robots that can carry out chemical
synthesis research with extraordinary efficiency. Researchers show how mobile
robots that use AI logic to make decisions were able to perform exploratory
chemistry research tasks to the same level as humans, but much faster.
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