{"id":68877,"date":"2025-06-16T10:06:06","date_gmt":"2025-06-16T08:06:06","guid":{"rendered":"https:\/\/fhi.nl\/?post_type=news&p=68877"},"modified":"2025-11-19T15:33:15","modified_gmt":"2025-11-19T14:33:15","slug":"de-chemie-tussen-mens-en-machine-in-het-laboratorium-van-de-toekomst","status":"publish","type":"news","link":"https:\/\/fhi.nl\/en\/news\/de-chemie-tussen-mens-en-machine-in-het-laboratorium-van-de-toekomst\/","title":{"rendered":"The chemistry between man and machine in the laboratory of the future"},"content":{"rendered":"
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By: Eline te Velde<\/h6>\n\t\t\t\t\n\t\t\t\t

\n\t\t\t\t\tThe chemistry between man and machine in the laboratory of the future\t\t\t\t<\/h1>\n\n\t\t\t\t
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Chemist Mathijs Mabesoone is working with his colleagues from the Big Chemistry Consortium on a fundamentally different way of doing materials research: the self-learning robot laboratory. By using AI and automation intelligently, the consortium wants to radically accelerate innovation. What does that mean for the laboratory of the future? And who will be turning the knobs?<\/strong><\/p>\n

Many everyday products are complex mixtures, so-called formulations. Their properties are created by subtle interactions between molecules. If a formulation needs to be adjusted \u2013 for example due to changing regulations or consumer wishes \u2013 we rarely go back to the drawing board. \u201cTake shampoo. If it needs to foam more, we add a molecule,\u201d says Mathijs Mabesoone, group leader of physical-organic chemistry at the Big Chemistry Consortium. \u201cWe rarely redesign these mixtures from scratch.\u201d The result: increasingly complex and difficult to understand compositions, which are not always sustainable or efficient.<\/p>\n

To change this, Mabesoone is working on a revolutionary robotics lab in which AI and robotization fundamentally change chemical research. The goal is to redesign formulations from the bottom up, based on molecular interactions and a solid scientific foundation. This requires a fully automated lab that generates data itself \u2013 day and night, without manual work. This data feeds an artificial intelligence that learns to predict which molecules work together, and why. \u201cA huge benefit is that we can now predict much better which experiments are really useful,\u201d says Mabesoone.<\/p>\n

Robots don't take breaks<\/h4>\n

The scale on which the robotic laboratory operates enables fundamental research through efficiency and time savings. An example is the fully automated analysis of soap. \u201cTraditionally, such an analysis would easily take an analyst a whole day,\u201d says Mabesoone. \u201cOur robot does ten to twenty a day.\u201d The robot works completely independently: it determines the correct dilutions, performs measurements, analyses the results and decides which follow-up steps are required. \u201cAnd this process continues 24 hours a day, even at night and during the weekend.\u201d Smart automation enables a major efficiency boost. In addition, this new technology creates enormous data sources and space for radical innovation.<\/p>\n

However, the robots also encounter unexpected limitations. \u201cSome actions that are very simple for people turn out to be extremely difficult for robots,\u201d says Mabesoone. \u201cTake weighing powders. Liquids can be automated well, but powders are a different story. Even an everyday ingredient like sugar has all kinds of variants \u2013 from powdered to crystal and caster sugar \u2013 that each behave differently. The robot lab must be able to deal with all those different manifestations of such a solid substance. And it is not that easy to solve that.\u201d<\/p>\n

Gut feeling<\/h4>\n

Robots are lightning fast, precise and tireless, but they lack something fundamental: intuition. \u201cThey are extremely good at collecting large amounts of data in a standardized way, or performing repetitive actions,\u201d says Mabesoone. \u201cBut they have no gut feeling.\u201d And that is precisely what is crucial. \u201cThere are countless examples where intuition was leading. Take the discovery of Teflon: an unexpected reaction during an experiment suddenly produced a material that did not stick to anything. That was unplanned, misunderstood. And it led to a completely new field of research. That is why I think that for fundamental research, where the question is not yet clear, human insight remains indispensable.\u201d<\/p>\n

The laboratory of the future<\/h4>\n

Automated labs make chemical research faster, bigger and more systematic. \u201cSmall labs working on general research questions can\u2019t compete with that,\u201d says Mabesoone. In line with that lies the ultimate ambition: a fully autonomous lab, driven by artificial intelligence. A so-called dark laboratory<\/em>, where no human is involved anymore. \u201cThat is the final stage of this project, but we are not there yet.\u201d<\/p>\n

\u201cComputers and robots can measure and automate a lot, but a critical pair of eyes remains essential,\u201d says Mabesoone. \u201cThe analyst of the future is less hands-on, but monitors the overview and quality of the process.\u201d Education must also move along with this. \u201cWe still train chemists too little in programming and data thinking. Within the Big Chemistry Consortium, we are strongly committed to this. We inspire students by having them work on large projects. This allows them to see the impact of their work more quickly. If we really want to train chemists who are ready for the future, we must structurally anchor data and automation in the curriculum.\u201d<\/p>\n

Radically different<\/h4>\n

For Mabesoone, the goal of Big Chemistry is clear. \u201cI hope that with this program we can show that by embracing AI, data and automation, we can make new molecules and materials possible \u2013 radically different from what we know now. We want to prove that this approach works, and that we can also take the doubters with us. Because all data, all measurements are valuable \u2013 provided you record them properly and share them with the community. If we can achieve that, knowledge will not remain in a dusty cupboard, but each experiment will build on the previous one.\u201d<\/p>\n

Want to know more? Mathijs Mabesoone is one of the speakers at the Lab of the Future seminar on Thursday 25 September during the LabNL trade fair. Discover which technologies are making a difference now and in the future, and see how the future of laboratory innovation is taking shape.<\/em><\/strong><\/p>\n

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