A robot scientist will dream up new materials to advance computing and fight pollution
In a laboratory that overlooks a busy shopping street in Cambridge, Massachusetts, a robot is attempting to create new materials.
A robot arm dips a pipette into a dish and transfers a tiny amount of bright liquid into one of many receptacles sitting in front of another machine. When all the samples are ready, the second machine tests their optical properties, and the results are fed to a computer that controls the arm. Software analyzes the results of these experiments, formulates a few hypotheses, and then starts the process over again. Humans are barely required.
The setup, developed by a startup called Kebotix, hints at how machine learning and robotic automation may be poised to revolutionize materials science in coming years. The company believes it may find new compounds that could, among other things, absorb pollution, combat drug-resistant fungal infections, and serve as more efficient optoelectronic components. The company’s software learns from 3-D models of molecules with known properties.
Software algorithms are already used to design chemical compounds and materials, but the process is slow and crude. Usually, a machine simply tests slight variations of a material, blindly searching for a viable new creation. Machine learning and robotics could make the process much faster and more effective. Kebotix is one of several startups working on this idea.
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