Research Acceleration in Self‐Driving Labs: Technological Roadmap toward Accelerated Materials and Molecular Discovery
The urgency of finding solutions to global energy, sustainability, and healthcare challenges has motivated rethinking of the conventional chemistry and material science workflows. Self‐driving labs, emerged through integration of disruptive physical and digital technologies, including robotics, addi...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2023-04-01
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| Series: | Advanced Intelligent Systems |
| Subjects: | |
| Online Access: | https://doi.org/10.1002/aisy.202200331 |
| _version_ | 1797842540970377216 |
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| author | Fernando Delgado-Licona Milad Abolhasani |
| author_facet | Fernando Delgado-Licona Milad Abolhasani |
| author_sort | Fernando Delgado-Licona |
| collection | DOAJ |
| description | The urgency of finding solutions to global energy, sustainability, and healthcare challenges has motivated rethinking of the conventional chemistry and material science workflows. Self‐driving labs, emerged through integration of disruptive physical and digital technologies, including robotics, additive manufacturing, reaction miniaturization, and artificial intelligence, have the potential to accelerate the pace of materials and molecular discovery by 10–100X. Using autonomous robotic experimentation workflows, self‐driving labs enable access to a larger part of the chemical universe and reduce the time‐to‐solution through an iterative hypothesis formulation, intelligent experiment selection, and automated testing. By providing a data‐centric abstraction to the accelerated discovery cycle, in this perspective article, the required hardware and software technological infrastructure to unlock the true potential of self‐driving labs is discussed. In particular, process intensification as an accelerator mechanism for reaction modules of self‐driving labs and digitalization strategies to further accelerate the discovery cycle in chemical and materials sciences are discussed. |
| first_indexed | 2024-04-09T16:49:35Z |
| format | Article |
| id | doaj.art-e02ae4366b7e44789391b4391251dba0 |
| institution | Directory Open Access Journal |
| issn | 2640-4567 |
| language | English |
| last_indexed | 2024-04-09T16:49:35Z |
| publishDate | 2023-04-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advanced Intelligent Systems |
| spelling | doaj.art-e02ae4366b7e44789391b4391251dba02023-04-22T02:52:33ZengWileyAdvanced Intelligent Systems2640-45672023-04-0154n/an/a10.1002/aisy.202200331Research Acceleration in Self‐Driving Labs: Technological Roadmap toward Accelerated Materials and Molecular DiscoveryFernando Delgado-Licona0Milad Abolhasani1Department of Chemical and Biomolecular Engineering North Carolina State University 911 Partners Way Raleigh NC 27695-7905 USADepartment of Chemical and Biomolecular Engineering North Carolina State University 911 Partners Way Raleigh NC 27695-7905 USAThe urgency of finding solutions to global energy, sustainability, and healthcare challenges has motivated rethinking of the conventional chemistry and material science workflows. Self‐driving labs, emerged through integration of disruptive physical and digital technologies, including robotics, additive manufacturing, reaction miniaturization, and artificial intelligence, have the potential to accelerate the pace of materials and molecular discovery by 10–100X. Using autonomous robotic experimentation workflows, self‐driving labs enable access to a larger part of the chemical universe and reduce the time‐to‐solution through an iterative hypothesis formulation, intelligent experiment selection, and automated testing. By providing a data‐centric abstraction to the accelerated discovery cycle, in this perspective article, the required hardware and software technological infrastructure to unlock the true potential of self‐driving labs is discussed. In particular, process intensification as an accelerator mechanism for reaction modules of self‐driving labs and digitalization strategies to further accelerate the discovery cycle in chemical and materials sciences are discussed.https://doi.org/10.1002/aisy.202200331accelerated discoveryautonomous experimentationdigital labsprocess intensificationself-driving labs |
| spellingShingle | Fernando Delgado-Licona Milad Abolhasani Research Acceleration in Self‐Driving Labs: Technological Roadmap toward Accelerated Materials and Molecular Discovery Advanced Intelligent Systems accelerated discovery autonomous experimentation digital labs process intensification self-driving labs |
| title | Research Acceleration in Self‐Driving Labs: Technological Roadmap toward Accelerated Materials and Molecular Discovery |
| title_full | Research Acceleration in Self‐Driving Labs: Technological Roadmap toward Accelerated Materials and Molecular Discovery |
| title_fullStr | Research Acceleration in Self‐Driving Labs: Technological Roadmap toward Accelerated Materials and Molecular Discovery |
| title_full_unstemmed | Research Acceleration in Self‐Driving Labs: Technological Roadmap toward Accelerated Materials and Molecular Discovery |
| title_short | Research Acceleration in Self‐Driving Labs: Technological Roadmap toward Accelerated Materials and Molecular Discovery |
| title_sort | research acceleration in self driving labs technological roadmap toward accelerated materials and molecular discovery |
| topic | accelerated discovery autonomous experimentation digital labs process intensification self-driving labs |
| url | https://doi.org/10.1002/aisy.202200331 |
| work_keys_str_mv | AT fernandodelgadolicona researchaccelerationinselfdrivinglabstechnologicalroadmaptowardacceleratedmaterialsandmoleculardiscovery AT miladabolhasani researchaccelerationinselfdrivinglabstechnologicalroadmaptowardacceleratedmaterialsandmoleculardiscovery |