Accelerating the discovery of materials for clean energy in the era of smart automation
| Autor: | Alán Aspuru-Guzik, Kristin A. Persson, Christoph J. Brabec, Muratahan Aykol, Semion K. Saikin, Dennis Sheberla, Joseph Montoya, Carlos Ortiz, Christoph Kreisbeck, Hermann Tribukait, Carlos Amador-Bedolla, Benji Maruyama, Daniel P. Tabor, Loïc M. Roch, Shyam Dwaraknath |
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| Rok vydání: | 2018 |
| Předmět: |
Computer science
business.industry Robotics 02 engineering and technology Integrated approach 010402 general chemistry 021001 nanoscience & nanotechnology 01 natural sciences Automation Field (computer science) 0104 chemical sciences Surfaces Coatings and Films Electronic Optical and Magnetic Materials Characterization (materials science) Biomaterials Software deployment Clean energy Materials Chemistry Systems engineering Artificial intelligence 0210 nano-technology business Energy (miscellaneous) Pace |
| Zdroj: | Nature Reviews Materials. 3:5-20 |
| ISSN: | 2058-8437 |
| DOI: | 10.1038/s41578-018-0005-z |
| Popis: | The discovery and development of novel materials in the field of energy are essential to accelerate the transition to a low-carbon economy. Bringing recent technological innovations in automation, robotics and computer science together with current approaches in chemistry, materials synthesis and characterization will act as a catalyst for revolutionizing traditional research and development in both industry and academia. This Perspective provides a vision for an integrated artificial intelligence approach towards autonomous materials discovery, which, in our opinion, will emerge within the next 5 to 10 years. The approach we discuss requires the integration of the following tools, which have already seen substantial development to date: high-throughput virtual screening, automated synthesis planning, automated laboratories and machine learning algorithms. In addition to reducing the time to deployment of new materials by an order of magnitude, this integrated approach is expected to lower the cost associated with the initial discovery. Thus, the price of the final products (for example, solar panels, batteries and electric vehicles) will also decrease. This in turn will enable industries and governments to meet more ambitious targets in terms of reducing greenhouse gas emissions at a faster pace. The discovery and development of advanced materials are imperative for the clean energy sector. We envision that a closed-loop approach, which combines high-throughput computation, artificial intelligence and advanced robotics, will sizeably reduce the time to deployment and the costs associated with materials development. |
| Databáze: | OpenAIRE |
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