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A Modular Programmable Inorganic Cluster Discovery Robot for the Discovery and Synthesis of Polyoxometalates
- Source :
- ACS Central Science, ACS Central Science, Vol 6, Iss 9, Pp 1587-1593 (2020)
- Publication Year :
- 2020
- Publisher :
- American Chemical Society (ACS), 2020.
-
Abstract
- The exploration of complex multicomponent chemical reactions leading to new clusters, where discovery requires both molecular self-assembly and crystallization, is a major challenge. This is because the systematic approach required for an experimental search is limited when the number of parameters in a chemical space becomes too large, restricting both exploration and reproducibility. Herein, we present a synthetic strategy to systematically search a very large set of potential reactions, using an inexpensive, high-throughput platform that is modular in terms of both hardware and software and is capable of running multiple reactions with in-line analysis, for the automation of inorganic and materials chemistry. The platform has been used to explore several inorganic chemical spaces to discover new and reproduce known tungsten-based, mixed transition-metal polyoxometalate clusters, giving a digital code that allows the easy repeat synthesis of the clusters. Among the many species identified in this work, the most significant is the discovery of a novel, purely inorganic W24FeIII–superoxide cluster formed under ambient conditions. The modular wheel platform was employed to undertake two chemical space explorations, producing compounds 1–4: (C2H8N)10Na2[H6Fe(O2)W24O82] (1, {W24Fe}), (C2H8N)72Na16[H16Co8W200O660(H2O)40] (2, {W200Co8}), (C2H8N)72Na16[H16Ni8W200O660(H2O)40] (3, {W200Ni8}), and (C2H8N)14[H26W34V4O130] (4, {W34V4}), along with many other known species, such as simple Keggin clusters and 1D {W11M2+} chains.<br />A low-cost, automated modular wheel platform (MWP) is described and used to explore a chemical space. Using a digital synthetic code, the MWP can reproduce known polyoxometalate syntheses and discover novel clusters.
- Subjects :
- 010405 organic chemistry
Computer science
business.industry
General Chemical Engineering
Robotics
General Chemistry
Modular design
010402 general chemistry
01 natural sciences
0104 chemical sciences
law.invention
Computational science
Chemistry
law
Cluster (physics)
Robot
Artificial intelligence
Crystallization
business
QD1-999
Research Article
Subjects
Details
- ISSN :
- 23747951
- Database :
- OpenAIRE
- Journal :
- ACS Central Science, ACS Central Science, Vol 6, Iss 9, Pp 1587-1593 (2020)
- Accession number :
- edsair.doi.dedup.....66536eb3487669022513d423e55127e2