<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Wu J</submitter><funding>China Scholarship Council</funding><funding>Deutscher Akademischer Austauschdienst</funding><funding>Deutsche Forschungsgemeinschaft</funding><funding>Solar Technologies go Hybrid</funding><funding>Alexander von Humboldt-Stiftung</funding><funding>Bayerisches Staatsministerium?f?r Wirtschaft und Medien,?Energie und Technologie</funding><funding>Bavarian State Government</funding><funding>National Natural Science Foundation of China</funding><funding>Technical Field Funds of 173 Project</funding><pagination>16517-16525</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC10401720</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>145(30)</volume><pubmed_abstract>High-throughput synthesis of solution-processable structurally variable small-molecule semiconductors is both an opportunity and a challenge. A large number of diverse molecules provide a possibility for quick material discovery and machine learning based on experimental data. However, the diversity of the molecular structure leads to the complexity of molecular properties, such as solubility, polarity, and crystallinity, which poses great challenges to solution processing and purification. Here, we first report an integrated system for the high-throughput synthesis, purification, and characterization of molecules with a large variety. Based on the principle "Like dissolves like," we combine theoretical calculations and a robotic platform to accelerate the purification of those molecules. </pubmed_abstract><journal>Journal of the American Chemical Society</journal><pubmed_title>Integrated System Built for Small-Molecule Semiconductors via High-Throughput Approaches.</pubmed_title><pmcid>PMC10401720</pmcid><funding_grant_id>44-6521a/20/4</funding_grant_id><funding_grant_id>62104031</funding_grant_id><funding_grant_id>1199604</funding_grant_id><funding_grant_id>24JJ210663A</funding_grant_id><funding_grant_id>182849149</funding_grant_id><pubmed_authors>Wu J</pubmed_authors><pubmed_authors>Barabash A</pubmed_authors><pubmed_authors>Seok SI</pubmed_authors><pubmed_authors>Zhang J</pubmed_authors><pubmed_authors>Torresi L</pubmed_authors><pubmed_authors>Friederich P</pubmed_authors><pubmed_authors>Brabec CJ</pubmed_authors><pubmed_authors>Xie Z</pubmed_authors><pubmed_authors>Hauch JA</pubmed_authors><pubmed_authors>Zhao Y</pubmed_authors><pubmed_authors>Kasian O</pubmed_authors><pubmed_authors>Guldi DM</pubmed_authors><pubmed_authors>Rocha-Ortiz JS</pubmed_authors><pubmed_authors>Luo J</pubmed_authors><pubmed_authors>Hu M</pubmed_authors><pubmed_authors>Perez-Ojeda ME</pubmed_authors><pubmed_authors>Reiser P</pubmed_authors><pubmed_authors>Wang Y</pubmed_authors><pubmed_authors>Lahn L</pubmed_authors></additional><is_claimable>false</is_claimable><name>Integrated System Built for Small-Molecule Semiconductors via High-Throughput Approaches.</name><description>High-throughput synthesis of solution-processable structurally variable small-molecule semiconductors is both an opportunity and a challenge. A large number of diverse molecules provide a possibility for quick material discovery and machine learning based on experimental data. However, the diversity of the molecular structure leads to the complexity of molecular properties, such as solubility, polarity, and crystallinity, which poses great challenges to solution processing and purification. Here, we first report an integrated system for the high-throughput synthesis, purification, and characterization of molecules with a large variety. Based on the principle "Like dissolves like," we combine theoretical calculations and a robotic platform to accelerate the purification of those molecules. </description><dates><release>2023-01-01T00:00:00Z</release><publication>2023 Aug</publication><modification>2025-04-27T00:04:19.447Z</modification><creation>2025-04-06T17:47:44.634Z</creation></dates><accession>S-EPMC10401720</accession><cross_references><pubmed>37467341</pubmed><doi>10.1021/jacs.3c03271</doi></cross_references></HashMap>