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大学・研究機関15法人を含む
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導入事例

Datachemical LABを用いた論文事例
Machine Learning Prediction of Au(III) Extractability of Various Organic Solvents Based on Ion Solvation in Hydrochloric Acid Media
Tatsuya Oshima, Yuhi Iwakiri, Hiroki Yokota, Asuka Inada
Selective recovery of gold from waste electrical and electronic equipment has attracted increasing attention. Au(III), which is present as tetrachloroauric acid (HAuCl4) in hydrochloric acid media, can be extracted by using various organic solvents, such as ketones and ethers. However, the decisive factors of the solvent for predicting Au(III) extractability have not been confirmed. In the present study, the relationship between the extraction percentage of Au(III) and the properties of the solvent was investigated for 79 types of solvents. Based on the relationships between the Hansen solubility parameters of the solvent and the extraction percentage of Au(III) in 5.0 M HCl with a threshold of 80%, the extractability was classified with 93.7% accuracy...
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Synthesis of Halogen-Bond-Donor-Site-Introduced Functional Monomers through Wittig Reaction of Perfluorohalogenated Benzaldehydes: Toward Digitalization as Reliable Strategy in Small-Molecule Synthesis
Tatsuaki Hori, Shuya Kakinuma, Naoya Ohtsuka, Takeshi Fujinami, Toshiyasu Suzuki, Norie Momiyama
The Wittig reaction of perfluoromonohalobenzaldehydes was systematically studied to synthesize 2,3,5,6-tetrafluoro-4-halostyrene (TFXSs) as functional monomers bearing halogen-bond donor sites. The reaction proceeded efficiently in tetrahydrofuran using 1,1,3,3-tetramethylguanidine as an organic base. Correlation analysis quantitatively identified three key factors required to obtain TFXSs in reasonable yields. The present approach not only contributes to the study of halogen-bond-based functional molecules, but also presents digitalization as a potential strategy in small-molecule synthesis.
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