Title: Front Cover: Failure‐Experiment‐Supported Optimization of Poorly Reproducible Synthetic Conditions for Novel Lanthanide Metal‐Organic Frameworks with Two‐Dimensional Secondary Building Units (Chem. Eur. J. 66/2021).
Authors: Kitamura, Yu; Terado, Emi; Zhang, Zechen; Yoshikawa, Hirofumi; Inose, Tomoko; Uji‐i, Hiroshi; Tanimizu, Masaharu; Inokuchi, Akihiro; Kamakura, Yoshinobu; Tanaka, Daisuke
Abstract: Lanthanides, machine learning, metal-organic frameworks, proton conductivity, solvothermal synthesis A decision tree uses digitized information to find the synthetic conditions for a new metal-organic framework that exhibits proton conductivity. Keywords: lanthanides; machine learning; metal-organic frameworks; proton conductivity; solvothermal synthesis EN lanthanides machine learning metal-organic frameworks proton conductivity solvothermal synthesis 16270 16270 1 12/01/21 20211125 NES 211125 B Exploring the desired crystal by decision tree analysis b .
Subjects: METAL-organic frameworks; PROTON conductivity; RARE earth metals; MACHINE learning; DECISION trees
Publication: Chemistry - A European Journal, 2021, Vol 27, Issue 66, p16270
ISSN: 0947-6539
Publication type: Academic Journal
DOI: 10.1002/chem.202104013

Front Cover: Failure‐Experiment‐Supported Optimization of Poorly Reproducible Synthetic Conditions for Novel Lanthanide Metal‐Organic Frameworks with Two‐Dimensional Secondary Building Units (Chem. Eur. J. 66/2021).

Kitamura, Yu; Terado, Emi; Zhang, Zechen; Yoshikawa, Hirofumi; Inose, Tomoko; Uji‐i, Hiroshi; Tanimizu, Masaharu; Inokuchi, Akihiro; Kamakura, Yoshinobu; Tanaka, Daisuke