2D Nanomaterials: Materials‐Informatics‐Assisted High‐Yield Synthesis of 2D Nanomaterials through Exfoliation (Adv. Theory Simul. 4/2019)

Nakada, Gentoku; Igarashi, Yasuhiko; Imai, Hiroaki; Oaki, Yuya

doi:10.1002/adts.201970014

Cited by 1 publication

(3 citation statements)

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“…Sparse modeling is applicable to smaller dataset than other informatics approaches. Our group efficiently explored appropriate experimental conditions for high‐yield synthesis of nanosheets using sparse modeling . In the present work, design strategy and discovery of new compounds for organic anode were efficiently explored by MI‐driven approach.…”

Section: Introductionmentioning

confidence: 99%

“…MI recently assists exploration of new synthetic processes, compounds, and materials for a variety of applications, such as battery, catalyst, and solar cell, without experience and intuition. If experience and intuition of experimental scientists are also combined with MI, the synergetic effects, that is, experiment‐oriented MI, accelerate exploration of new materials and functions.…”

Section: Introductionmentioning

confidence: 99%

“…If experience and intuition of experimental scientists are also combined with MI, the synergetic effects, that is, experiment‐oriented MI, accelerate exploration of new materials and functions. Sparse modeling is a recent informatics approach to construct a prediction model based on the inherent sparseness in high‐dimensional data . It means that a targeted whole behavior can be explained by a small number of strongly correlated factors .…”

Section: Introductionmentioning

confidence: 99%

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Experiment‐Oriented Materials Informatics for Efficient Exploration of Design Strategy and New Compounds for High‐Performance Organic Anode

Numazawa

Igarashi

Sato

et al. 2019

Advcd Theory and Sims

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High-performance organic energy storage has attracted much interest as a future battery. Organic anode has been developed as an alternate of graphite in the past decade. However, the design strategies are not fully studied for further development. The present work shows experiment-oriented materials informatics (MI) for efficient exploration of design strategy and new compounds for an active material of high-performance organic anode. A few important factors to achieve high specific capacity are extracted from training dataset containing experimentally measured specific capacity, calculation results, and literature data of the model compounds using sparse modeling, an informatics approach. Although the prediction model is not sufficiently accurate, the model assists in exploration of new compounds in combination with experience and intuition of experimental scientists. New compounds with high specific capacity, such as 227 mA h g -1 at 100 mA g -1 for benzo[1,2-b:4,5-b′]dithiophene (BdiTp), are efficiently discovered in a minimum number of experiments. Furthermore, polymerization of BdiTp exhibits the enhanced performances, such as 933 mA h g -1 at 20 mA g -1 and cycle stability, and rate performance. MI combined with experiment, calculation, and data accelerates design new materials and functions by experimental scientists having their small data, experience, and intuition.

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Section: Introductionmentioning

confidence: 99%