機械学習で有機合成ロボットを制御し,新しい反応性を探す
Jarosław M Granda1, Liva Donina1, Vincenza Dragone1
1School of Chemistry, University of Glasgow, Glasgow, UK.
Nature
|July 20, 2018
まとめ
この研究では 化学反応の結果を予測するために 機械学習を用いた 有機合成ロボットを導入し 発見を加速します このシステムは80%以上の精度で反応性を予測し,新しい反応の特定につながりました.
科学分野:
- 有機化学
- 化学工学
- 人工知能
背景:
- 化学反応の発見は予測不可能で時間がかかります
- 化学における現在のコンピュータ支援反応設計と機械学習の応用は まだ始まったばかりです
- 量子化学的方法を使って 反応性を予測することは 単純な分子でさえ 複雑です
研究 の 目的:
- 化学反応の迅速な探査と予測のための自動化されたシステムを開発する.
- 機械学習を活用して 化学反応空間を効率的に操作する
- 新しい化学反応の発見を加速させるため
主な方法:
- 有機合成ロボットは 反応と分析を行うために開発されました
- 機械学習アルゴリズムは,化学入力のバイナリエンコーディングを使用して,意思決定に使用されました.
- 核磁気共振 (NMR) と赤外線 (IR) スペクトロスコーピーを用いてリアルタイムで反応を評価した.
主要な成果:
- ロボットは手作業よりも速く 化学反応と分析を行いました
- 機械学習システムは, ~10%のデータを分析した後に, >80%の精度で ~1,000の反応組み合わせの反応性を予測しました.
- このアプローチは,公開されたデータセットとガイドされた手動検証で反応性を成功裏に予測し,結果として4つの新しい反応を発見した.
結論:
- 機械学習で制御されたロボットシステムは 化学反応の空間を急速に探査できます
- このアプローチは新しい化学反応の発見を大幅に加速します
- 自動合成と予測は 伝統的な時間のかかる方法の 強力な代替手段です
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