Jove
Visualize
お問い合わせ
JoVE
x logofacebook logolinkedin logoyoutube logo
JoVEについて
概要リーダーシップブログJoVEヘルプセンター
著者向け
出版プロセス編集委員会範囲と方針査読よくある質問投稿
図書館員向け
推薦の声購読アクセスリソース図書館諮問委員会よくある質問
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experimentsアーカイブ
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教員リソースセンター教員サイト
利用規約
プライバシーポリシー
ポリシー

関連する概念動画

Accelerators01:17

Accelerators

291
Accelerators in concrete serve as admixtures to speed up the hardening process, enabling the concrete to achieve early strength faster. Although accelerators do not necessarily impact the time it takes concrete to set, they reduce this time in practice. A common accelerator is calcium chloride, which is particularly useful for hastening early strength development in cold weather or for rapid repair jobs that require quick heat generation after mixing.
The effectiveness of calcium chloride can...
291
Turnover Number and Catalytic Efficiency01:19

Turnover Number and Catalytic Efficiency

21.6K
The turnover number of an enzyme is the maximum number of substrate molecules it can transform per unit time. Turnover numbers for most enzymes range from 1 to 1000 molecules per second. Catalase has the known highest turnover number, capable of converting up to 2.8×106 molecules of hydrogen peroxide into water and oxygen per second. Lysozyme has the lowest known turnover number of half a molecule per second.
Chymotrypsin is a pancreatic enzyme that breaks down proteins during digestion....
21.6K
Catalytically Perfect Enzymes01:07

Catalytically Perfect Enzymes

5.1K
The theory of catalytically perfect enzymes was first proposed by W.J. Albery and J. R. Knowles in 1976. These enzymes catalyze biochemical reactions at high-speed. Their catalytic efficiency values range from 108-109 M-1s-1. These enzymes are also called 'diffusion-controlled' as the only rate-limiting step in the catalysis is that of the substrate diffusion into the active site. Examples include triose phosphate isomerase, fumarase, and superoxide dismutase.
 
Most enzymes...
5.1K
Machines01:19

Machines

579
Machines are complex structures consisting of movable, pin-connected multi-force members that work together to transmit forces. One example of a machine is the cutting plier, which is used to cut wires by applying forces to its handles. When equal and opposite forces are exerted on the handles of the cutting plier, they cause the cutting edges to come together and apply equal and opposite reaction forces on the wire, which are greater than the applied forces.
A free-body diagram of the...
579
States of Water01:23

States of Water

57.0K
Water exists in any one of the three classical states: solid (ice), liquid (water), and gas (steam or water vapor). The state of water depends on i) the intermolecular forces that draw molecules together and ii) the kinetic energy that leads to movements that pull them apart.
Water freezes when the intermolecular forces are greater than the kinetic energy. Unlike most other substances, water is less dense in its solid state than in its liquid state. This is because each water molecule can form...
57.0K
Average Acceleration01:30

Average Acceleration

14.0K
The importance of understanding acceleration spans our day-to-day experiences, as well as the vast reaches of outer space and the tiny world of subatomic physics. In everyday conversation, to accelerate means to speed up. For instance, we are familiar with the acceleration of our car; the harder we apply our foot to the gas pedal, the faster we accelerate. The greater the acceleration, the greater the change in velocity over a given time. Acceleration is widely seen in experimental physics. In...
14.0K

こちらも読む

関連記事

共著者、ジャーナル、引用グラフによってこの研究に関連する記事。

並び替え
Same author

Gradient-Guided Graph Contrastive Learning for Mass Spectrometry-Based Proteomics Clustering.

Journal of chemical information and modeling·2026
Same author

Decoupling Processing-Morphology-Stability Relationships Enables 19.65% Organic Solar Cells With Exceptional Photostability.

Small (Weinheim an der Bergstrasse, Germany)·2026
Same author

Core-to-Wing Type Hybrid Dimeric Giant Molecule Acceptors With Different-Length Ester-Linked Alkyl Chains Enable 20.25% Efficiency Organic Solar Cells.

Angewandte Chemie (International ed. in English)·2026
Same author

Structural basis and immunogenic efficacy of porcine circovirus type 3 virus-like particle.

Nature communications·2026
Same author

Autophagy in plant male reproduction: conserved machinery, divergent functions.

The New phytologist·2026
Same author

Designing Biaryl Pyrazole Derivatives for Antibacterial Activity against Plant Pathogenic Bacteria.

Journal of agricultural and food chemistry·2026

関連する実験動画

Updated: Feb 6, 2026

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma
04:09

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma

Published on: October 10, 2018

8.8K

水処理用触媒プロセスの最適化を、自動化された知識抽出と機械学習によって加速する

Siyuan Jiang1, Ying Yang1, Ziang Liu1

  • 1Key Laboratory for Environmental Pollution Prediction and Control, College of Earth and Environmental Sciences, Lanzhou University, Lanzhou, Gansu Province 730000, PR China.

Journal of hazardous materials
|February 4, 2026
PubMed
まとめ

大規模言語モデルを使用した水処理の自動触媒発見は、手動レビューよりも約270倍高速です。このデータ駆動型アプローチは、効果的な高度酸化プロセス（AOP）触媒の特定を加速します。

キーワード:
高度酸化プロセス触媒最適化データマイニング機械学習仮想ハイスループットスクリーニング

さらに関連する動画

Asthma Detection Research Based on Voice Signal Processing and Machine Learning
04:04

Asthma Detection Research Based on Voice Signal Processing and Machine Learning

Published on: July 22, 2025

1.0K
Process Optimization using High Throughput Automated Micro-Bioreactors in Chinese Hamster Ovary Cell Cultivation
09:28

Process Optimization using High Throughput Automated Micro-Bioreactors in Chinese Hamster Ovary Cell Cultivation

Published on: May 18, 2020

9.2K

関連する実験動画

Last Updated: Feb 6, 2026

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma
04:09

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma

Published on: October 10, 2018

8.8K
Asthma Detection Research Based on Voice Signal Processing and Machine Learning
04:04

Asthma Detection Research Based on Voice Signal Processing and Machine Learning

Published on: July 22, 2025

1.0K
Process Optimization using High Throughput Automated Micro-Bioreactors in Chinese Hamster Ovary Cell Cultivation
09:28

Process Optimization using High Throughput Automated Micro-Bioreactors in Chinese Hamster Ovary Cell Cultivation

Published on: May 18, 2020

9.2K

科学分野:

  • 環境科学
  • 材料科学
  • 計算化学

背景:

  • 水処理のための従来の触媒発見は、手動の文献レビューによって妨げられ、データ取得のボトルネックにつながります。
  • 効率的な触媒の開発は、水処理技術を進歩させるために不可欠です。

研究 の 目的:

  • 水処理における効率的な触媒発見のための自動化されたパイプラインを開発すること。
  • データ駆動型の方法論を通じて環境触媒の材料最適化を加速すること。

主な方法:

  • 高忠実度ドキュメント解析と大規模言語モデルを統合した自動化パイプラインが開発されました。
  • 高度酸化プロセス（AOP）に関する3000以上の出版物から3276件のレコードからなる包括的なデータベースが構築されました。
  • キュレーションされたデータで多段階最適化XGBoostモデルがトレーニングされました。

主要な成果:

  • 自動化されたパイプラインは、手動の方法と比較して約270倍の効率を示しました。
  • XGBoostモデルは、分解速度定数でR²値0.6753、除去効率で0.8351を達成しました。
  • 3つの有望な触媒（Co₃O₄@BC、Fe₃O₄@GO、およびCoFe₂O₄）が特定され、4％未満のエラーで実験的に検証されました。

結論:

  • データ駆動型の方法論は、環境触媒における触媒発見と材料最適化を大幅に加速します。
  • 開発されたパイプラインとデータベースは、水処理の研究者にとって貴重なリソースを提供します。
  • 自動化されたアプローチは、従来のボトルネックを克服し、研究の焦点をデータ収集からイノベーションへとシフトさせることができます。