Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Supercritical Fluid Chromatography01:18

Supercritical Fluid Chromatography

209
Supercritical fluid chromatography (SFC) provides a beneficial substitute for gas chromatography (GC) and liquid chromatography (LC) for certain samples because it merges the top attributes of both techniques. SFC allows the separation and analysis of compounds that GC or LC does not easily manage. These compounds are traditionally nonvolatile or thermally unstable, making GC unsuitable and lacking functional groups required for HPLC analysis.
SFC utilizes a supercritical fluid mobile phase,...
209
Turbulent Flow: Problem Solving01:09

Turbulent Flow: Problem Solving

96
Carbonation is a process used to dissolve carbon dioxide gas in a liquid, commonly used in the production of carbonated beverages. Achieving efficient carbonation requires careful control of temperature, pressure, and flow conditions. By adjusting these parameters, carbonation efficiency can be maximized, producing a higher concentration of CO2 in the liquid.
Temperature is a key factor in CO2 solubility. In this case, the CO2 gas and the liquid are cooled to 20°C. Lower temperatures...
96

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Machine Learning-Driven Discovery of Sustainable Ionic Liquids for CO<sub>2</sub> Capture from Large Chemical Spaces.

The journal of physical chemistry. B·2026
Same author

Insights on the Adsorption of Per- and Polyfluoroalkyl Substances onto Laboratory Syringe Membrane Filters: Experimental, Materials, and Mechanism Evaluations.

ACS ES&T water·2026
Same author

Modular, On-Site Solutions with Lightweight Anomaly Detection for Sustainable Nutrient Management in Agriculture.

ACS ES&T engineering·2026
Same author

Rapid, High-Capacity, and Reusable Bovine Serum Albumin-Based Adsorbents for Perfluoroalkyl and Polyfluoroalkyl Substance Removal.

ACS applied materials & interfaces·2026
Same author

A Robust Gaussian Process Paradigm for Predictive Modeling on Small Data sets in Environmental Science: A Case Study in Ballasted Flocculation.

Environmental science & technology·2025
Same author

An Advanced Pore Flow Model for Uncoding Micropollutant Transport in Nanofiltration Membranes.

Environmental science & technology·2025

相关实验视频

Updated: Jun 7, 2025

Pretreatment of Lignocellulosic Biomass with Low-cost Ionic Liquids
10:42

Pretreatment of Lignocellulosic Biomass with Low-cost Ionic Liquids

Published on: August 10, 2016

18.0K

对CO2吸收的环境良性离子液体的选使用基于表示不确定性的机器学习.

Shifa Zhong1, Yushan Chen2, Jibai Li1

  • 1Department of Environmental Science, Institute of Eco-Chongming, School of Ecological and Environmental Sciences, East China Normal University, Shanghai 200241, P. R. China.

Environmental science & technology letters
|November 18, 2024
PubMed
概括

本研究引入了一种新的"表示不确定性" (RU) 方法,用于使用机器学习对离子液体 (IL) 进行可靠的选. 该RU方法提高了对环保IL的预测准确度,这对于碳捕获技术至关重要.

更多相关视频

Achieving Moderate Pressures in Sealed Vessels Using Dry Ice As a Solid CO2 Source
06:26

Achieving Moderate Pressures in Sealed Vessels Using Dry Ice As a Solid CO2 Source

Published on: August 17, 2018

9.9K
Author Spotlight: Standardizing the Development of Amine-Based Silica Composites as CO2 Adsorbents for Direct Air Capture
08:00

Author Spotlight: Standardizing the Development of Amine-Based Silica Composites as CO2 Adsorbents for Direct Air Capture

Published on: September 29, 2023

2.3K

相关实验视频

Last Updated: Jun 7, 2025

Pretreatment of Lignocellulosic Biomass with Low-cost Ionic Liquids
10:42

Pretreatment of Lignocellulosic Biomass with Low-cost Ionic Liquids

Published on: August 10, 2016

18.0K
Achieving Moderate Pressures in Sealed Vessels Using Dry Ice As a Solid CO2 Source
06:26

Achieving Moderate Pressures in Sealed Vessels Using Dry Ice As a Solid CO2 Source

Published on: August 17, 2018

9.9K
Author Spotlight: Standardizing the Development of Amine-Based Silica Composites as CO2 Adsorbents for Direct Air Capture
08:00

Author Spotlight: Standardizing the Development of Amine-Based Silica Composites as CO2 Adsorbents for Direct Air Capture

Published on: September 29, 2023

2.3K

科学领域:

  • 材料科学 材料科学 材料科学
  • 计算化学计算化学
  • 环境科学 环境科学

背景情况:

  • 机器学习 (ML) 模型对于选具有低粘度,低毒性和高二氧化碳吸收等理想性质的离子液体 (IL) 至关重要,以缓解气候变化.
  • 当候选IL在模型的训练数据范围 (外推区域) 之外时,ML模型的预测可能不可靠,导致效率低下的材料发现.

研究的目的:

  • 开发和验证一种"表示不确定性" (RU) 方法,以量化ML查ML模型中的预测不确定性.
  • 通过解决模型推断问题,提高识别有前途的IL候选人二氧化碳捕获的可靠性.

主要方法:

  • 采用了四种不同的IL表示:分子指纹,描述符,图像和图形,每个都被输入到单独的ML模型中.
  • 使用RU方法量化预测不确定性,计算为四种不同的ML模型中预测的标准偏差.
  • 开发集体ML模型,将来自四个基于表示的模型的预测结合起来.

主要成果:

  • 该RU方法在识别粘度,毒性,折射率和二氧化碳吸收数据集的不可靠预测方面表现优于传统模型不确定性 (MU).
  • 与基于单个表示的单个ML模型相比,集体模型表现出更好的预测性能.
  • 使用RU方法选了1420个IL,确定了37个具有可吸收二氧化碳的理想性质的有希望的候选者.
  • 实验验证证证实了整体模型的预测准确性和RU方法对二氧化碳吸收的有效性.

结论:

  • "表示不确定性"方法为选和设计离子液体提供了更可靠的方法,加速了碳捕获材料的发现.
  • 集成建模,以 RU 方法为指导,显著提高了预测准确度,并有助于识别高性能 IL.
  • 这项工作为开发强大的ML模型提供了新的视角,并增强了功能材料的发现管道.