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

Super-resolution Fluorescence Microscopy01:37

Super-resolution Fluorescence Microscopy

7.7K
Super-resolution fluorescence microscopy (SRFM) provides a better resolution than conventional fluorescence microscopy by reducing the point spread function (PSF). PSF is the light intensity distribution from a point that causes it to appear blurred. Due to PSF, each fluorescing point appears bigger than its actual size, and it is the PSF interference of nearby fluorophores that causes the blurred image. Various approaches to achieving higher resolution through SRFM have recently been...
7.7K

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

Ammonia pressure controls colloidal metal nitride synthesis in molten salts.

Nature·2026
Same author

Carbonylative Aminative Suzuki-Miyaura Coupling: Pd-Catalyzed Synthesis of Amides from Vinyl/Aryl Halides and Boronic Acids.

Journal of the American Chemical Society·2026
Same author

Predicting Nirmatrelvir Resistance in SARS-CoV-2 M<sup>pro</sup> Mutants with an Integrated Computational Framework.

The journal of physical chemistry. B·2026
Same author

FragScan: A Quantitative Fragment Scanning Strategy for Rational Drug Discovery.

Journal of chemical information and modeling·2026
Same author

Pd-Catalyzed Arylative Lossen Rearrangement: Synthesis of Secondary Amines from Aryl/Alkyl Carboxylic Acids and Aryl Halides.

Journal of the American Chemical Society·2026
Same author

Maternal trans-vaccenic acid shapes neonatal T cell development and early-life immune imprinting.

Science (New York, N.Y.)·2026

相关实验视频

Updated: Sep 13, 2025

Fluorescence Biomembrane Force Probe: Concurrent Quantitation of Receptor-ligand Kinetics and Binding-induced Intracellular Signaling on a Single Cell
14:09

Fluorescence Biomembrane Force Probe: Concurrent Quantitation of Receptor-ligand Kinetics and Binding-induced Intracellular Signaling on a Single Cell

Published on: August 4, 2015

12.6K

通过实验数据驱动的适应性β-VAE来探索优化的有机光体搜索.

Yuzhi Xu1,2, Yongrui Luo3, Bo Li4

  • 1Department of Chemistry, New York University, New York, New York 10003, United States.

JACS Au
|August 1, 2025
PubMed
概括

研究人员为有机光分子开发了一种新的反向设计策略. 这种方法优化了特定的实验性质,增强了针对定制光学应用的分子设计.

关键词:
光是一种光.反向的分子设计.分子建模分子建模分子分子分子的分子.它们具有光学特性.优化的优化优化优化.

更多相关视频

Automated System for Single Molecule Fluorescence Measurements of Surface-immobilized Biomolecules
10:57

Automated System for Single Molecule Fluorescence Measurements of Surface-immobilized Biomolecules

Published on: November 2, 2009

13.0K
Open Source High Content Analysis Utilizing Automated Fluorescence Lifetime Imaging Microscopy
09:30

Open Source High Content Analysis Utilizing Automated Fluorescence Lifetime Imaging Microscopy

Published on: January 18, 2017

12.1K

相关实验视频

Last Updated: Sep 13, 2025

Fluorescence Biomembrane Force Probe: Concurrent Quantitation of Receptor-ligand Kinetics and Binding-induced Intracellular Signaling on a Single Cell
14:09

Fluorescence Biomembrane Force Probe: Concurrent Quantitation of Receptor-ligand Kinetics and Binding-induced Intracellular Signaling on a Single Cell

Published on: August 4, 2015

12.6K
Automated System for Single Molecule Fluorescence Measurements of Surface-immobilized Biomolecules
10:57

Automated System for Single Molecule Fluorescence Measurements of Surface-immobilized Biomolecules

Published on: November 2, 2009

13.0K
Open Source High Content Analysis Utilizing Automated Fluorescence Lifetime Imaging Microscopy
09:30

Open Source High Content Analysis Utilizing Automated Fluorescence Lifetime Imaging Microscopy

Published on: January 18, 2017

12.1K

科学领域:

  • 有机材料科学 有机材料科学
  • 计算化学计算化学
  • 光物理学的光学物理学

背景情况:

  • 设计具有特定光学特性的有机光分子具有挑战性.
  • 现有的反向设计方法往往侧重于理论性质,而不是实验性质.

研究的目的:

  • 引入一种新的反向设计策略,以优化有机光分子的特定实验性质.
  • 为了增强产生的分子的强度和多样性.

主要方法:

  • 采用了一个自适应的β-变量自编码器 (自适应的β-VAE).
  • 结合了自适应的β-VAE与基于潜向量的预测模型.
  • 动态调整了库尔巴克-莱布勒分歧缩放因子 (β) 并使用了单独的训练策略.

主要成果:

  • 来自自适应性β-VAE的潜向量有效地预测了诸如光能量和量子产量等实验性质.
  • 该方法提高了发电机的稳定性和分子多样性.
  • 潜伏空间中的渐变导向搜索框架确定了最佳的分子设计.

结论:

  • 开发的策略允许在反向设计中直接优化实验性质.
  • 该方法显示了设计具有量身定制光学特征的多种有机光材料的巨大潜力.
  • 通过新合成的分子进行验证证实了该框架的有效性.