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相关概念视频

Behavior of Gas Molecules: Molecular Diffusion, Mean Free Path, and Effusion03:48

Behavior of Gas Molecules: Molecular Diffusion, Mean Free Path, and Effusion

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Although gaseous molecules travel at tremendous speeds (hundreds of meters per second), they collide with other gaseous molecules and travel in many different directions before reaching the desired target. At room temperature, a gaseous molecule will experience billions of collisions per second. The mean free path is the average distance a molecule travels between collisions. The mean free path increases with decreasing pressure; in general, the mean free path for a gaseous molecule will be...
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Passive Diffusion: Overview and Kinetics01:17

Passive Diffusion: Overview and Kinetics

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Passive diffusion is a critical process that allows small lipophilic drugs to cross the cell membrane along a concentration gradient. This mechanism's efficiency depends on four primary factors: the membrane's surface area, the drug's lipid-water partition coefficient, the concentration gradient, and the membrane's thickness.
When administered orally, drugs establish a substantial concentration gradient between the gastrointestinal (GI) lumen and the bloodstream, expediting...
440
Polymers: Molecular Weight Distribution01:10

Polymers: Molecular Weight Distribution

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For any given polymer, the weight average molecular weight (Mw) is higher than, if not equal to, the number average molecular weight (Mn). The only situation in which the weight average molecular weight and the number average molecular weight are equal is when a polymer consists only of chains with equal molecular weight. However, this never happens in a synthetic polymer, since it is difficult to control the polymerization process up to a molecular level with accuracy to a hundred percent.
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Diffusion01:21

Diffusion

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Diffusion is a type of passive transport. In passive transport, a substance tends to move from an area of high concentration to an area of low concentration until the concentration is equal across the space. For example, take the diffusion of substances through the air. When someone opens a perfume bottle in a room filled with people, the perfume is at its highest concentration in the bottle and is at its lowest at the edges of the room. The perfume vapor will diffuse, or spread away, from the...
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Molecular Models02:00

Molecular Models

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Physical models representing molecular architectures of chemical compounds play essential roles in understanding chemistry. The use of molecular models makes it easier to visualize the structures and shapes of atoms and molecules.
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Molecular Weight of Step-Growth Polymers01:08

Molecular Weight of Step-Growth Polymers

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Step growth polymerization involves bi or multifunctional monomers. Bifunctional monomers react to form linear step growth polymers, whereas multifunctional monomers react to form non-linear or branched polymers.
As the step-growth polymerization involves step-wise condensation of monomers, the molecular weight also builds up eventually. Consequently, high molecular weight polymers are obtained at the late stages of the polymerization, where 99% of monomers have been consumed.
The extent of the...
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相关实验视频

Updated: Jun 19, 2025

Generating Controlled, Dynamic Chemical Landscapes to Study Microbial Behavior
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扩散在两个层面上,并优化多种属性:一种新的方法来产生具有理想属性的分子.

Siyuan Guo, Jihong Guan, Shuigeng Zhou

    IEEE/ACM transactions on computational biology and bioinformatics
    |July 26, 2024
    PubMed
    概括

    这项研究引入了一种新的AI方法,用于使用先进的扩散模型生成具有所需特性的药物分子. 该方法增强了分子有效性,并优化了实用的药物发现应用的多种特征.

    科学领域:

    • 计算化学是一种计算化学.
    • 人工智能在药物发现中的作用

    背景情况:

    • 像GAN,VAE和扩散模型这样的生成模型用于分子生成.
    • 现有的模型往往侧重于基本属性 (有效性,独特性) 或单一属性优化,限制实际使用.
    • 同时优化多个分子性质对于有效的药物设计至关重要.

    研究的目的:

    • 开发一种新的AI方法,使用扩展扩散模型框架生成具有理想性质的分子.
    • 解决现有模型在产生实际有用分子方面的局限性.
    • 为了同时优化化学有效性和多个可取的分子性质.

    主要方法:

    • 提出了一个新的扩散模型框架,包含两个结构层:分子和分子碎片.
    • 开发了一种基于电子效应的碎片化方法,用于生成可取碎片.
    • 引入了能量导向功能以优化分子有效性.
    • 采用多目标机制,同时优化多个分子性质.

    主要成果:

    • 提出的方法在产生具有更好的有效性,独特性和新性的分子方面表现出卓越的性能.
    • 与最先进的模型相比,实现了更好的Fréchet ChemNet距离 (FCD),药物相似性的定量估计 (QED) 和logP (PlogP).
    • 在QM9和ZINC250k数据集上的实验验证证证了该方法的有效性.

    更多相关视频

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    结论:

    • 新型扩散模型框架有效地产生具有增强有效性和多种可取性质的分子.
    • 这种方法代表了人工智能驱动药物设计的重大进步,产生了更多实际有用的候选药物.
    • 该方法为未来的生成化学和药物发现研究提供了有希望的方向.