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相关概念视频

Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

Mechanistic Models: Compartment Models in Individual and Population Analysis

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Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least...
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Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

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Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
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Turnover Number and Catalytic Efficiency01:19

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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....
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Predicting Reaction Outcomes02:24

Predicting Reaction Outcomes

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Kinetics describes the rate and path by which a reaction occurs. In contrast, thermodynamics deals with state functions and describes the properties, behavior, and components of a system. It is not concerned with the path taken by the process and cannot address the rate at which a reaction occurs. Although it does provide information about what can happen during a reaction process, it does not describe the detailed steps of what appears on an atomic or a molecular level. On the other hand,...
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Analysis of Population Pharmacokinetic Data01:12

Analysis of Population Pharmacokinetic Data

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Analysis of population pharmacokinetic data involves studying the behavior of drugs within diverse populations to understand their pharmacokinetic parameters. Traditional pharmacokinetic methods typically involve collecting samples from a few individuals and estimating these parameters. While these methods are commonly used, they have limitations in capturing the variability in drug response among individuals or heterogeneous populations. Population pharmacokinetics is employed to address these...
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相关实验视频

Updated: Sep 11, 2025

Multiscale Sampling of a Heterogeneous Water/Metal Catalyst Interface using Density Functional Theory and Force-Field Molecular Dynamics
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机器学习潜力的数据库构建中的推断技术:在催化过程中采样符合性道中实现亚化学准确性.

Thantip Roongcharoen1, Giorgio Conter1, Giacomo Melani1

  • 1CNR-ICCOM, ConsiglioNazionale delle Ricerche, via Giuseppe Moruzzi 1, Pisa 56124, Italy.

Journal of chemical theory and computation
|August 15, 2025
PubMed
概括

我们开发了CSCP-X,一种用于创建精确机器学习原子间潜能 (MLIP) 的计算方法. 这加快了催化剂的发现,使复杂的反应路径的高预测准确性高效的探索.

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科学领域:

  • 计算化学的计算化学
  • 材料科学 材料科学 材料科学
  • 化学工程是化学工程的重要组成部分.

背景情况:

  • 准确预测催化反应路径对于催化剂设计至关重要.
  • 第一原则计算虽然准确,但对于大规模选而言,计算成本昂贵.
  • 机器学习的原子间潜力 (MLIP) 提供了一种加速这些计算的方法.

研究的目的:

  • 介绍一个计算工作流程,CSCP-X,用于构建高度准确的MLIP.
  • 为了加速对复杂的催化反应的潜在能量表面的探索.
  • 为了实现预测催化剂选的亚化学精度.

主要方法:

  • 开发了用抽象技术 (CSCP-X) 增强的催化过程的合规采样工作流.
  • 与DFT相比,构建的MLIP具有亚化学精度 (∼0.03 eV).
  • 在各种金属催化剂上将CSCP-X应用于甲醇分解.

主要成果:

  • MLIPs实现了高计算效率的催化剂选的目标精度.
  • 仅需要多达两个代主动学习步骤,数据集增长不大.
  • 证明了对反应能量障碍的准确预测,并发现了替代反应路径.

结论:

  • CSCP-X 能够强大而高效地加速新型催化材料的发现.
  • 该方法实现了与基于物理的模型可比的机械可转移性.
  • CSCP-X是用于高吞吐量催化剂选和设计的强大工具.