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

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

54
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...
54

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

Boosting the immune response and protective efficacy of inactivated PRV vaccine using cGAMP as a mucosal adjuvant.

BMC veterinary research·2026
Same author

Mapping neutralizing epitopes and developing protective chimeric antibodies against porcine epidemic diarrhea virus infection.

International journal of biological macromolecules·2026
Same author

Efficacy and safety of toripalimab in combination with cetuximab in patients with recurrent or metastatic head and neck squamous cell carcinoma (R/M HNSCC): a phase 1b/2 study.

Signal transduction and targeted therapy·2026
Same author

Multimodal deep-learning optimization of chiroptical properties in all-inorganic perovskite-coated TiO<sub>2</sub> nanohelices and inverse-design transfer to organic chiral luminophores.

Nature communications·2026
Same author

Interpretable machine learning model for predicting operative difficulty in robotic total mesorectal excision for mid-low rectal cancer.

Journal of robotic surgery·2026
Same author

Targeting VEGF signaling and stromal remodeling enhances chemoimmunotherapy efficacy in esophageal cancer.

Journal for immunotherapy of cancer·2026
Same journal

Long-term stabilization of intensity-difference squeezing from four-wave mixing in rubidium vapor.

Optics express·2026
Same journal

Robust 3D topography measurement of large-range high-aspect-ratio structures based on dual-domain statistical filtering in SD-OCT.

Optics express·2026
Same journal

Broadband transmissive terahertz metasurface for simultaneous quad-mode OAM multiplexing.

Optics express·2026
Same journal

Leveraging two-dimensional materials for high-sensitivity optical sensors: quasi-bound states in the continuum within hybrid metasurfaces.

Optics express·2026
Same journal

Resolution investigation for dual-spherical-wave optical scanning holographic microscopy: methods and performance.

Optics express·2026
Same journal

Robustness of parallel subnetwork-filtered diffractive deep neural networks.

Optics express·2026
查看所有相关文章

相关实验视频

Updated: Jul 1, 2025

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
11:53

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm

Published on: December 9, 2012

13.0K

使用NSGA-II进行多目标和多解决方案源面罩优化,以实现更直接的过程窗口增强.

Qingyan Zhang, Liu Junbo, Haifeng Sun

    Optics express
    |March 5, 2024
    PubMed
    概括
    此摘要是机器生成的。

    这项研究介绍了NSGA-SMO,这是一种新方法,用于源和面罩优化 (SMO) 在光刻法. 它增强了工艺窗口 (PW) 的性能,提高了 lithography 的稳定性和图像质量,用于高级关键维度 (CD).

    更多相关视频

    A Workflow for Lipid Nanoparticle LNP Formulation Optimization using Designed Mixture-Process Experiments and Self-Validated Ensemble Models SVEM
    13:54

    A Workflow for Lipid Nanoparticle LNP Formulation Optimization using Designed Mixture-Process Experiments and Self-Validated Ensemble Models SVEM

    Published on: August 18, 2023

    4.5K
    Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique
    04:48

    Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

    Published on: July 5, 2024

    399

    相关实验视频

    Last Updated: Jul 1, 2025

    Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
    11:53

    Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm

    Published on: December 9, 2012

    13.0K
    A Workflow for Lipid Nanoparticle LNP Formulation Optimization using Designed Mixture-Process Experiments and Self-Validated Ensemble Models SVEM
    13:54

    A Workflow for Lipid Nanoparticle LNP Formulation Optimization using Designed Mixture-Process Experiments and Self-Validated Ensemble Models SVEM

    Published on: August 18, 2023

    4.5K
    Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique
    04:48

    Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

    Published on: July 5, 2024

    399

    科学领域:

    • 半导体制造业 半导体制造业
    • 光学工程是指光学工程.
    • 计算式 lithography 的使用方法.

    背景情况:

    • 源和面具优化 (SMO) 对于光刻画的分辨率增强至关重要,因为临界尺寸 (CD) 缩小.
    • 传统的SMO方法专注于对焦成像质量,忽视了处理窗口 (PW),其中包括对焦深度 (DOF) 和曝光度 (EL),这对于石版强度至关重要.
    • 对基于梯度的SMO算法来说,评估PW是计算密集且具有挑战性的.

    研究的目的:

    • 开发一种新的SMO方法,直接优化流程窗口 (PW) 的性能.
    • 通过考虑石版工艺的变化来提高SMO的稳定性,从而产生先进技术节点.
    • 为了保持高焦点的图像质量,同时改善光刻工艺边缘.

    主要方法:

    • 提出了一种新的过程窗口增强SMO方法,称为NSGA-SMO,使用非主导排序遗传算法II (NSGA-II).
    • 采用了变量刻字模型 (VLIM),这是一个快速焦点变化的空中图像模型,用于直接PW优化.
    • 实施了多目标优化方法,以平衡对焦成像质量和PW性能.

    主要成果:

    • 与传统的多目标SMO相比,NSGA-SMO在焦点深度 (DOF) 和曝光度 (EL) 中表现出显著的改善.
    • 模拟显示,对于典型模式,DOF和EL的改善超过20%.
    • 对于复杂的模式,NSGA-SMO的结果高达单一目标SMO的四倍.

    结论:

    • 拟议的NSGA-SMO方法有效地优化了光刻光学中的工艺窗 (PW) 性能.
    • 这种方法提高了光刻工艺的稳定性,对于高级关键维度 (CD) 至关重要.
    • 在大批量制造业中,NSGA-SMO为改善成像质量和工艺利提供了可行的解决方案.