课题基金 / 基金详情

Variational Methods for Materials and Imaging Sciences

Variational Methods for Materials and Imaging Sciences
材料和成像科学的变分方法
批准号:
1411646
负责人:
Irene Fonseca
金额:
$122.23万
依托单位:
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2014
资助国家:
美国
项目状态:
已结题
起止时间:
2014-09-01 至 2020-08-31

项目摘要

项目成果

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中文摘要
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英文摘要
The objectives of this project are the identification and pursuit of emerging areas of applied analysis, motivated by contemporary issues in imaging and materials science at the core of advances in high-end technology and of national scientific importance. The two main topics of the project are(1) the mathematical study of modern semiconductors and nano structures, of pivotal importance in microelectric and optoelectronic technologies, such as reflective or anti-reflective coatings for optics, the fabrication of layers of insulators and semiconductors for integrated circuits, quantum well lasers, and(2) the analytical investigation of image segmentation and inpainting and recolorization for color images, fundamental to the advance of computer vision, medical imaging, film restoration, and scanning probe microscopy. Postdocs and graduate students are trained in the course of the project. Common features of the projects include the treatment of energies that involve terms of different dimensionality. These often exhibit a large range of length and time scales, higher order derivatives, and discontinuous underlying fields. Such features prevent the use of well understood functional analytic frameworks, they escape traditional mathematical theories, and they require state-of-the-art techniques, creative ideas, and the introduction of innovative mathematical tools. The investigator and her collaborators use new and recently developed methods and a deep articulation of ideas in the calculus of variations, geometric measure theory, and nonlinear partial differential equations, to address problems that include in topic (1) epitaxy and the formation of quantum dots, the onset and propagation of dislocations, homogenization of composite materials, and in topic (2) signal denoising and detexturing, dejittering, inpainting, and recolorization. These topics offer new opportunities for the integration of applied analysis in research and in the education of advanced graduate students and postdoctoral fellows, thus allowing for the training of a new generation of applied analysts at the forefront of contemporary mathematics as it interfaces with materials and imaging sciences.
期刊论文(4)
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科研奖励(0)
会议论文
DOI: 10.1137/20m1325654
发表时间: 2020-03
期刊: SIAM J. Math. Anal.
影响因子: --
作者: [I. Fonseca;Janusz Ginster;Stephan Wojtowytsch]
通讯作者: I. Fonseca;Janusz Ginster;Stephan Wojtowytsch
DOI: 10.1137/20m1341222
发表时间: 2020-05
期刊: SIAM J. Math. Anal.
影响因子: --
作者: [Rita Ferreira;I. Fonseca;R. Venkatraman]
通讯作者: Rita Ferreira;I. Fonseca;R. Venkatraman
ANISOTROPIC SURFACE TENSIONS FOR PHASE TRANSITIONS IN PERIODIC MEDIA
周期性介质中相变的各向异性表面张力
DOI: 10.1007/s00526-022-02216-5
发表时间: 2022
期刊: Calculus of variations and partial differential equations
影响因子: 2.1
作者: [CHOKSI, R., FONSECA, I., LIN, J., VENKATRAMAN, R.]
通讯作者: VENKATRAMAN, R.
Surface evolution of elastically stressed films
弹性应力薄膜的表面演化
DOI: 10.4171/mag/6
发表时间: 2021
期刊: Journal of the European Mathematical Society
影响因子: 2.6
作者: [Fonseca, I., Leoni, G.]
通讯作者: Leoni, G.
Variational Methods for Materials and Imaging
  • 批准号:
    2205627
  • 项目类别:
    Standard Grant
  • 资助金额:
    $55.0万
  • 财政年份:
    2022
  • 负责人:
    Irene Fonseca
  • 依托单位:
Mathematics of Microstructure in Origami, Robotics, and Electrochemistry
  • 批准号:
    2108784
  • 项目类别:
    Standard Grant
  • 资助金额:
    $58.24万
  • 财政年份:
    2021
  • 负责人:
    Irene Fonseca
  • 依托单位:
Variational Methods for Materials Science and Mathematical Imaging
  • 批准号:
    1906238
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $68.42万
  • 财政年份:
    2019
  • 负责人:
    Irene Fonseca
  • 依托单位:
Topics in Applied Nonlinear Analysis: Recent Advances and New Trends
  • 批准号:
    1601475
  • 项目类别:
    Standard Grant
  • 资助金额:
    $3.16万
  • 财政年份:
    2016
  • 负责人:
    Irene Fonseca
  • 依托单位:
国内基金
海外基金
Computational Methods for Analyzing Toponome Data