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Engineering Models of Permeation in Mixed Matrix Membranes

Engineering Models of Permeation in Mixed Matrix Membranes
混合基质膜渗透的工程模型
批准号:
DP150101996
负责人:
Prof Suresh Bhatia
金额:
$27.16万
依托单位国家:
澳大利亚
项目类别:
Discovery Projects
财政年份:
2015
资助国家:
澳大利亚
项目状态:
已结题
起止时间:
2015-01-01 至 2017-12-31

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中文摘要
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英文摘要
This project aims to develop next generation models of permeation in mixed matrix membranes by targeting the effects of isotherm nonlinearity, and its interplay with filler particle size and its distribution, and thereby provide the platform for achieving breakthroughs in separation processes based on such membranes. With this platform, improved performance of mixed matrix membranes for key industrially important separations is expected to be achieved, using novel filler/polymer combinations and by developing a broad, widely applicable, protocol for the tailoring of their interface. These advances are anticipated not only to transform the ways in such membranes are designed and optimised, but also to apply to transport in dispersion-based composites in general.
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Fluid Transport in Materials of Nanoscale Dimensions
  • 批准号:
    DP210101698
  • 项目类别:
    Discovery Projects
  • 资助金额:
    $16.88万
  • 财政年份:
    2021
  • 负责人:
    Prof Suresh Bhatia
  • 依托单位:
Interfacial Barriers to Transport in Nanomaterials
  • 批准号:
    DP150101824
  • 项目类别:
    Discovery Projects
  • 资助金额:
    $37.63万
  • 财政年份:
    2015
  • 负责人:
    Prof Suresh Bhatia
  • 依托单位:
Structural modelling of silicon carbide-derived microporous carbon and its application in carbon dioxide capture from moist gases
  • 批准号:
    DP120101480
  • 项目类别:
    Discovery Projects
  • 资助金额:
    $23.6万
  • 财政年份:
    2012
  • 负责人:
    Prof Suresh Bhatia
  • 依托单位:
Friction-based modelling of the dynamics of nanoconfined fluid mixtures
  • 批准号:
    DP1092437
  • 项目类别:
    Discovery Projects
  • 资助金额:
    $71.6万
  • 财政年份:
    2010
  • 负责人:
    Prof Suresh Bhatia
  • 依托单位:
国内基金
海外基金
Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis
新型手性NAD(P)H Models合成及生化模拟