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Systematic Generation and Screening ...

Wilmer, Christopher E.

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Systematic Generation and Screening of Hypothetical Metal-Organic Frameworks for Applications in Gas Storage and Separations.

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Systematic Generation and Screening of Hypothetical Metal-Organic Frameworks for Applications in Gas Storage and Separations./
作者:	Wilmer, Christopher E.
面頁冊數:	243 p.
附註:	Source: Dissertation Abstracts International, Volume: 75-01(E), Section: B.
Contained By:	Dissertation Abstracts International75-01B(E).
標題:	Engineering, Chemical. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3595775
ISBN:	9781303416873

Systematic Generation and Screening of Hypothetical Metal-Organic Frameworks for Applications in Gas Storage and Separations.
Wilmer, Christopher E.

Systematic Generation and Screening of Hypothetical Metal-Organic Frameworks for Applications in Gas Storage and Separations. - 243 p.

Source: Dissertation Abstracts International, Volume: 75-01(E), Section: B.

Thesis (Ph.D.)--Northwestern University, 2013.

Metal-organic frameworks (MOFs) are porous, crystalline materials that form from the self-assembly of modular molecular building blocks. MOFs are potentially useful for many gas storage and separations applications. However, there are a practically unlimited number of possible MOFs and it is often not clear which ones are optimal for a given application. This dissertation combines previously established molecular simulation techniques with a novel hypothetical MOF generation approach to rapidly explore the space of possible MOFs to find candidates for a variety of gas storage and separations applications, specifically natural gas storage in vehicles, separation of xenon from krypton, and carbon dioxide separation and capture. In addition to finding promising candidate MOFs for experimental synthesis, performing gas adsorption simulations on hundreds of thousands of hypothetical MOFs yielded a rich dataset, whose size was unprecedented in the MOF literature, that could be searched for structure-property relationships.

ISBN: 9781303416873Subjects--Topical Terms:

1018531
Engineering, Chemical.

Systematic Generation and Screening of Hypothetical Metal-Organic Frameworks for Applications in Gas Storage and Separations.
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245 1 0 $a Systematic Generation and Screening of Hypothetical Metal-Organic Frameworks for Applications in Gas Storage and Separations.
300 $a 243 p.
500 $a Source: Dissertation Abstracts International, Volume: 75-01(E), Section: B.
500 $a Advisers: Randall Q. Snurr; Linda J. Broadbelt.
502 $a Thesis (Ph.D.)--Northwestern University, 2013.
520 $a Metal-organic frameworks (MOFs) are porous, crystalline materials that form from the self-assembly of modular molecular building blocks. MOFs are potentially useful for many gas storage and separations applications. However, there are a practically unlimited number of possible MOFs and it is often not clear which ones are optimal for a given application. This dissertation combines previously established molecular simulation techniques with a novel hypothetical MOF generation approach to rapidly explore the space of possible MOFs to find candidates for a variety of gas storage and separations applications, specifically natural gas storage in vehicles, separation of xenon from krypton, and carbon dioxide separation and capture. In addition to finding promising candidate MOFs for experimental synthesis, performing gas adsorption simulations on hundreds of thousands of hypothetical MOFs yielded a rich dataset, whose size was unprecedented in the MOF literature, that could be searched for structure-property relationships.
520 $a This dissertation also describes the development of a novel partial charge estimation scheme, based on the charge equilibration approach of Rappe and Goddard, whose development was necessary to facilitate large-scale screening of MOFs where electrostatic interactions between the guest molecule and the host framework were important (e.g., CO2, H2, N 2).
520 $a A chapter is also devoted to the development of a new MOF, NU-125, that was investigated for its promise as an adsorbent for natural gas storage in vehicles based on structure-property relationships uncovered from the large-scale screening efforts.
520 $a Broadly, the work described in this dissertation lays the groundwork for applying advanced machine learning algorithms and data mining techniques, developed and applied widely in other fields, to the computational design of MOF materials.
590 $a School code: 0163.
650 4 $a Engineering, Chemical. $3 1018531
650 4 $a Chemistry, Inorganic. $3 517253
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