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Title: Grafting metal complexes onto amorphous supports: from elementary steps to catalyst site populations via kernel regression

Abstract

We use transition state theory, kernel regression, and population balance modeling techniques to model the grafting of metal complexes onto amorphous catalyst supports.

Authors:
ORCiD logo [1]; ORCiD logo [1]; ORCiD logo [2];  [3]
  1. Department of Chemical Engineering, University of California, Santa Barbara, USA
  2. Department of Chemical Engineering, University of California, Santa Barbara, USA, Department of Chemistry & Biochemistry
  3. Department of Chemical & Biomolecular Engineering, University of Illinois at Urbana-Champaign, Urbana, USA, Department of Chemistry
Publication Date:
Sponsoring Org.:
USDOE
OSTI Identifier:
1575096
Grant/Contract Number:  
SC0019488; FG02-03ER15467; 1725797; 1605867
Resource Type:
Publisher's Accepted Manuscript
Journal Name:
Reaction Chemistry & Engineering
Additional Journal Information:
Journal Name: Reaction Chemistry & Engineering; Journal ID: ISSN 2058-9883
Publisher:
Royal Society of Chemistry (RSC)
Country of Publication:
United Kingdom
Language:
English

Citation Formats

Khan, Salman A., Vandervelden, Craig A., Scott, Susannah L., and Peters, Baron. Grafting metal complexes onto amorphous supports: from elementary steps to catalyst site populations via kernel regression. United Kingdom: N. p., 2020. Web. doi:10.1039/C9RE00357F.
Khan, Salman A., Vandervelden, Craig A., Scott, Susannah L., & Peters, Baron. Grafting metal complexes onto amorphous supports: from elementary steps to catalyst site populations via kernel regression. United Kingdom. doi:10.1039/C9RE00357F.
Khan, Salman A., Vandervelden, Craig A., Scott, Susannah L., and Peters, Baron. Wed . "Grafting metal complexes onto amorphous supports: from elementary steps to catalyst site populations via kernel regression". United Kingdom. doi:10.1039/C9RE00357F.
@article{osti_1575096,
title = {Grafting metal complexes onto amorphous supports: from elementary steps to catalyst site populations via kernel regression},
author = {Khan, Salman A. and Vandervelden, Craig A. and Scott, Susannah L. and Peters, Baron},
abstractNote = {We use transition state theory, kernel regression, and population balance modeling techniques to model the grafting of metal complexes onto amorphous catalyst supports.},
doi = {10.1039/C9RE00357F},
journal = {Reaction Chemistry & Engineering},
number = ,
volume = ,
place = {United Kingdom},
year = {2020},
month = {1}
}

Journal Article:
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