MARC보기
LDR02202nam u200445 4500
001000000421103
00520190215165037
008181129s2018 |||||||||||||||||c||eng d
020 ▼a 9780438031500
035 ▼a (MiAaPQ)AAI10809155
035 ▼a (MiAaPQ)umn:19108
040 ▼a MiAaPQ ▼c MiAaPQ ▼d 247004
0820 ▼a 660
1001 ▼a Gupta, Udit.
24510 ▼a Microkinetic Modeling of Complex Reaction Networks using Automated Network Generation.
260 ▼a [S.l.]: ▼b University of Minnesota., ▼c 2018.
260 1 ▼a Ann Arbor: ▼b ProQuest Dissertations & Theses, ▼c 2018.
300 ▼a 211 p.
500 ▼a Source: Dissertation Abstracts International, Volume: 79-10(E), Section: B.
500 ▼a Advisers: Prodromos Daoutidis
5021 ▼a Thesis (Ph.D.)--University of Minnesota, 2018.
520 ▼a Complex reaction networks are found in a variety of engineered and natural chemical systems ranging from petroleum processing to atmospheric chemistry and including biomass conversion, materials synthesis, metabolism, and biological degradation
520 ▼a This research presents methods, computational tools, and applications to address the two challenges that emerge in the development of microkinetic models of complex reaction networks in the context of chemical and biochemical conversion---(a) id
520 ▼a In this context, this thesis presents methods to address the computational challenges in developing microkinetic models for complex reaction networks. Rule Input Network Generator (RING), a network generation computational tool, is used for the
590 ▼a School code: 0130.
650 4 ▼a Chemical engineering.
650 4 ▼a Applied mathematics.
650 4 ▼a Bioengineering.
690 ▼a 0542
690 ▼a 0364
690 ▼a 0202
71020 ▼a University of Minnesota. ▼b Chemical Engineering.
7730 ▼t Dissertation Abstracts International ▼g 79-10B(E).
773 ▼t Dissertation Abstract International
790 ▼a 0130
791 ▼a Ph.D.
792 ▼a 2018
793 ▼a English
85640 ▼u http://www.riss.kr/pdu/ddodLink.do?id=T14997859 ▼n KERIS ▼z 이 자료의 원문은 한국교육학술정보원에서 제공합니다.
980 ▼a 201812 ▼f 2019
990 ▼a ***1012033