scholarly journals A Two Transition State Model for Radical−Molecule Reactions:  Applications to Isomeric Branching in the OH−Isoprene Reaction

2007 ◽  
Vol 111 (25) ◽  
pp. 5582-5592 ◽  
Author(s):  
Erin E. Greenwald ◽  
Simon W. North ◽  
Yuri Georgievskii ◽  
Stephen J. Klippenstein
Keyword(s):  
Transition State ◽  
State Model

ChemInform Abstract: Transition-State Model for Subtilisin-Catalyzed Transesterifications of Secondary Alcohols.

ChemInform ◽  
2010 ◽  
Vol 30 (31) ◽  
pp. no-no
Author(s):  
Tadashi Ema ◽  
Ryoichi Okada ◽  
Minoru Fukumoto ◽  
Masahito Jittani ◽  
Mikiko Ishida ◽  
...  
Keyword(s):  
Transition State ◽  
State Model ◽  
Secondary Alcohols

A Two Transition State Model for Radical−Molecule Reactions:  A Case Study of the Addition of OH to C2H4

2005 ◽  
Vol 109 (27) ◽  
pp. 6031-6044 ◽  
Author(s):  
Erin E. Greenwald ◽  
Simon W. North ◽  
Yuri Georgievskii ◽  
Stephen J. Klippenstein
Keyword(s):  
Transition State ◽  
State Model

scholarly journals Electron Transfer from Cytochromec2to the Reaction Center: A Transition State Model for Ionic Strength Effects Due to Neutral Mutations

Biochemistry ◽  
2009 ◽  
Vol 48 (48) ◽  
pp. 11390-11398 ◽  
Author(s):  
Edward C. Abresch ◽  
Xiao-Min Gong ◽  
Mark L. Paddock ◽  
Melvin Y. Okamura
Keyword(s):  
Electron Transfer ◽  
Ionic Strength ◽  
Transition State ◽  
Reaction Center ◽  
State Model ◽  
Neutral Mutations

scholarly journals Quantum-Mechanical Transition-State Model Combined with Machine Learning Provides Catalyst Design Features for Selective Cr Olefin Oligomerization

2020 ◽  
Author(s):  
Steven Maley ◽  
Doo-Hyun Kwon ◽  
Nick Rollins ◽  
Johnathan Stanley ◽  
Orson Sydora ◽  
...  
Keyword(s):  
Machine Learning ◽  
Random Forest ◽  
Transition State ◽  
Data Science ◽  
Catalyst Design ◽  
Ethylene Oligomerization ◽  
State Model ◽  
General Strategy ◽  
Design Features ◽  
Molecular Catalyst

The use of data science tools to provide the emergence of nontrivial chemical features for catalyst design is an important goal in catalysis science. Additionally, there is currently no general strategy for computational homogeneous, molecular catalyst design. Here we report the unique combination of an experimentally verified DFT-transition-state model with a random forest machine learning model in a campaign to design new molecular Cr phosphine imine (Cr(P,N)) catalysts for selective ethylene oligomerization, specifically to increase 1-octene selectivity. This involved the calculation of 1-hexene:1- octene transition-state selectivity for 105 (P,N) ligands and the harvesting of 14 descriptors, which were then used to build a random forest regression model. This model showed the emergence of several key design features, such as Cr–N distance, Cr–α distance, and Cr distance out of pocket, which were then used to rapidly design a new generation of Cr(P,N) catalyst ligands that are predicted to give >95% selectivity for 1-octene<br>

Transition State Model for Grain Boundary Motion During Ion Bombardment

1988 ◽  
Vol 100 ◽  
Author(s):  
Harry A. Atwater ◽  
Carl V. Thompsonm ◽  
Henry I. Smith
Keyword(s):  
Grain Boundary ◽  
Transition State ◽  
Boundary Migration ◽  
Ion Bombardment ◽  
State Model ◽  
Boundary Motion ◽  
Frenkel Defect ◽  
Thermally Induced ◽  
Two Phases ◽  
Grain Boundary Motion

ABSTRACTIon bombardment of polycrystalline Ge, Si, and Au films leads to rates of grain boundary motion that greatly exceed rates of thermally-induced motion at the same temperature and which exhibit a weak temperature dependence. The enhanced migration rate is proportional to the rate of energy deposition in nuclear collisions at or very near the grain boundary. Experimental work is reviewed, and a transition state model is presented which accounts for the observed kinetics of grain boundary migration during bombardment. This model suggests that the rate limiting step in grain boundary motion may be thermally-induced migration of a bombardment-generated defect across the boundary. Also, the ratio of atomic jumps at grain boundaries to the local collision-induced Frenkel defect generation rate is shown to be characteristic of each material, but independent of ion mass and ion flux. The model is extended to the motion of an interface between two phases, and applications to crystallization during ion bombardment are discussed.

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