scholarly journals The Generation of the Oxidant Agent of a Mononuclear Nonheme Fe(II) Biomimetic Complex by Oxidative Decarboxylation. A DFT Investigation

Molecules ◽  
2020 ◽  
Vol 25 (2) ◽  
pp. 328
Author(s):  
Angela Parise ◽  
Maria Costanza Muraca ◽  
Nino Russo ◽  
Marirosa Toscano ◽  
Tiziana Marino

The oxidative decarboxylation of the iron(II) α-hydroxy acid (mandelic acid) complex model, biomimetic of Rieske dioxygenase, has been investigated at the density functional level. The explored mechanism sheds light on the role of the α-hydroxyl group on the dioxygen activation. The potential energy surfaces have been explored in different electronic spin states. The rate-determining step of the process is the proton transfer. The oxidative decarboxylation preferentially takes place on the quintet state.

2010 ◽  
Vol 09 (01) ◽  
pp. 233-247 ◽  
Author(s):  
JIAN XU ◽  
HUA-QING YANG ◽  
SONG QIN ◽  
CHANG-WEI HU

The reaction mechanism for methane hydroxylation catalyzed by mimic methane monooxygenase (MMO) with bis(μ-oxo)dimanganese core has been investigated on the septet and nonet potential energy surfaces by hybrid density functional method B3LYP. The key reactive compound Q of MMO was modeled by trans- (H2CNH)(COOH) Mn(μ-O)2(μ-HCOO)2Mn(H2CNH)(COOH) . The ground state of Q is located on the septet state, which has a diamond-core structure with two Mn(IV) atoms. It is shown that the reaction proceeds via a radical-rebound mechanism, in which the step of C–H cleavage is the rate-determining step both in the gas phase and solution. Furthermore, the reaction may proceed more easily as the polarity of solution is larger. On the other hand, the kinetic isotope effects (KIEs) for H atom abstraction from methane are taken into account on the basis of transition state theory with Wigner tunneling corrections. The mimic MMO with bis(μ-oxo)dimanganese core might be an effective mimic catalyst for methane hydroxylation.


2020 ◽  
Author(s):  
Justin S. Smith ◽  
Roman Zubatyuk ◽  
Benjamin T. Nebgen ◽  
Nicholas Lubbers ◽  
Kipton Barros ◽  
...  

<p>Maximum diversification of data is a central theme in building generalized and accurate machine learning (ML) models. In chemistry, ML has been used to develop models for predicting molecular properties, for example quantum mechanics (QM) calculated potential energy surfaces and atomic charge models. The ANI-1x and ANI-1ccx ML-based eneral-purpose potentials for organic molecules were developed through active learning; an automated data diversification process. Here, we describe the ANI-1x and ANI-1ccx data sets. To demonstrate data set diversity, we visualize them with a dimensionality reduction scheme, and contrast against existing data sets. The ANI-1x data set contains multiple QM properties from 5M density functional theory calculations, while the ANI-1ccx data set contains 500k data points obtained with an accurate CCSD(T)/CBS extrapolation. Approximately 14 million CPU core-hours were expended to generate this data. Multiple QM properties from density functional theory and coupled cluster are provided: energies, atomic forces, multipole moments, atomic charges, and more. We provide this data to the community to aid research and development of ML models for chemistry.</p>


2021 ◽  
Author(s):  
Dianwei Hou ◽  
Christopher Heard

Unbiased density functional global optimisation calculations, followed by kinetic Monte Carlo simulations are used to enumerate the potential energy surfaces for migration of noble metals Pt and Au inside the pore system of siliceous zeolite LTA. The effects of reducing adsorbates CO and H2 are determined. It is found that the two metals differ significantly in the strength and type of interaction with the framework, with strong, framework breaking interactions between Pt and and the zeolite, but only weak dispersive interactions between Au and the zeolite. Adsorbates are found to dramatically interfere with Pt-framework binding, leading to poorer atom-trapping, enhanced metal migration and faster equilibration.


2013 ◽  
Vol 446-447 ◽  
pp. 168-171
Author(s):  
Hong Fei Liu ◽  
Xin Min Min ◽  
Hai Xia Yang

The decarbonylation of acetaldehyde assisted by Ni+2, which was selected as a representative system of transition metal ions assisted decarbonylation of acetaldehyde, has been investigated using density functional theory (B3LYP) in conjunction with the 6-31+G** basis sets in C,H,O atoms and Lanl2dz basis sets in Ni atom The geometries and energies of the reactants, intermediates, products and transition states relevant to the reaction were located on the triplet ground potential energy surfaces of [Ni, O, C2,H4]+2. Our calculations indicate the decarbonylation of acetaldehyde takes place through four steps, that is, encounter complexation, CC activation, aldehyde H-shift and nonreactive dissociation, it is that CC activation by Ni+2that lead to the decarbonylation of acetaldehyde.


2012 ◽  
Vol 90 (8) ◽  
pp. 708-715 ◽  
Author(s):  
Yuyang Zhao ◽  
Jing Bai ◽  
Chenxi Zhang ◽  
Chen Gong ◽  
Xiaomin Sun

Density functional theory (DFT) was used to study the β-myrcene ozonolysis reaction. The reactants, intermediates, transition states, and products were optimized at the MPWB1K/6–31G(d,p) level. The single-point energies were performed at the MPWB1K/6–311+G(3df,2p) level. The profiles of the potential energy surfaces were constructed and the rate constants of the reaction steps were analyzed. The possible reaction mechanisms for the ozonolysis intermediates in real atmosphere are also discussed. Based on quantum chemistry information, the rate constants were calculated using Rice–Ramsperger–Kassel–Marcus (RRKM) theory and the canonical variational transition-state theory (CVT) with small curvature tunneling effect (SCT). Arrhenius equations of rate constants over the temperature range of 200–800 K are provided, and the lifetimes of the reaction species in the troposphere were estimated according to rate constants.


2009 ◽  
Vol 1219 ◽  
Author(s):  
Jyoti Singh ◽  
Subhash Chandra Singh ◽  
Narsingh Bahadur Singh

AbstractThis work is devoted to a study of the conformational properties of alanine dipeptide. We have studied potential energy surfaces of alanine dipeptide molecule using density functional theoretical approach with 6-311G basis set. For this purpose potential energies of this molecule are calculated as a function of Ramachandran angles φ and ψ, which are important factors for the characterizations of polypeptide chains. These degrees of freedoms φ and ψ are important for the characterization of protein folding systems. Stable conformations, energy barriers and reaction coordinates of this important dipeptide molecule are calculated. Energy required for the transition of one conformation into other are also discussed.


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