Density functional predictions for metal and ligand nuclear shielding constants in diamagnetic closed-shell first-row transition-metal complexes

2000 ◽  
Vol 2 (2) ◽  
pp. 187-194 ◽  
Author(s):  
Philip J. Wilson ◽  
Roger D. Amos ◽  
Nicholas C. Handy
Keyword(s):  
Transition Metal ◽  
Metal Complexes ◽  
Transition Metal Complexes ◽  
Density Functional ◽  
Closed Shell ◽  
Shielding Constants ◽  
Nuclear Shielding

scholarly journals Relativistic Frozen Density Embedding calculations of solvent effects on the NMR shielding constants of transition metal nuclei.

2021 ◽  
Author(s):  
Malgorzata Olejniczak ◽  
Andrej Antušek ◽  
Michal Jaszunski
Keyword(s):  
Transition Metal ◽  
Metal Complexes ◽  
Transition Metal Complexes ◽  
Solvent Effects ◽  
Density Functional ◽  
Functional Theory ◽  
Freeze And Thaw ◽  
Shielding Constants ◽  
Solvent Shifts ◽  
Solvent Molecules

Nuclear Magnetic Resonance (NMR) shielding constants of transition metals in solvated complexes are computed at the relativistic density functional theory (DFT) level. The solvent effects evaluated with subsystem-DFT approaches are compared with the reference solvent shifts predicted from supermolecular calculations. Two subsystem-DFT approaches are analyzed – in the standard frozen density embedding (FDE) scheme the transition metal complexes are embedded in an environment of solvent molecules whose density is kept frozen, in the second approach the densities of the complex and of its environment are relaxed in the “freeze-and-thaw” procedure. The latter approach improves the description of the solvent effects in most cases, nevertheless the FDE deficiencies are rather large in some cases. Keywords — Frozen Density Embedding, NMR shielding constant, solvent shifts, transition-metal complexes

scholarly journals Enumeration of de novo Inorganic Complexes for Chemical Discovery and Machine Learning

2019 ◽  
Author(s):  
Stefan Gugler ◽  
Jon Paul Janet ◽  
Heather Kulik
Keyword(s):  
Transition Metal ◽  
Metal Complexes ◽  
Transition Metal Complexes ◽  
Density Functional ◽  
De Novo ◽  
Functional Materials ◽  
Closed Shell ◽  
Ligand Field ◽  
Structure Property ◽  
Computational Screening

<p>Despite being attractive targets for functional materials, the discovery of transition metal complexes with high-throughput computational screening is challenged by the amount of feasible coordination numbers, spin states, or oxidation states and the potentially large sizes of ligands. To overcome these limitations, we take inspiration from organic chemistry where full enumeration of neutral, closed shell molecules under the constraint of size has enriched discovery efforts. We design monodentate and bidentate ligands from scratch for the construction of mononuclear, octahedral transition metal complexes with up to 13 heavy atoms (i.e., metal, C, N, O, P, or S). From > 11,000 theoretical ligands, we develop a heuristic score for ranking a chemically feasible 2,500 ligand subset, only 71 of which were previously included in common organic molecule databases. We characterize the top 20% of scored ligands with density functional theory (DFT) in an octahedral homoleptic ligand database (OHLDB). The OHLDB contains i) the geometry optimized structures of 1,250 homoleptic octahedral complexes obtained from the enumerated pool of ligands and an open-shell transition metal (M(II)/M(III), M = Cr, Mn, Fe, or Co), and ii) the resulting high-spin/low-spin adiabatic electronic energies (<b>Δ</b><i>E</i><sub>H-L</sub>) obtained with hybrid DFT. Over the OHLDB, we observe structure–property (i.e., <b>Δ</b><i>E</i><sub>H-L</sub>) relationships different from those expected on the basis of ligand field arguments or from our prior data sets. Finally, we demonstrate how incorporating OHLDB data into artificial neural network (ANN) training improves ANN out-of-sample performance on much larger transition metal complexes.</p>

scholarly journals Enumeration of de novo Inorganic Complexes for Chemical Discovery and Machine Learning

2019 ◽  
Author(s):  
Stefan Gugler ◽  
Jon Paul Janet ◽  
Heather Kulik
Keyword(s):  
Transition Metal ◽  
Metal Complexes ◽  
Transition Metal Complexes ◽  
Density Functional ◽  
De Novo ◽  
Functional Materials ◽  
Closed Shell ◽  
Ligand Field ◽  
Structure Property ◽  
Computational Screening

<p>Despite being attractive targets for functional materials, the discovery of transition metal complexes with high-throughput computational screening is challenged by the amount of feasible coordination numbers, spin states, or oxidation states and the potentially large sizes of ligands. To overcome these limitations, we take inspiration from organic chemistry where full enumeration of neutral, closed shell molecules under the constraint of size has enriched discovery efforts. We design monodentate and bidentate ligands from scratch for the construction of mononuclear, octahedral transition metal complexes with up to 13 heavy atoms (i.e., metal, C, N, O, P, or S). From > 11,000 theoretical ligands, we develop a heuristic score for ranking a chemically feasible 2,500 ligand subset, only 71 of which were previously included in common organic molecule databases. We characterize the top 20% of scored ligands with density functional theory (DFT) in an octahedral homoleptic ligand database (OHLDB). The OHLDB contains i) the geometry optimized structures of 1,250 homoleptic octahedral complexes obtained from the enumerated pool of ligands and an open-shell transition metal (M(II)/M(III), M = Cr, Mn, Fe, or Co), and ii) the resulting high-spin/low-spin adiabatic electronic energies (<b>Δ</b><i>E</i><sub>H-L</sub>) obtained with hybrid DFT. Over the OHLDB, we observe structure–property (i.e., <b>Δ</b><i>E</i><sub>H-L</sub>) relationships different from those expected on the basis of ligand field arguments or from our prior data sets. Finally, we demonstrate how incorporating OHLDB data into artificial neural network (ANN) training improves ANN out-of-sample performance on much larger transition metal complexes.</p>

Density Functional Calculations of EPR Parameter g Tensors of Some Transition Metal Complexes

2011 ◽  
Vol 2 (2) ◽  
pp. 139-141
Author(s):  
Vinita Prajapati ◽  
◽  
P.L.Verma P.L.Verma ◽  
Dhirendra Prajapati ◽  
B.K.Gupta B.K.Gupta
Keyword(s):  
Transition Metal ◽  
Metal Complexes ◽  
Transition Metal Complexes ◽  
Density Functional Calculations ◽  
Density Functional

scholarly journals 1,3,5-Triaza-7-Phosphaadamantane (PTA) as a 31P NMR Probe for Organometallic Transition Metal Complexes in Solution

Molecules ◽  
2021 ◽  
Vol 26 (5) ◽  
pp. 1390 ◽  
Author(s):  
Ilya G. Shenderovich
Keyword(s):  
Chemical Shift ◽  
Transition Metal ◽  
Metal Complexes ◽  
Transition Metal Complexes ◽  
Density Functional ◽  
Molecular Structures ◽  
Basis Sets ◽  
Functional Theory ◽  
Non Covalent Interactions ◽  
Covalent Interactions

Due to the rigid structure of 1,3,5-triaza-7-phosphaadamantane (PTA), its 31P chemical shift solely depends on non-covalent interactions in which the molecule is involved. The maximum range of change caused by the most common of these, hydrogen bonding, is only 6 ppm, because the active site is one of the PTA nitrogen atoms. In contrast, when the PTA phosphorus atom is coordinated to a metal, the range of change exceeds 100 ppm. This feature can be used to support or reject specific structural models of organometallic transition metal complexes in solution by comparing the experimental and Density Functional Theory (DFT) calculated values of this 31P chemical shift. This approach has been tested on a variety of the metals of groups 8–12 and molecular structures. General recommendations for appropriate basis sets are reported.

CO2 reduction catalysis by tunable square-planar transition-metal complexes: a theoretical investigation using nitrogen-substituted carbon nanotube models

2017 ◽  
Vol 19 (43) ◽  
pp. 29068-29076 ◽  
Author(s):  
Yu-Te Chan ◽  
Ming-Kang Tsai
Keyword(s):  
Density Functional Theory ◽  
Carbon Nanotube ◽  
Transition Metal ◽  
Metal Complexes ◽  
Transition Metal Complexes ◽  
Density Functional ◽  
Co2 Reduction ◽  
Functional Theory ◽  
Square Planar ◽  
Planar Transition

The CO2 reduction capabilities of transition-metal-chelated nitrogen-substituted carbon nanotube models (TM-4N2v-CNT, TM = Fe, Ru, Os, Co, Rh, Ir, Ni, Pt or Cu) are characterized by density functional theory.

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