CASPT2 molecular geometries of Fe(<scp>ii</scp>) spin-crossover complexes

Finney, Brian A.; Chowdhury, Sabyasachi Roy; Kirkvold, Clara; Vlaisavljevich, Bess

doi:10.1039/d1cp04885f

Cited by 15 publications

(13 citation statements)

References 82 publications

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“…C 2 symmetry is imposed in the case of [Fe(bpy) 3 ] 2+ and no symmetry restrictions are applied in [Fe(mtz) 6 ] 2+ . The Fe–N distances for the LS and HS states in the relaxed scan minima are in good agreement with the (XMS-)CASPT2 fully optimized geometries by Finney et al 21 Further information about the relaxed scan can be found in the ESI †…”

Section: Thermal Relaxationsupporting

confidence: 84%

Quantum dynamics simulations of the thermal and light-induced high-spin to low-spin relaxation in Fe(bpy)₃ and Fe(mtz)₆

2022

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Section: Thermal Relaxationsupporting

confidence: 84%

Quantum dynamics simulations of the thermal and light-induced high-spin to low-spin relaxation in Fe(bpy)₃ and Fe(mtz)₆

2022

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“…Although CASPT2 (and NEVPT2) analytical gradients have been available for several years, [135–140] most studies currently employed structures obtained at the DFT level of theory or from crystallographic data. We are aware of only one systematic study on the performance of CASPT2 in the description of TM complex geometries [141] …”

Section: Methodsmentioning

confidence: 99%

“…We are aware of only one systematic study on the performance of CASPT2 in the description of TM complex geometries. [141]…”

Section: Multireference Configuration Interaction and Second-order Mu...mentioning

confidence: 99%

Ab Initio Methods in First‐Row Transition Metal Chemistry

Feldt

Phung

2022

Eur J Inorg Chem

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Molecules containing 3d transition metals (TMs) are usually associated with versatile reactivity, partly due to their complicated electronic structures involving multiple close‐lying spin states. An accurate description of different electronic states is notoriously difficult and still a challenge for computational methodologies. Density functional theory, although repeatedly shown to give less reliable results for near‐degeneracy problems, remains the workhorse to explore the reactivity of TM complexes. Ab initio wavefunction theory has been lagging behind due to its high computational cost. However, tremendous efforts have been put to improve their applicability over the past few years, particularly local coupled cluster and low‐scaling multireference methods. In this mini‐review, we highlight major advancements of these ab initio techniques and discuss their recent applications in the calculations of spin state energetics of first‐row TM complexes, ranging from spin crossover compounds and metalloproteins to biomimetic complexes capable of activating C−H bonds.

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“…Virtual high-throughput screening (VHTS) − and machine learning (ML)-accelerated chemical discovery − with approximate density functional theory (DFT) have started to address the combinatorial challenges − in discovering and designing functional molecules and materials. Despite the balanced trade-off in computational cost and accuracy, DFT can fail prominently − for promising materials, such as the chemical space of transition metal complexes (TMCs). TMCs may have strong multireference (MR) character due to near-degenerate orbitals, , which cannot be accurately described in DFT due to the single-reference (SR) nature of the noninteracting wave function .…”

Section: Introductionmentioning

confidence: 99%

Exploiting Ligand Additivity for Transferable Machine Learning of Multireference Character across Known Transition Metal Complex Ligands

Duan

Ladera

Liu

et al. 2022

J. Chem. Theory Comput.

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Accurate virtual high-throughput screening (VHTS) of transition metal complexes (TMCs) remains challenging due to the possibility of high multireference (MR) character that complicates property evaluation. We compute MR diagnostics for over 5,000 ligands present in previously synthesized octahedral mononuclear transition metal complexes in the Cambridge Structural Database (CSD). To accomplish this task, we introduce an iterative approach for consistent ligand charge assignment for ligands in the CSD. Across this set, we observe that the MR character correlates linearly with the inverse value of the averaged bond order over all bonds in the molecule. We then demonstrate that ligand additivity of the MR character holds in TMCs, which suggests that the TMC MR character can be inferred from the sum of the MR character of the ligands. Encouraged by this observation, we leverage ligand additivity and develop a ligand-derived machine learning representation to train neural networks to predict the MR character of TMCs from properties of the constituent ligands. This approach yields models with excellent performance and superior transferability to unseen ligand chemistry and compositions.

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CASPT2 molecular geometries of Fe(ii) spin-crossover complexes

Abstract: Using fully internally contracted (FIC)-CASPT2 analytical gradients, geometry optimizations of spin-crossover complexes are reported. This approach is tested on a series of Fe(II) complexes with different sizes, ranging from 13...

Cited by 15 publications

References 82 publications

Quantum dynamics simulations of the thermal and light-induced high-spin to low-spin relaxation in Fe(bpy)₃ and Fe(mtz)₆

Quantum dynamics simulations of the thermal and light-induced high-spin to low-spin relaxation in Fe(bpy)₃ and Fe(mtz)₆

Ab Initio Methods in First‐Row Transition Metal Chemistry

Exploiting Ligand Additivity for Transferable Machine Learning of Multireference Character across Known Transition Metal Complex Ligands

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CASPT2 molecular geometries of Fe(ii) spin-crossover complexes

Abstract: Using fully internally contracted (FIC)-CASPT2 analytical gradients, geometry optimizations of spin-crossover complexes are reported. This approach is tested on a series of Fe(II) complexes with different sizes, ranging from 13...

Cited by 15 publications

References 82 publications

Quantum dynamics simulations of the thermal and light-induced high-spin to low-spin relaxation in Fe(bpy)3 and Fe(mtz)6

Quantum dynamics simulations of the thermal and light-induced high-spin to low-spin relaxation in Fe(bpy)3 and Fe(mtz)6

Ab Initio Methods in First‐Row Transition Metal Chemistry

Exploiting Ligand Additivity for Transferable Machine Learning of Multireference Character across Known Transition Metal Complex Ligands

Contact Info

Product

Resources

About

Quantum dynamics simulations of the thermal and light-induced high-spin to low-spin relaxation in Fe(bpy)₃ and Fe(mtz)₆

Quantum dynamics simulations of the thermal and light-induced high-spin to low-spin relaxation in Fe(bpy)₃ and Fe(mtz)₆