Assessment of Quantum Mechanical Methods for Copper and Iron Complexes by Photoelectron Spectroscopy

Applying Large Graph Neural Networks to Predict Transition Metal Complex Energies Using the tmQM_wB97MV Data Set

Machine learning (ML) methods have shown promise for discovering novel catalysts but are often restricted to specific chemical domains. Generalizable ML models require large and diverse training data sets, which exist for heterogeneous catalysis but not for homogeneous catalysis. The tmQM data set, which contains properties of 86,665 transition metal complexes calculated at the TPSSh/def2-SVP level of density functional theory (DFT), provided a promising training data set for homogeneous catalyst systems. However, we find that ML models trained on tmQM consistently underpredict the energies of a chemically distinct subset of the data. To address this, we present the tmQM_wB97MV data set, which filters out several structures in tmQM found to be missing hydrogens and recomputes the energies of all other structures at the ωB97M-V/def2-SVPD level of DFT. ML models trained on tmQM_wB97MV show no pattern of consistently incorrect predictions and much lower errors than those trained on tmQM. The ML models tested on tmQM_wB97MV were, from best to worst, GemNet-T > PaiNN ≈ SpinConv > SchNet. Performance consistently improves when using only neutral structures instead of the entire data set. However, while models saturate with only neutral structures, more data continue to improve the models when including charged species, indicating the importance of accurately capturing a range of oxidation states in future data generation and model development. Furthermore, a fine-tuning approach in which weights were initialized from models trained on OC20 led to drastic improvements in model performance, indicating transferability between ML strategies of heterogeneous and homogeneous systems.

Protocols for Understanding the Redox Behavior of Copper-Containing Systems

Suitability of single-reference density functional theory (DFT) methods for the calculation of redox potentials of copper-containing macrocycle complexes was confirmed by the use of T ₁ diagnostics along with a verification of negligible spin contamination or wave function instability. When examining the effect of improvement in the cc-pVnZ basis set series on calculated redox potentials, the results readily converged at the cc-pVTZ level. The all-electron Def2-TZVPP basis set is shown to be a suitable choice of a basis set for the calculation of redox potentials when utilizing a cc-pVTZ geometry. The best-performing model chemistries are determined to be the M06/polarizable continuum model (PCM); therefore, a scheme for redox potential calculations of copper macrocycles using either M06/cc-pVTZ with PCM solvation is proposed to reliably reproduce experimental trends.

Relative Populations and IR Spectra of Cu38 Cluster at Finite Temperature Based on DFT and Statistical Thermodynamics Calculations

The relative populations of Cu₃₈ isomers depend to a great extent on the temperature. Density functional theory and nanothermodynamics can be combined to compute the geometrical optimization of isomers and their spectroscopic properties in an approximate manner. In this article, we investigate entropy-driven isomer distributions of Cu₃₈ clusters and the effect of temperature on their IR spectra. An extensive, systematic global search is performed on the potential and free energy surfaces of Cu₃₈ using a two-stage strategy to identify the lowest-energy structure and its low-energy neighbors. The effects of temperature on the populations and IR spectra are considered via Boltzmann factors. The computed IR spectrum of each isomer is multiplied by its corresponding Boltzmann weight at finite temperature. Then, they are summed together to produce a final temperature-dependent, Boltzmann-weighted spectrum. Our results show that the disordered structure dominates at high temperatures and the overall Boltzmann-weighted spectrum is composed of a mixture of spectra from several individual isomers.

Phenol-Induced O-O Bond Cleavage in a Low-Spin Heme-Peroxo-Copper Complex: Implications for O2 Reduction in Heme-Copper Oxidases

This study evaluates the reaction of a biomimetic heme-peroxo-copper complex, {[(DCHIm)(F8)FeIII]-(O22-)-[CuII(AN)]}+ (1), with a phenolic substrate, involving a net H-atom abstraction to cleave the bridging peroxo O-O bond that produces FeIV═O, CuII-OH, and phenoxyl radical moieties, analogous to the chemistry carried out in heme-copper oxidases (HCOs). A 3D potential energy surface generated for this reaction reveals two possible reaction pathways: one involves nearly complete proton transfer (PT) from the phenol to the peroxo ligand before the barrier; the other involves O-O homolysis, where the phenol remains H-bonding to the peroxo OCu in the transition state (TS) and transfers the H+ after the barrier. In both mechanisms, electron transfer (ET) from phenol occurs after the PT (and after the barrier); therefore, only the interaction with the H+ is involved in lowering the O-O cleavage barrier. The relative barriers depend on covalency (which governs ET from Fe), and therefore vary with DFT functional. However, as these mechanisms differ by the amount of PT at the TS, kinetic isotope experiments were conducted to determine which mechanism is active. It is found that the phenolic proton exhibits a secondary kinetic isotope effect, consistent with the calculations for the H-bonded O-O homolysis mechanism. The consequences of these findings are discussed in relation to O-O cleavage in HCOs, supporting a model in which a peroxo intermediate serves as the active H+ acceptor, and both the H+ and e- required for O-O cleavage derive from the cross-linked Tyr residue present at the active site.

Asn47 and Phe114 modulate the inner sphere reorganization energies of type zero copper proteins

The geometric structures and electron transfer properties of type 1 Cu proteins are reasonably understood at the molecular level (E. I. Solomon and R. G. Hadt, Coord. Chem. Rev., 2011, 255, 774-789, J. J. Warren, K. M. Lancaster, J. H. Richards and H. B. Gray, J. Inorg. Biochem., 2012, 115, 119-126). Much understanding of type 1 copper electron transfer reactivity has come from site directed mutagenesis studies. For example, artificial "type zero" Cu-centres constructed in cupredoxin-azurin have showcased the capacity of outer-sphere hydrogen bonding networks to enhance Cu II/I electron transfer reactivity. In this paper, we have elaborated on earlier kinetics and electronic structural studies of type zero Cu by calculating the inner sphere reorganization energies of type 1, type 2, and type zero Cu proteins using density functional theory (DFT). Although the choice of density functionals for copper systems is not straightforward, we have benchmarked the density functionals against the recently reported ESI-PES data for two synthetic copper models (S. Niu, D.-L. Huang, P. D. Dau, H.-T. Liu, L.-S. Wang and T. J. Ichiye, Chem. Theory Comput., 2014, 10, 1283). For the Cu proteins, our calculations predict that changes in the coordination number upon metal reduction lead to large inner sphere reorganization energies for type 2 Cu sites, whereas retention in the coordination number is observed for type zero Cu sites. These variations in the coordination number are modulated by the outer-sphere coordinating residues Asn47 and Phe114, which are involved in hydrogen bonding with the Asp112 side chain.