Dehydrogenation Free Energy of Co2+(aq) from Density Functional Theory-Based Molecular Dynamics

Hybrid Functional and Plane Waves based Ab Initio Molecular Dynamics Study of the Aqueous Fe2+ /Fe3+ Redox Reaction

Kohn-Sham density functional theory and plane wave basis set based ab initio molecular dynamics (AIMD) simulation is a powerful tool for studying complex reactions in solutions, such as electron transfer (ET) reactions involving Fe²⁺ /Fe³⁺ ions in water. In most cases, such simulations are performed using density functionals at the level of Generalized Gradient Approximation (GGA). The challenge in modelling ET reactions is the poor quality of GGA functionals in predicting properties of such open-shell systems due to the inevitable self-interaction error (SIE). While hybrid functionals can minimize SIE, standard plane-wave based AIMD at that level of theory is typically 150 times slower than GGA for systems containing ∼100 atoms. Among several approaches reported to speed-up AIMD simulations with hybrid functionals, the noise-stabilized MD (NSMD) procedure, together with the use of localized orbitals to compute the required exchange integrals, is an attractive option. In this work, we demonstrate the application of the NSMD approach for studying the Fe²⁺ /Fe³⁺ redox reaction in water. It is shown here that long AIMD trajectories at the level of hybrid density functionals can be obtained using this approach. Redox properties of the aqueous Fe²⁺ /Fe³⁺ system computed from these simulations are compared with the available experimental data for validation.

Method to Construct Volcano Relations by Multiscale Modeling: Building Bridges between the Catalysis and Biosimulation Communities

Understanding the complex interactions of different building blocks within a sophisticated drug-delivery system (DDS), aimed at targeted transport of the drug to malignant cells, requires modeling techniques on different time and length scales. On the example of the anthracycline antibiotic doxorubicin (DOX), we investigate a potential DDS component, consisting of a gold nanoparticle and a short peptide sequence as carriers of DOX. The combination of atomistic molecular dynamics simulations and density functional theory calculations facilitates compiling a volcano plot, which allows deriving general conclusions on DDS constituents for chemotherapeutic agents within the class of anthracycline antibiotics: the nanoparticle and peptide carrier moieties need to be chosen in such a way that the anthracycline body of the drug is able to intercalate between both entities or between two (π-stacking) residues of the peptide. Using the popular volcano framework as a guideline, the present article connects the catalysis and biosimulation communities, thereby identifying a strategy to overcome the limiting volcano relation by tuning the coordination number of the drug in the DDS component.

Comparison of Penta and Tetra-pyridyl Cobalt-based Catalysts for Water Reduction: H2 Production Cycle, Solvent Response and Reduction Free Energy

Understanding water reduction towards H₂ generation is crucial to overcome today's renewable energy obstacles. Previous studies have shown the superior H₂ production performances of Cobalt based penta-pyridyl (CoaPPy) and tetra-pyridyl (CoaTPy) complexes in solution. We investigate H₂ production cycles of CoaPPy and CoaTPy complexes immersed in water solution by means of Ab-initio Molecular Dynamics and Density Functional Theory. We monitor dynamic properties of the systems, solvent response and structural changes occurring in the catalysts, by simulating all intermediate steps of the H₂ production cycle. Reduction free energies and reorganization energies are calculated. Our results show that, following the first electron injection, H₂ production proceeds with the singlet spin state. Following the first electron insertion, we observe a significant rearrangement of the hydrogen bonding network in the first solvation shell. The cobalt center turns out to be more accessible for the surrounding water molecules in the case of CoaTPy at all the intermediate steps, which explains its higher catalytic performance over CoaPPy. Following the first reduction reaction, a larger gain in reduction free energy is estimated for CoaTPy with respect to CoaPPy, with a difference of 0.14 eV, in line with the experiments. For the second reduction, instead, CoaPPy shows more negative reduction potential, by 0.41 eV.

How accurate are approximate quantum chemical methods at modelling solute-solvent interactions in solvated clusters?

In this paper, the performance of a wide range of DFT methods is assessed for the calculation of interaction energies of thermal clusters of a solute in water. Three different charge states (neutral, proton transfer transition state and zwitterion) of glycine were solvated by 1 to 40 water molecules as sampled from molecular dynamics simulations. While some ab initio composite methods that employ insufficiently large basis sets incurred significant errors even for a cluster containing only 5 water molecules relative to the W1X-2 benchmark, the DLPNO-CCSD(T)/CBS and DSD-PBEP86 (triple zeta basis set) levels of theory predicted very accurate interaction energies. These levels of theory were used to benchmark the performance of 16 density functionals from different rungs of Jacob's Ladder. Of the Rung 4 functionals examined, the ωB97M-V and ωB97X-V functionals stood out for predicting absolute interaction energies in 40-water clusters with mean absolute deviations (MAD) ∼4 kJ mol-1. The B3LYP-D3(BJ) functional performed exceptionally well with a MAD ∼1.7 kJ mol-1 and is the overall best performing method. Calculations of relative interaction energies allow for cancellation of systematic errors, including basis set truncation and superposition errors, and the ωB97M-V and B3LYP-D3(BJ) double zeta basis set calculations yielded relative interaction energies that are within ∼3 kJ mol-1 of the benchmark. The ONIOM approximation provides another strategy for accelerating the calculation of accurate absolute interaction energies provided that the calculations have converged with respect to the size of the "high-level-layer".

Computational Modeling of Cobalt-Based Water Oxidation: Current Status and Future Challenges

A lot of effort is nowadays put into the development of novel water oxidation catalysts. In this context, mechanistic studies are crucial in order to elucidate the reaction mechanisms governing this complex process, new design paradigms and strategies how to improve the stability and efficiency of those catalysts. This review is focused on recent theoretical mechanistic studies in the field of homogeneous cobalt-based water oxidation catalysts. In the first part, computational methodologies and protocols are summarized and evaluated on the basis of their applicability toward real catalytic or smaller model systems, whereby special emphasis is laid on the choice of an appropriate model system. In the second part, an overview of mechanistic studies is presented, from which conceptual guidelines are drawn on how to approach novel studies of catalysts and how to further develop the field of computational modeling of water oxidation reactions.