DFT-based Theoretical Simulations for Photocatalytic Applications Using TiO2

TiO2 has been shown to be a potential candidate for photoinitiated processes, such as dye sensitized solar cells and water splitting in production of H2. The large band gap of TiO2 can be reduced by functionalizing the oxide by adsorbing dye molecules and/or water reduction/oxidation catalysts, by metal/nonmetal doping, and by mixing with another oxide. Due to these methods, several different TiO2‐based complexes can be constructed having different geometries, electronic structures, and optical characteristics. It is practically impossible to test the photocatalytic activity of all possible TiO2‐based complexes using only experimental techniques. Instead, density functional theory (DFT)‐based theoretical simulations can easily guide experimental studies by screening materials and providing insights into the photoactivity of the complexes. The aim of this chapter is to provide an outlook for current research on DFT‐based simulations of TiO2 complexes for dye sensitized solar cells and water splitting applications and to address challenges of theoretical simulations

Comparison of penta and tetra‐pyridyl cobalt‐based catalysts for water reduction: H 2 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. The water reduction reaction is a clean and sustainable way of producing hydrogen energy, however designing an effective catalyst is the other side of the coin. Our theoretical work reveals the dynamical aspect of the water reduction reaction mechanism. The relative stability of the intermediate states, the role of the solvent, the role of the coordination pocket around Co and reduction free energies are determined by modeling the different oxidation states, CoII, CoI, CoIII–H, and CoII–H

A new approach for predicting gas separation performances of MOF membranes

Metal organic framework (MOF) membranes are widely used for gas separations. Permeability and selectivity of MOF membranes can be accurately calculated using ‘the detailed method’ which computes transport diffusivities of gases in MOFs' pores. However, this method is computationally demanding therefore not suitable to screen large numbers of MOFs. Another approach is to use ‘the approximate method’ which uses self-diffusivities of gases to predict gas permeabilities of MOF membranes. The approximate method requires fewer amounts of time compared to the detailed method but significantly underestimates gas permeabilities since mixture correlation effects are ignored in this method. In this work, we first used computationally demanding detailed method to calculate permeabilities and selectivities of 8 different MOF membranes for Xe/Kr and Xe/Ar separations. We then compared these results with the predictions of the approximate method. After observing significant underestimation of the gas permeabilities by the approximate method, we proposed a new computational method to accurately predict gas separation properties of MOF membranes. This new method requires the same computational time and resources with the approximate method but makes much more accurate predictions for gas permeabilities. The new method that we proposed in this work will be very useful for large-scale screening of MOFs to identify the most promising membrane materials prior to extensive computational calculations and experimental efforts

[CoII(BPyPy2COH)(OH2)2]2+: A Catalytic Pourbaix Diagram and AIMD Simulations on Four Key Intermediates

Proton reduction by [CoII(BPyPy2COH)(OH2)2]2+ (BPyPy2COH = [2,2'-bipyridin]-6-yl-di[pyridin-2-yl]methanol) proceeds through two distinct, pH-dependent pathways involving proton-coupled electron transfer (PCET), reduction and protonation steps. In this account we give an overview of the key mechanistic aspects in aqueous solution from pH 3 to 10, based on electrochemical data, time-resolved spectroscopy and ab initio molecular dynamics simulations of the key catalytic intermediates. In the acidic pH branch, a PCET to give a CoIII hydride is followed by a reduction and a protonation step, to close the catalytic cycle. At elevated pH, a reduction to CoI is observed, followed by a PCET to a CoII hydride, and the catalytic cycle is closed by a slow protonation step. In our simulation, both CoI and CoII–H feature a strong interaction with the surrounding solvent via hydrogen bonding, which is expected to foster the following catalytic step

Predicting Noble Gas Separation Performance of Metal Organic Frameworks Using Theoretical Correlations

In this work, we examined the accuracy of theoretical correlations that predict the performance of metal organic frameworks (MOFs) in separation of noble gas mixtures using only the single-component adsorption and diffusion data. Single component adsorption isotherms and self-diffusivities of Xe, Kr, and Ar in several MOFs were computed by grand canonical Monte Carlo and equilibrium molecular dynamics simulations. These pure component data were then used to apply Ideal Adsorbed Solution Theory (IAST) and Krishna–Paschek (KP) correlation for estimating the adsorption isotherms and self-diffusivities of Xe/Kr and Xe/Ar mixtures at various compositions in several representative MOFs. Separation properties of MOFs such as adsorption selectivity, working capacity, diffusion selectivity, permeation selectivity, and gas permeability were evaluated using the predictions of theoretical correlations and compared with the data obtained from computationally demanding molecular simulations. Results showed that theoretical correlations that predict mixture properties based on single-component data make accurate estimates for the separation performance of many MOFs which will be very useful for materials screening purposes

Atomically Detailed Modeling of Metal Organic Frameworks for Adsorption, Diffusion, and Separation of Noble Gas Mixtures

Atomically detailed simulations have been widely used to assess gas storage and gas separation properties of metal organic frameworks (MOFs). We used molecular simulations to examine adsorption, diffusion, and separation of noble gas mixtures in MOFs. Adsorption isotherms and self-diffusivities of Xe/Kr and Xe/Ar mixtures at various compositions in ten representative MOFs were computed using grand canonical Monte Carlo and equilibrium molecular dynamics simulations. Several properties of MOFs such as adsorption selectivity, working capacity, diffusion selectivity, permeation selectivity, and gas permeability were evaluated and compared with those of traditional nanoporous materials. Results showed that MOFs are promising candidates for Xe/Kr and Xe/Ar separations due to their high Xe selectivity and permeability

[CoII(BPyPy2COH)(OH2)2]2+: A Catalytic Pourbaix Diagram and AIMD Simulations on Four Key Intermediates

Proton reduction by [CoII(BPyPy2COH)(OH2)2]2+ (BPyPy2COH = [2,2'-bipyridin]-6-yl-di[pyridin-2-yl]methanol) proceeds through two distinct, pH-dependent pathways involving proton-coupled electron transfer (PCET), reduction and protonation steps. In this account we give an overview of the key mechanistic aspects in aqueous solution from pH 3 to 10, based on electrochemical data, time-resolved spectroscopy and ab initio molecular dynamics simulations of the key catalytic intermediates. In the acidic pH branch, a PCET to give a CoIII hydride is followed by a reduction and a protonation step, to close the catalytic cycle. At elevated pH, a reduction to CoI is observed, followed by a PCET to a CoII hydride, and the catalytic cycle is closed by a slow protonation step. In our simulation, both CoI and CoII–H feature a strong interaction with the surrounding solvent via hydrogen bonding, which is expected to foster the following catalytic step