Ethanol, O, and CO adsorption on Pt nanoparticles: effects of nanoparticle size and graphene support.

Pt nanoparticles dispersed over carbonaceous supports are widely used as catalysts for different applications, making studies on the interplay between size and support effects indispensable for rational catalyst design. Here, we use DFT calculations to simulate the interaction between O, CO, and ethanol with free platinum cuboctahedral nanoparticles with up to 147 atoms and with the same Pt nanoparticles supported on a single layer of graphene with up to 720 carbon atoms. We compute adsorption energies for each adsorbate on different adsorption sites for supported and unsupported Pt nanoparticles. We show that as the Pt nanoparticle grows the adsorption energy decreases, and that the size effect is more important for O and CO adsorption than for ethanol. We observe that the generalized coordination number of each adsorption site controls the interaction strength for O and CO to a much larger extent than for ethanol. Electronic charge redistributions and density of states projected on the d band of the interacting Pt facets are used to obtain a better understanding of the differences between the electronic interactions for each adsorbate. For Pt nanoparticles supported on graphene, the support effects weaken the adsorption energies for all the adsorbates, but this effect rapidly decreases with larger nanoparticles, and it is only significant for our smallest nanoparticle Pt13. By demonstrating that the effects of nanoparticle size and support are different for ethanol as compared with O and CO, we conclude that it should be possible to modify different parameters in the catalyst design in order to tune the Pt nanoparticle to interact with specific adsorbates.

DFT calculation of oxygen adsorption on platinum nanoparticles: coverage and size effects.

Catalysts made of Pt nanoparticles and Pt alloys are considered state-of-the-art catalysts for the anodic and cathodic reactions involved in hydrogen fuel cells. The optimal size of such nanoparticles for each chemical reaction is an unsolved problem that depends on environmental variables, such as reactant concentration, solvent, temperature, etc. From a theoretical point of view, this problem has been tackled mainly by observing how single key adsorbates react with different nanoparticles under controlled conditions. In this work, we use large-scale DFT calculations to examine the interplay between the Pt nanoparticle size and O coverage effects. We examine single O adsorptions for three adsorption sites on cuboctahedral platinum nanoparticles with different sizes. As we grow the nanoparticle size, the binding strength decreases and we observed a quick convergence of the adsorption energies with increasing nanoparticle size, which correlates with the calculated d-band centre for (111) Pt facets on such nanoparticles. We also carried out a detailed study of the effect of oxygen coverage with varying fractions of O monolayer coverage, computing adsorption energies per O atom for Pt55, Pt147 and Pt309 nanoparticles with several O coverages. In general, an increase of O coverage led to weaker adsorption energies per O atom, and when analysing the results in terms of oxygen monolayers, this effect is more pronounced for larger nanoparticles. The O coverage dependency of the adsorption energy per O atom is analysed in terms of the O distribution for each nanoparticle size and electronic changes that the adsorbed oxygen causes to the Pt nanoparticle. In studying nanoparticle size and oxygen coverage effects simultaneously, we offer insights with DFT accuracy to help on heterogeneous catalyst design.

Molecular dynamics simulation of potentiometric sensor response: the effect of biomolecules, surface morphology and surface charge.

The silica-water interface is critical to many modern technologies in chemical engineering and biosensing. One technology used commonly in biosensors, the potentiometric sensor, operates by measuring the changes in electric potential due to changes in the interfacial electric field. Predictive modelling of this response caused by surface binding of biomolecules remains highly challenging. In this work, through the most extensive molecular dynamics simulation of the silica-water interfacial potential and electric field to date, we report a novel prediction and explanation of the effects of nano-morphology on sensor response. Amorphous silica demonstrated a larger potentiometric response than an equivalent crystalline silica model due to increased sodium adsorption, in agreement with experiments showing improved sensor response with nano-texturing. We provide proof-of-concept that molecular dynamics can be used as a complementary tool for potentiometric biosensor response prediction. Effects that are conventionally neglected, such as surface morphology, water polarisation, biomolecule dynamics and finite-size effects, are explicitly modelled.

Intuitive Density Functional Theory-Based Energy Decomposition Analysis for Protein-Ligand Interactions.

First-principles quantum mechanical calculations with methods such as density functional theory (DFT) allow the accurate calculation of interaction energies between molecules. These interaction energies can be dissected into chemically relevant components such as electrostatics, polarization, and charge transfer using energy decomposition analysis (EDA) approaches. Typically EDA has been used to study interactions between small molecules; however, it has great potential to be applied to large biomolecular assemblies such as protein-protein and protein-ligand interactions. We present an application of EDA calculations to the study of ligands that bind to the thrombin protein, using the ONETEP program for linear-scaling DFT calculations. Our approach goes beyond simply providing the components of the interaction energy; we are also able to provide visual representations of the changes in density that happen as a result of polarization and charge transfer, thus pinpointing the functional groups between the ligand and protein that participate in each kind of interaction. We also demonstrate with this approach that we can focus on studying parts (fragments) of ligands. The method is relatively insensitive to the protocol that is used to prepare the structures, and the results obtained are therefore robust. This is an application to a real protein drug target of a whole new capability where accurate DFT calculations can produce both energetic and visual descriptors of interactions. These descriptors can be used to provide insights for tailoring interactions, as needed for example in drug design.

Dynamic behaviour of the silica-water-bio electrical double layer in the presence of a divalent electrolyte.

Electronic devices are becoming increasingly used in chemical- and bio-sensing applications and therefore understanding the silica-electrolyte interface at the atomic scale is becoming increasingly important. For example, field-effect biosensors (BioFETs) operate by measuring perturbations in the electric field produced by the electrical double layer due to biomolecules binding on the surface. In this paper, explicit-solvent atomistic calculations of this electric field are presented and the structure and dynamics of the interface are investigated in different ionic strengths using molecular dynamics simulations. Novel results from simulation of the addition of DNA molecules and divalent ions are also presented, the latter of particular importance in both physiological solutions and biosensing experiments. The simulations demonstrated evidence of charge inversion, which is known to occur experimentally for divalent electrolyte systems. A strong interaction between ions and DNA phosphate groups was demonstrated in mixed electrolyte solutions, which are relevant to experimental observations of device sensitivity in the literature. The bound DNA resulted in local changes to the electric field at the surface; however, the spatial- and temporal-mean electric field showed no significant change. This result is explained by strong screening resulting from a combination of strongly polarised water and a compact layer of counterions around the DNA and silica surface. This work suggests that the saturation of the Stern layer is an important factor in determining BioFET response to increased salt concentration and provides novel insight into the interplay between ions and the EDL.

Effect of graphene support on large Pt nanoparticles.

State-of-the-art catalysts are often created via deposition of monolayers, sub-monolayers or nanoparticles of the catalytic material over supports, aiming to increase the surface area and decrease the loading of the catalytic material and therefore the overall cost. Here, we employ large-scale DFT calculations to simulate platinum clusters with up to 309 atoms interacting with single layer graphene supports with up to 880 carbon atoms. We compute the adsorption, cohesion and formation energies of two and three-dimensional Pt clusters interacting with the support, including dispersion interactions via a semi-empirical dispersion correction and a vdW functional. We find that three-dimensional Pt clusters are more stable than the two-dimensional when interacting with the support, and that the difference between their stabilities increases with the system size. Also, the dispersion interactions are more pronounced as we increase the nanoparticle size, being essential to a reliable description of larger systems. We observe inter-atomic expansion (contraction) on the closest (farthest) Pt facets from the graphene sheet and charge redistribution with overall charge being transferred from the platinum clusters to the support. The Pt-Pt expansion, which is related to the charge transfer in the system, correlates with the adsorption energy per Pt atom in contact with the graphene. These, and other electronic and structural observations show that the effect of the support cannot be neglected. Our study provides for the first time, to the best of our knowledge, quantitative results on the non-trivial combination of size and support effects for nanoparticles sizes which are relevant to catalyst design.

Energy Decomposition Analysis Based on Absolutely Localized Molecular Orbitals for Large-Scale Density Functional Theory Calculations in Drug Design.

We report the development and implementation of an energy decomposition analysis (EDA) scheme in the ONETEP linear-scaling electronic structure package. Our approach is hybrid as it combines the localized molecular orbital EDA (Su, P.; Li, H. J. Chem. Phys., 2009, 131, 014102) and the absolutely localized molecular orbital EDA (Khaliullin, R. Z.; et al. J. Phys. Chem. A, 2007, 111, 8753-8765) to partition the intermolecular interaction energy into chemically distinct components (electrostatic, exchange, correlation, Pauli repulsion, polarization, and charge transfer). Limitations shared in EDA approaches such as the issue of basis set dependence in polarization and charge transfer are discussed, and a remedy to this problem is proposed that exploits the strictly localized property of the ONETEP orbitals. Our method is validated on a range of complexes with interactions relevant to drug design. We demonstrate the capabilities for large-scale calculations with our approach on complexes of thrombin with an inhibitor comprised of up to 4975 atoms. Given the capability of ONETEP for large-scale calculations, such as on entire proteins, we expect that our EDA scheme can be applied in a large range of biomolecular problems, especially in the context of drug design.

The potential of imogolite nanotubes as (co-)photocatalysts: a linear-scaling density functional theory study.

We report a linear-scaling density functional theory (DFT) study of the structure, wall-polarization absolute band-alignment and optical absorption of several, recently synthesized, open-ended imogolite (Imo) nanotubes (NTs), namely single-walled (SW) aluminosilicate (AlSi), SW aluminogermanate (AlGe), SW methylated aluminosilicate (AlSi-Me), and double-walled (DW) AlGe NTs. Simulations with three different semi-local and dispersion-corrected DFT-functionals reveal that the NT wall-polarization can be increased by nearly a factor of four going from SW-AlSi-Me to DW-AlGe. Absolute vacuum alignment of the NT electronic bands and comparison with those of rutile and anatase TiO2 suggest that the NTs may exhibit marked propensity to both photo-reduction and hole-scavenging. Characterization of the NTs' band-separation and optical properties reveal the occurrence of (near-)UV inside-outside charge-transfer excitations, which may be effective for electron-hole separation and enhanced photocatalytic activity. Finally, the effects of the NTs' wall-polarization on the absolute alignment of electron and hole acceptor states of interacting water (H2O) molecules are quantified and discussed.

Linear-scaling calculation of Hartree-Fock exchange energy with non-orthogonal generalised Wannier functions.

We present a method for the calculation of four-centre two-electron repulsion integrals in terms of localised non-orthogonal generalised Wannier functions (NGWFs). Our method has been implemented in the ONETEP program and is used to compute the Hartree-Fock exchange energy component of Hartree-Fock and Density Functional Theory (DFT) calculations with hybrid exchange-correlation functionals. As the NGWFs are optimised in situ in terms of a systematically improvable basis set which is equivalent to plane waves, it is possible to achieve large basis set accuracy in routine calculations. The spatial localisation of the NGWFs allows us to exploit the exponential decay of the density matrix in systems with a band gap in order to compute the exchange energy with a computational effort that increases linearly with the number of atoms. We describe the implementation of this approach in the ONETEP program for linear-scaling first principles quantum mechanical calculations. We present extensive numerical validation of all the steps in our method. Furthermore, we find excellent agreement in energies and structures for a wide variety of molecules when comparing with other codes. We use our method to perform calculations with the B3LYP exchange-correlation functional for models of myoglobin systems bound with O2 and CO ligands and confirm that the same qualitative behaviour is obtained as when the same myoglobin models are studied with the DFT+U approach which is also available in ONETEP. Finally, we confirm the linear-scaling capability of our method by performing calculations on polyethylene and polyacetylene chains of increasing length.