Statistical block copolymers, composed of donor (D) and acceptor (A) blocks, are a novel type of material for organic photovoltaics (OPVs) devices. In particular a new series of polymers based on PBTZT-stat-BDTT-8, recently developed by Merck, offers high solubility in different solvents, and a high power conversion efficiency (PCE) in different device architectures. Although it is known that the electronic properties of these materials may be significantly affected by attaching different functional groups on different blocks, it is not fully clear how important the influence of the polymer composition (i.e., the D/A block ratio) is, even if previous studies suggest that this might also have an effect. Therefore, the effect of the polymer composition in terms of HOMO, LUMO energies, and band gap was explored by studying a number of long chain oligomers with more than 1000 atoms each and with different D/A ratios. This study, that is novel both conceptually and methodologically, was made possible by using the linear-scaling reformulation of DFT implemented in the ONETEP code. Our results showed that changing the composition has a significant effect on the electronic structure of statistical copolymers, making this an alternative and suitable strategy to obtain materials with desired properties. Also, a systematic analysis of the effect of a range of different substituents placed in the D and A blocks of PBTZT-stat-BDTT-8 was performed in order to investigate how this class of materials responds to functionalization. We found that it is not possible to know a priori using chemical intuition what kind of influence different types of functional groups may have on these systems, and therefore, computational modeling is essential.

In this work, the crystal properties, HOMO and LUMO energies, band gaps, density of states, as well as the optical absorption spectra of fullerene C60 and its derivative phenyl-C61-butyric-acid-methyl-ester (PCBM) co-crystallised with various solvents such as benzene, biphenyl, cyclohexane, and chlorobenzene were investigated computationally using linear-scaling density functional theory with plane waves as implemented in the ONETEP program. Such solvates are useful materials as electron acceptors for organic photovoltaic (OPV) devices. We found that the fullerene parts contained in the solvates are unstable without solvents, and the interactions between fullerene and solvent molecules in C60 and PCBM solvates make a significant contribution to the cohesive energies of solvates, indicating that solvent molecules are essential to keep C60 and PCBM solvates stable. Both the band gap (Eg) and the HOMO and LUMO states of C60 and PCBM solvates are mainly determined by the fullerene parts contained in solvates. Chlorobenzene- and ortho-dichlorobenzene-solvated PCBM are the most promising electron-accepting materials among these solvates for increasing the driving force for charge separation in OPVs due to their relatively high LUMO energies. The UV-Vis absorption spectra of solvent-free C60 and PCBM crystals in the present work are similar to those of C60 and PCBM thin films shown in the literature. Changes in the absorption spectra of C60 solvates relative to the solvent-free C60 crystal are more significant than those of PCBM solvates due to the weaker effect of solvents on the π-stacking interactions between fullerene molecules in the latter solvates. The main absorptions for all C60 and PCBM crystals are located in the ultraviolet (UV) region.

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 partitioning of the energy in ab initio quantum mechanical calculations into its chemical origins (e.g., electrostatics, exchange–repulsion, polarization, and charge transfer) is a relatively recent development; such concepts of isolating chemically meaningful energy components from the interaction energy have been demonstrated by variational and perturbation based energy decomposition analysis approaches. The variational methods are typically derived from the early energy decomposition analysis of Morokuma [Morokuma, J. Chem. Phys., 1971, 55, 1236], and the perturbation approaches from the popular symmetry-adapted perturbation theory scheme [Jeziorski et al., Methods and Techniques in Computational Chemistry: METECC-94, 1993, ch. 13, p. 79]. Since these early works, many developments have taken place aiming to overcome limitations of the original schemes and provide more chemical significance to the energy components, which are not uniquely defined. In this review, after a brief overview of the origins of these methods we examine the theory behind the currently popular variational and perturbation based methods from the point of view of biochemical applications. We also compare and discuss the chemical relevance of energy components produced by these methods on six test sets that comprise model systems that display interactions typical of biomolecules (such as hydrogen bonding and π–π stacking interactions) including various treatments of the dispersion energy.

Density functional theory molecular dynamics (DFT-MD) provides an efficient framework for accurately computing several types of spectra. The major benefit of DFT-MD approaches lies in the ability to naturally take into account the effects of temperature and anharmonicity, without having to introduce any ad hoc or a posteriori corrections. Consequently, computational spectroscopy based on DFT-MD approaches plays a pivotal role in the understanding and assignment of experimental peaks and bands at finite temperature, particularly in the case of floppy molecules. Linear-scaling DFT methods can be used to study large and complex systems, such as peptides, DNA strands, amorphous solids, and molecules in solution. Here, we present the implementation of DFT-MD IR spectroscopy in the Onetep linear-scaling code. In addition, two methods for partitioning the dipole moment within the Onetep framework are presented. Dipole moment partitioning allows us to compute spectra of molecules in solution, which fully include the effects of the solvent, while at the same time removing the solvent contribution from the spectra.

The Fourier interpolation of 3D data-sets is a performance critical operation in many fields, including certain forms of image processing and density functional theory (DFT) quantum chemistry codes based on plane wave basis sets, to which this paper is targeted. In this paper we describe three different algorithms for performing this operation built from standard discrete Fourier transform operations, and derive theoretical operation counts. The algorithms compared consist of the most straightforward implementation and two that exploit techniques such as phase-shifts and knowledge of zero padding to reduce computational cost. Through a library implementation (tintl) we explore the performance characteristics of these algorithms and the performance impact of different implementation choices on actual hardware. We present comparisons within the linear-scaling DFT code ONETEP where we replace the existing interpolation implementation with our library implementation configured to choose the most efficient algorithm. Within the ONETEP Fourier interpolation stages, we demonstrate speed-ups of over 1.55×.

HypothesisSilanol groups at the silica–water interface determine not only the surface charge, but also have an important role in the binding of ions and biomolecules. As the pH is increased above pH 2, the silica surface develops a net negative charge primarily due to deprotonation of the silanol group. An improved understanding of the energetics and mechanisms of this fundamentally important process would further understanding of the relevant dynamics.SimulationsDensity Functional Theory ab initio   molecular dynamics and geometry optimisations were used to investigate the mechanisms of surface neutralisation and charging in the presence of OH-OH- and H3O+H3O+ respectively. This charging mechanism has received little attention in the literature.FindingsThe protonation or deprotonation of isolated silanols in the presence of H3O+H3O+ or OH-OH-, respectively, was shown to be a highly rapid, exothermic reaction with no significant activation energy. This process occurred via a concerted motion of the protons through ‘water wires’. Geometry optimisations of large water clusters at the silica surface demonstrated proton transfer to the surface occurring via the rarely discussed ‘proton holes’ mechanism. This indicates that surface protonation is possible even when the hydronium ion is distant (at least 4 water molecules separation) from the surface.Figure optionsDownload full-size imageDownload high-quality image (134 K)Download as PowerPoint slide

We present a hybrid MPI-OpenMP implementation of Linear-Scaling Density Functional Theory within the ONETEP code. We illustrate its performance on a range of high performance computing (HPC) platforms comprising shared-memory nodes with fast interconnect. Our work has focused on applying OpenMP parallelism to the routines which dominate the computational load, attempting where possible to parallelize different loops from those already parallelized within MPI. This includes 3D FFT box operations, sparse matrix algebra operations, calculation of integrals, and Ewald summation. While the underlying numerical methods are unchanged, these developments represent significant changes to the algorithms used within ONETEP to distribute the workload across CPU cores. The new hybrid code exhibits much-improved strong scaling relative to the MPI-only code and permits calculations with a much higher ratio of cores to atoms. These developments result in a significantly shorter time to solution than was possible using MPI alone and facilitate the application of the ONETEP code to systems larger than previously feasible. We illustrate this with benchmark calculations from an amyloid fibril trimer containing 41,907 atoms. We use the code to study the mechanism of delamination of cellulose nanofibrils when undergoing sonification, a process which is controlled by a large number of interactions that collectively determine the structural properties of the fibrils. Many energy evaluations were needed for these simulations, and as these systems comprise up to 21,276 atoms this would not have been feasible without the developments described here.

The accurate prediction of ligand binding affinities to a protein remains a desirable goal of computational biochemistry. Many available methods use molecular mechanics (MM) to describe the system, however, MM force fields cannot fully describe the complex interactions involved in binding, specifically electron transfer and polarization. First principles approaches can fully account for these interactions, and with the development of linear-scaling first principles programs, it is now viable to apply first principles calculations to systems containing tens of thousands of atoms. In this paper, a quantum mechanical Poisson−Boltzmann surface area approach is applied to a model of a protein−ligand binding cavity, the “tennis ball” dimer. Results obtained from this approach demonstrate considerable improvement over conventional molecular mechanics Poisson−Boltzmann surface area due to the more accurate description of the interactions in the system. For the first principles calculations in this study, the linear-scaling density functional theory program ONETEP is used, allowing the approach to be applied to receptor−ligand complexes of pharmaceutical interest that typically include thousands of atoms.

In this work, the crystal properties, HOMO and LUMO energies, band gaps, density of states, as well as the optical absorption spectra of fullerene C60 and its derivative phenyl-C61-butyric-acid-methyl-ester (PCBM) co-crystallised with various solvents such as benzene, biphenyl, cyclohexane, and chlorobenzene were investigated computationally using linear-scaling density functional theory with plane waves as implemented in the ONETEP program. Such solvates are useful materials as electron acceptors for organic photovoltaic (OPV) devices. We found that the fullerene parts contained in the solvates are unstable without solvents, and the interactions between fullerene and solvent molecules in C60 and PCBM solvates make a significant contribution to the cohesive energies of solvates, indicating that solvent molecules are essential to keep C60 and PCBM solvates stable. Both the band gap (Eg) and the HOMO and LUMO states of C60 and PCBM solvates are mainly determined by the fullerene parts contained in solvates. Chlorobenzene- and ortho-dichlorobenzene-solvated PCBM are the most promising electron-accepting materials among these solvates for increasing the driving force for charge separation in OPVs due to their relatively high LUMO energies. The UV-Vis absorption spectra of solvent-free C60 and PCBM crystals in the present work are similar to those of C60 and PCBM thin films shown in the literature. Changes in the absorption spectra of C60 solvates relative to the solvent-free C60 crystal are more significant than those of PCBM solvates due to the weaker effect of solvents on the π-stacking interactions between fullerene molecules in the latter solvates. The main absorptions for all C60 and PCBM crystals are located in the ultraviolet (UV) region.

The partitioning of the energy in ab initio quantum mechanical calculations into its chemical origins (e.g., electrostatics, exchange–repulsion, polarization, and charge transfer) is a relatively recent development; such concepts of isolating chemically meaningful energy components from the interaction energy have been demonstrated by variational and perturbation based energy decomposition analysis approaches. The variational methods are typically derived from the early energy decomposition analysis of Morokuma [Morokuma, J. Chem. Phys., 1971, 55, 1236], and the perturbation approaches from the popular symmetry-adapted perturbation theory scheme [Jeziorski et al., Methods and Techniques in Computational Chemistry: METECC-94, 1993, ch. 13, p. 79]. Since these early works, many developments have taken place aiming to overcome limitations of the original schemes and provide more chemical significance to the energy components, which are not uniquely defined. In this review, after a brief overview of the origins of these methods we examine the theory behind the currently popular variational and perturbation based methods from the point of view of biochemical applications. We also compare and discuss the chemical relevance of energy components produced by these methods on six test sets that comprise model systems that display interactions typical of biomolecules (such as hydrogen bonding and π–π stacking interactions) including various treatments of the dispersion energy.

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.