Focus on Novel Materials Discovery

Via computer simulations, we investigate the linear and nonlinear viscoelastic response of polymer grafted nanoparticle networks subject to oscillatory shear at different amplitudes and frequencies. The individual nanoparticles are composed of a rigid spherical core and a corona of grafted polymers that encompass reactive end groups. With the overlap of the coronas on adjacent particles, the reactive end groups form permanent or labile bonds, and thus form a 'dual cross-linked' network. The existing labile bonds between particles can break and reform depending on the bond rupture rate, extent of deformation and the frequency of oscillation. We study how the viscoelastic behavior of the material depends on the energy of the labile bonds and identify the network characteristics that give rise to the observed viscoelastic response. We observe that with an increase in labile bond energy, the storage modulus increases while the loss modulus shows a more complex response depending on the labile bond energy. Specifically, in the case of the samples with the weaker labile bonds, the loss modulus increases monotonically, while for the samples with the stronger labile bonds, the loss modulus exhibits a minimum with an increase in frequency. We show that an increase in the storage modulus corresponds to an enhancement in the average number of bonds in the samples and the characteristics of the loss modulus depend on both the bond kinetics and the mobility of the particles in the network. Furthermore, we determine that the effective contribution of the bonds to the storage modulus decreases with increase in strain amplitude. In particular, while bond formation at small amplitude drives an increase in storage modulus, at large amplitudes it promotes clustering and formation of voids leading to strain softening. Our simulations provide a mesoscopic picture of how the nature of labile bonds affects the performance of cross-linked polymer-grafted nanoparticle networks.

The optical properties of metals are mainly determined by their plasmonic excitations, with various intriguing phenomena associated with systems in reduced dimensions. In this paper, we present a systematic study of the plasmonic excitations in ultrathin metal films on dielectric substrates using two different theoretical approaches, and with Mg thin films on Si as prototype systems. The bulk of the results are obtained using the first approach within first-principles time-dependent local density approximation. We show that the presence of the substrate substantially modifies the plasmon hybridization of the metal films; in turn, the plasmon excitation in the films strongly enhances the absorption of the substrate. The detailed absorption spectra contain several intriguing features. Above the Mg surface plasmon mode, we observe a broad resonance due to the hybridization between the antisymmetric surface plasmon and multipole surface plasmon. Furthermore, below the Mg surface plasmon mode, there also exists a broad absorption feature, caused by individual electron–hole pair excitations. In the second approach, we use a semi-classical local optics model to reveal an intrinsic connection between the broad absorption feature and the multipole surface plasmon modes, which result from the single-particle and collective excitations of the same surface electrons, respectively. Our theoretical predictions on the plasmon dispersions and absorption spectra are also shown to be qualitatively consistent with the latest experimental observations using electron energy loss spectroscopy for Mg thin films grown on Si substrates.

Nanocrystalline soft magnetic materials are the latest and most promising of the soft magnetic materials that were developed at the end of the 20th century. They have since been studied extensively, and various alloy compositions have been developed and optimized for ambient and extreme (cryogenic and elevated temperature) applications. Their advantage lies in the unique combination of fine microstructure, crystal structure and composition, which can be achieved by rapid solidification and subsequent controlled annealing. In this article, we discuss the requirements and the challenges of the alloy designing these alloys and how it affects the crystal structure, microstructure and eventually the magnetic performance of new alloys designed for use at temperatures below 150 K in applications as varied as cryo-power electronics and magnetic shielding. The results from our latest studied alloy series are mentioned as an example.

We report on the electronic and optical properties of two theoretically predicted stable spinel compounds of the form ZnB$_{2}$O$_{4}$, where B = Ni or Cu; neither compound has been previously synthesized, so we compare them to the previously studied p-type ZnCo$_{2}$O$_{4}$ spinel. These new materials exhibit spin polarization, which is useful for spintronics applications, and broad conductivity maxima near the valence band edge that indicate good p-type dopability. We show that $3{\rm{d}}$ electrons on the octahedrally coordinated Zn atom fall deep within the valence band and do not contribute significantly to the electronic structure near the band edge of the material, while the O $2{\rm{p}}$ and tetrahedrally coordinated B $3{\rm{d}}$ electrons hybridize broadly in the shallow valence states, resulting in increasing curvature (i.e., decreased electron effective mass) of valence bands near the band edge. In particular, ZnCu$_{2}$O$_{4}$ exhibits high electrical conductivities in the p-doping region near the valence band edge that, at $\sigma =2\times {{10}^{4}}\ {\rm{S}}\;{\rm{c}}{{{\rm{m}}}^{-1}}$, are twice the maximum found for ZnCo$_{2}$O$_{4}$ , a previously synthesized compound in this class of materials. This material also exhibits ferromagnetism in all of its most stable structures, which makes it a good candidate for further study as a dilute magnetic semiconductor.

At the interface between a superconductor and a ferromagnetic metal spin-singlet Cooper pairs can penetrate into the ferromagnetic part of the heterostructure with an oscillating and decaying spin-singlet Cooper pair density. However, if the interface allows for a spin-mixing effect, equal-spin spin-triplet Cooper pairs can be generated that can penetrate much further into the ferromagnetic part of the heterostructure, known as the long-range proximity effect. Here, we present results of spin-mixing based on self-consistent solutions of the microscopic Bogoliubov–de Gennes equations in the clean limit incorporating a tight-binding model. In particular, we include a conical magnet into our model heterostructure to generate the spin-triplet Cooper pairs and analyse the influence of conical and ferromagnetic layer thickness on the unequal-spin and equal-spin spin-triplet pairing correlations. It will be shown that, in agreement with experimental observations, a minimum thickness of the conical magnet is necessary to generate a sufficient amount of equal-spin spin-triplet Cooper pairs allowing for the long-range proximity effect.

Oxide heterostructures have been shown to exhibit unusual physics and hold the promise of novel electronic applications. We present a set of criteria to select and design interfaces, particularly those that can sustain a high-density two-dimensional electron gas (2DEG). We describe how first-principles calculations can contribute to a qualitative and quantitative understanding, illustrated with the key issue of band alignment. Band offsets determine on which side of the interface the 2DEG will reside, as well as the degree of confinement. We use hybrid density functional calculations to determine the band alignments of a number of complex oxides, considering materials with different types of conduction-band character, polar or nonpolar character and band insulators as well as Mott insulators. We suggest promising materials combinations that could lead to a 2DEG with optimized properties, such as high 2DEG densities and high electron mobilities.

In contrast to the broad knowledge about aqueous polyelectrolyte solutions, less is known about the properties in aprotic and apolar solvents. We therefore investigate the behavior of sulfonated polyelectrolytes in sodium form in the presence of different solvents via all-atom molecular dynamics simulations. The results clearly reveal strong variations in ion condensation constants and polyelectrolyte conformations for different solvents like water, dimethyl sulfoxide (DMSO) and chloroform. The binding free energies of the solvent contacts with the polyelectrolyte groups validate the influence of different solvent qualities. With regard to the ion condensation behavior, the numerical findings show that the explicit values for the condensation constants depend on the preferential binding coefficient as derived by the evaluation of Kirkwood–Buff integrals. Surprisingly, the smallest ion condensation constant is observed for DMSO compared to water, whereas in the presence of chloroform, virtually no free ions are present, which is in good agreement to the donor number concept. In contrast to the results for the low condensation constants, the sodium conductivity in DMSO is smaller compared to water. We are able to relate this result to the observed smaller diffusion coefficient for the sodium ions in DMSO.

Density functional calculations have been tremendously useful in understanding the microscopic origin of multiferroicity and in quantifying relevant properties in many multiferroics and magnetoelectrics. Here, we focus on a relatively new and promising compound, PbNiO₃. The structural, electronic and magnetic properties of its two polymorphs, i.e. the orthorhombic structure with space group Pnma and the rhombohedral LiNbO₃-type structure with space group R3c have been studied by using density functional calculations within DFT + U and hybrid functional schemes. Our data convey an accurate description of the pressure-induced phase transition from the rhombohedral to orthorhombic phase at a predicted critical pressure of 5 GPa in agreement with the measured value of 3 GPa. Both phases show the G-type antiferromagnetic configuration as a magnetic ground state, but differ in the spatial anisotropy associated with nearest-neighbor exchange couplings, which is strongly weakened in the rhombohedral LiNbO₃-type phase. The predicted large ferroelectric polarization of the rhombohedral phase (Hao et al 2012 Phys. Rev. B 014116) has been re-explored and analyzed in detail using partial density of states, Born effective charge tensors, charge density difference, electron localization function analysis and distortion mode analysis. The asymmetric bonding between the Pb 6s and O 2p orbitals along the [111]-direction is responsible for the polar cationic displacement, giving rise to a predicted large ferroelectric polarization as high as  ∼ 100 μC cm⁻².

We present a method to map the full equilibrium distribution of the primitive-path (PP) length, obtained from multi-chain simulations of polymer melts, onto a single-chain mean-field 'target' model. Most previous works used the Doi–Edwards tube model as a target. However, the average number of monomers per PP segment, obtained from multi-chain PP networks, has consistently shown a discrepancy of a factor of two with respect to tube-model estimates. Part of the problem is that the tube model neglects fluctuations in the lengths of PP segments, the number of entanglements per chain and the distribution of monomers among PP segments, while all these fluctuations are observed in multi-chain simulations. Here we use a recently proposed slip-link model, which includes fluctuations in all these variables as well as in the spatial positions of the entanglements. This turns out to be essential to obtain qualitative and quantitative agreement with the equilibrium PP-length distribution obtained from multi-chain simulations. By fitting this distribution, we are able to determine two of the three parameters of the model, which govern its equilibrium properties. This mapping is executed for four different linear polymers and for different molecular weights. The two parameters are found to depend on chemistry, but not on molecular weight. The model predicts a constant plateau modulus minus a correction inversely proportional to molecular weight. The value for well-entangled chains, with the parameters determined ab initio, lies in the range of experimental data for the materials investigated.

An important approach in the design of new environmentally friendly materials is represented by the study of analogous systems already existing in nature. In the search for new water splitting catalysts, the corresponding natural analogue is represented by the oxygen-evolving complex of photosystem II, which is a large membrane protein complex present in photosynthetic organisms. The understanding of the catalytic strategy of its active Mn₄CaO₅ core is important to unravel the mechanisms of water oxidation in photosynthesis and can serve as an inspiring model for the design of biomimetic catalysts based on largely non-toxic, earth abundant elements. The magnetic interactions between Mn ions are studied in the present work by means of DFT + U broken symmetry ab initio molecular dynamics within a quantum mechanics/molecular mechanics framework. The room temperature dynamics of two different structural models (i.e. with total high-spin and total low-spin ground states) was stable during the simulated time. We observed large fluctuations of the magnetic coupling constants calculated on both the structural models of the complex, causing occasionally instantaneous swapping of the ferromagnetic/antiferromagnetic coupling between the metal centers.

This work demonstrates how databases of diffusion-related properties can be developed from high-throughput ab initio calculations. The formation and migration energies for vacancies of all adequately stable pure elements in both the face-centered cubic (fcc) and hexagonal close packing (hcp) crystal structures were determined using ab initio calculations. For hcp migration, both the basal plane and z-direction nearest-neighbor vacancy hops were considered. Energy barriers were successfully calculated for 49 elements in the fcc structure and 44 elements in the hcp structure. These data were plotted against various elemental properties in order to discover significant correlations. The calculated data show smooth and continuous trends when plotted against Mendeleev numbers. The vacancy formation energies were plotted against cohesive energies to produce linear trends with regressed slopes of 0.317 and 0.323 for the fcc and hcp structures respectively. This result shows the expected increase in vacancy formation energy with stronger bonding. The slope of approximately 0.3, being well below that predicted by a simple fixed bond strength model, is consistent with a reduction in the vacancy formation energy due to many-body effects and relaxation. Vacancy migration barriers are found to increase nearly linearly with increasing stiffness, consistent with the local expansion required to migrate an atom. A simple semi-empirical expression is created to predict the vacancy migration energy from the lattice constant and bulk modulus for fcc systems, yielding estimates with errors of approximately 30%.

The nature of the lowest-energy electronic excitations in prototypical molecular solids is studied here in detail by combining electron energy loss spectroscopy (EELS) experiments and state-of-the-art many-body calculations based on the Bethe–Salpeter equation. From a detailed comparison of the spectra in picene, coronene and tetracene we generally find a good agreement between theory and experiment, with an upshift of the main features of the calculated spectrum of 0.1–0.2 eV, which can be considered the error bar of the calculation. We focus on the anisotropy of the spectra, which illustrates the complexity of this class of materials, showing a high sensitivity with respect to the three-dimensional packing of the molecular units in the crystal. The differences between the measured and the calculated spectra are explained in terms of the small differences between the crystal structures of the measured samples and the structural model used in the calculations. Finally, we discuss the role played by the different electron–hole interactions in the spectra. We thus demonstrate that the combination of highly accurate experimental EELS and theoretical analysis is a powerful tool to elucidate and understand the electronic properties of molecular solids.

In this paper a computational high-throughput screening (HTS) approach to the search for alternative permanent magnetic materials is presented. Systems considered for a start are binary intermetallic compounds composed of rare-earth (RE) and transition metal (TM) elements. With the tight-binding-linear muffin-tin-orbital-atomic-sphere-approximation (TB-LMTO-ASA) method of density functional theory (DFT) a variety of RE–TM intermetallic phases is investigated and their magnetic properties are obtained at rather low computational costs. Next, interstitial elements such as boron, carbon and nitrogen in these phases are considered. For promising candidate phases with high and stable spontaneous ferromagnetic polarization, the calculated local magnetic moments and exchange coupling parameters, as obtained from TB-LMTO-ASA calculations, are then used for Monte Carlo simulations to identify candidates with sufficiently high Curie temperatures (T_c). Finally, magnetocrystalline anisotropy constants (K₁) of the most promising candidate phases are calculated with accurate, potential-shape-unrestricted DFT calculations using the Vienna ab initio simulation package. The computational HTS procedure is illustrated by results for a selection of hard-magnetic RE–TM phases like RETM₅, RE₂TM₁₇ and RE₂TM₁₄B.

This paper demonstrates a method for screening transition metal and metal alloy catalysts based on their predicted rates and stabilities for a given catalytic reaction. This method involves combining reaction and activation energies (available to the public via a web-based application 'CatApp') with a microkinetic modeling technique to predict the rates and selectivities of a prospective material. This paper illustrates this screening technique using the steam reforming of methane to carbon monoxide and hydrogen as a test reaction. While catalysts are already commercially available for this process, the method demonstrated in this paper is very general and could be applied to a wide range of catalytic reactions. Following the steps outlined herein, such an analysis could potentially enable researchers to understand reaction mechanisms on a fundamental level and, on this basis, develop leads for new metal alloy catalysts.

We develop a multiscale hybrid scheme for simulations of soft condensed matter systems, which allows one to treat the system at the particle level in selected regions of space, and at the continuum level elsewhere. It is derived systematically from an underlying particle-based model by field theoretic methods. Particles in different representation regions can switch representations on the fly, controlled by a spatially varying tuning function. As a test case, the hybrid scheme is applied to simulate colloid–polymer composites with high resolution regions close to the colloids. The hybrid simulations are significantly faster than reference simulations of a pure particle-based model, and the results are in good agreement.

Two-dimensional (2D) transition-metal dichalcogenides (TMDs) are gaining increasing attention as an alternative to graphene for their very high potential in optoelectronics applications. Here, we consider two prototypical metallic 2D TMDs, NbSe₂ and TaS₂. Using a first-principles approach, we investigate the properties of the localized intraband d plasmon that cannot be modeled on the basis of the homogeneous electron gas. Finally, we discuss the effects of the reduced dimensionality on the plasmon dispersion through the interplay between the interband transitions and the local-field effects. This result can be exploited to tune the plasmonic properties of these novel 2D materials.

In steels and single-crystal superalloys the control of the formation of topologically close-packed (TCP) phases is critical for the performance of the material. The structural stability of TCP phases in multi-component transition-metal alloys may be rationalized in terms of the average valence-electron count $\bar {N}$ and the composition-dependent relative volume-difference $\overline {\Delta V/V}$. We elucidate the interplay of these factors by comparing density-functional theory calculations to an empirical structure map based on experimental data. In particular, we calculate the heat of formation for the TCP phases A15, C14, C15, C36, χ, μ and σ for all possible binary occupations of the Wyckoff positions. We discuss the isovalent systems V/Nb–Ta to highlight the role of atomic-size difference and observe the expected stabilization of C14/C15/C36/μ by $\overline {\Delta V/V}$ at ΔN = 0 in V–Ta. In the systems V/Nb–Re, we focus on the well-known trend of A15 → σ → χ stability with increasing $\bar {N}$ and show that the influence of $\overline {\Delta V/V}$ is too weak to stabilize C14/C15/C36/μ in Nb–Re. As an example for a significant influence of both $\bar {N}$ and $\overline {\Delta V/V}$, we also consider the systems Cr/Mo–Co. Here the sequence A15 → σ → χ is observed in both systems but in Mo–Co the large size-mismatch stabilizes C14/C15/C36/μ. We also include V/Nb–Co that cover the entire valence range of TCP stability and also show the stabilization of C14/C15/C36/μ. Moreover, the combination of a large volume-difference with a large mismatch in valence-electron count reduces the stability of the A15/σ/χ phases in Nb–Co as compared to V–Co. By comparison to non-magnetic calculations we also find that magnetism is of minor importance for the structural stability of TCP phases in Cr/Mo–Co and in V/Nb–Co.

Intermetallic compounds made of alkali metals and gold have intriguing electronic and structural properties that have not been extensively explored. We perform a systematic study of the phase diagram of one binary system belonging to this family, namely Na_xAu_1−x, using the ab initio minima hopping structural prediction method. We discover that the most stable composition is NaAu₂, in agreement with available experimental data. We also confirm the crystal structures of NaAu₂ and Na₂Au, that were fully characterized in experiments, and identify a candidate ground-state structure for the experimental stoichiometry NaAu. Moreover, we obtain three other stoichiometries, namely Na₃Au₂, Na₃Au and Na₅Au, that could be thermodynamically stable. We do not find any evidence for the existence of the experimentally proposed composition NaAu₅. Finally, we perform phonon calculations to check the dynamical stability of all reported phases and we simulate x-ray diffraction spectra for comparison with future experimental data.

The metal-organic framework (MOF) MFU-4 l containing Co(II) centers and Cl⁻ ligands has recently shown promising redox activity. Aiming for further improved MOF catalysts for oxidation processes employing molecular oxygen we present a density-functional theory (DFT) based computational screening approach to identify promising metal center and ligand combinations within the MFU-4 l structural family. Using the O₂ binding energy as a descriptor for the redox property, we show that relative energetic trends in this descriptor can reliably be obtained at the hybrid functional DFT level and using small cluster (scorpionate-type complex) models. Within this efficient computational protocol we screen a range of metal center/ligand combinations and identify several candidate systems that offer more exothermic O₂ binding than the original Co/Cl-based MFU-4 l framework.

Virtual screening involves the generation of structure libraries, automated analysis to predict properties related to application performance and subsequent screening to identify lead systems and estimate critical structure–property limits across a targeted chemical design space. This approach holds great promise for informing experimental discovery and development efforts for next-generation materials, such as organic semiconductors. In this work, the virtual screening approach is illustrated for nitrogen-substituted pentacene molecules to identify systems for development as electron acceptor materials for use in organic photovoltaic (OPV) devices. A structure library of tetra-azapentacenes (TAPs) was generated by substituting four nitrogens for CH at 12 sites on the pentacene molecular framework. Molecular properties (e.g. E_LUMO, E_g and μ) were computed for each candidate structure using hybrid DFT at the B3LYP/6-311G** level of theory. The resulting TAPs library was then analyzed with respect to intrinsic properties associated with OPV acceptor performance. Marcus reorganization energies for charge transport for the most favorable TAP candidates were then calculated to further determine suitability as OPV electron acceptors. The synthesis, characterization and OPV device testing of TAP materials is underway, guided by these results.

Direct production of hydrogen from water and sunlight requires stable and abundantly available semiconductors with well positioned band edges relative to the water red-ox potentials. We have used density functional theory (DFT) calculations to investigate 300 oxides and oxynitrides in the Ruddlesden–Popper phase of the layered perovskite structure. Based on screening criteria for the stability, bandgaps and band edge positions, we suggest 20 new materials for the light harvesting photo-electrode of a one-photon water splitting device and 5 anode materials for a two-photon device with silicon as photo-cathode. In addition, we explore a simple rule relating the bandgap of the perovskite to the number of octahedra in the layered structure and the B-metal ion. Finally, the quality of the GLLB-SC potential used to obtain the bandgaps, including the derivative discontinuity, is validated against G₀W₀@LDA gaps for 20 previously identified oxides and oxynitrides in the cubic perovskite structure.

Carbon atoms can form structures in one, two and three dimensions due to their unique chemical versatility. In terms of thermal conductivity, carbon polymorphs cover a wide range from very low values with amorphous carbon to very high values with diamond, carbon nanotubes and graphene. Schwarzites are a class of three-dimensional fully covalent sp²-bonded carbon polymorphs, with the same local chemical environment as graphene and carbon nanotubes, but negative Gaussian curvature. We calculate the thermal conductivity of a (10,0) carbon nanotube, graphene and two schwarzites with different curvature, by molecular dynamics simulations based on the Tersoff empirical potential. We find that schwarzites present a thermal conductivity two orders of magnitude smaller than nanotubes and graphene. The reason for such large difference is explained by anharmonic lattice dynamics calculations, which show that phonon group velocities and mean free paths are much smaller in schwarzites than in nanotubes and graphene. Their reduced thermal conductivity, in addition to tunable electronic properties, indicate that schwarzites could pave the way towards all-carbon thermoelectric technology with high conversion efficiency.

The phase stability, electronic structure and transport properties of binary 3d, 4d and 5d transition metal silicides are investigated using high-throughput density functional calculations. An overall good agreement is found between the calculated 0 K phase diagrams and experiment. We introduce descriptors for the phase-stability and thermoelectric properties and hereby identify several candidates with potential for thermoelectric applications. This includes known thermoelectrics like Mn₄Si₇, β-FeSi₂, Ru₂Si₃ and CrSi₂ as well as new potentially meta-stable materials like Rh₃Si₅, Fe₂Si₃ and an orthorhombic CrSi₂ phase. Analysis of the electronic structure shows that the gap formation in most of the semiconducting transition metal silicides can be understood with simple hybridization models. The transport properties of the Mn₄Si₇, Ru₂Ge₃ and Ir₃Si₅ structure types and the orthorhombic CrSi₂ phase are discussed. The calculated transport properties are in good agreement with available experimental data. It is shown that a better thermoelectric performance may be achieved upon optimal doping. Finally, the high-throughput data are analysed and rationalized using a simple tight-binding model.

We present an adaptive resolution simulation of aqueous salt (NaCl) solutions at ambient conditions using the adaptive resolution scheme. Our multiscale approach concurrently couples the atomistic and coarse-grained models of the aqueous NaCl, where water molecules and ions change their resolution while moving from one resolution domain to the other. We employ standard extended simple point charge (SPC/E) and simple point charge (SPC) water models in combination with AMBER and GROMOS force fields for ion interactions in the atomistic domain. Electrostatics in our model are described by the generalized reaction field method. The effective interactions for water–water and water–ion interactions in the coarse-grained model are derived using structure-based coarse-graining approach while the Coulomb interactions between ions are appropriately screened. To ensure an even distribution of water molecules and ions across the simulation box we employ thermodynamic forces. We demonstrate that the equilibrium structural, e.g. radial distribution functions and density distributions of all the species, and dynamical properties are correctly reproduced by our adaptive resolution method. Our multiscale approach, which is general and can be used for any classical non-polarizable force-field and/or types of ions, will significantly speed up biomolecular simulation involving aqueous salt.

State-of-the-art alloys for hard coating applications, such as TiAlN, are known to suffer from decreased hardness during heat treatment in excess of 900 °C due to the formation of detrimental wurtzite AlN phases. Recent research has shown that multicomponent alloying with additional transition metals (TMs) such as Cr can shift the onset of the phase transformations to higher temperatures, but a search for new alloys is generally time-consuming due to the large number of processes that influence material properties along with the large number of alloy compositions that have to be synthesized. To overcome this difficulty we carry out systematic first-principles calculations aimed at finding potential new multicomponent TM aluminum nitride alloys for advanced hard coating applications. We direct our search towards a specific property, the thermal stability of the coating. In particular, we concentrate on the thermodynamic stability of the cubic B1 TM–Al–N phase relative to the wurtzite phase, and choose the enthalpy difference between them as our search descriptor. We perform ab initio calculations for all TMs, considered as impurities in AlN, and identify the most promising candidates that may improve the thermal stability. We present arguments that these elements should be targeted in future in-depth studies, theoretical, as well as experimental.

Nowadays, simulation techniques are routinely used to generate accurate models of the structures of crystalline and amorphous solids, to study surfaces, defects and the properties of complex systems, and to screen possible candidate materials for the most diverse types of technological applications. The screening of novel molecular structures has been so far pursued by calculation of intrinsic properties with first-principle methods. Still, the use of intrinsic properties as scoring functions may not always be optimal for systems of high complexity. In these cases, increasingly detailed and realistic simulations that take into account the interaction with the surrounding molecules are of crucial importance. In this paper, we present an effective way to screen different solvents with respect to their chemical stability versus Li₂O₂ solid particles. To achieve this, the minimum energy paths for different types of reactions of a series of aprotic solvents (acetonitrile and pivalonitrile, dimethyl sulphoxide, N-methyl-2-pyrrolidone and some of its derivatives, penta ethylene glycol (PEG-5) and a fluorinated derivative) with solid Li₂O₂ are computed and reported. From these data, we can extract the reaction energy barriers, which compare extremely well with the available experimental data and offer a convenient way for screening and designing suitable solvents for Li–air batteries from first-principle calculations.

The combination of modern scientific computing with electronic structure theory can lead to an unprecedented amount of data amenable to intelligent data analysis for the identification of meaningful, novel and predictive structure–property relationships. Such relationships enable high-throughput screening for relevant properties in an exponentially growing pool of virtual compounds that are synthetically accessible. Here, we present a machine learning model, trained on a database of ab initio calculation results for thousands of organic molecules, that simultaneously predicts multiple electronic ground- and excited-state properties. The properties include atomization energy, polarizability, frontier orbital eigenvalues, ionization potential, electron affinity and excitation energies. The machine learning model is based on a deep multi-task artificial neural network, exploiting the underlying correlations between various molecular properties. The input is identical to ab initio methods, i.e. nuclear charges and Cartesian coordinates of all atoms. For small organic molecules, the accuracy of such a 'quantum machine' is similar, and sometimes superior, to modern quantum-chemical methods—at negligible computational cost.

The design of self-assembling materials in the nanometer scale focuses on the fabrication of a class of organic and inorganic subcomponents that can be reliably produced on a large scale and tailored according to their vast applications for, e.g. electronics, therapeutic vectors and diagnostic imaging agent carriers, or photonics. In a recent publication (Capone et al 2012 Phys. Rev. Lett. 109 238301), diblock copolymer stars have been shown to be a novel system, which is able to hierarchically self-assemble first into soft patchy particles and thereafter into more complex structures, such as the diamond and cubic crystal. The self-aggregating single star patchy behavior is preserved from extremely low up to high densities. Its main control parameters are related to the architecture of the building blocks, which are the number of arms (functionality) and the fraction of attractive end-monomers. By employing a variety of computational and theoretical tools, ranging from the microscopic to the mesoscopic, coarse-grained level in a systematic fashion, we investigate the crossover between the formation of microstructure versus macroscopic phase separation, as well as the formation of gels and networks in these systems. We finally show that telechelic star polymers can be used as building blocks for the fabrication of open crystal structures, such as the diamond or the simple-cubic lattice, taking advantage of the strong correlation between single-particle patchiness and lattice coordination at finite densities.