Morphology dictated heterogeneous dynamics in two-dimensional aggregates.

Particulate aggregates occur in a variety of non-equilibrium steady-state morphologies ranging from finite-size compact crystalline structures to non-compact string-like conformations. This diversity is due to the competition between pair-wise short range attraction and long range repulsion between particles. We identify different microscopic mechanisms in action by following the simulated particle trajectories for different morphologies in two dimensions at a fixed density and temperature. In particular, we show that the compact clusters are governed by symmetric caging of particles by their nearest neighbors while sidewise asymmetric binding of particles leads to non-compact aggregates. The measured timescales for these two mechanisms are found to be distinctly different providing phenomenological evidence of a relation between microstructure and dynamics of particulate aggregates. Supporting these findings, the time dependent diffusivity is observed to differ across the morphological hierarchy, while the average long-time dynamics is, in general, sub-diffusive at 'low' temperatures. Finally, one generic relation between diffusivity and structural randomness, applicable to simple equilibrium systems, is validated for complex aggregate forming systems through further analysis of the same system at different temperatures.

A minimal description of morphological hierarchy in two-dimensional aggregates.

A dimensionless parameter Λ is proposed to describe a hierarchy of morphologies in two-dimensional (2D) aggregates formed due to varying competition between short-range attraction and long-range repulsion. Structural transitions from finite non-compact to compact to percolated structures are observed in the configurations simulated by molecular dynamics at a constant temperature and density. Configurational randomness across the transition, measured by the two-body excess entropy S2, exhibits data collapse with the average potential energy [small epsilon, Greek, macron] of the systems. Independent master curves are presented among S2, the reduced second virial coefficient B2* and Λ, justifying this minimal description. This work lays out a coherent basis for the study of 2D aggregate morphologies relevant to diverse nano- and bio-processes.

Proposal for manipulating functional interface properties of composite organic semiconductors with addition of designed macromolecules.

The arrangement of the electronic levels in an interface between organic semiconductors is crucial for the operation of devices such as solar cells and light emitting diodes. With the addition of designed macromolecules, we show that it is possible to control the relative position of the highest occupied molecular orbital and lowest unoccupied molecular orbital levels, and consequently improve the performance. The designed macromolecules consist of two end segments, each compatible with one of the interface components, and a central segment which adds functionality to the interface. The tails control the position and the orientation of the functional units. When the central functional unit is an electric dipole, an electrostatic field is created due to the orientation of the dipoles, which shifts the electronic levels in a controlled way. We develop a theoretical framework, based on self-consistent field theory, to study the concentration and the orientation of the central functional units. We find that the levels can shift by as much as several tenths of an eV.

Magnetic nonuniformity and thermal hysteresis of magnetism in a manganite thin film.

We measured the chemical and magnetic depth profiles of a single crystalline (La(1-x)Pr(x))(1-y)Ca(y)MnO(3-δ) (x=0.52±0.05, y=0.23±0.04, δ=0.14±0.10) film grown on a NdGaO(3) substrate using x-ray reflectometry, electron microscopy, electron energy-loss spectroscopy, and polarized neutron reflectometry. Our data indicate that the film exhibits coexistence of different magnetic phases as a function of depth. The magnetic depth profile is correlated with a variation of chemical composition with depth. The thermal hysteresis of ferromagnetic order in the film suggests a first-order ferromagnetic transition at low temperatures.

Strain-induced metal-insulator phase coexistence in perovskite manganites.

The coexistence of distinct metallic and insulating electronic phases within the same sample of a perovskite manganite, such as La(1-x-y)Pr(y)Ca(x)MnO3, presents researchers with a tool for tuning the electronic properties in materials. In particular, colossal magnetoresistance in these materials--the dramatic reduction of resistivity in a magnetic field--is closely related to the observed texture owing to nanometre- and micrometre-scale inhomogeneities. Despite accumulated data from various high-resolution probes, a theoretical understanding for the existence of such inhomogeneities has been lacking. Mechanisms invoked so far, usually based on electronic mechanisms and chemical disorder, have been inadequate to describe the multiscale, multiphase coexistence within a unified picture. Moreover, lattice distortions and long-range strains are known to be important in the manganites. Here we show that the texturing can be due to the intrinsic complexity of a system with strong coupling between the electronic and elastic degrees of freedom. This leads to local energetically favourable configurations and provides a natural mechanism for the self-organized inhomogeneities over both nanometre and micrometre scales. The framework provides a physical understanding of various experimental results and a basis for engineering nanoscale patterns of metallic and insulating phases.

Stress distributions in diblock copolymers.

We demonstrate how a generalized self-consistent field theory for polymer melts that includes elastic stress and strain fields can be applied to the study of AB diblock copolymers melts. By obtaining the stress distributions for volume conserving strain loadings where lamellar and hexagonal morphologies are stable, we show that the local stress is reduced at the domain interface but slightly enhanced in the immediate vicinity of the interface. The overall stress profile is the result of the combined effects of chain connectivity across the interface, which yields a positive contribution, and the immiscible nature of the monomers, which leads to a stress reduction because of interfacial tension.

Three-dimensional imaging of vortex structure in a ferroelectric nanoparticle driven by an electric field.

Topological defects of spontaneous polarization are extensively studied as templates for unique physical phenomena and in the design of reconfigurable electronic devices. Experimental investigations of the complex topologies of polarization have been limited to surface phenomena, which has restricted the probing of the dynamic volumetric domain morphology in operando. Here, we utilize Bragg coherent diffractive imaging of a single BaTiO3 nanoparticle in a composite polymer/ferroelectric capacitor to study the behavior of a three-dimensional vortex formed due to competing interactions involving ferroelectric domains. Our investigation of the structural phase transitions under the influence of an external electric field shows a mobile vortex core exhibiting a reversible hysteretic transformation path. We also study the toroidal moment of the vortex under the action of the field. Our results open avenues for the study of the structure and evolution of polar vortices and other topological structures in operando in functional materials under cross field configurations.Imaging of topological states of matter such as vortex configurations has generally been limited to 2D surface effects. Here Karpov et al. study the volumetric structure and dynamics of a vortex core mediated by electric-field induced structural phase transition in a ferroelectric BaTiO3 nanoparticle.

Machine learning bandgaps of double perovskites.

The ability to make rapid and accurate predictions on bandgaps of double perovskites is of much practical interest for a range of applications. While quantum mechanical computations for high-fidelity bandgaps are enormously computation-time intensive and thus impractical in high throughput studies, informatics-based statistical learning approaches can be a promising alternative. Here we demonstrate a systematic feature-engineering approach and a robust learning framework for efficient and accurate predictions of electronic bandgaps of double perovskites. After evaluating a set of more than 1.2 million features, we identify lowest occupied Kohn-Sham levels and elemental electronegativities of the constituent atomic species as the most crucial and relevant predictors. The developed models are validated and tested using the best practices of data science and further analyzed to rationalize their prediction performance.

Lateral diffusion of gramicidin S, M-13 coat protein and glycophorin in bilayers of saturated phospholipids. Mean field and Monte Carlo studies.

We have developed a general model that relates the lateral diffusion coefficient of one isolated large intrinsic molecule (mol. wt. greater than or approximately 1000) in a phosphatidylcholine bilayer to the static lipid hydrocarbon chain order. We have studied how protein lateral diffusion can depend upon protein-lipid interactions but have not investigated possible non-specific contributions from gel-state lattice defects. The model has been used in Monte Carlo simulations or in mean-field approximations to study the lateral diffusion coefficients of Gramicidin S, the M-13 coat protein and glycophorin in dimyristoyl- and dipalmitoylphosphatidylcholine (DMPC and DPPC) bilayers as functions of temperature. Our calculated lateral diffusion coefficients for Gramicidin S and the M-13 coat protein are in good agreement with what has been observed and suggest that Gramicidin S is in a dimeric form in DMPC bilayers. In the case of glycophorin we find that the 'ice breaker' effect can be understood as a consequence of perturbation of the lipid polar region around the protein. In order to understand this effect is necessary that the protein hydrophilic section perturb the polar regions of at least approx. 24 lipid molecules, in good agreement with the numbers of 29-30 measured using 31P-NMR. Because of lipid-lipid interactions this effect extends itself out to four or five lipid layers away from the protein so that the hydrocarbon chains of between approx. 74 and approx. 108 lipid molecules are more disordered in the gel phase, so contributing less to the transition enthalpy, in agreement with the numbers of 80-100 deduced from differential scanning calorimetry (DSC). An understanding of the abrupt change in the diffusion coefficient at a temperature below the main bilayer transition temperature requires an additional mechanism. We propose that this change may be a consequence of a 'coupling-uncoupling' transition involving the protein hydrophilic section and the lipid polar regions, which may be triggered by the lipid bilayer pretransition. Our calculation of the average number of gauche bonds per lipid chain as a function of temperature and distance away from an isolated polypeptide or integral protein shows the extent of statically disordered lipid around such molecules. The range of this disorder depends upon temperature, particularly near the main transition.

Classification of octet AB-type binary compounds using dynamical charges: A materials informatics perspective.

The role of dynamical (or Born effective) charges in classification of octet AB-type binary compounds between four-fold (zincblende/wurtzite crystal structures) and six-fold (rocksalt crystal structure) coordinated systems is discussed. We show that the difference in the dynamical charges of the fourfold and sixfold coordinated structures, in combination with Harrison's polarity, serves as an excellent feature to classify the coordination of 82 sp-bonded binary octet compounds. We use a support vector machine classifier to estimate the average classification accuracy and the associated variance in our model where a decision boundary is learned in a supervised manner. Finally, we compare the out-of-sample classification accuracy achieved by our feature pair with those reported previously.

Classification of ABO3 perovskite solids: a machine learning study.

We explored the use of machine learning methods for classifying whether a particular ABO3 chemistry forms a perovskite or non-perovskite structured solid. Starting with three sets of feature pairs (the tolerance and octahedral factors, the A and B ionic radii relative to the radius of O, and the bond valence distances between the A and B ions from the O atoms), we used machine learning to create a hyper-dimensional partial dependency structure plot using all three feature pairs or any two of them. Doing so increased the accuracy of our predictions by 2-3 percentage points over using any one pair. We also included the Mendeleev numbers of the A and B atoms to this set of feature pairs. Doing this and using the capabilities of our machine learning algorithm, the gradient tree boosting classifier, enabled us to generate a new type of structure plot that has the simplicity of one based on using just the Mendeleev numbers, but with the added advantages of having a higher accuracy and providing a measure of likelihood of the predicted structure.

Efficient computation of the structural phase behavior of block copolymers.

A numerical implementation of self-consistent mean-field theory for the structural phase behavior of block copolymers is proposed. Our scheme does not require a priori assumptions of the underlying mesoscopic symmetries. The method potentially enables us to characterize, with high accuracy, the structural phase diagram of block copolymers with significant architectural complexity. We illustrate the method by applying it to a triblock copolymer system.

Ordering mechanisms in triblock copolymers.

The ordering mechanisms for an ABC triblock copolymer system are studied using self-consistent field theory. We find a two-phase mechanism, similar to what has been suggested experimentally (two-step mechanism). Analysis of free energy components shows that the two-phase process comes about through a competition between stretching energy and interfacial energy. The mechanism is found to be sufficiently robust so as to make it potentially useful for device applications.

Mechanical loss in multiferroic materials at high frequencies: friction and the evolution of ferroelastic microstructures.

Energy absorption in multiferroic materials stems typically from strain relaxation which can be strong even when no extrinsic defects exist in the material. Computer simulations of a simple two-dimensional model on a generic, proper ferroelastic material identify the dissipative mechanisms associated with the dynamical motion as: a) advance and retraction of needle-shaped twin domains and, b) movement of kinks inside twin boundaries. Both movements involve friction losses.

High junction and twin boundary densities in driven dynamical systems.

A novel mechanism for the generation of device materials with very high domain boundary densities is described: we shear the sample in a computer experiment and achieve higher twin densities than in rapid quench. These domain patterns are very stable. Elastically soft materials (image with 6.4$ \times $10(5) atoms) has greater twin densities than hard materials, even for nano-crystals.

First-principles study of stability of the bcc and ω phases of a low Al concentration Nb1-xAlx alloy.

The phase stability and site occupancy of bcc (body centered cubic) Nb(5)Al and slightly rearranged atomic structures have been examined by means of first-principles calculations. In order to use first-principles methods, a periodic cell is required and we used ordered Nb(5)Al compounds as a tractable example of a low Al concentration Nb(1 - x)Al(x) alloy (in this case, for about 17 at.% Al). The instability against an ω-structure atomic displacement was also studied, since this structure is detrimental to ductility. Mulliken population analysis was used to provide an understanding of the hybridization between the atoms and the electronic origin of the site occupancy and instability of the underlying bcc structures. By making calculations for several different configurations of the Nb-Al system we estimated the strengths of the Nb-Nb and Nb-Al bonds. It is shown that the stability of the underlying bcc phases is directly related to Nb-Nb and Nb-Al first-nearest-neighbor interactions. The first-principles calculations were extended to finite temperature by including various contributions to the free energy. In particular, the vibrational free energy was calculated within the quasiharmonic approximation, and it is shown that the contribution of the low energy modes to the lattice entropy helps to stabilize ordered bcc phases against ω-type phase transformations. Semi-quasi-random structures were employed to study the stability of the ordered and disordered bcc phases. Our study showed, in agreement with experiment, that the ω, ordered, and disordered phases can coexist in a nonequilibrium state at finite temperature.