Towards Understanding the Self-assembly of Complicated Particles via Computation.

We develop advanced Monte Carlo sampling schemes and new methods of calculating thermodynamic partition functions that are used to study the self-assembly of complicated ``patchy '' particles. Patchy particles are characterized by their strong anisotropic interactions, which can cause critical slowing down in Monte Carlo simulations of their self-assembly. We prove that detailed balance is maintained for our implementation of Monte Carlo cluster moves that ameliorate critical slowing down and use these simulations to predict the structures self-assembled by patchy tetrominoes. We compare structures predicted from our simulations with those generated by an alternative learning-augmented Monte Carlo approach and show that the learning-augmented approach fails to sample thermodynamic ensembles. We prove one way to maintain detailed balance when parallelizing Monte Carlo using the checkerboard domain decomposition scheme by enumerating the state-to-state transitions for a simple model with general applicability. Our implementation of checkerboard Monte Carlo on graphics processing units enables accelerated sampling of thermodynamic properties and we use it to confirm the fluid-hexatic transition observed at high packing fractions of hard disks. We develop a new method, bottom-up building block assembly, which generates partition functions hierarchically. Bottom-up building block assembly provides a means to answer the question of which structures are favored at a given temperature and allows accelerated prediction of potential energy minimizing structures, which are difficult to determine with Monte Carlo methods. We show how the sequences of clusters generated by bottom-up building block assembly can be used to inform ``assembly pathway engineering'', the design of patchy particles whose assembly propensity is optimized for a target structure. The utility of bottom-up building block assembly is demonstrated for systems of CdTe/CdS tetrahedra, DNA-tethered nanospheres, colloidal analogues of patchy tetrominoes and shape-shifting particles.Ph.D.Chemical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/91509/1/erjank_1.pd

Computationally Connecting Organic Photovoltaic Performance to Atomistic Arrangements and Bulk Morphology

Rationally designing roll-to-roll printed organic photovoltaics requires a fundamental understanding of active layer morphologies optimized for charge separation and transport, and which ingredients can be used to self-assemble those morphologies. In this review article we discuss advances in three areas of computational modeling that provide insight into active layer morphology and the charge transport properties that result. We explain the computational bottlenecks prohibiting atomistically-detailed simulations of device-scale active layers and the coarse-graining and hardware acceleration strategies for overcoming them. We review coarse-grained simulations of organic photovoltaic active layers and show that high throughput simulations of experimentally-relevant length scales are now accessible. We describe a new Python package diffractometer that permits grazing-incidence X-ray scattering patterns of simulated active layers to be compared against experiments. We explain the accurate calculation of charge-carrier mobilities from coarse-grained active layer morphologies by using atomistic backmapping, quantum chemical calculations, and kinetic Monte Carlo simulations. We employ these simulations to show that ordering of poly(3-hexylthiophene-2,5-diyl) explains a factor of 1000 improvement in charge mobility. In concert, we present a suite of computational tools enabling large-scale electronic properties of organic photovoltaics to be studied and screened for by molecular simulations

Using Graphs to Quantify Energetic and Structural Order in Semicrystalline Oligothiophene Thin Films

In semicrystalline conjugated polymer thin films, the mobility of charges depends on the arrangement of the individual polymer chains. In particular, the ordering of the polymer backbones affects the charge transport within the film, as electron transfer generally occurs along the backbones with alternating single and double bonds. In this paper, we demonstrate that polymer ordering should be discussed not only in terms of structural but also energetic ordering of polymer chains. We couple data from molecular dynamics simulations and quantum chemical calculations to quantify both structural and energetic ordering of polymer chains. We leverage a graph-based representation of the polymer chains to quantify the transport pathways in a computationally efficient way. Next, we formulate the morphological descriptors that correlate well with hole mobility determined using kinetic Monte Carlo simulations. We show that the shortest and fastest path calculations are predictive of mobility in equilibrated morphologies. In this sense, we leverage graph-based descriptors to provide a basis for the quantitative structure property relationships

Self Assembled Clusters of Spheres Related to Spherical Codes

We consider the thermodynamically driven self-assembly of spheres onto the surface of a central sphere. This assembly process forms self-limiting, or terminal, anisotropic clusters (N-clusters) with well defined structures. We use Brownian dynamics to model the assembly of N-clusters varying in size from two to twelve outer spheres, and free energy calculations to predict the expected cluster sizes and shapes as a function of temperature and inner particle diameter. We show that the arrangements of outer spheres at finite temperatures are related to spherical codes, an ideal mathematical sequence of points corresponding to densest possible sphere packings. We demonstrate that temperature and the ratio of the diameters of the inner and outer spheres dictate cluster morphology and dynamics. We find that some N-clusters exhibit collective particle rearrangements, and these collective modes are unique to a given cluster size N. We present a surprising result for the equilibrium structure of a 5-cluster, which prefers an asymmetric square pyramid arrangement over a more symmetric arrangement. Our results suggest a promising way to assemble anisotropic building blocks from constituent colloidal spheres.Comment: 15 pages, 10 figure

Hybrid Material Based on the Lindquist Polyoxometalate [W6O19]2− and the organosulfur donor o-Me2TTF: A Combined Structural and Spectroscopic Study

International audienceThe synthesis, crystal structure and spectroscopic properties of the hybrid radical cation salt containing oxidized o-3,4-dimethyltetrathiafulvalene (o-Me2TTF) and the Lindquist polyoxometalate anion [W6O19]2− are reported. The title salt represents the first time a Lindquist polyoxometalate has been utilized as the counter anion with this unsymmetrical member of the TTF family of derivatives. The salt crystallizes in the triclinic space group P1¯ with a = 7.6211(7) Å, b = 9.5231(9) Å, c = 12.2148(11) Å, α = 105.5870(10)°, β = 106.8340(10)° and γ = 95.6950(10)°. Resolution of the solid state structure revealed that the o-Me2TTF radical cations aggregate as isolated face-to-face dimers with intradimer interactions between neighboring sulfur atoms at distances <3.6 Å. Hydrogen bonding was also observed between hydrogen atoms bound to sp 2-hybridized carbon atoms of o-Me2TTF and bridging oxygen atoms of [W6O19]2−. Single crystal IR and Raman spectra were also collected and provide further evidence that the o-Me2TTF donors have been oxidized to their corresponding radical cationic states

On the Tapping Mode Measurement for Young’s Modulus of Nanocrystalline Metal Coatings

Young’s modulus of nanocrystalline metal coatings is measured using the oscillating, that is, tapping, mode of a cantilever with a diamond tip. The resonant frequency of the cantilever changes when the diamond tip comes in contact with a sample surface. A Hertz-contact-based model is further developed using higher-order terms in a Taylor series expansion to determine a relationship between the reduced elastic modulus and the shift in the resonant frequency of the cantilever during elastic contact between the diamond tip and sample surface. The tapping mode technique can be used to accurately determine Young’s modulus that corresponds with the crystalline orientation of the sample surface as demonstrated for nanocrystalline nickel, vanadium, and tantalum coatings

Coarse-Graining of Anisotropic Molecules for Energy Materials Simulations

Coarse-graining--simplifying models of molecules by representing a collection of atoms with a simulation element like a sphere or ellipsoid--can significantly increase the timescales accessible to simulations without loss of structural accuracy. Spherical simulation elements are inaccurate representations of flat molecular structures, though, which are better represented with anisotropic shapes like ellipsoids. In this work we debug and extend open source software (GRiTS) for calculating the shapes and orientations of an ellipsoid representing a collection of atoms. These functionalities are useful for both validating the correctness of coarse-grained models and for training advanced anisotropic potentials that can be used in accelerated molecular simulations