Machine learning for crystal identification and discovery

As computers get faster, researchers -- not hardware or algorithms -- become the bottleneck in scientific discovery. Computational study of colloidal self-assembly is one area that is keenly affected: even after computers generate massive amounts of raw data, performing an exhaustive search to determine what (if any) ordered structures occur in a large parameter space of many simulations can be excruciating. We demonstrate how machine learning can be applied to discover interesting areas of parameter space in colloidal self assembly. We create numerical fingerprints -- inspired by bond orientational order diagrams -- of structures found in self-assembly studies and use these descriptors to both find interesting regions in a phase diagram and identify characteristic local environments in simulations in an automated manner for simple and complex crystal structures. Utilizing these methods allows analysis methods to keep up with the data generation ability of modern high-throughput computing environments.Comment: Fixed typo, added missing acknowledgment, added supplementary informatio

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

Liquid-Solid Transitions with Applications to Self-Assembly.

We study the thermodynamic and kinetic pathways by which liquids transform into solids, and their relation to the metastable states that commonly arise in self-assembly applications. As a case study in the formation of ordered metastable solids, we investigate the atomistic mechanism by which quasicrystals form. We show that the aperiodic growth of quasicrystals is controlled by the ability of the growing quasicrystal "nucleus" to incorporate kinetically trapped atoms into the solid phase with minimal rearrangement. In a related study, we propose a two-part mechanism for forming 3d dodecagonal quasicrystals by self-assembly. Our mechanism involves (1) attaching small mobile particles to the surface of spherical particles to encourage icosahedral packing and (2) allowing a subset of particles to deviate from the ideal spherical shape, to discourage close-packing. In addition to studying metastable ordered solids, we investigate the phenomenology and mechanism of the glass transition. We report measurements of spatially heterogeneous dynamics in a system of air-driven granular beads approaching a jamming transition, and show that the dynamics in our granular system are quantitatively indistinguishable from those for a supercooled liquid approaching a glass transition. In a second study of the glass transition, we use transition path sampling to study the structure, statistics and dynamics of localized excitations for several model glass formers. We show that the excitations are sparse and localized, and their size is temperature-independent. We show that their equilibrium concentration is proportional to exp[-Ja(1/T-1/To)], where "Ja" is the energy scale for irreversible particle displacements of length "a," and "To" is an onset temperature. We show that excitation dynamics is facilitated by the presence of other excitations, causing dynamics to slow in a hierarchical way as temperature is lowered. To supplement our studies of liquid-solid transitions, we introduce a shape matching framework for characterizing structural transitions in systems with complex particle shapes or morphologies. We provide an overview of shape matching methods, explore a particular class of metrics known as "harmonic descriptors," and show that shape matching methods can be applied to a wide range of nanoscale and microscale assembly applications.Ph.D.Chemical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/78931/1/askeys_1.pd

Multi-Scale Modeling of Cellulosic Polymers for Optimal Drug Delivery Properties in Solid Dispersion Formulation

Solid dispersion formulation is a promising method to maintain in vivo drug solubility and to improve drug efficacy. However, the exact drug stabilization and release mechanisms of the solid dispersion formulation are unclear. In this doctoral work, we present a multi-scale modeling approach to study the solvation behavior of cellulosic polymers and their interactions with the model drug phenytoin. We compare a number of atomistic force fields and find they give similar predictions for the stiffness of the cellulose chains. We then develop systematic coarse-grained (CG) force fields for two cellulosic polymers, namely methylcellulose and hydroxylpropyl methylcellulose acetate succinate (HPMCAS), based on the radial distribution functions obtained from atomistic simulations. We use the methylcellulose CG model to simulate the self-assembly of multiple 1000 monomers long polymer chains, and find that they spontaneously form ring or tubular structures with outer diameter of 14nm and void fraction of 26%. These structures appear to be precursors to the methylcellulose fibrils, whose diameter and structure are in good agreement with both theoretical and experimental results, and thus shine light on the methylcellulose gelation mechanism. We also present a simplified continuum analytical model to predict a phase map of the collapse conformations of a single self-attractive semiflexible polymer chain in solution into either folded or ring structures depending on the chains bending energy and self-interaction energy. The predicted phase map is in good qualitative agreement with simulation results for these collapsed structures. We use the HPACAS CG model to study the intermolecular interaction modes between 9 functional groups on HPMCAS and model drug phenytoin. We adopt two criteria to quantify the effectiveness of the polymeric excipients, namely 1) the ability to inhibit drug aggregation and 2) the ability to slow down drug release. We find the size of the functional group is more responsible for the former, while the intermolecular interaction strength is more responsible for the later. Therefore, hydroxypropyl acetyl group, which has both bulky size and strong interaction strength, is the most effective functional group, followed by hydroxypropyl and acetyl group, in good agreement with the results from experimental dissolution tests. In addition, we provide continuum models and predict that the drug release time from a typical solid dispersion particle with 2μm diameter ranges from several seconds to less than 10 minutes depending on the functional group. The systematic coarse-graining approach offer molecular level insights that aid the design of high performance polymeric excipients, and can be extended to cellulosic polymers with novel functional groups and additional drug candidates of interest. Thus, our multi-scale modeling approach is of great interest to the pharmaceutical and material design fields.PHDChemical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/138745/1/wenjunh_1.pd

Molecular Dynamics Modelling of Barium Silicate and Barium Fluorozirconate Glasses

Advancement in science and technology has profoundly depended on new types of glass innovation. The glasses that were studied in this project are binary barium silicate glasses, binary barium fluorozirconate glasses, ZBLAN glasses and ?Eu?^(3+) doped ZBLAN glass (the ZBLAN glasses are based on binary barium fluorozirconate glass). The high atomic number of barium in the barium silicate glasses provides high mass and high electron density providing its applications for heat and X-ray shielding. The phenomena such as phase separation in the barium silicate glass will affect its properties of durability and electrical conductivity. On the other hand, ZBLAN glasses have a broad infrared optical transmission window due to the weaker bonding/interaction of F^- ions. Due to the presence of lanthanum in the composition ZBLAN glass can be easily doped with rare-earth ions such as ?Eu?^(3+) giving it many optical applications such as optical amplifier and fibre lasers. Hence, it's essential to study the structure of these glasses to understand their properties for applications. This thesis used the classical molecular dynamics modelling technique to study the static atomic structure of glass. Generally, fluoride glasses can be formed by totally replacing oxygen atoms in oxide glasses by fluorine atoms. The oxide silicate glasses are common glasses that follow the Zachriasen rules of glass formation but the fluorozirconate glasses do not and lack fixed structural units. The structure analysis was performed at short-range order (e.g. coordination number, bond length and bond angle), medium-range order (e.g. network connectivity) and long- range order (e.g. phase separation). The related crystals were also simulated in similar conditions to the glasses to compare their atomic structure. Normally at short-range order glass structure is similar to its related crystal but the differences between them starts from the position and number of next nearest neighbours and increases thereafter. Additionally, the new methods such as rotational invariants and grid analysis were used to scrutinise structural units and phase separation respectively. The model of barium silicate glass shows good agreement with experimental diffraction data. The typical bond length and coordination number for Ba were 2.97 Å and approximately 7 respectively. The model did not show any phase separation at low Ba content and hence for further investigation very large models of alkaline earth silicate glasses were studied to see how Ba, Ca and Mg are distributed in the glass. The grid analysis was used to see the distributions which show homogeneity for Ba and Ca and inhomogeneity for Mg cation. The structural units of fluorozirconate glasses were carefully studied as they do not follow the Zachriasen glass model. The coordination number for Zr was mixture of 7 and 8. The rotational invariant analysis shows that the structural units of ZrF_n polyhedra for coordination number 7 and 8 were similar to Augmented Triangular Prism and Biaugmented Triangular Prism respectively. However, rotational invariant values for BaF_n polyhedra tend more towards random. The large complex model of ?Eu?^(3+) doped ZBLAN glass was made as it is studied for optical applications. The initial analysis was to observe whether Zr and Ba has similar structural roles as in binary fluorozirconate glass system which they do. Considering the extra elements in ZBLAN glass, Al behaves like a network former and has octahedra structural units whereas La and Na behave like modifiers. In the glass Eu was uniformly distributed with predominantly coordination number of 8 and does not have well defined structural units