Theories and simulations of polymers using coarse-grained models

2014 Fall.Includes bibliographical references.Full atomistic simulations of many-chain systems such as polymer melts are not feasible at present due to their formidable computational requirements. Molecular simulations with coarse-grained (CG) models have to be used instead, which interact with soft potentials that allow complete particle overlapping. One advantage of soft potentials is that it allows to simulate systems with experimentally accessible fluctuations and correlations because the invariant degree of polymerization (controlling the system fluctuations and correlations) and the polymer chain length N are decoupled using soft potentials. Another advantage is that it provides a powerful means for unambiguously and quantitatively revealing the effects of fluctuations and correlations of polymers when comparing simulation results with corresponding theoretical predictions based on the same model systems thus without any parameter fitting. Using the recently proposed fast lattice Monte Carlo (FLMC) simulations and the corresponding lattice self-consistent field (LSCF) calculations based on the same model system, where multiple occupancy of lattice sites is allowed, we studied the coil-globule transition (CGT) of one-mushroom polymeric systems and the fused-separated transition (FST) of two-mushroom polymeric systems. With soft potential, we systematically constructed the phase diagrams of one- and two-mushroom systems using LSCF theory, which neglects the interchain fluctuations and correlations. The LSCF predictions were then directly compared with the simulation results without any parameter-fitting, the fluctuation/correlation effects on these phase transitions are then unambiguously quantified. Similarly, for disordered symmetric diblock copolymers in continuum, we directly compared the thermodynamic and structural properties from fast off-lattice Monte Carlo simulations, integral equation (IE) theories (including the reference interaction site model and polymer reference interaction site model), and Gaussian fluctuation theory based on the same model systems, and unambiguously quantified the consequences of various theoretical approximations and the validity of these theories in describing the fluctuations/correlations in disordered diblock copolymers. In order to answer the questions of how to obtain the CG model and how the CG level affects the properties of CG model, we then performed systematic and simulation-free coarse graining of homopolymer melts. In this work, we proposed a systematic and simulation-free strategy for structure-based coarse graining of homopolymer melts, where each chain of Nm monomers is uniformly divided into N segments, with the spatial position of each segment corresponding to the center-of-mass of its monomers. We used integral-equation theories, instead of molecular simulations, to obtain the structural and thermodynamic properties of both original and CG systems, and quantitatively examined how the effective pair potentials between CG segments and the thermodynamic properties of CG systems vary with N. Our coarse-graining strategy is much faster than those using molecular simulations and provides the quantitative basis for choosing the appropriate N-values. Taking the simple hard-core Gaussian thread model (K. S. Schweizer and J. G. Curro, Chem. Phys. 149, 105 (1990)) as the original system, we demonstrated our strategy and compared in detail the various integral-equation theories and closures for coarse graining. Our numerical results showed that the effective CG potentials using various closures can be collapsed approximately onto the same curve for different N, and that structure-based coarse graining cannot give the thermodynamic consistency between original and CG systems at any N < Nm. The CG potential from structure-based coarse graining can further be used to parameterize CG potentials with a given analytic functional form containing finite number of parameters, which is much more convenient to use in molecular simulations than the numerically tabulated CG potentials from structure-based coarse graining. In this work, we applied our systematic and simulation-free strategy to the recently proposed relative-entropy-based coarse graining, which minimizes the information loss quantified by the relative entropy. The values of relative entropy obtained from relative-entropy-based coarse graining with different CG potential functional forms can further be compared to determine the appropriate functional form or number of parameters. Note that the ideal-chain conformations were used in both structure-based and relative-entropy-based coarse-graining strategies, which is not valid for systems with strong pair interactions or small invariant degree of polymerization, self-consistent integral equation theory can be used to obtain more accurate intrachain pair correlations. In order to improve the quality of coarse graining, our proposed systematic and simulation-free coarse-graining strategy can be further combined with the self-consistent integral equation theory. This work will be remained for future researchers

Hyperspectral Anomaly Detection via Dictionary Construction-Based Low-Rank Representation and Adaptive Weighting

Anomaly detection (AD), which aims to distinguish targets with significant spectral differences from the background, has become an important topic in hyperspectral imagery (HSI) processing. In this paper, a novel anomaly detection algorithm via dictionary construction-based low-rank representation (LRR) and adaptive weighting is proposed. This algorithm has three main advantages. First, based on the consistency with AD problem, the LRR is employed to mine the lowest-rank representation of hyperspectral data by imposing a low-rank constraint on the representation coefficients. Sparse component contains most of the anomaly information and can be used for anomaly detection. Second, to better separate the sparse anomalies from the background component, a background dictionary construction strategy based on the usage frequency of the dictionary atoms for HSI reconstruction is proposed. The constructed dictionary excludes possible anomalies and contains all background categories, thus spanning a more reasonable background space. Finally, to further enhance the response difference between the background pixels and anomalies, the response output obtained by LRR is multiplied by an adaptive weighting matrix. Therefore, the anomaly pixels are more easily distinguished from the background. Experiments on synthetic and real-world hyperspectral datasets demonstrate the superiority of our proposed method over other AD detectors

Quantitative Study of Fluctuation Effects by Fast Lattice Monte Carlo Simulations. V. Incompressible Homopolymer Melts

Using fast lattice Monte Carlo (FLMC) simulations (Wang, Q. <i>Soft Matter</i> <b>2009</b>, <i>5</i>, 4564) and the corresponding polymer lattice field theories, including the lattice self-consistent field and Gaussian-fluctuation (LGF) theories, we studied a model system of incompressible homopolymer melts on a hexagonal lattice, where each lattice site is occupied by a total of ρ₀ ≥ 1 polymer segments. We generalized the cooperative motion algorithm (Pakula, T. <i>Macromolecules</i> <b>1987</b>, <i>20</i>, 679), as well as the related vacancy diffusion algorithm (Reiter, J.; Edling, T.; Pakula, T. <i>J. Chem. Phys.</i> <b>1990</b>, <i>93</i>, 837), originally proposed for the self- and mutual-avoiding walk (where ρ₀ = 1) to the case of ρ₀ > 1, where our generalized algorithm is highly efficient (i.e., nearly rejection-free). On the other hand, we extended the method of Wang (Wang, Z.-G. <i>Macromolecules</i> <b>1995</b>, <i>28</i>, 570) to calculate various single-chain properties in LGF theory. Direct comparisons between FLMC and LGF results, both of which are based on the same Hamiltonian (thus without any parameter-fitting between them), unambiguously and quantitatively reveal the effects of non-Gaussian fluctuations neglected by the latter. We found that FLMC results approach LGF predictions with increasing ρ₀, and that the leading order of non-Gaussian fluctuation effects on the single-chain properties is inversely proportional to ρ₀². Our work suggests that theories capturing the first-order non-Gaussian fluctuation effects may give quantitative agreement with FLMC simulations of incompressible homopolymer melts at ρ₀ ≥ 2 in two and three dimensions

Illumina sequencing analysis of the ruminal microbiota in high-yield and low-yield lactating dairy cows.

In this study, differences in the ruminal bacterial community between high-yield and low-yield lactating dairy cows under the same dietary conditions were investigated. Sixteen lactating dairy cows with similar parity and days in milk were divided into high-yield (HY) and low-yield (LY) groups based on their milk yield. On day 21, rumen content samples were collected, and their microbiota compositions were determined using high-throughput sequencing of the 16S rRNA gene by the Illumina MiSeq platform. During the study period, dry matter intake (DMI) and milk yield were measured daily, and milk composition was assessed 3 times per week. The results showed that the milk of the LY group tended to have higher fat (P = 0.08), protein (P = 0.01) and total solid contents (P = 0.04) than that of the HY group, while the HY group had higher ruminal propionate (P = 0.08) proportion and volatile fatty acid (VFA) (P = 0.02) concentrations. Principal coordinate analysis indicated significant differences in ruminal bacterial community compositions and structures between the HY group and LY group. The abundances of Ruminococcus 2, Lachnospiraceae and Eubacterium coprostanoligenes were significantly higher in the HY group than in the LY group. In addition, Bacteroides, Ruminococcus 2 and Candidatus-Saccharimonas were positively correlated with ruminal propionate proportion (r>0.4, P<0.05). These findings enhance the understanding of bacterial synthesis within the rumen and reveal an important mechanism underlying differences in milk production in dairy cows