Multiscale modeling of polymers closely coupled to Broad Q neutron scattering from NIMROD

2013 ◽  
Vol 1524 ◽  
Author(s):  
Thomas Gkourmpis ◽  
Daniel Lopez ◽  
Geoffrey R. Mitchell
Keyword(s):  
Structure Factor ◽  
Chain Structure ◽  
Distribution Functions ◽  
Chain Conformation ◽  
Coarse Grained ◽  
Lamellar Thickness ◽  
Single Chain ◽  
Crystal Unit Cell ◽  
Key Length ◽  
Using Data

ABSTRACTWe use data over an extended Q range from 0.01 to 100Å-1 from the recently commissioned NIMROD instrument at the ISIS pulsed neutron source to develop a multi-scale inverse modeling procedure which will provide insight in to the phase transformations of polymer systems. The first level of our procedure is atomistic and we use internal coordinates (bond length, bond angles and torsion angles) to define the polymer chain in full atomistic detail. Values were assigned to each internal coordinate within the chain using a stochastic Monte Carlo method in which the probabilities were drawn from distributions representing the possible range of values. Using this approach, random chain configurations could be rapidly built and the intrachain structure factor calculated utilizing a small set of parameters and compared with the experimental function. Parameters representing the probability distribution functions were systematically varied using a grid search to find the values which gave the best fit to the structure factor for Q > 3Å-1 in order to determine the details of the chain conformation in the molten phase. This process was repeated for data over the same extended Q range obtained at lower temperatures where the polymer was expected to crystallize. Polymers crystallize via chainfolded thin lamellae crystals. Such crystals give rise to an intense peak at Q ∼ 0.03Å-1. This scattering can be calculated using a lamellar stack model, coarse-grained from the single chain structure. We describe this approach using data obtained on the crystallization from the melt phase of perdeuterated polymers. The objective here is to follow the three key length scales; the chain folded lamellar thickness of ∼ 10nm, the crystal unit cell ∼ 1nm and the detail of the chain conformation is ∼ 0.1nm.

scholarly journals Conformation of Flexible and Semiflexible Chains Confined in Nanoposts Array of Various Geometries

Polymers ◽  
2020 ◽  
Vol 12 (5) ◽  
pp. 1064 ◽  
Author(s):  
Zuzana Benková ◽  
Lucia Rišpanová ◽  
Peter Cifra
Keyword(s):  
Structure Factor ◽  
Volume Fraction ◽  
Occupation Number ◽  
Chain Extension ◽  
Coarse Grained ◽  
Square Lattice ◽  
Structural Behavior ◽  
Single Chain ◽  
Flexible Chain ◽  
Two Factors

The conformation and distribution of a flexible and semiflexible chain confined in an array of nanoposts arranged in parallel way in a square-lattice projection of their cross-section was investigated using coarse-grained molecular dynamics simulations. The geometry of the nanopost array was varied at the constant post diameter dp and the ensuing modifications of the chain conformation were compared with the structural behavior of the chain in the series of nanopost arrays with the constant post separation Sp as well as with the constant distance between two adjacent post walls (passage width) wp. The free energy arguments based on an approximation of the array of nanopost to a composite of quasi-channels of diameter dc and quasi-slits of height wp provide semiqualitative explanations for the observed structural behavior of both chains. At constant post separation and passage width, the occupation number displays a monotonic decrease with the increasing geometry ratio dc/wp or volume fraction of posts, while a maximum is observed at constant post diameter. The latter finding is attributed to a relaxed conformation of the chains at small dc/wp ratio, which results from a combination of wide interstitial volumes and wide passage apertures. This maximum is approximately positioned at the same dc/wp value for both flexible and semiflexible chains. The chain expansion from a single interstitial volume into more interstitial volumes also starts at the same value of dc/wp ratio for both chains. The dependence of the axial chain extension on the dc/wp ratio turns out to be controlled by the diameter of the interstitial space and by the number of monomers in the individual interstitial volumes. If these two factors act in the same way on the axial extension of chain fragments in interstitial volumes the monotonic increase of the axial chain extension with the dc/wp in the nanopost arrays is observed. At constant wp, however, these two factors act in opposite way and the axial chain extension plotted against the dc/wp ratio exhibits a maximum. In the case of constant post diameter, the characteristic hump in the single chain structure factor whose position correlates with the post separation is found only in the structure factor of the flexible chain confined in the nanopost array of certain value of Sp. The structure factor of the flexible chain contains more information on the monomer organization and mutual correlations than the structure factor of the semiflexible chain. The stiffer chain confined in the nanopost array is composed of low number of statistical segments important for the presence of respective hierarchical regimes in the structure factor.

scholarly journals Targeted sequence design within the coarse-grained polymer genome

2020 ◽  
Vol 6 (43) ◽  
pp. eabc6216
Author(s):  
Michael A. Webb ◽  
Nicholas E. Jackson ◽  
Phwey S. Gil ◽  
Juan J. de Pablo
Keyword(s):  
Machine Learning ◽  
Materials Science ◽  
Chain Structure ◽  
Data Availability ◽  
Data Driven ◽  
Coarse Grained ◽  
Grand Challenge ◽  
Sequence Information ◽  
Single Chain ◽  
Sequence Design

The chemical design of polymers with target structural and/or functional properties represents a grand challenge in materials science. While data-driven design approaches are promising, success with polymers has been limited, largely due to limitations in data availability. Here, we demonstrate the targeted sequence design of single-chain structure in polymers by combining coarse-grained modeling, machine learning, and model optimization. Nearly 2000 unique coarse-grained polymers are simulated to construct and analyze machine learning models. We find that deep neural networks inexpensively and reliably predict structural properties with limited sequence information as input. By coupling trained ML models with sequential model-based optimization, polymer sequences are proposed to exhibit globular, swollen, or rod-like behaviors, which are verified by explicit simulations. This work highlights the promising integration of coarse-grained modeling with data-driven design and represents a necessary and crucial step toward more complex polymer design efforts.

Rapid Isolation of High Molecular Weight Urokinase from Native Human Urine

1982 ◽  
Vol 47 (03) ◽  
pp. 197-202 ◽  
Author(s):  
Kurt Huber ◽  
Johannes Kirchheimer ◽  
Bernd R Binder
Keyword(s):  
Molecular Weight ◽  
High Molecular Weight ◽  
Human Urine ◽  
Gel Filtration ◽  
Chain Structure ◽  
The Other ◽  
Single Chain ◽  
Apparent Homogeneity ◽  
Sequential Adsorption

SummaryUrokinase (UK) could be purified to apparent homogeneity starting from crude urine by sequential adsorption and elution of the enzyme to gelatine-Sepharose and agmatine-Sepharose followed by gel filtration on Sephadex G-150. The purified product exhibited characteristics of the high molecular weight urokinase (HMW-UK) but did contain two distinct entities, one of which exhibited a two chain structure as reported for the HMW-UK while the other one exhibited an apparent single chain structure. The purification described is rapid and simple and results in an enzyme with probably no major alterations. Yields are high enough to obtain purified enzymes for characterization of UK from individual donors.

scholarly journals Single Chain Dynamic Structure Factor of Linear Polymers in an All-Polymer Nano-Composite

2016 ◽  
Vol 49 (6) ◽  
pp. 2354-2364 ◽  
Author(s):  
Arantxa Arbe ◽  
José A. Pomposo ◽  
Isabel Asenjo-Sanz ◽  
Debsindhu Bhowmik ◽  
Oxana Ivanova ◽  
...  
Keyword(s):  
Structure Factor ◽  
Dynamic Structure ◽  
Dynamic Structure Factor ◽  
Linear Polymers ◽  
Single Chain ◽  
Nano Composite ◽  
Chain Dynamic

scholarly journals Single chain structure in thin polymer films: corrections to Flory’s and Silberberg’s hypotheses

2005 ◽  
Vol 17 (20) ◽  
pp. S1697-S1709 ◽  
Author(s):  
A Cavallo ◽  
M Müller ◽  
J P Wittmer ◽  
A Johner ◽  
K Binder
Keyword(s):  
Polymer Films ◽  
Chain Structure ◽  
Thin Polymer Films ◽  
Single Chain ◽  
Thin Polymer

scholarly journals Probabilistic Damage Detection and Identification of Coupled Structural Parameters using Bayesian Model Updating with Added Mass

2021 ◽  
Author(s):  
jice zeng ◽  
Young Hoon Kim
Keyword(s):  
Convergence Rate ◽  
Damage Detection ◽  
Bayesian Model ◽  
Model Updating ◽  
Coupling Effect ◽  
Structural Parameters ◽  
Added Mass ◽  
Distribution Functions ◽  
Single Chain ◽  
Characteristic Equations

Damage detection inevitably involves uncertainties originated from measurement noise and modeling error. It may cause incorrect damage detection results if not appropriately treating uncertainties. To this end, vibration-based Bayesian model updating (VBMU) is developed to utilize vibration responses or modal parameters to identify structural parameters (e.g., mass and stiffness) as probability distribution functions (PDF) and uncertainties. However, traditional VBMU often assumes that mass is well known and invariant because simultaneous identification of mass and stiffness may yield an unidentifiable problem due to the coupling effect of the mass and stiffness. In addition, the posterior PDF in VBMU is usually approximated by single-chain based Markov Chain Monte Carlo (MCMC), leading to a low convergence rate and limited capability for complex structures. This paper proposed a novel VBMU to address the coupling effect and identify mass and stiffness by adding known mass. Two vibration data sets are acquired from original and modified systems with added mass, giving the new characteristic equations. Then, the posterior PDF is reformulated by measured data and predicted counterparts from new characteristic equations. For efficiently approximating the posterior PDF, Differential Evolutionary Adaptive Metropolis (DREAM) Algorithm are adopted to draw samples by running multiple Markov chains parallelly to enhance convergence rate and sufficiently explore possible solutions. Finally, a numerical example with a ten-story shear building and a laboratory-scale three-story frame structure are utilized to demonstrate the efficacy of the proposed VBMU framework. The results show that the proposed method can successfully identify both mass and stiffness, and their uncertainties. Reliable probabilistic damage detection can also be achieved.

Comparison of Annual Maximum and Peaks Over Threshold Methods with Automated Threshold Selection in Flood Frequency Analysis: A Case Study for Australia

2021 ◽  
Author(s):  
Xiao Pan ◽  
Ataur Rahman
Keyword(s):  
Frequency Analysis ◽  
Flood Frequency ◽  
Distribution Functions ◽  
Flood Frequency Analysis ◽  
Annual Maximum ◽  
Threshold Selection ◽  
Peaks Over Threshold ◽  
Design Flood ◽  
Threshold Detection ◽  
Using Data

Abstract Flood frequency analysis (FFA) enables fitting of distribution functions to observed flow data for estimation of flood quantiles. Two main approaches, Annual Maximum (AM) and peaks-over-threshold (POT) are adopted for FFA. POT approach is under-employed due to its complexity and uncertainty associated with the threshold selection and independence criteria for selecting peak flows. This study evaluates the POT and AM approaches using data from 188 gauged stations in south-east Australia. POT approach adopted in this study applies a different average numbers of events per year fitted with Generalised Pareto (GP) distribution with an automated threshold detection method. The POT model extends its parametric approach to Maximum Likelihood Estimator (MLE) and Point Moment Weighted Unbiased (PMWU) method. Generalised Extreme Value (GEV) distribution using L-moment estimator is used for AM approach. It has been found that there is a large difference in design flood estimates between the AM and POT approaches for smaller average recurrence intervals (ARI), with a median difference of 25% for 1.01 year ARI and 5% for 50 and 100 years ARIs.

UNRES-Dock—protein–protein and peptide–protein docking by coarse-grained replica-exchange MD simulations

2020 ◽  
Author(s):  
Paweł Krupa ◽  
Agnieszka S Karczyńska ◽  
Magdalena A Mozolewska ◽  
Adam Liwo ◽  
Cezary Czaplewski
Keyword(s):  
Protein Complexes ◽  
Md Simulations ◽  
Protein Docking ◽  
Conformational Space ◽  
Coarse Grained ◽  
Supplementary Information ◽  
Replica Exchange ◽  
Variable Degree ◽  
Single Chain ◽  
Simulation Speed

Abstract Motivation The majority of the proteins in living organisms occur as homo- or hetero-multimeric structures. Although there are many tools to predict the structures of single-chain proteins or protein complexes with small ligands, peptide–protein and protein–protein docking is more challenging. In this work, we utilized multiplexed replica-exchange molecular dynamics (MREMD) simulations with the physics-based heavily coarse-grained UNRES model, which provides more than a 1000-fold simulation speed-up compared with all-atom approaches to predict structures of protein complexes. Results We present a new protein–protein and peptide–protein docking functionality of the UNRES package, which includes a variable degree of conformational flexibility. UNRES-Dock protocol was tested on a set of 55 complexes with size from 43 to 587 amino-acid residues, showing that structures of the complexes can be predicted with good quality, if the sampling of the conformational space is sufficient, especially for flexible peptide–protein systems. The developed automatized protocol has been implemented in the standalone UNRES package and in the UNRES server. Availability and implementation UNRES server: http://unres-server.chem.ug.edu.pl; UNRES package and data used in testing of UNRES-Dock: http://unres.pl. Supplementary information Supplementary data are available at Bioinformatics online.

MX-type single chain complexes with an aromatic in-plane ligand: incorporation of aromatic interactions for stabilizing the chain structure

2019 ◽  
Vol 48 (22) ◽  
pp. 7828-7834 ◽  
Author(s):  
Unjila Afrin ◽  
Hiroaki Iguchi ◽  
Mohammad Rasel Mian ◽  
Shinya Takaishi ◽  
Hiromichi Yamakawa ◽  
...  
Keyword(s):  
Chain Structure ◽  
Single Chain ◽  
One Dimensional ◽  
Aromatic Interactions ◽  
Chain Complexes ◽  
First Time

MX-type one-dimensional complexes containing only an aromatic in-plane ligand were synthesized for the first time.

scholarly journals Multi-point observations of intermittency in the cusp regions

2007 ◽  
Vol 14 (4) ◽  
pp. 525-534 ◽  
Author(s):  
M. M. Echim ◽  
H. Lamy ◽  
T. Chang
Keyword(s):  
Magnetic Field ◽  
Magnetic Energy ◽  
Haar Wavelet ◽  
Distribution Functions ◽  
Statistical Properties ◽  
Coarse Grained ◽  
Haar Wavelet Transform ◽  
Intermittent Behavior ◽  
Field Fluctuations ◽  
The Magnetic Field

Abstract. In this paper we investigate the statistical properties of magnetic field fluctuations measured by the four Cluster spacecraft in the cusp and close to the interface with the magnetospheric lobes, magnetopause and magnetosheath. At lower altitudes along the outbound orbit of 26 February 2001, the magnetic field fluctuations recorded by all four spacecraft are random and their Probability Distribution Functions (PDFs) are Gaussian at all scales. The flatness parameter, F – related to the kurtosis of the time series, is equal to 3. At higher altitudes, in the cusp and its vicinity, closer to the interface with the magnetopause and magnetosheath, the PDFs from all Cluster satellites are non-Gaussian and show a clear intermittent behavior at scales smaller than τG≈ 61 s (or 170 km). The flatness parameter increases to values greater than 3 for scales smaller than τG. A Haar wavelet transform enables the identification of the "events" that produce sudden variations of the magnetic field and of the scales that have most of the power. The LIM parameter (i.e. normalized wavelet power) indicates that events for scales below 65 s are non-uniformly distributed throughout the cusp passage. PDFs, flatness and wavelet analysis show that at coarse-grained scales larger than τG the intermittency is absent in the cusp. Fluctuations of the magnetic energy observed during the same orbit in the magnetosheath show PDFs that tend toward a Gaussian at scales smaller than τG found in the cusp. The flatness analysis confirms the decreasing of τG from cusp to magnetosheath. Our analysis reveals the turbulent cusp as a transition region from a non-intermittent turbulent state inside the magnetosphere to an intermittent turbulent state in the magnetosheath that has statistical properties resembling the solar wind turbulence. The observed turbulent fluctuations in the cusp suggests a phenomenon of nonlinear interactions of plasma coherent structures as in contemporary models of space plasma turbulence.

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