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As a machine-recognizable representation of polymer connectivity, BigSMILES line notation extends SMILES from deterministic to stochastic structures. The same framework that allows BigSMILES to accommodate stochastic covalent connectivity can be extended to non-covalent bonds, enhancing its value for polymers, supramolecular materials, and colloidal chemistry. Non-covalent bonds are captured through the inclusion of annotations to pseudo atoms serving as complementary binding pairs, minimal key/value pairs to elaborate other relevant attributes, and indexes to specify the pairing among potential donors and acceptors or bond delocalization. Incorporating these annotations into BigSMILES line notation enables the representation of four common classes of non-covalent bonds in polymer science: electrostatic interactions, hydrogen bonding, metal-ligand complexation, and π-π stacking. The principal advantage of non-covalent BigSMILES is the ability to accommodate a broad variety of non-covalent chemistry with a simple user-orientated, semi-flexible annotation formalism. This goal is achieved by encoding a universal but non-exhaustive representation of non-covalent or stochastic bonding patterns through syntax for (de)protonated and delocalized state of bonding as well as nested bonds for correlated bonding and multi-component mixture. By allowing user-defined descriptors in the annotation expression, further applications in data-driven research can be envisioned to represent chemical structures in many other fields, including polymer nanocomposite and surface chemistry.

Polymeric materials are integral components of nearly every aspect of modern life. Today, polymer scientists and engineers devote significant resources to the design and development of these materials to meet growing societal needs. However, developing cheminformatic solutions for polymers has been difficult since they are large stochastic molecules with hierarchical structures spanning multiple length scales from chemical bonds to large molecular assemblies. Here we present the design for a general material data model that underpins the Community Resource for Innovation in Polymer Technology (CRIPT) data ecosystem. Among the key challenges that the data model addresses are the high complexity in defining a polymer structure and the intricacies involved with characterizing material properties. The core design of the data model is graph-based which provides flexibility, robustness, and scalability to support the community-driven mission. This approach to structuring material data provides the key advancements that the community needs to bring cheminformatics to polymer science and accelerate the development of new materials.

We show that the average length ⟨ L ⟩ of threadlike micelles in surfactant solutions predicted by fitting results of a mesoscopic simulation, the “pointer algorithm,” to experimental G′(ω), G″(ω) data, is longer than, and more accurate than, that from a scaling law that equates ⟨ L ⟩ / l e to the modulus ratio G 0 / G m i n ′ ′. Here, G0 is the plateau modulus, G m i n ′ ′ is obtained at the local minimum in G″, and l e is the entanglement length. The accuracy of the pointer algorithm is supported by the agreement of its predictions with results from a recent application of the slip-spring simulation method to threadlike micelles. Improved fits of the pointer algorithm to the slip-spring results are obtained for weakly entangled micelles (with an average number of entanglements of Z

Using both coarse-grained (CG) and fine-grained (FG) simulations we show how strain hardening in polymeric glasses under uniaxial extension arises from highly stretched strands that form as the pol...

We combine mechanical rheometry, diffusing wave spectroscopy (DWS), and small angle neutron scattering (SANS) with a simulation model, the "pointer algorithm", to obtain characteristic lengths and time constants for wormlike micelle (WLM) solutions over a range of salt concentrations encompassing the transition from unentangled to entangled solutions. The solutions contain sodium lauryl ethylene glycol sulfate (SLE1S), cocamidopropyl betaine (CAPB), and NaCl. The pointer algorithm is extended to include relaxation of unentangled micelles, allowing micelle parameters to be extracted from the rheology of partially entangled solutions. DWS provides the data at high frequency needed to determine micelle persistence length accurately. From pointer algorithm fits to rheology, we observe a salt-induced rapid change in micellar length as the solution enters the well-entangled regime and a weaker growth with surfactant concentration consistent with mean-field theory. At a lower surfactant concentration, micelle length and persistence length from SANS are roughly consistent with values from rheology once the lower surfactant concentration used in SANS is accounted for. This is, to our knowledge, the first time that quantitative comparisons of structural features including micelle length are made between rheology and SANS. Finally, scaling laws for micelle diffusion and recombination times indicate that micelle kinetics are reaction controlled leading to mean-field recombination with surrounding micelles over the entire range of concentration of interest except at very low and very high surfactant concentrations where either short micelles or branched micelle clusters are dominant.

We link micellar structures to their rheological properties for two surfactant body-wash formulations at various concentrations of salts and perfume raw materials (PRMs) using molecular simulations and micellar-scale modeling, as well as traditional surfactant packing arguments. The two body washes, namely, BW-1EO and BW-3EO, are composed of sodium lauryl ethylene glycol ether sulfate (SLEnS, where n is the average number of ethylene glycol repeat units), cocamidopropyl betaine (CAPB), ACCORD (which is a mixture of six PRMs), and NaCl salt. BW-3EO is an SLE3S-based body wash, whereas BW-1EO is an SLE1S-based body wash. Additional PRMs are also added into the body washes. The effects of temperature, salt, and added PRMs on micellar lengths, breakage times, end-cap free energies, and other properties are obtained from fits of the rheological data to predictions of the "Pointer Algorithm" [ Zou , W. ; Larson , R.G. J. Rheol. 2014 , 58 , 1 - 41 ], which is a simulation method based on the Cates model of micellar dynamics. Changes in these micellar properties are interpreted using the Israelachvili surfactant packing argument. From coarse-grained molecular simulations, we infer how salt modifies the micellar properties by changing the packing between the surfactant head groups, with the micellar radius remaining nearly constant. PRMs do so by partitioning to different locations within the micelles according to their octanol/water partition coefficient P

We present a hybrid model for polymeric glasses under deformation that combines a minimal model of segmental dynamics with a beads-and-springs model of a polymer, solved by Brownian dynamics (BD) simulations, whose relaxation is coupled to the segmental dynamics through the drag coefficient of the beads. This coarse-grained model allows simulations that are much faster than molecular dynamics and successfully capture the entire range of mechanical response including yielding, plastic flow, strain-hardening, and incomplete strain recovery. The beads-and-springs model improves upon the dumbbell model for glassy polymers proposed by Fielding et al. (Phys. Rev. Lett., 2012, 108, 048301) by capturing the small elastic recoil seen experimentally without the use of ad hoc adjustments of parameters required in the model of Fielding et al. With appropriate choice of parameters, predictions of creep, recovery, and segmental relaxation are found to be in good agreement with poly(methylmethacrylate) (PMMA) data of Lee et al. (Science, 2009, 323, 231-234). Our model shows dramatic differences in behavior of the segmental relaxation time between extensional creep and steady extension, and between extension and shear. The non-monotonic response of the segmental relaxation time to extensional creep and the small elastic recovery after removal of stress are shown to arise from sub-chains that are trapped between folds, and that become highly oriented and stretched at strains of order unity, connecting the behavior of glassy polymers under creep to that of dilute polymer solutions under fast extensional flows. We are also able to predict the effects of polymer pre-orientation in the parallel or orthogonal direction on the subsequent response to extensional deformation.

We apply our recently developed mesoscopic simulation method for entangled wormlike micelle (WLM) solutions to extract multiple micellar characteristic lengths and time constants: i.e., average micelle length, breakage rate, and entanglement and persistence lengths, from linear rheological measurements on commercial surfactant solutions, one containing sodium lauryl one ether sulfate (SLE1S), and the other containing both SLE1S and cocamidopropyl betaine, as well as a perfume mixture, in both cases with a sample salt (NaCl) added. Measurements include both mechanical rheometry and diffusing wave spectroscopy, the latter providing the high-frequency data needed to determine micelle persistence length accurately. By fitting the experimental data ( G′ and G″) across the entire frequency range through our iteration procedure, the method is of practical use in predicting micellar parameters, which are difficult to obtain from other theoretical or experimental methods. The dependence of micellar parameters on a...

We present a fast “pointer” simulation method that extends the model of Cates and coworkers for the rheology of entangled wormlike micelles. Our method includes not only reptation, breakage/rejoining, contour length fluctuations, and Rouse modes, which were included in Cates' model, but also constraint release, bending modes, and a cross-over to the tight entanglement regime, which had not been previously considered. Our method also contains correlations in micelle length across multiple breakage/rejoining cycles, not included in previous approaches. Our method uses “pointers” that track the ends of unrelaxed regions along each micelle, thereby allowing efficient simulations of relaxation dynamics for ensembles containing thousands of micelles, to obtain accurate results without preaveraging or neglecting correlations. A modified genetic algorithm is applied to transform the simulation data from the time to the frequency domain. The method can span several regimes of behavior depending on the relative rat...

Thermal engineering related to industrial applications needs fast and accurate prediction for complex heat transfer problems. Proper orthogonal decomposition (POD) method can achieve this target. In this paper, the performances of POD interpolation and POD projection methods are compared for the purpose of method selection in those applications. The results show that under the same sampling condition, POD interpolation method can simulate the four-variable heat conduction problem quite accurately (maximum relative deviation is smaller than 1 × 10−8%) but losses accuracy for the six-variable heat conduction problem (maximum relative deviation is up to more than 50%); while POD projection method can obtain accurate results for both the problems (maximum relative deviations are only 0.187% and 1.83% respectively). Thus, POD projection method is more robust and adaptive than POD interpolation method for wider ranges of heat transfer problems. Moreover, the conclusion is also suitable for the guidance of applications in the fields of chemical engineering and fluid mechanics etc.

In general, proper orthogonal decomposition (POD) method is used to deal with single-parameter problems in engineering practice, and the linear interpolation is employed to establish the reduced model. Recently, this method is extended to solve the double-parameter problems with the amplitudes being achieved by cubic B-spline interpolation. In this paper, the accuracy of reduced models, which are established with linear interpolation and cubic B-spline interpolation, respectively, is verified via two typical examples. Both results of the two methods are satisfying, and the results of cubic B-spline interpolation are more accurate than those of linear interpolation. The results are meaningful for guiding the application of the POD interpolation to complex multiparameter problems.