Almost all studies of specific ion binding by carboxylates (–COO-) have considered only a single cation, but clustering of ions and ligands is a common phenomenon. We apply density functional theory to investigate how variations in the number of acetate ligands in binding to two monovalent cations affects ion binding preferences. We study a series of monovalent (Li+, Na+, K+, Cs+) ions relevant to experimental work on many topics, including ion channels, battery storage, water purification and solar cells. We find that the preferred optimal structure has 3 acetates except for Cs+, which has 2 acetates. The optimal coordination of the cation by the carboxylate O atoms is 4 for both Na+ and K+, and 3 for Li+ and Cs+. There is a 4-fold coordination minimum just a few kcal mol-1 higher than the optimal 3-fold structure for Li+. For two cations, multiple minima occur in the vicinity of the lowest free energy state. Here we find that, for Li, Na and K, the preferred optimal structure with two cations is favored over a mixture of single cation complexes, providing a basis for understanding ionic cluster formation that is relevant for engineering proteins and other materials for rapid, selective ion transport.
The principle of least action is the cornerstone of classical mechanics, theory of relativity, quantum mechanics, and thermodynamics. Here, we describe how a neural network (NN) learns to find the trajectory for a Lennard-Jones (LJ) system that maintains balance in minimizing the Onsager–Machlup (OM) action and maintaining the energy conservation. The phase-space trajectory thus calculated is in excellent agreement with the corresponding results from the “ground-truth” molecular dynamics (MD) simulation. Furthermore, we show that the NN can easily find structural transformation pathways for LJ clusters, for example, the basin-hopping transformation of an LJ38 from an incomplete Mackay icosahedron to a truncated face-centered cubic octahedron. Unlike MD, the NN computes atomic trajectories over the entire temporal domain in one fell swoop, and the NN time step is a factor of 20 larger than the MD time step. The NN approach to OM action is quite general and can be adapted to model morphometrics in a variety of applications.
Since the classical molecular dynamics simulator LAMMPS was released as an open source code in 2004, it has become a widely-used tool for particle-based modeling of materials at length scales ranging from atomic to mesoscale to continuum. Reasons for its popularity are that it provides a wide variety of particle interaction models for different materials, that it runs on any platform from a single CPU core to the largest supercomputers with accelerators, and that it gives users control over simulation details, either via the input script or by adding code for new interatomic potentials, constraints, diagnostics, or other features needed for their models. As a result, hundreds of people have contributed new capabilities to LAMMPS and it has grown from fifty thousand lines of code in 2004 to a million lines today. In this paper several of the fundamental algorithms used in LAMMPS are described along with the design strategies which have made it flexible for both users and developers. We also highlight some capabilities recently added to the code which were enabled by this flexibility, including dynamic load balancing, on-the-fly visualization, magnetic spin dynamics models, and quantum-accuracy machine learning interatomic potentials. Program Summary: Program Title: Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) CPC Library link to program files: https://doi.org/10.17632/cxbxs9btsv.1 Developer's repository link: https://github.com/lammps/lammps Licensing provisions: GPLv2 Programming language: C++, Python, C, Fortran Supplementary material: https://www.lammps.org Nature of problem: Many science applications in physics, chemistry, materials science, and related fields require parallel, scalable, and efficient generation of long, stable classical particle dynamics trajectories. Within this common problem definition, there lies a great diversity of use cases, distinguished by different particle interaction models, external constraints, as well as timescales and lengthscales ranging from atomic to mesoscale to macroscopic. Solution method: The LAMMPS code uses parallel spatial decomposition, distributed neighbor lists, and parallel FFTs for long-range Coulombic interactions [1]. The time integration algorithm is based on the Størmer-Verlet symplectic integrator [2], which provides better stability than higher-order non-symplectic methods. In addition, LAMMPS supports a wide range of interatomic potentials, constraints, diagnostics, software interfaces, and pre- and post-processing features. Additional comments including restrictions and unusual features: This paper serves as the definitive reference for the LAMMPS code. References: [1] S. Plimpton, Fast parallel algorithms for short-range molecular dynamics. J. Comp. Phys. 117 (1995) 1–19. [2] L. Verlet, Computer experiments on classical fluids: I. Thermodynamical properties of Lennard–Jones molecules, Phys. Rev. 159 (1967) 98–103.
For strongly charged polyelectrolytes in salt-free solutions, we use molecular dynamics simulations of a coarse-grained bead-spring model to calculate overlap concentrations c∗ and chain structure for polymers containing N = 10 to 1600 monomers. Over much of this range, we find that the end-to-end distance R∗ at c∗ increases faster than linearly with increasing N, as chains at the overlap concentration approach strongly extended conformations. This trend results in the overlap concentration c∗ decreasing as a stronger function of N than the classical prediction c∗ ∼N-2. This stronger dependence can be fit either by a logarithmic correction to scaling or by an apparent scaling c∗ ∼N-m, with m > 2.
This report summarizes molecular and continuum simulation studies focused on developing physics - based predictive models for the evolution of polymer molecular order during the nonlinear processing flows of additive manufacturing. Our molecular simulations of polymer elongation flows identified novel mechanisms of fluid dissipation for various polymer architectures that might be harnessed to enhance material processability. In order to predict the complex thermal and flow history of polymer realistic additive manufacturing processes, we have developed and deployed a high - performance mesh - free hydrodynamics module in Sandia's LAMMPS software. This module called RHEO – short for Reproducing Hydrodynamics and Elastic Objects – hybridizes an updated - Lagrange reproducing - kernel method for complex fluids with a bonded particle method (BPM) to capture solidification and solid objects in multiphase flows. In combination, our two methods allow rapid, multiscale characterization of the hydrodynamics and molecular evolution of polymers in realistic processing geometries.
Designing polymers with controlled nanoscale morphologies and scalable synthesis is of great interest in the development of fluorine-free materials for proton-exchange membranes in fuel cells. This study focuses on a precision polyethylene with phenylsulfonic acid branches at every fifth carbon, p5PhSA, with a high ion-exchange capacity (4.2 mmol/g). The polymers self-assemble into hydrophilic and hydrophobic co-continuous nanoscale domains. In the hydrated state, the hydrophilic domain, composed of polar sulfonic acid moieties and water, serves as a pathway for efficient mesoscopic proton conductivity. The morphology and proton transport of p5PhSA are evaluated under hydrated conditions using in situ X-ray scattering and electrochemical impedance spectroscopy techniques. At 40 °C and 95% relative humidity, the proton conductivity of p5PhSA is 0.28 S/cm, which is four times greater than Nafion 117 under the same conditions. Atomistic molecular dynamics (MD) simulations are also used to elucidate the interplay between the structure and the water dynamics. The MD simulations show strong nanophase separation between the percolated hydrophilic and hydrophobic domains over a wide range of water contents. The percolated hydrophilic nanoscale domain facilitates the rapid proton transport in p5PhSA and demonstrates the potential of precise hydrocarbon-based polymers as processible and effective proton-exchange membranes.
Polymerization induced phase separation (PIPS) in a three component thermoset is studied using molecular dynamics simulations of a new coarse-grained thermoset model. The system includes two crosslinker molecules, which differ in their glass transition temperatures (Tg) and chain length and thus have the potential for phase separation. One crosslinker has a high Tg corresponding to a rubbery behavior, and simulations were performed for a short length (4 beads) and a long length (33 beads). The resin and other crosslinker have low Tg. A coarse-grained model is developed with these features and with interaction parameters determined so that for either rubbery crosslinker length, the system is in the liquid state at the cure temperature. For sufficiently slow reaction rates, the long rubbery molecule exhibits PIPS into a bicontinuous array of nanoscale domains, but the short one does not, reproducing recent experimental results. The simulations demonstrate that the reaction rates must be slow enough to allow diffusion to yield phase separation. Particularly, the reaction rate corresponding to the secondary amine must be very slow, else the structure of crosslinked clusters and the substantially increased diffusion time will prevent PIPS.
Umbrella sampling, coupled with a weighted histogram analysis method (US-WHAM), can be used to construct potentials of mean force (PMFs) for studying the complex ion permeation pathways of membrane transport proteins. Despite the widespread use of US-WHAM, obtaining a physically meaningful PMF can be challenging. Here, we provide a protocol to resolve that issue. Then, we apply that protocol to compute a meaningful PMF for sodium ion permeation through channelrhodopsin chimera, C1C2, for illustration.
Dynamic instability of microtubules is characterized by stochastically alternating phases of growth and shrinkage and is hypothesized to be controlled by the conformation and nucleotide state of tubulin dimers within the microtubule lattice. Specifically, conformation changes (compression) in the tubulin dimer following the hydrolysis of GTP have been suggested to generate stress and drive depolymerization. In the present study, molecular dynamics simulations were used in tandem with in vitro experiments to investigate changes in depolymerization based on the presence of islands of uncompressed (GMPCPP) dimers in the microtubule lattice. Both methods revealed an exponential decay in the kinetic rate of depolymerization corresponding to the relative level of uncompressed (GMPCPP) dimers, beginning at approximately 20% incorporation. This slowdown was accompanied by a distinct morphological change from unpeeling “ram’s horns” to blunt-ended dissociation at the microtubule end. Collectively these data demonstrated that islands of uncompressed dimers can alter the mechanism and kinetics of depolymerization in a manner consistent with promoting rescue events.
We describe a set of precise single-ion conducting polymers that form self-assembled percolated ionic aggregates in glassy polymer matrices and have decoupled transport of metal cations. These precise single-ion conductors (SICs), synthesized by a scalable ring-opening metathesis polymerization, consist of a polyethylene backbone with a sulfonated phenyl group pendant on every fifth carbon and are fully neutralized by a counterion X+ (Li+, Na+, or Cs+). Experimental X-ray scattering measurements and fully atomistic molecular dynamics (MD) simulations are in good agreement. The MD simulations show that the ionic groups nanophase separate from the polymer backbone to form percolating ionic aggregates. Using graph theory, we find that within the Li+- and Na+-neutralized polymers the percolated aggregates exhibit planar and ribbon-like configurations at intermediate length scales, while the percolated aggregates within the Cs+-neutralized polymers are more isotropic. Electrical impedance spectroscopy measurements show that the ionic conductivities exhibit Arrhenius behavior, with conductivities of 10-7 to 10-6 S/cm at 180 °C. In the MD simulations, the cations move between sulfonate groups in the percolated aggregates, larger ions travel further, and overall cations travel further than the polymer backbones, indicating a decoupled ion-transport mechanism. Thus, the percolated ionic aggregates in these polymers can serve as pathways to facilitate decoupled ion motion through a glassy polymer matrix.
We calculate the solvation energy of monovalent and divalent ions in various liquids with coarse-grained molecular dynamics simulations. Our theory treats the solvent as a Stockmayer fluid, which accounts for the intrinsic dipole moment of molecules and the rotational dynamics of the dipoles. Despite the simplicity of the model, we obtain qualitative agreement between the simulations and experimental data for the free energy and enthalpy of ion solvation, which indicates that the primary contribution to the solvation energy arises mainly from the first and possibly second solvation shells near the ions. Our results suggest that a Stockmayer fluid can serve as a reference model that enables direct comparison between theory and experiment and may be invoked to scale up electrostatic interactions from the atomic to the molecular length scale.
Single-ion conducting polymers such as ionomers are promising battery electrolyte materials, but it is critical to understand how rates and mechanisms of free cation transport depend on the nanoscale aggregation of cations and polymer-bound anions. We perform coarse-grained molecular dynamics simulations of ionomer melts to understand cation mobility as a function of polymer architecture, background relative permittivity, and corresponding ionic aggregate morphology. In systems exhibiting percolated ionic aggregates, cations diffuse via stepping motions along the ionic aggregates. These diffusivities can be quantitatively predicted by calculating the lifetimes of continuous association between oppositely charged ions, which equal the time scales of the stepping (diffusive) motions. In contrast, predicting cation diffusivity for systems with isolated ionic aggregates requires another time scale. Our results suggest that to improve conductivity the Coulombic interaction strength should be strong enough to favor percolated aggregates but weak enough to facilitate ion dissociation.
Origami offers a distinct approach for designing and engineering new material structures and properties. The folding and stacking of atomically thin van der Waals (vdW) materials, for example, can lead to intriguing new physical properties including bandgap tuning, Van Hove singularity, and superconductivity. On the other hand, achieving well-controlled folding of vdW materials with high spatial precision has been extremely challenging and difficult to scale toward large areas. Here, a deterministic technique is reported to fold vdW materials at a defined position and direction using microfluidic forces. Electron beam lithography (EBL) is utilized to define the folding area, which allows precise control of the folding geometry, direction, and position beyond 100 nm resolution. Using this technique, single-atomic-layer vdW materials or their heterostructures can be folded without the need for any external supporting layers in the final folded structure. In addition, arrays of patterns can be folded across a large area using this technique and electronic devices that can reconfigure device functionalities through folding are also demonstrated. Such scalable formation of folded vdW material structures with high precision can lead to the creation of new atomic-scale materials and superlattices as well as opening the door to realizing foldable and reconfigurable electronics.
Innes-Gold, Sarah N.; Pincus, Philip A.; Stevens, Mark J.; Saleh, Omar A.
The configuration of charged polymers is heavily dependent on interactions with surrounding salt ions, typically manifesting as a sensitivity to the bulk ionic strength. Here, we use single-molecule mechanical measurements to show that a charged polysaccharide, hyaluronic acid, shows a surprising regime of insensitivity to ionic strength in the presence of trivalent ions. Using simulations and theory, we propose that this is caused by the formation of a "jacket" of ions, tightly associated with the polymer, whose charge (and thus effect on configuration) is robust against changes in solution composition.
Microtubules are stiff biopolymers that self-assemble via the addition of GTP-tubulin (αβ-dimer bound to GTP), but hydrolysis of GTP- to GDP-tubulin within the tubules destabilizes them toward catastrophically-fast depolymerization. The molecular mechanisms and features of the individual tubulin proteins that drive such behavior are still not well-understood. Using molecular dynamics simulations of whole microtubules built from a coarse-grained model of tubulin, we demonstrate how conformational shape changes (i.e., deformations) in subunits that frustrate tubulin-tubulin binding within microtubules drive depolymerization of stiff tubules via unpeeling "ram's horns" consistent with experiments. We calculate the sensitivity of these behaviors to the length scales and strengths of binding attractions and varying degrees of binding frustration driven by subunit shape change, and demonstrate that the dynamic instability and mechanical properties of microtubules can be produced based on either balanced or imbalanced strengths of lateral and vertical binding attractions. Finally, we show how catastrophic depolymerization can be interrupted by small regions of the microtubule containing undeformed dimers, corresponding to incomplete lattice hydrolysis. The results demonstrate a mechanism by which microtubule rescue can occur.
Very large molecular dynamics simulations with open ends between two solid adherends have been performed treating tensile deformation of coarse-grained, highly crosslinked polymer networks modeling epoxy systems. The open boundary and the presence of corners dramatically alter the fracture behavior. In contrast to systems with periodic boundaries, the failure strain decreases with increasing system size until a critical size is reached. This decrease greatly reduces the difference in the crack initiation strains between simulation and experiment. In the open geometry, the sides of the polymer network contract inward forming wedge shaped corners. The stress and strain are concentrated in the corners where the shear component is present and large. The nonuniformity of the strain results in accumulation of bond breaking in the corners and crack initiation there. Moreover, the corner strain is system size dependent, which results in a system size dependence of the failure strain.
We present simulations of the force-extension curves of strong polyelectrolytes with varying intrinsic stiffness as well as specifically treating hyaluronic acid, a polyelectrolyte of intermediate stiffness. Whereas fully flexible polyelectrolytes show a high-force regime where extension increases nearly logarithmically with force, we find that the addition of even a small amount of stiffness alters the short-range structure and removes this logarithmic elastic regime. This further confirms that the logarithmic regime is a consequence of the short-ranged "wrinkles" in the flexible chain. As the stiffness increases, the force-extension curves tend toward and reach the wormlike chain behavior. Using the screened Coulomb potential and a simple bead-spring model, the simulations are able to reproduce the hyaluronic acid experimental force-extension curves for salt concentrations ranging from 1 to 500 mM. Furthermore, the simulation data can be scaled to a universal curve like the experimental data. The scaling analysis is consistent with the interpretation that, in the low-salt limit, the hyaluronic acid chain stiffness scales with salt with an exponent of -0.7, rather than either of the two main theoretical predictions of -0.5 and -1. Furthermore, given the conditions of the simulation, we conclude that this exponent value is not due to counterion condensation effects, as had previously been suggested.
Trigg, Edward B.; Gaines, Taylor W.; Maréchal, Manuel; Moed, Demi E.; Rannou, Patrice; Wagener, Kenneth B.; Stevens, Mark J.; Winey, Karen I.
Recent advances in polymer synthesis have allowed remarkable control over chain microstructure and conformation. Capitalizing on such developments, here we create well-controlled chain folding in sulfonated polyethylene, leading to highly uniform hydrated acid layers of subnanometre thickness with high proton conductivity. The linear polyethylene contains sulfonic acid groups pendant to precisely every twenty-first carbon atom that induce tight chain folds to form the hydrated layers, while the methylene segments crystallize. The proton conductivity is on par with Nafion 117, the benchmark for fuel cell membranes. We demonstrate that well-controlled hairpin chain folding can be utilized for proton conductivity within a crystalline polymer structure, and we project that this structure could be adapted for ion transport. This layered polyethylene-based structure is an innovative and versatile design paradigm for functional polymer membranes, opening doors to efficient and selective transport of other ions and small molecules on appropriate selection of functional groups.
Microtubules exhibit a dynamic instability between growth and catastrophic depolymerization. GTP-tubulin (αβ-dimer bound to GTP) self-assembles, but dephosphorylation of GTP- to GDP-tubulin within the tubule results in destabilization. While the mechanical basis for destabilization is not fully understood, one hypothesis is that dephosphorylation causes tubulin to change shape, frustrating bonds and generating stress. To test this idea, we perform molecular dynamics simulations of microtubules built from coarse-grained models of tubulin, incorporating a small compression of α-subunits associated with dephosphorylation in experiments. We find that this shape change induces depolymerization of otherwise stable systems via unpeeling "ram's horns" characteristic of microtubules. Depolymerization can be averted by caps with uncompressed α-subunits, i.e., GTP-rich end regions. Thus, the shape change is sufficient to yield microtubule behavior.
Enzymes that degrade specific small molecules could save lives by neutralizing threats from chemical agents in the blood or environment, or by starving pathogenic cells, but promiscuous interactions with other molecules typically limit their effectiveness by blocking the enzyme active site. An obvious solution would be to re-engineer the enzyme to enhance catalytic fidelity, but lack of understanding about how enzymes discriminate between molecules remains a formidable challenge to this approach. Our recent work in collaboration with the University of Texas (UT) suggested a new approach and a model system for understanding enzyme specificity. Asparaginase enzymes catalyze degradation of asparagine, which forms the basis of a medical treatment. Com- petition by the abundant and chemically similar molecule, glutamine, interferes with asparagine decomposition, thus hindering enzyme efficacy. Asparaginase is advantageous as a model degra- dation enzyme because variants that demonstrate different binding affinities and catalytic rates can be compared. Here, we leveraged Sandia and the University of Maryland's strengths in molecu- lar simulation, and UT experimental expertise in asparaginase modification and functional assays, to understand asparaginase specificity. Our results advanced a new hypothesis about asparagi- nase catalytic mechanism that explains for the first time why proximity between the substrate's alpha-carboxyl and carboxamide is absolutely required for catalysis. Based on those insights, we developed the first mutant (Q59L) asparaginase from E. coli that lacks activity toward glutamine. We used that mutant to show that glutaminase activity is required to kill cancer cells that have asparagine synthetase enzymes (ASNS), but not ASNS-negative cancer cells.
The directed, head-to-tail self-assembly of microtubule filaments may be generalized in the context of Janus colloidal rods. Specifically, their assembly at the tens of micron-length scale involves a careful balance between long-range electrostatic repulsion and short-range attractive forces. Here we show that the addition of counterion salts increases the rate of directed assembly by screening the electrostatic forces and enhancing the effectiveness of short-range interactions at the microtubule ends.
The aim of this study was to alter polymerization chemistry to improve network homogeneity in free-radical crosslinked systems. It was hypothesized that a reduction in heterogeneity of the network would lead to improved mechanical performance. Experiments and simulations were carried out to investigate the connection between polymerization chemistry, network structure and mechanical properties. Experiments were conducted on two different monomer systems - the first is a single monomer system, urethane dimethacrylate (UDMA), and the second is a two-monomer system consisting of bisphenol A glycidyl dimethacrylate (BisGMA) and triethylene glycol dimethacrylate (TEGDMA) in a ratio of 70/30 BisGMA/TEGDMA by weight. The methacrylate systems were crosslinked using traditional radical polymeriza- tion (TRP) with azobisisobutyronitrile (AIBN) or benzoyl peroxide (BPO) as an initiator; TRP systems were used as the control. The monomers were also cross-linked using activator regenerated by electron transfer atom transfer radical polymerization (ARGET ATRP) as a type of controlled radical polymerization (CRP). FTIR and DSC were used to monitor reac- tion kinetics of the systems. The networks were analyzed using NMR, DSC, X-ray diffraction (XRD), atomic force microscopy (AFM), and small angle X-ray scattering (SAXS). These techniques were employed in an attempt to quantify differences between the traditional and controlled radical polymerizations. While a quantitative methodology for characterizing net- work morphology was not established, SAXS and AFM have shown some promising initial results. Additionally, differences in mechanical behavior were observed between traditional and controlled radical polymerized thermosets in the BisGMA/TEGDMA system but not in the UDMA materials; this finding may be the result of network ductility variations between the two materials. Coarse-grained molecular dynamics simulations employing a novel model of the CRP reaction were carried out for the UDMA system, with parameters calibrated based on fully atomistic simulations of the UDMA monomer in the liquid state. Detailed metrics based on network graph theoretical approaches were implemented to quantify the bond network topology resulting from simulations. For a broad range of polymerization parameters, no discernible differences were seen between TRP and CRP UDMA simulations at equal conversions, although clear differences exist as a function of conversion. Both findings are consistent with experiments. Despite a number of shortcomings, these models have demonstrated the potential of molecular simulations for studying network topology in these systems.
We calculated the force-extension curves for a flexible polyelectrolyte chain with varying charge separations by performing Monte Carlo simulations of a 5000 bead chain using a screened Coulomb interaction. At all charge separations, the force-extension curves exhibit a Pincus-like scaling regime at intermediate forces and a logarithmic regime at large forces. As the charge separation increases, the Pincus regime shifts to a larger range of forces and the logarithmic regime starts are larger forces. We also found that force-extension curve for the corresponding neutral chain has a logarithmic regime. Decreasing the diameter of bead in the neutral chain simulations removed the logarithmic regime, and the force-extension curve tends to the freely jointed chain limit. This result shows that only excluded volume is required for the high force logarithmic regime to occur.
We perform molecular dynamics simulations of a coarse-grained model of ionomer melts in an applied oscillating electric field. The frequency-dependent conductivity and susceptibility are calculated directly from the current density and polarization density, respectively. At high frequencies, we find a peak in the real part of the conductivity due to plasma oscillations of the ions. At lower frequencies, the dynamic response of the ionomers depends on the ionic aggregate morphology in the system, which consists of either percolated or isolated aggregates. We show that the dynamic response of the model ionomers to the applied oscillating field can be understood by comparison with relevant time scales in the systems, obtained from independent calculations.
A coarse-grained (CG) model is developed for the thermoresponsive polymer poly(N-isopropylacrylamide) (PNIPAM), using a hybrid top-down and bottom-up approach. Nonbonded parameters are fit to experimental thermodynamic data following the procedures of the SDK (Shinoda, DeVane, and Klein) CG force field, with minor adjustments to provide better agreement with radial distribution functions from atomistic simulations. Bonded parameters are fit to probability distributions from atomistic simulations using multi-centered Gaussian-based potentials. The temperature-dependent potentials derived for the PNIPAM CG model in this work properly capture the coil-globule transition of PNIPAM single chains and yield a chain-length dependence consistent with atomistic simulations.
The performance and reliability of many mechanical and electrical components depend on the integrity of po lymer - to - solid interfaces . Such interfaces are found in adhesively bonded joints, encapsulated or underfilled electronic modules, protective coatings, and laminates. The work described herein was aimed at improving Sandia's finite element - based capability to predict interfacial crack growth by 1) using a high fidelity nonlinear viscoelastic material model for the adhesive in fracture simulations, and 2) developing and implementing a novel cohesive zone fracture model that generates a mode - mixity dependent toughness as a natural consequence of its formulation (i.e., generates the observed increase in interfacial toughness wi th increasing crack - tip interfacial shear). Furthermore, molecular dynamics simulations were used to study fundamental material/interfa cial physics so as to develop a fuller understanding of the connection between molecular structure and failure . Also reported are test results that quantify how joint strength and interfacial toughness vary with temperature.
For more than a decade now, biomolecular systems have served as an inspiration for the development of synthetic nanomaterials and systems that are capable of reproducing many of unique and emergent behaviors of living systems. One intriguing element of such systems may be found in a specialized class of proteins known as biomolecular motors that are capable of performing useful work across multiple length scales through the efficient conversion of chemical energy. Microtubule (MT) filaments may be considered within this context as their dynamic assembly and disassembly dissipate energy, and perform work within the cell. MTs are one of three cytoskeletal filaments in eukaryotic cells, and play critical roles in a range of cellular processes including mitosis and vesicular trafficking. Based on their function, physical attributes, and unique dynamics, MTs also serve as a powerful archetype of a supramolecular filament that underlies and drives multiscale emergent behaviors. In this review, we briefly summarize recent efforts to generate hybrid and composite nanomaterials using MTs as biomolecular scaffolds, as well as computational and synthetic approaches to develop synthetic one-dimensional nanostructures that display the enviable attributes of the natural filaments.
We present atomistic simulations of a single PNIPAM-alkyl copolymer surfactant in aqueous solution at temperatures below and above the LCST of PNIPAM. We compare properties of the surfactant with pure PNIPAM oligomers of similar lengths, such as the radius of gyration and solvent accessible surface area, to determine the differences in their structures and transition behavior. We also explore changes in polymer-polymer and polymer-water interactions, including hydrogen bond formation. The expected behavior is observed in the pure PNIPAM oligomers, where the backbone folds onto itself above the LCST in order to shield the hydrophobic groups from water. The surfactant, on the other hand, does not show much conformational change as a function of temperature, but instead folds to bring the hydrophobic alkyl tail and PNIPAM headgroup together at all temperatures. The atomic detail available from these simulations offers important insight into understanding how the transition behavior is changed in PNIPAM-based systems.
Designing acid- and ion-containing polymers for optimal proton, ion, or water transport would benefit profoundly from predictive models or theories that relate polymer structures with ionomer morphologies. Recently, atomistic molecular dynamics (MD) simulations were performed to study the morphologies of precise poly(ethylene-co-acrylic acid) copolymer and ionomer melts. Here, we present the first direct comparisons between scattering profiles, I(q), calculated from these atomistic MD simulations and experimental X-ray data for 11 materials. This set of precise polymers has spacers of exactly 9, 15, or 21 carbons between acid groups and has been partially neutralized with Li, Na, Cs, or Zn. In these polymers, the simulations at 120 °C reveal ionic aggregates with a range of morphologies, from compact, isolated aggregates (type 1) to branched, stringy aggregates (type 2) to branched, stringy aggregates that percolate through the simulation box (type 3). Excellent agreement is found between the simulated and experimental scattering peak positions across all polymer types and aggregate morphologies. The shape of the amorphous halo in the simulated I(q) profile is in excellent agreement with experimental I(q). The modified hard-sphere scattering model fits both the simulation and experimental I(q) data for type 1 aggregate morphologies, and the aggregate sizes and separations are in agreement. Given the stringy structure in types 2 and 3, we develop a scattering model based on cylindrical aggregates. Both the spherical and cylindrical scattering models fit I(q) data from the polymers with type 2 and 3 aggregates equally well, and the extracted aggregate radii and inter- and intra-aggregate spacings are in agreement between simulation and experiment. Furthermore, these dimensions are consistent with real-space analyses of the atomistic MD simulations. By combining simulations and experiments, the ionomer scattering peak can be associated with the average distance between branches of type 2 or 3 aggregates. This direct comparison of X-ray scattering data to the atomistic MD simulations is a substantive step toward providing a comprehensive, predictive model for ionomer morphology, gives substantial support for this atomistic MD model, and provides new credibility to the presence of stringy, branched, and percolated ionic aggregates in precise ionomer melts.
Cao, Zhen; Stevens, Mark J.; Carrillo, Jan M.; Dobrynin, Andrey V.
We use a combination of the molecular dynamics simulations and scaling analysis to study interactions between gel-like nanoparticles and substrates covered with rectangular shape posts. Our simulations have shown that nanoparticles in contact with substrate undergo a first-order transition between the Cassie-Baxter and Wenzel states, which depends on nanoparticle shear modulus, the strength of nanoparticle-substrate interactions, height of the substrate posts, and nanoparticle size, Rp. There is a range of system parameters where these two states coexist such that the average indentation δ produced by substrate posts changes with nanoparticle shear modulus, Gp. We have developed a scaling model that describes deformation of nanoparticle in contact with patterned substrate. In the framework of this model, the effect of the patterned substrate can be taken into account by introducing an effective work of adhesion, Weff, which describes the first-order transition between Wenzel and Cassie-Baxter states. There are two different shape deformation regimes for nanoparticles with shear modulus Gp and surface tension γp. The shape of small nanoparticles with size Rp < γp3/2Gp-1Weff-1/2 is controlled by capillary forces, while deformation of large nanoparticles, Rp > γp3/2Gp-1Weff-1/2, is determined by nanoparticle elastic and contact free energies. The model predictions are in good agreement with simulation results.
We have developed a generalized model of particle-substrate interactions describing both adhesion and wetting behavior. Using a combination of the molecular dynamics simulations and scaling analysis we have shown that the crossover between adhesion and wetting-like behavior for a particle with size Rp and shear modulus Gp interacting with a substrate of shear modulus Gs is determined by the dimensionless parameter β ∞ γ∗(G∗ Rp)-2/3W-1/3, where G∗ = GpGs/(Gp + Gs) is the effective shear modulus, W is the work of adhesion between particle and substrate, and γ∗ = Wgr + γp(1-2gr) + γspgr2 is the effective surface tension of the particle/substrate system with γp and γs being surface tensions of particle and substrate, γsp - surface tension of the particle-substrate interface, and gr = Gp/(Gp + Gs). This parameter β is proportional to the ratio of elastocapillary length γ∗/G∗ and contact radius a, β ∞ γ∗/G∗a. In the limit of small values of the parameter β < 1, when the contact radius a is larger than the elastocapillary length γ∗/G∗, our model reproduces Johnson, Kendall, and Roberts results for particle adhesion on elastic substrates (adhesion regime). However, in the opposite limit, β > 1 (a < γ∗/G∗), the capillary forces play a dominant role and determine particle-substrate interactions (wetting regime). Model predictions are in a very good agreement with simulation and experimental results.
Microtubules (MTs) are biological polymer filaments that display unique polymerization dynamics, and serve as inspiration for developing synthetic nanomaterials that exhibit similar assembly-derived behaviours. Here we explore an assembly process in which extended 1D nano-arrays (NAs) are formed through the directed, head-to-tail self-assembly of MT filaments. In particular, we demonstrate that the elongation of NAs over time is due to directed self-assembly of MTs by a process that is limited by diffusion and follows second-order rate kinetics. We further described a mechanism, both experimental and through molecular dynamics simulations, where stable junctions among MT building blocks are formed by alignment and adhesion of opposing filament ends, which is followed by formation of a stable junction through the incorporation of free tubulin and the removal of lattice vacancies. The fundamental principles described in this directed self-assembly process provide a promising basis for new approaches to manufacturing complex, heterostructured nanocomposites.