Kinetics versus thermodynamics dichotomy and growth -mechanisms in linear self-assembly of mixed nanoblocks

Self-assembly is a low energy synthesis process, prominent in biological systems, in which smaller building blocks spontaneously associate to form highly organized structures of great complexity. Thus, it is one of the most promising strategies to engineer hierarchical functional nanostructures. Of special interest are one-dimensional arrays of nanobuilding blocks (e.g., nanoparticles, peptides, colloids, etc.), such as nanowires, nanotubes or polymer-like structures, due to their potential applications ranging from nanosensing, optoelectronics, or molecular selective transport to mechanical reinforcement in structural composites. However, despite considerable advances on the synthesis side in the past few years, there is lack of understanding of the physics underlying the self-assembly kinetics and the mixing of diverse building blocks in low-dimensional structures. Short-term kinetic mechanisms of growth (in the order of nanoseconds to milliseconds) are difficult to reach with computationally intensive molecular simulations and yet occur too rapidly to be resolved with experiments. The growth mechanisms and kinetics of systems such as peptide nanotubes remain unexplored. Regarding supramolecular organization, the effect of kinetic traps on the formation of arrested phases is not yet fully understood, particularly in systems where self-assembly is driven by enthalpic interactions and nonequilibrium configurations are prevalent. Here, we present recent results from classical and replica exchange molecular dynamics simulations that establish the mechanisms underpinning the growth kinetics of a binary mix of nanorings that form striped nanotubes via self-assembly type. We show that a step-growth coalescence model captures adequately the growth process of the nanotubes, which suggests that high-aspect ratio nanostructures can grow by obeying the universal laws of self-similar coarsening, contrary to existing belief that growth occurs exclusively through nucleation and elongation (e.g., amyloid fibrils). Notably, we found that striped patterns do not depend on specific growth mechanisms, but are governed by tempering conditions that control the likelihood of depropagation and fragmentation

Evaluation of the dismissed forensic medicine specialists and other forensic professionals in Turkey

The right to work, one of the fundamental human rights, expresses the right of all individuals to maintain a dignified life by having an income, earned through work (UDHR, 1948). Following the coup attempt on 15 July 2016, the Turkish government declared a state of emergency on 20 July 2016. This lasted 730 days until 20 July 2018. During this period, 32 decrees were issued by the Turkish government. With these decrees, 150,348 public officials including judges, pros- ecutors, civil servants, teachers, bureaucrats, medical doctors and academics were dismissed without any investigation (Turkey Purge, 2019). With regard to the group of forensic professional experts, many have been dismissed following decrees issued by the Turkish government

Molecular and nanostructural mechanisms of deformation, strength and toughness of spider silk fibrils

Spider silk is one of the strongest, most extensible and toughest biological materials known, exceeding the properties of many engineered materials including steel. Silks feature a hierarchical architecture where highly organized, densely H-bonded beta-sheet nanocrystals are arranged within a semi-amorphous protein matrix consisting of 31-helices and beta-turn protein structures. By using a bottom-up molecular-based mesoscale model that bridges the scales from Angstroms to hundreds of nanometers, here we show that the specific combination of a crystalline phase and a semi-amorphous matrix is crucial for the unique properties of silks. Specifically, our results reveal that the superior mechanical properties of spider silk can be explained solely by structural effects, where the geometric confinement of beta-sheet nanocrystals combined with highly extensible semi-amorphous domains with a large hidden length is the key to reach great strength and great toughness, despite the dominance of mechanically inferior chemical interactions such as H-bonding. Our model directly shows that semi-amorphous regions unravel first when silk is being stretched, leading to the large extensibility of silk. Conversely, the large-deformation mechanical properties and ultimate tensile strength of silk is controlled by the strength of beta-sheet nanocrystals, which is directly related to their size, where small beta-sheet nanocrystals are crucial to reach outstanding levels of strength and toughness. Our model agrees well with observations in recent experiments, where it was shown that a significant change in the strength and toughness can be achieved solely by tuning the size of beta-sheet nanocrystals. Our findings unveil the material design strategy that enables silks to achieve superior material performance despite simple and inferior constituents, resulting in a new paradigm in materials design where enhanced functionality is not achieved using complex building blocks, but rather through the utilization of simple repetitive constitutive elements arranged in hierarchical structures

Atomistic simulation and modeling of the interface between -cellulose nanocrystal elementary fibrils

Cellulose nanocrystals (CNCs) are ubiquitous in some of nature’s toughest biological nanocomposites such as wood and bacterial cell walls [1] and exhibit outstanding mechanical properties rivaling those of synthetic materials such as Kevlar [2]. Although the impressive elastic properties of CNCs and mechanical properties of macroscale cellulosic materials have been well characterized, a molecular level understanding of how cellulose-based materials achieve high fracture toughness with relatively weak secondary interactions remains to be explained. Earlier study [3] focused on understanding the molecular interactions within individual CNCs and revealed key information on the types of molecular mechanisms at work in these systems, as well as size effects that govern the optimal size of CNCs from a fracture perspective. To further understand this molecular level of how CNCs develop high resistance to failure, here we present new analyses based on atomistic, steered molecular dynamics (SMD) simulations and theoretical considerations to calculate the fracture energy of interfaces between CNCs. In this work, CNCs of “elementary size” (36 individual cellulose chains arranged hexagonally [4]) are considered as they are commonly found and extracted from biological systems. This study focuses on understanding the (200)–(200) and (110)–(110) interfaces between elementary fibrils as the (200) and (110) surfaces are exposed in this particular arrangement of cellulose chains. In order to better understand the interfaces between CNC elementary fibrils, simulations were performed using SMD techniques to forcibly separate the crystals both perpendicular (i.e., pulling apart) and parallel (i.e., shearing) to the interfaces. Pull-apart simulations show that the (110)–(110) interface has a higher fracture energy than the (200)–(200) interface, which is attributed to different molecular interactions dominating at the interface; hydrogen bonding for (110)–(110) and van der Waals for (200)–(200). Shearing simulations show a common mechanism and common shape of the shear energy landscape for both the (110)–(110) and (200)–(200) interfaces. During shearing, fibrils move between local energy minima along the interface due to the geometry of the surfaces, while also exhibiting an underlying increase in energy. The distance between these energy minimums is observed to be a function of the surface geometry, whereas the magnitude of the energy -barrier that must be overcome to reach the next minimum is a function of the dominant molecular interaction mechanism. Based on the results of SMD simulations, analytical models are proposed to describe the energy landscape of interactions between CNC elementary fibrils. These analytical models will allow us to develop a coarse-grained description of CNC elementary fibrils that is capable of modeling the potential energy landscape of both separation and shearing of adjacent fibrils. This will be useful in future work that will focus on an examination of macroscale cellulosic materials, such as CNC neat films and CNC-polymer composites, which would be impractical to explore with fully atomistic simulations. REFERENCES [1] Fratzl, P., Weinkamer, R. Prog. Mater. Sci. 2007, 52(8), 1263−1334. [2] Moon, R.J., Martini, A., Nairn, J., Simonsen, J., Youngblood, J. Chem. Soc. Rev. 2011, 40(7), 3941−3994. [3] Sinko, R., Mishra, S., Ruiz, L., Brandis, N., Keten, S. ACS Macro Letters. 2014, 3(1), 64–69. [4] Habibi, Y., Lucia, L.A., Rojas, O.J. Chem. Rev. 2010, 110(6), 3479−3500

Premenstrual Syndrome Experiences and Coping Levels of University Students: A Mixed Method Study

Objective:Premenstrual syndrome (PMS) is common among young female university students. Determining students’ PMS experience and coping levels with them can contribute to the development of effective strategies. This research was carried out to determine the premenstrual symptoms, coping experiences of the students with them and coping levels of the students experiencing PMS.Methods:This research is in a mixed method design that includes quantitative and qualitative data collection methods. The number of participants was 436 students. Quantitative data of the study were collected through an introductory information form, premenstrual coping measure (PCM), and qualitative data were collected through individual interviews using a semi-structured form.Results:The mean age of the participants was 20.65±1.68, mean age at menarche was 12.96±1.22. The rate of students experiencing PMS frequently was 41.1%, the rate of those who had regular menstruation was 73.9%, and the rate of those with dysmenorrhea was 90.3%. The most common symptoms were anxiety (73.4%), fatigue (72.3%), breast tenderness (71.1%), appetite changes (70.6%). The students' coping skills with PMS were at a good level. The highest PCM sub-dimension score was in the self-care (14.82±3.81) and awareness and acceptance of premenstrual change (34.49±7.86) dimensions. Strategies used by students to cope with PMS included practices such as conflict avoidance, being alone, rest, sleep, massage, exercise and drinking herbal tea.Conclusion:This study showed students’ common PMS symptoms and coping strategies with thme. Health professionals should be aware of students’ problems and provide comprehensive health services that support them coping with PMS

Effect of PEG conjugation on entropy driven self-assembly of coiled coils

Coiled coil helix bundles are one of the most common protein motifs known, playing significant roles in various mechanobiological processes. The desirable functionalities of -helical coiled coils are dependent upon their thermal and structural stability, which can be lost under extreme environmental conditions such as elevated temperatures, pressures, or pH. Recently, conjugation of -helices with polymers, particularly poly(ethylene glycol) (PEG), has been utilized to produce environmentally responsive protein-based block copolymers with improved structural and thermal stability. A fundamental question regarding helix–PEG conjugates is how PEG conjugation affects the secondary structure of helices [1] as well as their tertiary structure, which is the mechanism of self-assembly. In particular, the influence of PEG conjugation site on the assembly of helix bundles remains to be fully characterized. In order to address these questions, we perform coarse-grained molecular dynamics simulations of a trimeric coiled coil conjugated with PEG [2]. The effect of conjugation location is studied by covalently attaching the PEG chain either to the end or to the side of each helix in the three-helix assembly. First, we utilize annealing simulations to investigate the melting behavior and thermal stability of the coiled coil with no PEG attached, with side-conjugated PEG, and with end-conjugated PEG. Our simulation predictions for the coiled coil melting temperature are in good agreement with experimental data and show an insignificant difference between the melting temperatures of peptide itself and peptide-PEG conjugates. Next, we study the entropy driven self-assembly patterns of coiled coils with and without PEG by considering various peptide concentrations in the simulation box. Our results show that as the concentration increases, the number of assembled clusters decreases while the aggregation number in each cluster increases. Coiled coils without PEG, with end-conjugated PEG, and with side-conjugated PEG have the smallest number of clusters and the largest aggregation number, in order. These observations confirm that the peptide assembly patterns are affected not only by the presence of PEG chain, but also by the location of PEG conjugation. These findings lay the groundwork for the study of mechanisms underpinning the thermomechanical stability and assembly of coiled coils as well as other helix bundles. REFERENCES [1] Hamed, E., Xu, T., Keten, S. Poly(ethylene glycol) conjugation stabilizes the secondary structure of α-helices by reducing peptide solvent accessible surface area. Biomacromolecules. 2013, 14, 4053–4060. [2] Hamed, E, Ma, D, Keten, S. Effect of PEG conjugation on thermomechanical stability and self-assembly of coiled coil helix bundles (In submission)

Implicit Chain Particle Model for Polymer Grafted Nanoparticles

Matrix-free nanocomposites made from polymer grafted nanoparticles (PGN) represent a paradigm shift in materials science because they greatly improve nanoparticle dispersion and offer greater tunability over rheological and mechanical properties in comparison to neat polymers. Utilizing the full potential of PGNs requires a deeper understanding of how polymer graft length, density, and chemistry influence interfacial interactions between particles. There has been great progress in describing these effects with molecular dynamics (MD). However, the limitations of the length and time scales of MD make it prohibitively costly to study systems involving more than a few PGNs. Here, we address some of these challenges by proposing a new modeling paradigm for PGNs using a strain-energy mapping framework involving potential of mean force (PMF) calculations. In this approach, each nanoparticle is coarse-grained into a representative particle with chains treated implicitly, namely, the implicit chain particle model (ICPM). Using a chemistry-specific CG-MD model of PMMA as a testbed, we derive the effective interaction between particles arranged in a closed-packed lattice configuration by matching bulk dilation/compression strain energy densities. The strain-rate dependence of the mechanical work in ICPM is also discussed. Overall, the ICPM model increases the computational speed by approximately 5-6 orders of magnitude compared to the CG-MD models. This novel framework is foundational for particle-based simulations of PGNs and their blends and accelerates the understanding and predictions of emergent properties of PGN materials

Dependence of polymer thin film adhesion energy on cohesive interactions between chains

The adhesion of supported polymer thin films is predominantly influenced by the substrate-film interfacial properties. Utilizing steered molecular dynamics simulations, here we uncover that the cohesive noncovalent forces between polymer chains in the film also have a significant effect on the adhesive properties of supported film. We demonstrate that weaker interchain interactions, all else being the same, can induce higher adhesion energy within the interface. Three different adhesion regimes in the substrate–film interaction strength profile can be characterized by a nonlinear scaling relationship that earlier theoretical predictions currently do not capture. In the weak substrate–film interaction regime, the adhesion energy of the films exhibits near independence of cohesive forces, and entropic contributions to the surface free energy are consequential. In the intermediate regime, weaker film cohesive forces achieve higher adhesion energy due to the ability of polymer chains to pack more effectively in the interfacial region, thereby increasing the adhesive interaction density. In the strong interaction regime, the adhesion energy increases linearly with the adhesive interaction strength because of saturation of local packing in the interfacial region. These findings corroborate recent polymer wetting observations that have hinted on the importance of local relaxation and packing effects on interfacial properties

Mesoscale simulation of stress relaxation in thin polymer films and the connection to nanocomposites

Key insight into interphase formation and confinement effects in nanocomposites has recently come from studies on polymer thin films supported on solid substrates. In these thin films, both the free surface and the solid supporting layer cause complex changes in the behavior of the polymer. The range and magnitude of these effects have been singled out by systematically varying the boundary conditions (free standing film, supported thin film, and polymer layer confined between two surfaces) and surface/polymer chemistry. Most importantly, the Schadler group and the Torkelson group have shown a quantitative equivalence between nanocomposites and thin films with regards to glass-transition temperature (Tg) via the calculation of an equivalent metric of confinement within the nanocomposite from the distribution of filler surface-to-surface distances. This finding is important because it allows for direct prediction of the Tg of the nanocomposite directly from thin film measurements and microstructural statistics, leveraging current capabilities in accurate computational/experimental characterization of film properties. However, it is currently unknown whether the thin-film analogy can be extended into the constitutive behavior of polymer nanocomposites, most importantly the stress relaxation behavior of the matrix that governs viscoelastic behavior. With an ultimate aim to address this issue, we have begun examining the stress-relaxation in doubly supported polymer thin films through coarse grained simulation using the FENE model. The current study elucidates the connection among film thickness, interfacial energy, and stress relaxation dynamics. In order to characterize the dynamic relaxation behavior of the films at constant temperature, we calculate via an extended, tensorial Green–Kubo relation the linear shear-relaxation modulus from equilibrium coarse-grained simulations of the bulk and of films of varying thickness. We then compare the simulated relaxation moduli to both the Rouse model and the theory of Likhtman and McLeish (originally based on the based on the tube model), with the additional changes proposed by Hou, Svaneborg, Everaers, and Grest. Applications to the continuum mechanics of both thin films and nanocomposites will be discussed