Block copolymers confined in a nanopore: Pathfinding in a curving and frustrating flatland

We have studied structure formation in a confined block copolymer melt by means of dynamic density functional theory (DDFT). The confinement is two-dimensional, and the confined geometry is that of a cylindrical nanopore. Although the results of this study are general, our coarse-grained molecular model is inspired by an experimental lamellae-forming PS-PBD diblock copolymer system (Shin et al, Science, 306, 76 (2004)), in which an exotic toroidal structure was observed upon confinement in alumina nanopores. Our computational study shows that a zoo of exotic structures can be formed, although the majority, including the catenoid, helix and double helix that were also found in Monte Carlo (MC) nanopore studies, are metastable states. We introduce a general classification scheme and consider the role of kinetics and elongational pressure on stability and formation pathway of both equilibrium and metastable structures in detail. We find that helicity and three-fold connections mediate structural transitions on a larger scale. Moreover, by matching the remaining parameter in our mesoscopic method, the Flory-Huggins parameter, to the experimental system, we obtain a structure that resembles the experimental toroidal structure in great detail. Here, the most important factor seems to be the roughness of the pore, i.e. small variations of the pore radius on a scale that is larger than the characteristic size in the system.Comment: The following article has been accepted by JCP. After it is published, it will be found at http://jcp.aip.org

Phase diagram for diblock copolymer melts under cylindrical confinement

We extensively study the phase diagram of a diblock copolymer melt confined in a cylindrical nanopore using real-space self-consistent mean-field theory. We discover a rich variety of new two-dimensional equilibrium structures that have no analog in the unconfined system. These include non-hexagonally coordinated cylinder phases and structures intermediate between lamellae and cylinders. We map the stability regions and phase boundaries for all the structures we find. As the pore radius is decreased, the pore accommodates fewer cylindrical domains and structural transitions occur as cylinders are eliminated. Our results are consistent with experiments, but we also predict phases yet to be observed.Comment: 12 pages, 3 figures. submitted to Physical Review Letter

Asymmetric block copolymers confined in a thin film

Supramolecular & Biomaterials Chemistr

Influence of confinement on the orientational phase transitions in the lamellar phase of a block copolymer melt under shear flow

In this work we incorporate some real-system effects into the theory of orientational phase transitions under shear flow (M. E. Cates and S. T. Milner, Phys. Rev. Lett. v.62, p.1856 (1989) and G. H. Fredrickson, J. Rheol. v.38, p.1045 (1994)). In particular, we study the influence of the shear-cell boundaries on the orientation of the lamellar phase. We predict that at low shear rates the parallel orientation appears to be stable. We show that there is a critical value of the shear rate at which the parallel orientation loses its stability and the perpendicular one appears immediately below the spinodal. We associate this transition with a crossover from the fluctuation to the mean-field behaviour. At lower temperatures the stability of the parallel orientation is restored. We find that the region of stability of the perpendicular orientation rapidly decreases as shear rate increases. This behaviour might be misinterpreted as an additional perpendicular to parallel transition recently discussed in literature.Comment: 25 pages, 4 figures, submitted to Phys. Rev.

Gyroid-Forming Diblock Copolymers Confined in Cylindrical Geometry: A Case of Extreme Makeover for Domain Morphology

The self-assembly of gyroid-forming diblock copolymers confined in cylindrical geometry is studied using a combination of computer simulations and experiments. The simulations, based on a system qualitatively representative of poly(styrene-b-isoprene), are performed with cylindrical nanopores of different diameter (D) and surface selectivity. The effects of the pore size and surface selectivity on morphology are systematically investigated. Different morphological sequences are predicted for two gyroid-forming diblock copolymers. The experiments are carried out on two gyroid-forming poly(styrene-b-dimethylsiloxane) block copolymer samples confined in the core of continuous core−shell nanofibers of different diameters, which are obtained by a coaxial two-fluid electrospinning technique. The internal microphase-separated morphologies of these fibers are investigated by transmission electron microscopy (TEM). Both simulations and experiments demonstrate that a rich variety of structures spontaneously form for the gyroid-forming diblock copolymers, depending on the conditions of cylindrical confinement. Many of these confinement-induced structures are quite different from those of cylinder-forming or lamella-forming block copolymers. Simulations further show that these structures depend sensitively on the block copolymer composition, surface selectivity, and the ratio D/L0 where L0 is the period of the equilibrium gyroid phase. While the simulation and experimental systems are representative of different chemistries, the morphological predictions of simulations are qualitatively consistent with the experimental observations.Massachusetts Institute of Technology. Institute for Soldier Nanotechnologies (Contract DAAD-19-02-D-0002)United States. Army Research Offic

A computational view on nanomaterial intrinsic and extrinsic features for nanosafety and sustainability

In recent years, an increasing number of diverse Engineered Nano-Materials (ENMs), such as nanoparticles and nanotubes, have been included in many technological applications and consumer products. The desirable and unique properties of ENMs are accompanied by potential hazards whose impacts are difficult to predict either qualitatively or in a quantitative and predictive manner. Alongside established methods for experimental and computational characterisation, physics-based modelling tools like molecular dynamics are increasingly considered in Safe and Sustainability-by-design (SSbD) strategies that put user health and environmental impact at the centre of the design and development of new products. Hence, the further development of such tools can support safe and sustainable innovation and its regulation. This paper stems from a community effort and presents the outcome of a four-year-long discussion on the benefits, capabilities and limitations of adopting physics-based modelling for computing suitable features of nanomaterials that can be used for toxicity assessment of nanomaterials in combination with data-based models and experimental assessment of toxicity endpoints. We review modern multiscale physics-based models that generate advanced system-dependent (intrinsic) or timeand environment-dependent (extrinsic) descriptors/features of ENMs (primarily, but not limited to nanoparticles, NPs), with the former being related to the bare NPs and the latter to their dynamic fingerprinting upon entering biological media. The focus is on (i) effectively representing all nanoparticle attributes for multicomponent nanomaterials, (ii) generation and inclusion of intrinsic nanoform properties, (iii) inclusion of selected extrinsic properties, (iv) the necessity of considering distributions of structural advanced features rather than only averages. This review enables us to identify and highlight a number of key challenges associated with ENMs’ data generation, curation, representation and use within machine learning or other advanced data-driven models to ultimately enhance toxicity assessment. Finally, the set up of dedicated databases as well as the development of grouping and read-across strategies based on the mode of action of ENMs using omics methods are identified as emerging methodologies for safety assessment and reduction of animal testing

Advancing the defensive explanation for anxiety disorders: lorazepam effects on human defense are systematically modulated by personality and threat-type

Clinically effective drugs against human anxiety and fear systematically alter the innate defensive behavior of rodents, suggesting that in humans these emotions reflect defensive adaptations. Compelling experimental human evidence for this theory is yet to be obtained. We report the clearest test to date by investigating the effects of 1 and 2mg of the anti-anxiety drug lorazepam on the intensity of threat-avoidance behavior in 40 healthy adult volunteers (20 females). We found lorazepam modulated the intensity of participants’ threat-avoidance behavior in a dose-dependent manner. However, the pattern of effects depended upon two factors: type of threat-avoidance behavior and theoretically relevant measures of personality. In the case of flight behavior (one-way active avoidance), lorazepam increased intensity in low scorers on the Fear Survey Schedule tissuedamage fear but reduced it in high scorers. Conversely, in the case of risk-assessment behavior (two-way active avoidance), lorazepam reduced intensity in low scorers on the Spielberger trait anxiety but increased it in high scorers. Anti-anxiety drugs do not systematically affect rodent flight behavior; therefore, we interpret this new finding as suggesting that lorazepam has a broader effect on defense in humans than in rodents, perhaps by modulating general perceptions of threat intensity. The different patterning of lorazepam effects on the two behaviors implies that human perceptions of threat intensity are nevertheless distributed across two different neural streams, which influence effects observed on one-way or two-way active avoidance demanded by the situation

A computational view on nanomaterial intrinsic and extrinsic features for nanosafety and sustainability

In recent years, an increasing number of diverse Engineered Nano-Materials (ENMs), such as nanoparticles and nanotubes, have been included in many technological applications and consumer products. The desirable and unique properties of ENMs are accompanied by potential hazards whose impacts are difficult to predict either qualitatively or in a quantitative and predictive manner. Alongside established methods for experimental and computational characterisation, physics-based modelling tools like molecular dynamics are increasingly considered in Safe and Sustainability-by-design (SSbD) strategies that put user health and environmental impact at the centre of the design and development of new products. Hence, the further development of such tools can support safe and sustainable innovation and its regulation.This paper stems from a community effort and presents the outcome of a four-year-long discussion on the benefits, capabilities and limitations of adopting physics-based modelling for computing suitable features of nanomaterials that can be used for toxicity assessment of nanomaterials in combination with data-based models and experimental assessment of toxicity endpoints. We reviewmodern multiscale physics-based models that generate advanced system-dependent (intrinsic) or time -and environment-dependent (extrinsic) descriptors/features of ENMs (primarily, but not limited to nanoparticles, NPs), with the former being related to the bare NPs and the latter to their dynamic fingerprinting upon entering biological media. The focus is on (i) effectively representing all nanoparticle attributes for multicomponent nanomaterials, (ii) generation and inclusion of intrinsic nanoform properties, (iii) inclusion of selected extrinsic properties, (iv) the necessity of considering distributions of structural advanced features rather than only averages. This review enables us to identify and highlight a number of key challenges associated with ENMs' data generation, curation, representation and use within machine learning or other advanced data-driven models to ultimately enhance toxicity assessment. Finally, the set up of dedicated databases as well as the development of grouping and read-across strategies based on the mode of action of ENMs using omics methods are identified as emerging methodologies for safety assessment and reduction of animal testing.Horizon 2020(H2020)814426Solid state NMR/Biophysical Organic ChemistrySupramolecular & Biomaterials Chemistr