ترغب بنشر مسار تعليمي؟ اضغط هنا

Exploiting classical nucleation theory for reverse self-assembly

107   0   0.0 ( 0 )
 نشر من قبل William Miller
 تاريخ النشر 2010
  مجال البحث فيزياء
والبحث باللغة English




اسأل ChatGPT حول البحث

In this paper we introduce a new method to design interparticle interactions to target arbitrary crystal structures via the process of self-assembly. We show that it is possible to exploit the curvature of the crystal nucleation free-energy barrier to sample and select optimal interparticle interactions for self-assembly into a desired structure. We apply this method to find interactions to target two simple crystal structures: a crystal with simple cubic symmetry and a two-dimensional plane with square symmetry embedded in a three-dimensional space. Finally, we discuss the potential and limits of our method and propose a general model by which a functionally infinite number of different interaction geometries may be constructed and to which our reverse self-assembly method could in principle be applied.



قيم البحث

اقرأ أيضاً

We derive a model describing spatio-temporal organization of an array of microtubules interacting via molecular motors. Starting from a stochastic model of inelastic polar rods with a generic anisotropic interaction kernel we obtain a set of equation s for the local rods concentration and orientation. At large enough mean density of rods and concentration of motors, the model describes an orientational instability. We demonstrate that the orientational instability leads to the formation of vortices and (for large density and/or kernel anisotropy) asters seen in recent experiments. We derive the specific form of the interaction kernel from the detailed analysis of microscopic interaction of two filaments mediated by a moving molecular motor, and extend our results to include variable motor density and motor attachment to the substrate.
Nucleation is an out-of-equilibrium process, which can be strongly affected by the presence of external fields. In this letter, we report a simple extension of classical nucleation theory to systems submitted to an homogeneous shear flow. The theory involves accounting for the anisotropy of the critical nucleus formation, and introduces a shear rate dependent effective temperature. This extended theory is used to analyze the results of extensive molecular dynamics simulations, which explore a broad range of shear rates and undercoolings. At fixed temperature, a maximum in the nucleation rate is observed, when the relaxation time of the system is comparable to the inverse shear rate. In contrast to previous studies, our approach does not require a modification of the thermodynamic description, as the effect of shear is mainly embodied into a modification of the kinetic prefactor and of the temperature.
DNA is an ideal candidate to organize matter on the nanoscale, primarily due to the specificity and complexity of DNA based interactions. Recent advances in this direction include the self-assembly of colloidal crystals using DNA grafted particles. I n this article we theoretically study the self-assembly of DNA-caged particles. These nanoblocks combine DNA grafted particles with more complicated purely DNA based constructs. Geometrically the nanoblock is a sphere (DNA grafted particle) inscribed inside a polyhedron (DNA cage). The faces of the DNA cage are open, and the edges are made from double stranded DNA. The cage vertices are modified DNA junctions. We calculate the equilibriuim yield of self-assembled, tetrahedrally caged particles, and discuss their stability with respect to alternative structures. The experimental feasability of the method is discussed. To conclude we indicate the usefulness of DNA-caged particles as nanoblocks in a hierarchical self-assembly strategy.
We develop a multi-scale approach to simulate hydrated nanobio systems under realistic condi- tions (e.g., nanoparticles and protein solutions at physiological conditions over time-scales up to hours). We combine atomistic simulations of water at bio -interfaces (e.g., proteins or membranes) and nano-interfaces (e.g., nanoparticles or graphene sheets) and coarse-grain models of hydration water for protein folding and protein design. We study protein self-assembly and crystallization, in bulk or under confinement, and the kinetics of protein adsorption onto nanoparticles, verify- ing our predictions in collaboration with several experimental groups. We try to find answers for fundamental questions (Why water is so important for life? Which properties make water unique for biological processes?) and applications (Can we design better drugs? Can we limit protein- aggregations causing Alzheimer? How to implement nanotheranostic?). Here we focus only on the two larger scales of our approach: (i) The coarse-grain description of hydrated proteins and protein folding at sub-nanometric length-scale and milliseconds-to-seconds time-scales, and (ii) the coarse-grain modeling of protein self-assembly on nanoparticles at 10-to-100 nm length-scale and seconds-to-hours time-scales.
Controlling the topology of structures self-assembled from a set of heterogeneous building blocks is highly desirable for many applications, but is poorly understood theoretically. Here we show that the thermodynamic theory of self-assembly involves an inevitable divergence in chemical potential. The divergence and its detailed structure are controlled by the spectrum of the transfer matrix, which summarizes all of self-assembly design degrees of freedom. By analyzing the transfer matrix, we map out the phase boundary between the designable structures and the unstructured aggregates, driven by the level of cross-talk.
التعليقات
جاري جلب التعليقات جاري جلب التعليقات
سجل دخول لتتمكن من متابعة معايير البحث التي قمت باختيارها
mircosoft-partner

هل ترغب بارسال اشعارات عن اخر التحديثات في شمرا-اكاديميا