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The correlations between the sequence of monomers in a polymer and its three-dimensional structure is a grand challenge in polymer science and biology. The properties and functions of macromolecules depend on their 3D shape that has appeared to be dictated by their monomer sequence. However, the progress towards understanding the sequence-structure-property correlations and their utilization in materials engineering are slow because it is almost impossible to characterize astronomically large number of possible sequences of a copolymer using traditional experimental and simulation methods. To address this problem, here, we combine evolutionary computing and coarse-grained molecular dynamics simulation and study the sequence-structure correlations of a model AB type copolymer system. The CGMD based evolutionary algorithm screens the sequence space of the copolymer efficiently and identifies wide range of single molecule structures including extremal radius of gyrations. The data provide new insights on the sequence-Rg correlations of the copolymer system and their impact on the structure and functionality of polymeric materials. The work highlights the opportunities of sequence specific control of macromolecular structure for designing materials with exceptional properties.
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We discuss the efficacy of evolutionary method for the purpose of structural analysis of amorphous solids. At present ab initio molecular dynamics (MD) based melt-quench technique is used and this deterministic approach has proven to be successful to study amorphous materials. We show that a stochastic approach motivated by Darwinian evolution can also be used to simulate amorphous structures. Applying this method, in conjunction with density functional theory (DFT) based electronic, ionic and cell relaxation, we re-investigate two well known amorphous semiconductors, namely silicon and indium gallium zinc oxide (IGZO). We find that characteristic structural parameters like average bond length and bond angle are within $sim$ 2% to those reported by ab initio MD calculations and experimental studies.
New developments in the field of topological matter are often driven by materials discovery, including novel topological insulators, Dirac semimetals and Weyl semimetals. In the last few years, large efforts have been performed to classify all known inorganic materials with respect to their topology. Unfortunately, a large number of topological materials suffer from non-ideal band structures. For example, topological bands are frequently convoluted with trivial ones, and band structure features of interest can appear far below the Fermi level. This leaves just a handful of materials that are intensively studied. Finding strategies to design new topological materials is a solution. Here we introduce a new mechanism that is based on charge density waves and non-symmorphic symmetry to design an idealized Dirac semimetal. We then show experimentally that the antiferromagnetic compound GdSb$_{0.46}$Te$_{1.48}$ is a nearly ideal Dirac semimetal based on the proposed mechanism, meaning that most interfering bands at the Fermi level are suppressed. Its highly unusual transport behavior points to a thus far unknown regime, in which Dirac carriers with Fermi energy very close to the node seem to gradually localize in the presence of lattice and magnetic disorder.
Using a reference system approach, we develop an analytical theory for the adsorption of random heteropolymers with exponentially decaying and/or oscillating sequence correlations on planar homogeneous surfaces. We obtain a simple equation for the adsorption-desorption transition line. This result as well as the validity of the reference system approach is tested by a comparison with numerical lattice calculations.
It is well known that the crystalline structure of the III-V nanowires (NWs) is mainly controlled by the wetting contact angle of the catalyst droplet which can be tuned by the III and V flux. In this work we present a method to control the wurtzite (WZ) or zinc-blende (ZB) structure in self-catalyzed GaAs NWs grown by molecular beam epitaxy, using in situ reflection high energy electron diffraction (RHEED) diagram analysis. Since the diffraction patterns of the ZB and WZ structures differ according to the azimuth [1-10], it is possible to follow the evolution of the intensity of specific ZB and WZ diffraction spots during the NW growth as a function of the growth parameters such as the Ga flux. By analyzing the evolution of the WZ and ZB spot intensities during some NW growths with specific changes of Ga flux, it is then possible to control the crystal structure of the NWs. ZB GaAs NWs with a controlled WZ segment have thus been realized. Using a semi-empirical model for the NW growth and our in situ RHEED measurements, the critical wetting angle of the catalyst droplet for the structural transition is deduced.
Scattering maps from strained or disordered nano-structures around a Bragg reflection can either be computed quickly using approximations and a (Fast) Fourier transform, or using individual atomic positions. In this article we show that it is possible to compute up to 4.10^10 $reflections.atoms/s using a single graphic card, and we evaluate how this speed depends on number of atoms and points in reciprocal space. An open-source software library (PyNX) allowing easy scattering computations (including grazing incidence conditions) in the Python language is described, with examples of scattering from non-ideal nanostructures.
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