Template-assisted fabrication of patchy particles with uniform patches

Patchy particles with uniform patches of specific shape and size have been predicted to have a rich potential in fabricating new structures; however, an effective method to control the patch shape and size is still missing. In the method presented here, a template is used to assist the fabrication of patchy particles with patches of uniform shape and controlled size by use of the glancing angle deposition method (GLAD). Uniform shadowing effects are caused by the wall of the grooves carved into the surface of a silicon wafer. The ratio of template dimension to particle diameter and the angle of incidence of the metal vapor rays determine the patch shape and size. Mathematical calculations are applied to predict the patch shape and size. Scanning electron microscopy is used to demonstrate the efficiency of the method. Scaling analysis shows that the template-assisted GLAD method leads to a 3100-fold increase in patchy particle fabrication volumes compared to the template-free GLAD method.     

Synthesis of oxygen-deficient luminescent mesoporous silica nanoparticles for synchronous drug delivery and imaging

Oxygen-deficient luminescent mesoporous silica nanoparticles with uniform morphology/size and integrated mesoporosity-luminescent property in a single nanoparticle are successfully synthesized by a bottom-up self-assembly route followed by a post-calcination process, and can be used to facilely load/deliver drugs into cells and luminescently image cells.     

Self-assembly of patchy particles into diamond structures through molecular mimicry

Fabrication of diamond structures by self-assembly is a fundamental challenge in making three-dimensional photonic crystals. We simulate a system of model hard particles with attractive patches and show that they can self-assemble into a diamond structure from an initially disordered state. We quantify the extent to which the formation of the diamond structure can be facilitated by "seeding" the system with small diamond crystallites or by introducing a rotation interaction to mimic a carbon-carbon antibonding interaction. Our results suggest patchy particles may serve as colloidal "atoms" and "molecules" for the bottom-up self-assembly of three-dimensional crystals.     

The bottom-up approach to molecular-level devices and machines

The macroscopic concepts of a device and a machine can be extended to the molecular level. Molecular-level devices and machines are constructed by a bottom-up approach. The atom-by-atom bottom-up approach is unrealistic from the chemical viewpoint. The bottom-up approach molecule-by-molecule following the guidelines of supramolecular (multicomponent) chemistry has proved to be successful. The extension of the concepts of a device and a machine to the molecular level is of interest not only for basic research, but also for the growth of nanoscience and the development of nanotechnology.     

Engineering Surface Patterning of Colloidal Rings through Plateau–Rayleigh Instability

Plateau–Rayleigh (P‐R) instability occurring on Brownian colloidal particles is presented. This instability can be used for the surface patterning of Brownian colloidal rings. This idea was realized by employing polystyrene(PS)/SiO₂ core/shell rings, for which PS layer was selectively grown onto the interior surface of SiO₂ rings. The P‐R instability was initiated in the ring's dispersion by adding a good solvent of PS. By using both experiments and theory, it is shown that the number of patches is tunable and that it is linearly related to a function of two variables, namely, solvent quantity and contact angle. In particular, one‐patch Janus rings and patchy disks were also synthesized at high yields. The patch size of all particles is tunable by step‐by‐step polymerization and the patches can be functionalized, for example by ATRP grafting with pH‐sensitive polymers. This approach can be adapted for the synthesis of other patchy colloids with designated complexity.     

Defect topologies in a nematic liquid crystal near a patchy colloid

Using isothermal-isobaric Monte Carlo simulations we investigate defect topologies due to a spherical colloidal particle immersed in a nematic liquid crystal. Defects arise because of the competition between the preferential orientation at the colloid's surface and the far-field director ?n(0). Considering a chemically homogeneous colloid as a special case we observe the well-known surface and saturn ring defect topologies for weak and strong perpendicular anchoring, respectively; for homogeneous, strong parallel anchoring we find a boojum defect topology that has been seen experimentally [see P. Poulin and D. A. Weitz, Phys. Rev. E 57, 626 (1998)] but not in computer simulations. We also consider a heterogeneous, patchy colloid where the liquid-crystal molecules anchor either preferentially planar or perpendicular at the surface of the colloid. For a patchy colloid we observe a boojum ring defect topology in agreement with recent experimental studies [see M. Conradi, M. Ravnik, M. Bele, M. Zorko, S. Z?umer, and I. Mus?evic?, Soft Matter 5, 3905 (2009)]. We also observe two other novel defect topologies that have not been reported thus far neither experimentally nor theoretically.     

Directing the Self‐Assembly of Semiconducting Copolymers: The Consequences of Grafting Linear or Hyperbranched Polyether Side Chains

The synthesis and self‐assembly of novel semiconducting rod–coil type graft block copolymers based on poly(para‐phenylene vinylene) (PPV) copolymers is presented, focusing on the ordering effect of linear versus hyperbranched side chains. Using an additional reactive ester block, highly polar, linear poly(ethylene glycol), and hyperbranched polyglycerol side chains are attached in a grafting‐to approach. Remarkably, the resulting novel semiconducting graft copolymers with polyether side chains show different solubility and side‐chain directed self‐assembly behavior in various solvents, e.g., cylindrical or spherical superstructures in the size range of 10 to 120 nm, as shown by TEM. By adjusting the molecular weight and the topology of the polyether segments, self‐assembly into defined superstructures can be achieved, which is important for the efficient charge transport in potential electronic applications.

     

Modeling nutrient impacts on microalgae cells via image analyses

A nonlinear multivariate regression methodology is presented for modeling the responses of microalgae cells regarding their physical appearance (size, shape) to shifts in their chemical environment. This chemometric approach builds on a novel image analysis method recently published in this Journal and augments it such that: (i) the measured effect is expressed mathematically rather than described empirically and (ii) incorporates effects of multiple ambient parameters so that their interactions can be investigated. Copyright © 2013 John Wiley & Sons, Ltd.     

Amphiphilic Patchy Composite Colloids

A new approach to fabricate patchy silica/polymeric gel composite colloids with amphiphilic performance is reported. The amphiphilic performance is rendered by selectively modifying the silica framework with a silane that contains an oleophilic alkyl chain. The patchy composite colloids are dispersible in both water and oil, and may be used as a solid particle surfactant. The modified silica framework can also assist other functional materials to disperse in a desired media. The corresponding silica/carbon composite colloids become amphiphilic after a sequential activation of carbon and modification of silica, and meanwhile possess as good electron conductivity as the as‐prepared silica/carbon composite colloids.

     

Synthesis of Fibrous Phosphorus Micropillar Arrays with Pyro-Phototronic Effects

The bottom-up preparation of two-dimensional material micro-nano structures at scale facilitates the realisation of integrated applications in optoelectronic devices. Fibrous Phosphorus (FP), an allotrope of black phosphorus (BP), is one of the most promising candidate materials in the field of optoelectronics with its unique crystal structure and properties.^[1] However, to date, there are no bottom-up micro-nano structure preparation methods for crystalline phosphorus allotropes.^{[1c, 2]} Herein, we present the bottom-up preparation of fibrous phosphorus micropillar (FP-MP) arrays via a low-pressure gas-phase transport (LP-CVT) method that controls the directional phase transition from amorphous red phosphorus (ARP) to FP. In addition, self-powered photodetectors (PD) of FP-MP arrays with pyro-phototronic effects achieved detection beyond the band gap limit. Our results provide a new approach for bottom-up preparation of other crystalline allotropes of phosphorus.     

Bottom-up computational modeling of semi-crystalline fibers: from atomistic to continuum scale

A bottom-up computational approach involving Molecular Dynamics (MD) of silk fiber subunits and Finite Element (FE) simulations of whole spider silk fibers is presented. The approach is discussed with an emphasis on the benefits and bottlenecks of incorporating the atomistic and continuum models of crystalline and disordered domains in the fibers. The approach does not require any empirical parameters and it is applicable to similar semi-crystalline systems.     

Synthesis and characterization of polyhedral Pt nanoparticles: their catalytic property, surface attachment, self-aggregation and assembly

In this paper, we presented the preparation procedure of Pt nanoparticles with the well-controlled polyhedral morphology and size by a modified polyol method using AgNO(3) in accordance with the reduction of H(2)PtCl(6) in EG at high temperature around 160°C. The methods of UV-vis spectroscopy, X-ray diffraction (XRD), transmission electron microscopy (TEM), and high resolution (HR) TEM measurements were used to characterize their surface morphology, size, and crystal structure. We have observed that the polyhedral Pt nanoparticles of sharp edges and corners were produced in the preferential homogenous growth as well as the formation of porous and large Pt particles by self-aggregation and assembly originating from as-prepared polyhedral Pt nanoparticles. It is most impressive to find that the arrangement of Pt nanoparticles was observed in their surface attachments, self-aggregation, random and directed surface self-assembly by the bottom-up approach. Their high electrocatalytic activity for methanol oxidation was predicted. The findings and results showed that the polyhedral Pt nanoparticle-based catalysts exhibited the high electrocatalytic activity for their potential applications in developing the efficient Pt-based catalysts for direct methanol fuel cells.     

New Type of Columnar Liquid Crystal Superlattice in Double-Taper Ionic Minidendrons

Wedge-shaped molecules, such as dendrons, are among the most important building blocks for directed supramolecular self-assembly. Here we present a new approach aimed at widening the range and complexity of potential mesophases by introducing double-tapered mesogens. Two series of compounds are presented, both alkali metal salts (Li, Na, Cs) of 3,4,5-tris-alkoxybenzoic acid with a second tapered tris-alkoxyaryl group attached at the end of an alkoxy chain. The double-tapered compounds all display an unusual hexagonal columnar phase consisting of one ionic and three non-ionic columns per unit cell. The cation size has an unexpectedly drastic effect on unit cell size. Unlike most columnar phases, the current phases show unusually high dimensional stability on heating, and high stiffness in spite of being 80–85 % aliphatic, attributed to their molecular topology. The described approach may lead to co-assemblies of multifunctional materials, for example, parallel p- and n-semiconducting nanowires or parallel ionic and electronic conductors.     

An improved pixel-based approach for analyzing images in two-dimensional gel electrophoresis

An improved pixel-based approach for analyzing 2-DE images is presented. The key feature of the method is to create a mask based on all gels in the experiment using image morphology, followed by multivariate analysis on the pixel level. The method reduces the impact of noise and background by identifying regions in the image where protein spots are present, but make no assumption on individual spot boundaries for isolated spots. This makes it possible to detect significant changes in complex regions, and visualize these changes over multiple gels in an easy way. False missing values and spot volumes caused by imposing erroneous spot boundaries are thus circumvented. The approach presented gives improved pixel-based information from the gels, and is also an alternative to existing methods for data-reduction, significance testing and visualization of 2-DE data. Results are compared with software using a common spot boundary approach on an experiment consisting of 35 full size gel images. Gel alignment is required before analysis.     

Design of anti-icing coatings using supercooled droplets as nano-to-microscale probes

A multiscale simulation-based approach is presented for predicting anti-icing properties of nanocomposite coatings. Development of robust anti-icing coatings is a challenging task. An anti-icing coating that can prevent in-flight icing is of particular interest to the aircraft industry. A multiscale simulations based approach is developed to provide insights into the complex effect of coating material and surface topology on the prevention of in-flight icing. Chemical properties of different coatings and kinetics of icing or inhibition of ice nucleation are calculated from nanoscale atomistic simulations. In addition, in-flight icing environments including impingement and rolling of supercooled microdroplet and nucleation of ice under wind shear have been implemented using fluid dynamics methodologies. A model for icing in nano-to-microscale for surfaces with known chemical composition and surface topology is used for developing predictive capabilities regarding anti-icing performance of potential coatings. In this work, fluorinated polyhedral oligomericsilsesquioxanes molecules have been used to increase nanoscale roughness when embedded in a polycarbonate polymeric matrix. The findings suggest that a successful anti-icing coating will require precise control over nanoscale and microscale roughness. The multiscale methodology presented therefore can potentially help in identifying coupled effects of material, surface topology, and icing environment for promising coatings before performing icing tunnel experiments.     

The mechanism of magnetic interactions in the bulk ferromagnet para-(methylthio)phenyl nitronyl nitroxide (YUJNEW): a first principles, bottom-up, theoretical study

The mechanism of magnetic interactions in the bulk ferromagnet para-(methylthio)phenyl nitronyl nitroxide crystal (YUJNEW) has been theoretically reinvestigated, using only data from ab initio calculations and avoiding any a priori assumptions. We first calculate the microscopic magnetic interactions (JAB exchange couplings) between all unique radical pairs in the crystal, and then generate the macroscopic magnetic properties from the energy levels of the corresponding Heisenberg Hamiltonian. We thus propose a first principles, bottom-up (i.e. micro-to-macro) approach that brings theory and experiment together. We have applied this strategy to study the magnetism of YUJNEW using data from the previously reported 298 and 114 K crystal structures, and also data from a 10 K neutron diffraction structure fully reported in this work. The magnetic topology at 298 K is two-dimensional: noninteracting planes, with three different in-plane JAB pair interactions (+0.24, +0.09, and -0.11 cm(-1)) and one numerically negligible (+0.02 cm(-1)) inter-plane JAB interaction. In contrast, the magnetic topology at 114 and 10 K is three-dimensional, with two non-negligible in-plane JAB constants (+0.11 and +0.07 cm(-1) at 114 K; +0.22 and +0.07 cm(-1) at 10 K) and one inter-plane pair interaction (+0.07 cm(-1) at 114 K; +0.08 cm(-1) at 10 K). Although this three-dimensional magnetic topology is consistent with YUJNEW being a bulk ferromagnet, there is only a qualitative agreement between computed and experimental magnetic susceptibility chiT(T) data at 114 K. However, the experimental chiT(T) curve is quantitatively reproduced at 10 K. The heat capacity curve presents a peak at around 0.12 K, close to the estimated experimental peak (0.20 K).     

A HMM-based method to predict the transmembrane regions of beta-barrel membrane proteins

A novel method is developed to model and predict the transmembrane regions of beta-barrel membrane proteins. It is based on a Hidden Markov model (HMM) with architecture obeying those proteins' construction principles. The HMM is trained and tested on a non-redundant set of 11 beta-barrel membrane proteins known to date at atomic resolution with a jack-knife procedure. As a result, the method correctly locates 97% of 172 transmembrane beta-strands. Out of the 11 proteins, the barrel size for ten proteins and the overall topology for seven proteins are correctly predicted. Additionally, it successfully assigns the entire topology for two new beta-barrel membrane proteins that have no significant sequence homology to the 11 proteins. Predicted topology for two candidates for beta-barrel structure of the outer mitochondrial membrane is also presented in the paper.     

Site-selective patterning of organic luminescent molecules via gas phase deposition

In this paper, we present a bottom-up approach to pattern organic luminescent molecules with a feature size down to sub-100 nm over wafer-sized areas. This method is based on the selective gas deposition of organic molecules on self-organized patterned structures, which consist of an organic monolayer with two different phases rather than different materials. The site selectivity is controllable by deposition rate and the pattern features. The reason for the site selectivity may be due to the nucleation and diffusion behaviors of the deposited organic molecules on different monolayer phases.     

Bottom-up synthesis of gold octahedra with tailorable hollow features

Gold octahedra with hollow features have been synthesized in high yield via the controlled overgrowth of preformed concave cube seeds. This Ag(+)-assisted, seed-mediated synthesis allows for the average edge length of the octahedra and the size of the hollow features to be independently controlled. We propose that a high concentration of Ag(+) stabilizes the {111} facets of the octahedra through underpotential deposition while the rate of Au(+) reduction controls the dimensions of the hollow features. This synthesis represents a highly controllable bottom-up approach for the preparation of hollow gold nanostructures.     

Application of Deep Learning Workflow for Autonomous Grain Size Analysis

Traditional grain size determination in materials characterization involves microscopy images and a laborious process requiring significant manual input and human expertise. In recent years, the development of computer vision (CV) has provided an alternative approach to microstructural characterization with preliminary implementations greatly simplifying the grain size determination process. Here, an end-to-end workflow to measure grain size in microscopy images without any manual input is presented. Following the ASTM standards for grain size determination, results from the line intercept (Heyn’s method) and planimetric (Saltykov’s method) approaches are used as the baseline. A pre-trained holistically nested edge detection (HED) model is used for CV-based edge detection, and the results are further compared to the classic Canny edge detection method. Post-processing was performed using open-source image processing packages to extract the grain size. In optical microscope images, the pre-trained HED model achieves much higher accuracy than the Canny edge detection method while reducing the image processing time by one to two orders of magnitude compared to traditional methods. The effects of morphological operations on the predicted grain size accuracy are also explored. Overall, the proposed end-to-end convolutional neural network (CNN)-based workflow can significantly reduce the processing time while maintaining the same accuracy as the traditional manual method.