MLExchange: A web-based platform enabling exchangeable machine learning workflows for scientific studies.

Machine learning (ML) algorithms are showing a growing trend in helping the scientific communities across different disciplines and institutions to address large and diverse data problems. However, many available ML tools are programmatically demanding and computationally costly. The MLExchange project aims to build a collaborative platform equipped with enabling tools that allow scientists and facility users who do not have a profound ML background to use ML and computational resources in scientific discovery. At the high level, we are targeting a full user experience where managing and exchanging ML algorithms, workflows, and data are readily available through web applications. Since each component is an independent container, the whole platform or its individual service(s) can be easily deployed at servers of different scales, ranging from a personal device (laptop, smart phone, etc.) to high performance clusters (HPC) accessed (simultaneously) by many users. Thus, MLExchange renders flexible using scenarios-users could either access the services and resources from a remote server or run the whole platform or its individual service(s) within their local network.

Xi-cam: a versatile interface for data visualization and analysis.

Xi-cam is an extensible platform for data management, analysis and visualization. Xi-cam aims to provide a flexible and extensible approach to synchrotron data treatment as a solution to rising demands for high-volume/high-throughput processing pipelines. The core of Xi-cam is an extensible plugin-based graphical user interface platform which provides users with an interactive interface to processing algorithms. Plugins are available for SAXS/WAXS/GISAXS/GIWAXS, tomography and NEXAFS data. With Xi-cam's `advanced' mode, data processing steps are designed as a graph-based workflow, which can be executed live, locally or remotely. Remote execution utilizes high-performance computing or de-localized resources, allowing for the effective reduction of high-throughput data. Xi-cam's plugin-based architecture targets cross-facility and cross-technique collaborative development, in support of multi-modal analysis. Xi-cam is open-source and cross-platform, and available for download on GitHub.

Self-assembled nanoparticle micro-shells templated by liquid crystal sorting.

A current goal in nanotechnology focuses on the assembly of different nanoparticle types into 3D organized structures. In this paper we report the use of a liquid crystal host phase in a new process for the generation of micron-scale vesicle-like nanoparticle shells stabilized by ligand-ligand interactions. The constructs formed consist of a robust, thin spherical layer, composed of closely packed quantum dots (QDs) and stabilized by local crystallization of the mesogenic ligands. Ligand structure can be tuned to vary QD packing within the shell and made UV cross-linkable to allow for intact shell extraction into toluene. The assembly method we describe could be extended to other nanoparticle types (metallic, magnetic etc.), where hollow shell formation is controlled by thermally sorting mesogen-functionalized nanoparticles in a liquid crystalline host material at the isotropic to nematic transition. This process represents a versatile method for making non-planar 3D nano-assemblies.

Magnetic field induced quantum dot brightening in liquid crystal synergized magnetic and semiconducting nanoparticle composite assemblies.

The design and development of multifunctional composite materials from artificial nano-constituents is one of the most compelling current research areas. This drive to improve over nature and produce 'meta-materials' has met with some success, but results have proven limited with regards to both the demonstration of synergistic functionalities and in the ability to manipulate the material properties post-fabrication and in situ. Here, magnetic nanoparticles (MNPs) and semiconducting quantum dots (QDs) are co-assembled in a nematic liquid crystalline (LC) matrix, forming composite structures in which the emission intensity of the quantum dots is systematically and reversibly controlled with a small applied magnetic field (<100 mT). This magnetic field-driven brightening, ranging between a two- to three-fold peak intensity increase, is a truly cooperative effect: the LC phase transition creates the co-assemblies, the clustering of the MNPs produces LC re-orientation at atypical low external field, and this re-arrangement produces compaction of the clusters, resulting in the detection of increased QD emission. These results demonstrate a synergistic, reversible, and an all-optical process to detect magnetic fields and additionally, as the clusters are self-assembled in a fluid medium, they offer the possibility for these sensors to be used in broad ranging fluid-based applications.

Designing highly tunable semiflexible filament networks.

Semiflexible polymers can generate a range of filamentous networks significantly different in structure from those seen in conventional polymer solutions. Our coarse-grained simulations with an implicit cross-linker potential show that networks of branching bundles, knotted morphologies, and structural chirality can be generated by a generalized approach independent of specific cross-linkers. Network structure depends primarily on filament flexibility and separation, with significant connectivity increase after percolation. Results should guide the design of engineered semiflexible polymers.

Tuning quantum-dot organization in liquid crystals for robust photonic applications.

Mesogenic ligands have the potential to provide control over the dispersion and stabilization of nanoparticles in liquid crystal (LC) phases. The creation of such hybrid materials is an important goal for the creation of soft tunable photonic devices, such as the LC laser. Herein, we present a comparison of isotropic and mesogenic ligands attached to the surface of CdSe (core-only) and CdSe/ZnS (core/shell) quantum dots (QDs). The mesogenic ligand's flexible arm structure enhances ligand alignment, with the local LC director promoting QD dispersion in the isotropic and nematic phases. To characterize QD dispersion on different length scales, we apply fluorescence microscopy, X-ray scattering, and scanning confocal photoluminescent imaging. These combined techniques demonstrate that the LC-modified QDs do not aggregate into the dense clusters observed for dots with simple isotropic ligands when dispersed in liquid crystal, but loosely associate in a fluid-like droplet with an average interparticle spacing >10 nm. Embedding the QDs in a cholesteric cavity, we observe comparable coupling effects to those reported for more closely packed isotropic ligands.