Site-specific fabrication and epitaxial conversion of functional oxide nanodisk arrays

Nanodisk arrays of technologically important magnetic (CoFe(2)O(4)) and ferroelectric (BaTiO(3)) oxides are fabricated on diverse substrates with well-defined size and separation using the soft-eBL approach. We demonstrate that below a certain pattern size, the as-deposited amorphous nanodisks can be readily converted into dense, single-crystal form that exhibit cube-on-cube heteroepitaxy with respect to the underlying single-crystal substrate. Such single-crystal disks show well-defined truncated-pyramid morphology that is consistent with Wulff construction. The mechanism of morphology development with the pattern size change is discussed. Localized characterization of the crystallinity, chemical composition, and magnetic behavior of the CFO nanodisk patterns are carried out using analytical transmission electron microscopy and magnetic force microscopy. Such solution-based epitaxial conversion of patterned arrays of multifunctional oxides has potential for viable cost-effective technological applications.     

Data generative machine learning model for the assessment of outdoor thermal and wind comfort in a northern urban environment

Predicting comfort levels in cities is challenging due to the many metric assessment. To overcome these challenges, much research is being done in the computing community to develop methods capable of generating outdoor comfort data. Machine Learning (ML) provides many opportunities to discover patterns in large datasets such as urban data. This paper proposes a data-driven approach to build a predictive and data-generative model to assess outdoor thermal comfort. The model benefits from the results of a study, which analyses Computational Fluid Dynamics (CFD) urban simulation to determine the thermal and wind comfort in Tallinn, Estonia. The ML model was built based on classification, and it uses an opaque ML model. The results were evaluated by applying different metrics and show us that the approach allows the implementation of a data-generative ML model to generate reliable data on outdoor comfort that can be used by urban stakeholders, planners, and researchers.     

Engineering a drug eluting ocular patch for delivery and sustained release of anti-inflammatory therapeutics

Ocular inflammation is commonly associated with eye disease or injury. Effective and sustained ocular delivery of therapeutics remains a challenge due to the eye physiology and structural barriers. Herein, we engineered a photocrosslinkable adhesive patch (GelPatch) incorporated with micelles (MCs) loaded with loteprednol etabonate (LE) for delivery and sustained release of drug. The engineered drug loaded adhesive hydrogel, with controlled physical properties, provided a matrix with high adhesion to the ocular surfaces. The incorporation of MCs within the GelPatch enabled solubilization of LE and its sustained release within 15 days. In vitro studies showed that MC loaded GelPatch supported cell viability and growth. In addition, subcutaneous implantation of the MC loaded GelPatch in rats confirmed its in vivo biocompatibility and stability within 28 days. This non-invasive, adhesive, and biocompatible drug eluting patch can be used as a matrix for the delivery and sustained release of hydrophobic drugs.