Incorporation strategy for organic dyes into gold nanoparticle supercrystals.

Ordered arrays of plasmonic nanoparticles, supercrystals can lead to the formation of plasmon-polaritons. Coupling light emitters with plasmon polaritons might allow the formation of exciton-plasmon polaritons with properties tuneable by the supercrystal design. To construct such optically active materials, the inclusion of emitters is imperative.

Fetal circulatory physiology and brain development in complex congenital heart disease: A multi-modal imaging study.

Objective: Fetuses with complex congenital heart disease have altered physiology, contributing to abnormal neurodevelopment. The effects of altered physiology on brain development have not been well studied. We used multi-modal imaging to study fetal circulatory physiology and brain development in hypoplastic left heart syndrome (HLHS) and d-transposition of the great arteries (TGA).

Collective States in Molecular Monolayers on 2D Materials.

Collective excited states form in organic two-dimensional layers through Coulomb coupling of the molecular transition dipole moments. They manifest as characteristic strong and narrow peaks in the excitation and emission spectra that are shifted to lower energies compared with the monomer transition. We study experimentally and theoretically how robust the collective states are against homogeneous and inhomogeneous broadening, as well as spatial disorder that occurs in real molecular monolayers.

Microscopic Understanding of Reaction Rates Observed in Plasmon Chemistry of Nanoparticle-Ligand Systems.

Surface-enhanced Raman scattering (SERS) is an effective and widely used technique to study chemical reactions induced or catalyzed by plasmonic substrates, since the experimental setup allows us to trigger and track the reaction simultaneously and identify the products. However, on substrates with plasmonic hotspots, the total signal mainly originates from these nanoscopic volumes with high reactivity and the information about the overall consumption remains obscure in SERS measurements. This has important implications; for example, the apparent reaction order in SERS measurements does not correlate with the real reaction order, whereas the apparent reaction rates are proportional to the real reaction rates as demonstrated by finite-difference time-domain (FDTD) simulations.

Enhanced Critical Congenital Cardiac Disease Screening by Combining Interpretable Machine Learning Algorithms.

Critical Congenital Heart Disease (CCHD) screening that only uses oxygen saturation (SpO2), measured by pulse oximetry, fails to detect an estimated 900 US newborns annually. The addition of other pulse oximetry features such as perfusion index (PIx), heart rate, pulse delay and photoplethysmography characteristics may improve detection of CCHD, especially those with systemic blood flow obstruction such as Coarctation of the Aorta (CoA). To comprehensively study the most relevant features associated with CCHD, we investigated interpretable machine learning (ML) algorithms by using Recursive Feature Elimination (RFE) to identify an optimal subset of features.