Controlled Self-assembly of Gold(I) Complexes by Multiple Kinetic Aggregation States with Nonlinear Optical and Waveguide Properties.

Introduction of multiple kinetic aggregation states (Aggs) into the self-assembly pathway could bring complexity and flexibility to the self-assemblies, which is difficult to realize due to the delicate equilibria established among different Aggs bonded by weak noncovalent interactions. Here, we describe a series of chiral and achiral d10 AuI bis(N-heterocyclic carbene, NHC) complexes, and the achiral complex could undergo self-assembly with multiple kinetic Aggs. Generation of multiple kinetic Aggs was realized by applying chiral or achiral seeds exhibiting large differences in elongation temperatures for their respective cooperative self-assembly processes. We further showed that the chiral AuI self-assemblies having non-centrosymmetric packing forms exhibit nonlinear optical response of second harmonic generation (SHG), while the SHG signal is absent in the achiral analogue. The crystalline achiral AuI self-assemblies could function as optical waveguides with strong emission polarization.

Printable Block Molecular Assemblies with Controlled Exciton Dynamics.

Creating hierarchical molecular block heterostructures, with the control over size, shape, optical, and electronic properties of each nanostructured building block can help develop functional applications, such as information storage, nanowire spectrometry, and photonic computing. However, achieving precise control over the position of molecular assemblies, and the dynamics of excitons in each block, remains a challenge. In the present work, the first fabrication of molecular heterostructures with the control of exciton dynamics in each block, is demonstrated. Additionally, these heterostructures are printable and can be precisely positioned using Direct Ink Writing-based (DIW) 3D printing technique, resulting in programable patterns. Singlet excitons with emission lifetimes on nanosecond or microsecond timescales and triplet excitons with emission lifetimes on millisecond timescales appear simultaneously in different building blocks, with an efficient energy transfer process in the heterojunction. These organic materials also exhibit stimuli-responsive emission by changing the power or wavelength of the excitation laser. Potential applications of these organic heterostructures in integrated photonics, where the versatility of fluorescence, phosphorescence, efficient energy transfer, printability, and stimulus sensitivity co-exist in a single nanowire, are foreseen.

Optical Signal Modulation in Photonic Waveguiding Heteroarchitectures with Continuously Variable Visible-To-Near-Infrared Emission Color.

Photonic circuit systems based on optical waveguiding heteroarchitectures have attracted considerable interest owing to their potential to overcome the speed limitation in electronic circuits by modulating the optical signal at the micro- or nanoscale. However, controlling the parameters, including the wavelength and polarization of the light outcoupling, as well as the sequence among different building blocks, remains a key issue. Herein, supramolecular heteroarchitectures made by phosphorescent organometallic complexes of Pt, Pd, Cu, and Au are applied as photonic logic gates that show continuously variable emission colors from 475 to 810 nm, low waveguide losses down to 0.0077 dB µm-1 , and remarkable excitation-light polarization-dependent photoluminescence with anisotropy ratios up to 0.68. The sequences among Pt, Pd, Au, and Cu building blocks in the heteroarchitectures are controlled by living supramolecular polymerization or crystallization-driven self-assembly synthetic approaches. The results indicate the prospects for using organometallic complexes and supramolecular synthetic approaches to prepare photonic circuit systems with tunable emission color and controllable sequences among different blocks that achieve modulation of the optical signal in the visible-to-near-infrared spectral region.

Variance-aware attention U-Net for multi-organ segmentation.

PURPOSE: With the continuous development of deep learning based medical image segmentation technology, it is expected to attain more robust and accurate performance for more challenging tasks, such as multi-organs, small/irregular areas, and ambiguous boundary issues. METHODS: We propose a variance-aware attention U-Net to solve the problem of multi-organ segmentation. Specifically, a simple yet effective variance-based uncertainty mechanism is devised to evaluate the discrimination of each voxel via its prediction probability. The proposed variance uncertainty is further embedded into an attention architecture, which not only aggregates multi-level deep features in a global-level but also enforces the network to pay extra attention to voxels with uncertain predictions during training. RESULTS: Extensive experiments on challenging abdominal multi-organ CT dataset show that our proposed method consistently outperforms cutting-edge attention networks with respect to the evaluation metrics of Dice index (DSC), 95% Hausdorff distance (95HD) and average symmetric surface distance (ASSD). CONCLUSIONS: The proposed network provides an accurate and robust solution for multi-organ segmentation and has the potential to be used for improving other segmentation applications.