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Alwin Wester

Publications and source records attributed to Alwin Wester.

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Continuous spectral and coupling-strength encoding with dual-gradient metasurfaces

Enhancing and controlling light-matter interactions is crucial in nanotechnology and material science, propelling research on green energy, laser technology, and quantum cryptography. Central to enhanced light-matter coupling are two parameters: the spectral overlap between an optical cavity mode and the material's spectral features (e.g., excitonic or molecular absorption lines), and the quality factor of the cavity. Controlling both parameters simultaneously is vital, especially in complex systems requiring extensive data to uncover the numerous effects at play. However, so far, photonic approaches have focused solely on sampling a limited set of data points within this 2D parameter space. Here we introduce a nanophotonic approach that can simultaneously and continuously encode the spectral and quality factor parameter space of light-matter interactions within a compact spatial area. Our novel dual-gradient metasurface design is composed of a 2D array of smoothly varying subwavelength nanoresonators, each supporting a unique mode. This results in 27,500 distinct modes within one array and a resonance density approaching the theoretical upper limit for metasurfaces. By applying our dual-gradient to surface-enhanced molecular sensing, we demonstrate the importance of coupling tailoring and unveil an additional coupling-based dimension of spectroscopic data. Our metasurface design paves the way for generalized light-matter coupling metasurfaces, leading to advancements in the field of photocatalysis, chemical sensing, and entangled photon generation.

physics.optics

Pixelated high-Q metasurfaces for in-situ biospectroscopy and AI-enabled classification of lipid membrane photoswitching dynamics

Nanophotonic devices excel at confining light into intense hot spots of the electromagnetic near fields, creating unprecedented opportunities for light-matter coupling and surface-enhanced sensing. Recently, all-dielectric metasurfaces with ultrasharp resonances enabled by photonic bound states in the continuum have unlocked new functionalities for surface-enhanced biospectroscopy by precisely targeting and reading out molecular absorption signatures of diverse molecular systems. However, BIC-driven molecular spectroscopy has so far focused on endpoint measurements in dry conditions, neglecting the crucial interaction dynamics of biological systems. Here, we combine the advantages of pixelated all-dielectric metasurfaces with deep learning-enabled feature extraction and prediction to realize an integrated optofluidic platform for time-resolved in-situ biospectroscopy. Our approach harnesses high-Q metasurfaces specifically designed for operation in a lossy aqueous environment together with advanced spectral sampling techniques to temporally resolve the dynamic behavior of photoswitchable lipid membranes. Enabled by a software convolutional neural network, we further demonstrate the real-time classification of the characteristic cis and trans membrane conformations with 98% accuracy. Our synergistic sensing platform incorporating metasurfaces, optofluidics, and deep learning opens exciting possibilities for studying multi-molecular biological systems, ranging from the behavior of transmembrane proteins to the dynamic processes associated with cellular communication.

physics.optics