Institut des Nanotechnologies de Lyon

Accurate knowledge of the uneven free spectral range of an optical microresonator, which provides direct insight into group velocity dispersion, is essential for understanding and controlling Kerr frequency comb dynamics. In this work, we present a simple and highly precise method for measuring the free spectral range over a 5 THz bandwidth in silicon nitride microresonators, leveraging a wavemeter with 0.4 MHz resolution. Our fully fibered plug-and-play experimental setup enables accurate extraction of resonance frequencies. By carefully analyzing the spectral position of each resonance, we measure both second- and third-order free spectral range expansion coefficients. This approach offers a robust and accessible tool for dispersion characterization in integrated photonic circuits, paving the way for next generation of Kerr comb sources and quantum photonic technologies.

The study focuses on the design of a spiral microfluidic device, aiming to efficiently sort particle by size, at tailored flow rate for downstream processing. While spiral devices exploiting Dean vortices are recognized for their high-throughput capabilities, they often require high flow rates that limit their integration with other microfluidic functions and reduce sorting performance. Our work aims to design a low flowrate-operating-spiral (~ 50 mL/h) by investigating the influence of spiral geometric parameters and flow conditions on sorting efficiency. Through combined experimental and theoretical analysis, we evaluate how particle size and flow dynamics determine particle positions within the spiral, validating underlying models. This approach provides valuable insights for optimizing spiral microfluidic systems particularly their design, performance, and versatility in applications such as the isolation of rare cell isolation. The spiral design achieved efficient size-based sorting of 10 and 15μm microbeads at a flow rate of 50 mL/h. When applied to biological samples, the system removed 89% of white blood cells from a 1:1 lysed blood sample (≈ 10⁷ cells/min) while maintaining a recovery of more than 75% for all tested CTC-mimicking cells.

The inverse design of metasurfaces faces inherent challenges due to the nonlinear and highly complex relationship between geometric configurations and their electromagnetic behavior. Traditional optimization approaches often suffer from excessive computational demands and a tendency to converge to suboptimal solutions. This study presents a diffusion-based generative framework that incorporates a dedicated consistency constraint and advanced posterior sampling methods to ensure adherence to desired electromagnetic specifications. Through rigorous validation on small-scale metasurface configurations, the proposed approach demonstrates marked enhancements in both accuracy and reliability of the generated designs. Furthermore, we introduce a scalable methodology that extends inverse design capabilities to large-scale metasurfaces, validated for configurations of up to $98 \times 98$ nanopillars. Notably, this approach enables rapid design generation completed in minute by leveraging models trained on substantially smaller arrays ($23 \times 23$). These innovations establish a robust and efficient framework for high-precision metasurface inverse design.

Physical unclonable functions (PUFs) leverage process variability to generate unique signatures in electronic devices. They are a strong alternative to conventional security mechanisms as they do not rely on non-volatile memories (NVMs) to store the secrets. However, PUFs can be influenced by external factors and may exhibit biased output distributions, leading to vulnerabilities that could compromise their uniqueness and resistance to cloning. The quality of a PUF is evaluated through a common set of metrics such as uniformity, bit-aliasing, uniqueness, and reliability. However, the lack of standardized methodologies hinders effective comparisons between diverse PUF designs, limiting the broader understanding of their performance. Besides, the underlying physics and mechanisms of PUFs makes them difficult to study and mitigate potential vulnerabilities and attacks. Overall, the quality metrics for PUFs are still evolving, and there is ongoing research to address these challenges and develop more robust and reliable PUFs. In this article, we demonstrate the limitations of current PUF evaluation metrics using experimental data and introduce a novel set of metrics that provide a more rigorous and comprehensive assessment.

We develop a generalized non-Hermitian Hamiltonian formalism for guided resonances in photonic crystal slabs, derived directly from Maxwell’s equations through a systematic guided-mode expansion. By expanding the electromagnetic fields over the complete mode basis of an unpatterned slab and systematically integrating out radiative Fabry–Pérot channels, we obtain the analytical operator structure of the Hamiltonian, which treats guided-mode coupling and radiation losses on equal footing. The resulting Hamiltonian provides explicit expressions for both dispersive and radiative coupling terms in terms of modal overlap integrals and Fourier components of the permittivity modulation. For specific geometries, the Hamiltonian coefficients can be extracted from full-wave simulations, enabling accurate modeling without phenomenological assumptions. As a case study, we investigate hexagonal lattices with both preserved and broken C6 symmetry, demonstrating predictive agreement for complex band structures, near-field distributions, and far-field polarization patterns. In particular, the formalism reproduces symmetry-protected bound states in the continuum (BICs) at the Γ point, accidental off-Γ BICs near the Γ point, and the emergence of chiral exceptional points (EPs). It also captures the tunable behavior of eigenmodes near the K point, including Dirac-point shifts and the emergence of quasi-BICs or bandgap openings, depending on the nature of C6 symmetry breaking. We further demonstrate in the Appendix that the same formalism extends naturally to other symmetry classes, including C2 (1D grating) and C4 (square lattice) photonic crystal slabs. This approach enables predictive and efficient modeling of complex photonic resonances, revealing their topological and symmetry-protected characteristics in non-Hermitian systems.

Photonic integrated devices are progressively evolving beyond passive components into fully programmable systems, notably driven by the progress in chalcogenide phase-change materials (PCMs) for non-volatile reconfigurable nanophotonics. However, the stochastic nature of their crystal grain formation results in strong spatial and temporal crystalline inhomogeneities. Here, the concept of spatially-controlled planar guided crystallization is proposed, a novel method for programming the growth of optically homogeneous low-loss Sb2S3 PCM, leveraging the seeded directional and progressive crystallization within confined channels. This guided crystallization method is experimentally shown to circumvent the current limitations of conventional PCM-based nanophotonic devices, including a multilevel non-volatile optical phase-shifter exploiting a silicon nitride-based Mach-Zehnder interferometer, and a programmable metasurface with spectrally reconfigurable bound state in the continuum. Precisely controlling the growth of PCMs to ensure optically uniform crystalline properties across devices is the cornerstone for the industrial development of non-volatile reconfigurable photonic integratedcircuits.

Phase change materials (PCMs) are revolutionizing nanophotonics by providing ways to locally tune and reconfigure optical devices. The last decade has witnessed many exciting reports of novel devices exploiting PCMs such as for example beam-steering, tunable light emission, reflection and absorption, programmable metasurfaces and reconfigurable neural networks. A large majority of the first studies were using standard PCMs such as GeSbTe as simple binary on-off switches, in which the ON state is the amorphous phase and the OFF state the fully crystalline phase. However, PCMs present another degree of freedom for tunability: the possibility to encode multilevel non-volatile states via partial change of phase. Furthermore, recently a new class of low-loss PCMs emerged (e.g. Sb2S3 and Sb2Se3), with negligible optical absorption in the near-infrared. In this talk, we will present recent results on original methods to program PCMs into various multilevel states of crystallization. We will then present nanophotonic devices leveraging this multilevel programming and conclude on the perspectives of this technology

This study examines the effect of temperature during pyrolysis on the capacity of cedar wood-derived biochar to be employed as a sustainable electrode material for supercapacitors. Cedar wood-derived biochars were produced at different temperatures of 800 °C, 900 °C, 1000 °C and 1100 °C and fully characterized in terms of their structural, physicochemical and electrochemical properties, including specific surface area, hydrophobicity, electrical conductivity, and surface functional groups. The results indicated that the cedar wood biochar obtained through pyrolysis at 900 °C (BC900) provided optimal electrical conductivity, hydrophobicity, and porosity characteristics relative to the other cedar wood biochars produced by pyrolysis at 800 °C to 1100 °C. Specifically, when compared to commercial activated carbon (AC), BC900 provided half the specific capacitance at a current density of 1 A g−1 and indicated that there is more potential for improvement with further activation and doping. The influence of the binder (either polyvinylidene fluoride (PVDF) or chitosan) in combination with conductive carbon black (CB) was also examined. Electrodes fabricated with PVDF binder showed higher specific capacitance, while biochar electrodes made from CB and chitosan (BC900/CB/chitosan) showed better electrical conductivity, wettability, and good electrochemical stability with >95% capacity retention even after 10,000 cycles.

This study presents finite element modelling of a two-electrode standardised measuring cell filled with materials mimicking the electrical properties of biological tissues. Samples, prepared using various formulations, were characterised via bioelectrical impedance spectroscopy (BIS) over a frequency range from 1 kHz to 1 MHz. Impedance values were calculated as the ratio of output voltage to applied current. The standardised measuring cells were modelled in Ansys® Maxwell finite element software, using electrical parameters derived from experimental data. The results demonstrate that the finite element model closely mirrors the experimental measurement. Once the model will accurately replicate the electrical behaviour of these specific materials in simple geometries, more complex anthropomorphic models may be considered.Clinical Relevance- The clinical relevance of this study lies in its potential to enhance the accuracy and efficiency of bioimpedance-based diagnostic tools by offering a reliable numerical modelling approach for tissue phantoms. This could improve the understanding of tissue composition, tissue hydration, and cellular health in clinical settings.