Abstract
Spectral analysis of cultural heritage materials offers valuable insights into the restoration and preservation of historical artifacts, revealing details about the materials used and the manufacturing techniques employed. However, given their historical and artistic significance, the extraction of elemental information from these fragile samples poses a unique challenge, as these objects must be examined using minimally invasive methods to prevent irreversible damage. Laser-induced Breakdown Spectroscopy (LIBS) is one such technique, providing a rapid and detailed elemental characterization. Yet, extensive LIBS analysis can still compromise the integrity of these delicate objects. In this work, a novel approach that integrates spectral and RGB data clustering to significantly reduce the number of LIBS measurements required is introduced. By segmenting the material into visually and chemically distinct clusters, this method enables targeted LIBS analysis using only a few representative shots per cluster, thus preserving the integrity of cultural heritage artifacts while still delivering reliable compositional insights. (c) 2026 The Author(s). Published by Elsevier Masson SAS. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)

Abstract
The ability to assess molecular binding kinetics in real time is critical for advancing our understanding of molecular interactions in biochemical and biotechnological systems. This work presents a novel optical tweezer (OT)-based method to monitor molecular affinity in real time, focusing on the high-affinity streptavidin-biotin system as a model. Transparent poly(methyl methacrylate) (PMMA) microparticles functionalized with streptavidin were trapped before, during, and after binding with biotinylated bovine serum albumin (biotin-BSA), enabling the analysis of forward-scattered signals to detect nanoscale changes in particle size. By applying the Power Spectral Density method, the friction coefficient of individual particles was calculated, allowing for real-time tracking of binding dynamics and the estimation of the association rate constant (kon approximate to 106M-1s-1). These results are consistent with literature values and demonstrate the potential of this OT-based approach for non-invasive, label-free detection of molecular interactions. Compared to existing techniques, such as atomic force microscopy and cantilever-based sensors, this method offers significant advantages, including real-time monitoring, adaptability to different bioaffinity systems, and compatibility with miniaturized setups. This work establishes a foundation for using OT-based tools to monitor high-affinity molecular interactions in real time. While demonstrated here using biotinylated BSA as a model ligand, future studies will explore the method's applicability to smaller ligands and more subtle surface modifications.

Abstract
Abstract The development of computing paradigms alternative to von Neumann architectures has recently fueled significant progress in novel all-optical processing solutions. In this work, we investigate how the coherence properties can be exploited for computing by expanding information onto a higher-dimensional space in the photonic extreme learning machine framework. A theoretical framework is provided based on the transmission matrix formalism, mapping the input plane onto the output camera plane, resulting in the establishment of the connection with complex extreme learning machines and derivation of upper bounds for the hidden space dimensionality as well as the form of the activation functions. Experiments using free-space propagation through a diffusive medium, performed in low-dimensional input space regimes, validate the model and the proposed estimator for the dimensionality. Overall, the framework presented and the findings enclosed have the potential to foster further research in a multitude of directions, from the development of robust general-purpose all-optical hardware to a full-stack integration with optical sensing devices toward edge computing solutions.

Abstract
Polarization optical fiber sensors are based on modifications of fiber birefringence by an external measurand (e.g., strain, pressure, acoustic waves). Yet, this means that different input states of polarization will result in very distinct behaviors, which may or may not be optimal in terms of sensitivity and signal-to-noise ratio. To tackle this challenge, this manuscript presents an optimization technique for the input polarization state using the Fisher information formalism, which allows for achieving maximal precision for a statistically unbiased metric. By first measuring the variation of the Mueller matrix of the optical fiber in response to controlled acoustic perturbations induced by piezo speakers, we compute the corresponding Fisher information operator. Using maximal information states of the Fisher information, it was possible to observe a significant improvement in the performance of the sensor, increasing the signal-to-noise ratio from 4.3 to 37.6 dB, attaining an almost flat response from 1.5 kHz up to 15 kHz. As a proof-of-concept for dynamic audio signal detection, a broadband acoustic signal was also reconstructed with significant gain, demonstrating the usefulness of the introduced formalism for high-precision sensing with polarimetric fiber sensors. (c) 2025 Optica Publishing Group. All rights, including for text and data mining (TDM), Artificial Intelligence (AI) training, and similar technologies, are reserved.

Abstract
Solid-state batteries are prominent in today's research landscape due to their advantages in capacity and safety. This work explores anode-less all-solid-state batteries, a configuration with industrial benefits as it avoids handling alkali metal anodes, albeit with room for improvement. To elucidate the intricacies of these batteries, Laser-Induced Breakdown Spectroscopy (LIBS) served as a pivotal analytical tool, primarily focusing on the negative current collector surface where Li+ nucleation occurs from the Li-rich electrolyte. The use of a fiber-laser for breakdown spectroscopy offers advantages over conventional lasers by producing high beam quality, enabling minimal spot size, and ensuring excellent spatial resolution. LIBS is an asset to verify Li presence, discerning its source, assessing nucleation and distinguishing it from electrolyte-derived Li. For instance, in this work utilizing Li2.99Ba0.005ClO as the electrolyte, LIBS is crucial to elucidate the relationship between Li and other elements like Cl, Zn, or Fe, shedding light on key battery performance aspects. LIBS demonstrated a high potential for verifying in situ Li metal nucleation in anode-less cells. This study highlights its effectiveness in conceptual and product development and advanced quality testing. The application of a clustering method enhanced result interpretability and the distinction between electrolyte and in situ anode regions.