It has recently been shown that Terahertz sensors can effectively detect the spin resonances of Dirac fermions in graphene. The associated photovoltaic measurement technique allows for the investigation of the intrinsic spin-orbit coupling in graphene as well as its topological properties from microwave to Terahertz frequencies. In this work, using graphene/MoS₂-based Field-Effect Transistors, we observed a magnetic resonance photovoltage signal in the Gigahertz range that is independent on the gate bias. The dispersion of the associated spin-flip transitions remains intriguingly unaffected by the MoS₂ layer. In parallel, the spin-related signal consistently appears as a drop in photovoltage, regardless of the signal's polarity or origin, whether it is due to plasma wave rectification or thermoelectric effects. This behavior is interpreted as a decrease in the system's spin polarization due to spin-dependent recombination or scattering of photocarriers. Understanding the various photovoltaic signals in highly sensitive Gigahertz/Terahertz sensors paves the way for exploring spin-dependent mechanisms in two-dimensional quantum materials, influenced by proximity effects such as spin-orbit coupling, topology, and magnetism.

Mock modular forms, first invented by Ramanujan, provide a beautiful generalization of the usual modular forms. In recent years, it was found that they capture generating functions of the number of microstates of BPS black holes appearing in compactifications of string theory with 8 and 16 supercharges. This review describes these results and their applications which range from the actual computation of these generating functions for both compact and non-compact compactification manifolds (encoding, respectively, Donaldson-Thomas and Vafa-Witten topological invariants) to the construction of new non-commutative structures on moduli spaces of Calabi-Yau threefolds.

Macrophytes are a key component of lagoon ecosystems, and the spatio-temporal variation of their biomass reflects the effect of environmental drivers. Understandingthese dynamics is essential for managing, preserving and anticipating the fate of such fragile ecosystems. First, using both satellite data and field observations,we showcase here a machine learning approach to accurately detect submerged vegetation in a preserved lagoon in South France, the Bagnas lagoon. Second,we investigate the statistical relationship between the surface area of Stuckenia pectinata and abiotic factors known to influence the life history of this aquatic plant.We thus identify and evaluate the factors that most impact Stuckenia pectinata population dynamics within the lagoon. We find that water temperature, salinity, anddepth are significantly related to submerged aquatic vegetation (SAV) coverage. We show that the SAV surface area reaches a peak during summer, which can varyacross years. Furthermore, we examine the lifetime distribution of SAV during each year cycle across the pond. We show that the average annual lifespan differssignificantly from one year to the next, which can be explained by annual differences in exposure time to sufficiently high water levels.

The stacking sequence of two-dimensional hexagonal boron nitride (hBN) is a critical factor that determines its polytypes and its distinct physical properties. Although most hBN layers adopt the thermodynamically stable AA′ stacking sequence, achieving alternative stacking configurations has remained a long-standing challenge. Here we demonstrate the scalable synthesis of hBN featuring unprecedented AA stacking, where atomic monolayers align along the c axis without any translation or rotation. This previously considered thermodynamically unfavourable hBN polytype is achieved through epitaxial growth on a two-inch single-crystalline gallium nitride wafer, using a metal–organic chemical vapour deposition technique. Comprehensive structural and optical characterizations, complemented by theoretical modelling, evidence the formation of AA-stacked multilayer hBN and reveal that hBN nucleation on the vicinal gallium nitride surface drives the unidirectional alignment of layers. Here electron doping plays a central role in stabilizing the AA stacking configuration. Our findings provide further insights into the scalable synthesis of engineered hBN polytypes, characterized by unique properties such as large optical nonlinearity.

Collagen, the primary structural protein in the extracellular matrix, plays a critical role in tissue architecture and mechanical integrity. This study investigates the structural and nonlinear optical properties of atelocollagen (Acol) and telocollagen (Tcol) in response to pH variations using Second Harmonic Scattering (SHS), polarization-resolved SHS (P-SHS), and Atomic Force Microscopy (AFM). AFM imaging revealed distinct morphological differences, with Acol forming wavy, non-cross-linked, and randomly arranged fibers, while Tcol exhibited a more interconnected, mesh-like fibrillar network. SHS and P-SHS measurements further confirmed these differences, indicating significant variations in hyperpolarizability and depolarization ratio (DR) between Acol and Tcol. The results suggest that telopeptides play a crucial role in collagen fibrillogenesis, influencing molecular symmetry and optical responses. The observed differences in nonlinear optical properties highlight the potential of SHS as a powerful tool for characterizing collagen self-assembly mechanisms. These findings contribute to the broader understanding of collagen organization in biological and biomaterial contexts, with implications for tissue engineering, fibrosis research, and regenerative medicine. Future work should explore how external factors such as ionic strength and cross-linking agents further modulate collagen fibril formation and its mechanical properties.