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.

We present a scalable solution-processing method for fabricating high-quality graphene and graphene/1T-MoS2 heterostructure films. The process begins with the synthesis of potassiumintercalated graphite (KC8), which is exfoliated in tetrahydrofuran (THF) to produce stable dispersions of negatively charged (electron rich) graphene sheets. The graphene is subsequently transferred to water, forming a surfactant-free aqueous dispersion suitable for creating homogenous graphene films via vacuum filtration and stamping. Additionally, graphene is combined with 1T-MoS2 nanosheets to fabricate graphene/1T-MoS2 bulk heterostructure films. Comprehensive characterization, including X-ray diffraction (XRD), absorption spectroscopy, scanning electron microscopy (SEM), transmission electron microscopy (TEM), Raman spectroscopy, and X-ray photon emission spectroscopy (XPS), reveals that the heterostructure films exhibit enhanced optical and electronic properties, including improved light absorption, which could lead to novel photo-responsive devices. Raman spectroscopy shows significant changes in the graphene's structural and electronic properties upon interaction with MoS2, indicating strong interlayer coupling and potential charge transfer between the layered components. The graphene films demonstrate highly sensitive detection of dopamine (DA), while the graphene/1T-MoS2 bulk heterostructure films exhibit capacitance values up to 38.3

Fg -1 at 5 mV s -1 in non-aqueous electrolytes. These results highlight the potential of these films for advanced applications in molecular sensing and energy storage.

This study addresses the challenge of analyzing the growth kinetics of carbon nanotubes using in-situ homodyne polarization microscopy (HPM) by developing an automated deep learning (DL) approach. A Mask-RCNN architecture, enhanced with a ResNet-50 backbone, was employed to recognize and track individual nanotubes in microscopy videos, significantly improving the efficiency and reproducibility of kinetic data extraction. The method involves a series of video processing steps to enhance contrast and used differential treatment techniques to manage low signal and fast kinetics. The DL model demonstrates consistency with manual measurements and increased throughput, laying the foundation for statistical studies of nanotube growth. The approach can be adapted for other types of in-situ microscopy studies, emphasizing the importance of automation in high-throughput data acquisition for research on individual nano-objects.