We demonstrate photogating in a graphene/Si–SiO₂ stack, where vertical motion of photogenerated charge is converted into a corresponding change in graphene channel conductance in real time. Under pulsed illumination, holes accumulate at the Si/SiO₂ interface, creating a surface photovoltage that shifts the flat-band condition and electrostatically suppresses graphene conductance. A dual-readout scheme—simultaneously tracking interfacial charging dynamics and the graphene channel—cleanly separates optical charge injection (cause) from electronic transduction (effect). This separation allows for the direct extraction of practical figures of merit without conventional transfer sweeps, including flat-band shift per pulse, retention time constants, and trap occupancy. Interface kinetics then define two operating regimes: a fast, resettable detector when traps are sparse or rapid, and a trap-assisted analog-memory state when slow traps retain charge between pulses. The mechanism is complementary metal-oxide–semiconductor compatible (CMOS-compatible) and needs no cryogenics or exotic materials. Together, these results outline a compact route to engineer integrating photodetectors, pixel-level memory for adaptive imaging, and neuromorphic optoelectronic elements that couple sensing with in situ computation.

In this study, we develop a graphene-trenched silicon Schottky junction for humidity sensing. This novel structure comprises suspended graphene bridging etched trenches on a silicon substrate, creating both free-standing and substrate-contacting regions of graphene that enhance water adsorption sensing. Suspended graphene is intrinsically insensitive to water adsorption, making it difficult for adsorbed H₂O to effectively dope the graphene. In contrast, when graphene is supported on the silicon substrate, water molecules can effectively dope the graphene by modifying the silicon’s impurity bands and their hybridization with graphene. This humidity-induced doping leads to a significant modulation of the Schottky barrier at the graphene–silicon interface, which serves as the core sensing mechanism. We investigate the current–voltage (I–V) characteristics of these devices as a function of trench width and relative humidity. Our analysis shows that humidity influences key device parameters, including the Schottky barrier height, ideality factor, series resistance, and normalized sensitivity. Specifically, larger trench widths reduce the graphene density of states, an effect that is accounted for in our analysis of these parameters. The sensor operates under both forward and reverse bias, enabling tunable sensitivity, high selectivity, and low power consumption. These features make it promising for applications in industrial and home safety, environmental monitoring, and process control.

A detailed numerical study on Ge and Si ultrathin-body (UTB) p-type double-gate MOSFET (pDG-FET) is carried out with the help of in-house developed non-equilibrium Green's function (NEGF) simulator employing the six-band k·p model. Six typical confinement/transport crystal orientation configurations and three recent technology nodes are taken into account for better evaluation of device performance. The ballistic velocity and effective mass (m eff ) are investigated and compared in detail between 3nm-thick Ge and Si films, with a better understanding of crystal orientation effect obtained. Device performance metrics, such as the ballistic ON-current (I ON ) and subthreshold swing (SS), are also extracted and compared. With the source-to-drain tunneling (SDT) effect characterized, further numerical analysis indicates that Ge device suffers from more terrible SDT than Si device at all the considered channel lengths. As the physics behind is clarified, some expectations and suggestions for improving device performance, especially for Ge case, are addressed in the end.