Related papers: Ultra-sensitive graphene-based electro-optic senso…
Acousto-optic devices utilize the overlap of acoustic and optical fields to facilitate photon-phonon interactions. For tightly confined optical and acoustic fields, such as the sub-wavelength scales achievable in integrated devices, this…
Wearable human activity sensors developed in the past decade show a distinct trend of becoming thinner and more imperceptible while retaining their electrical qualities, with graphene e-tattoos, as the ultimate example. A persistent…
This work presents an innovative magnetoelastic (ME) biosensor using graphene functionalized with the SARS-CoV-2 N protein for antibody detection via magnetoelastic resonance. Graphene was chosen for its biocompatibility and high surface…
Conventional spectrometer and polarimeter systems rely on bulky optics, fundamentally limiting compact integration and hindering multi-dimensional optical sensing capabilities. Here, we propose a spectropolarimeter enabled by…
Biomonitoring wearable sensors based on two-dimensional nanomaterials have lately elicited keen research interest and potential for a new range of flexible nanoelectronic devices. Practical nanomaterial-based devices suited for real-world…
Mobile devices increasingly require the parallel execution of several computing tasks offloaded at the wireless edge. Existing communication systems only support parallel transmissions at the bit level, which fundamentally limits the number…
An electro-absorption optical modulator concept based upon a dual-graphene layer is presented. The device consists of a silicon-on-insulator waveguide upon which two graphene layers reside, separated by a thin insulating region. The lower…
High-precision sensors are of fundamental importance in modern society and technology.Although numerous sensors have been developed, obtaining sensors with higher levels of sensitivity and stronger robustness has always been expected. Here,…
All-electronic interrogation of biofluid flow velocity by sensors incorporated in ultra-low-power or self-sustained systems offers the promise of enabling multifarious emerging research and applications. Electrical sensors based on…
Graph Neural Networks (GNNs) have demonstrated impressive performance across diverse graph-based tasks by leveraging message passing to capture complex node relationships. However, on large-scale real-world graphs, GNNs face two major…
Optical interconnects are becoming attractive alternatives to electrical wiring in intra- and inter-chip communication links. Particularly, the integration with silicon complementary metal-oxide-semiconductor (CMOS) technology has received…
Exploiting quantum interference of charge carriers, epitaxial graphene grown on silicon carbide emerges as a game-changing platform for ultra-sensitive bolometric sensing, featuring an intrinsic resistive thermometer response unmatched by…
Optoelectronic devices based on graphene and other two-dimensional (2D) materials, such as transition metal dichalcogenides (TMDs) are the focus of wide research interest. The characterization these emerging atomically thin materials and…
Extremely increased unstructured data brought by the large-scale intelligent sensing devices application have big challenges not only in data storing and processing but also power consumption surging. Therefore, to improve energy efficiency…
Among its many outstanding properties, graphene supports terahertz surface plasma waves -- sub-wavelength charge density oscillations connected with electromagnetic fields that are tightly localized near the surface[1,2]. When these waves…
Compressive sensing has been used to demonstrate scene reconstruction and source localization in a wide variety of devices. To date, optical compressive sensors have not been able to achieve significant volume reduction relative to…
Optical materials with colour-changing abilities have been explored for display devices, smart windows, or modulation of visual appearance. The efficiency of these materials, however, has strong wavelength dependence, which limits their…
Neuromorphic computing offers a pathway toward energy-efficient processing of data, yet hardware platforms combining nanoscale integration and multimodal functionality remain scarce. Here we demonstrate a gallium-phosphide…
Integrated circuits based on CMOS (complementary metal-oxide semiconductors) are at the heart of the technological revolution of the past 40 years, as these have enabled compact and low cost micro-electronic circuits and imaging systems.…
The goal of this work is to address two limitations in autoencoder-based models: latent space interpretability and compatibility with unstructured meshes. This is accomplished here with the development of a novel graph neural network (GNN)…