RESUMEN
Selective control of light is essential for optical science and technology, with numerous applications. However, optical selectivity in the angular momentum of light has been quite limited, remaining constant by increasing the incident light power on previous passive optical devices. Here, we demonstrate a nonlinear boost of optical selectivity in both the spin and orbital angular momentum of light through near-field selective excitation of single-mode nanolasers. Our designed hybrid nanolaser circuits consist of plasmonic metasurfaces and individually placed perovskite nanowires, enabling subwavelength focusing of angular-momentum-distinctive plasmonic fields and further selective excitation of nanolasers in nanowires. The optically selected nanolaser with a nonlinear increase of light emission greatly enhances the baseline optical selectivity offered by the metasurface from about 0.4 up to near unity. Our demonstrated hybrid nanophotonic platform may find important applications in all-optical logic gates and nanowire networks, ultrafast optical switches, nanophotonic detectors, and on-chip optical and quantum information processing.
RESUMEN
Two-dimensional layered (BA)2PbI4 (BA = C4H9NH3) perovskites are emerging as a new class of layered materials and show great potential in optoelectronic applications. Elucidating how exciton-phonon interaction affects the excitonic emission is of great importance for a better knowledge of their optoelectronic properties. In this letter, we synthesized high-quality (BA)2PbI4 microplates via solution methods, and dual-excitonic emission peaks (surface-emission and interior-emission) were detected from the as-grown samples at low temperatures. Furthermore, we determine the energies for the longitudinal optical phonon modes to be â¼27 and â¼18 meV, and the exciton-phonon coupling strengths to be â¼177 and â¼21 meV for the surface-emission and interior-emission bands, respectively. Compared to the interior-emission band, the stronger exciton-phonon interaction results in a considerable degree of spectral broadening and red-shift for the surface-emission with increasing temperature. In contrast, the (OA)2PbI4 (OA = C8H17NH2) microplates with longer alkyl chains between Pb-I layers, exhibit only one excitonic emission peak, as well as a large exciton-phonon coupling strength. Our work clarifies the influence of exciton-phonon coupling on the excitonic emission of (BA)2PbI4 microplates, and also suggests the intrinsic relationship between the exciton-phonon coupling and the length of organic carbon chain ligands.
RESUMEN
Artificial synapse networks capable of massively parallel computing and mimicking biological neural networks can potentially improve the processing efficiency of existing information technologies. Semiconductor devices functioning as excitatory and inhibitory synapses are crucial for developing intelligence systems, such as traffic control systems. However, achieving reconfigurability between two working modes (inhibitory and excitatory) and bilingual synaptic behavior in a single transistor remains challenging. This study successfully mimics a bilingual synaptic response using an artificial synapse based on an ambipolar floating gate memory comprising tungsten selenide (WSe2)/hexagonal boron nitride (h-BN)/ molybdenum telluride (MoTe2). In this WSe2/h-BN/MoTe2 structure, ambipolar semiconductors WSe2 and MoTe2 are inserted as channel and floating gates, respectively, and h-BN serves as the tunneling barrier layer. Using either positive or negative pulse amplitude modulations at the control gate, this device with bipolar channel conduction produced eight distinct resistance states. Based on this, we experimentally projected that we could achieve 490 memory states (210 hole-resistance states + 280 electron-resistance states). Using the bipolar charge transport and multistorage states of WSe2/h-BN/MoTe2 floating gate memory, we mimicked reconfigurable excitatory and inhibitory synaptic plasticity in a single device. Furthermore, the convolution neural network formed by these synaptic devices can recognize handwritten digits with an accuracy of >92%. This study identifies the unique properties of heterostructure devices based on two-dimensional materials as well as predicts their applicability in advanced recognition of neuromorphic computing.