The rapid development of information technology has fueled an ever-increasing demand for ultrafast and ultralow-energy-consumption computing. Existing computing instruments are pre-dominantly electronic processors, which use electrons as information carriers and possess von Neumann architecture featured by physical separation of storage and processing. The scaling of computing speed is limited not only by data transfer between memory and processing units, but also by RC delay associated with integrated circuits. Moreover, excessive heating due to Ohmic losses is becoming a severe bottleneck for both speed and power consumption scaling. Using photons as information carriers is a promising alternative. Owing to the weak third-order optical nonlinearity of conventional materials, building integrated photonic computing chips under traditional von Neumann architecture has been a challenge. Here, we report a new all-optical computing framework to realize ultrafast and ultralow-energy-consumption all-optical computing based on convolutional neural networks. The device is constructed from cascaded silicon Y-shaped waveguides with side-coupled silicon waveguide segments which we termed “weight modulators” to enable complete phase and amplitude control in each waveguide branch. The generic device concept can be used for equation solving, multifunctional logic operations as well as many other mathematical operations. Multiple computing functions including transcendental equation solvers, multifarious logic gate operators, and half-adders were experimentally demonstrated to validate the all-optical computing performances. The time-of-flight of light through the network structure corresponds to an ultrafast computing time of the order of several picoseconds with an ultralow energy consumption of dozens of femtojoules per bit. Our approach can be further expanded to fulfill other complex computing tasks based on non-von Neumann architectures and thus paves a new way for on-chip all-optical computing.

Encoding information in light polarization is of great importance in facilitating optical data storage (ODS) for information security and data storage capacity escalation. However, despite recent advances in nanophotonic techniques vastly enhancing the feasibility of applying polarization channels, the data fidelity in reconstructed bits has been constrained by severe crosstalks occurring between varied polarization angles during data recording and reading process, which gravely hindered the utilization of this technique in practice. In this paper, we demonstrate an ultra-low crosstalk polarization-encoding multilayer ODS technique for high-fidelity data recording and retrieving by utilizing a nanofibre-based nanocomposite film involving highly aligned gold nanorods (GNRs). With parallelizing the gold nanorods in the recording medium, the information carrier configuration minimizes miswriting and misreading possibilities for information input and output, respectively, compared with its randomly self-assembled counterparts. The enhanced data accuracy has significantly improved the bit recall fidelity that is quantified by a correlation coefficient higher than 0.99. It is anticipated that the demonstrated technique can facilitate the development of multiplexing ODS for a greener future.

Holography, with the capability of recording and reconstructing wavefronts of light, has emerged as an ideal approach for future deep-immersive naked-eye display. However, the shortcomings (e.g., small field of view, twin imaging, multiple orders of diffraction) of traditional dynamic holographic devices bring many challenges to their practical applications. Metasurfaces, planar artificial materials composed of subwavelength unit cells, have shown great potential in light field manipulation, which is useful for overcoming these drawbacks. Here, we review recent progress in the field of dynamic metasurface holography, from realization methods to design strategies, mainly including typical research works on dynamic meta-holography based on tunable metasurfaces and multiplexed metasurfaces. Emerging applications of dynamic meta-holography have been found in 3D display, optical storage, optical encryption, and optical information processing, which may accelerate the development of light field manipulation and micro/nanofabrication with higher dimensions. A number of potential applications and possible development paths are also discussed at the end.

This article reviews the most recent advances in the development of flexible substrates used as surface-enhanced Raman scattering (SERS) platforms for detecting several hazardous materials (e.g., explosives, pesticides, drugs, and dyes). Different flexible platforms such as papers/filter papers, fabrics, polymer nanofibers, and cellulose fibers have been investigated over the last few years and their SERS efficacies have been evaluated. We start with an introduction of the importance of hazardous materials trace detection followed by a summary of different SERS methodologies with particular attention on flexible substrates and their advantages over the nanostructures and nanoparticle-based solid/hybrid substrates. The potential of flexible SERS substrates, in conjunction with a simple portable Raman spectrometer, is the power to enable practical/on-field/point of interest applications primarily because of their low-cost and easy sampling.