Superconducting niobium nitride (NbN) continues to be investigated decades on, largely in part to its advantageous superconducting properties and wide use in superconducting electronics. Particularly, NbN-based superconducting nanowire single-photon detectors (SNSPDs) have shown exceptional performance. Recent experimental results have indicated that NbN remains as the material of choice in developing future generation quantum devices. In this perspective, we describe the processing-structure-property relationships governing the superconducting properties of NbN films. We further discuss the complex interplay between the material properties, processing parameters, substrate materials, device architectures, and performance of SNSPDs. We also highlight the latest progress in optimizing SNSPD performance parameters.

We present a recyclable perovskite−graphene heterostructure that demonstrates ultrahigh X-ray detection sensitivities over 10 8 μC/Gy air •cm 2 for medical imaging applications. The high mobility of the graphene pixel is preserved to over 1200 cm 2 /V•s after perovskite deposition and enables large conversion efficiency for ultrahigh sensitivity. Increasing the operational bias of the graphene channel increased the X-ray detection signal-to-noise ratio from 30 to over 200. The perovskite can be washed off by an organic solvent at room temperature without damaging the graphene. Redepositing the perovskite layer retains the detectors' high gain, making our heterostructure X-ray detector a recyclable device. The perovskite−graphene device exhibits robust operation given 10,000 gate sweeps and multicycle X-ray irradiations. Here we have demonstrated a high-performance, low-cost, plug-and-play solution with a recyclable design that could significantly reduce the manufacturing and maintenance costs associated with X-ray cameras in medical imaging.

Heterogeneities in structure and polarization have been employed to enhance the energy storage properties of ferroelectric films. The presence of nonpolar phases, however, weakens the net polarization. Here, we achieve a slush-like polar state with fine domains of different ferroelectric polar phases by narrowing the large combinatorial space of likely candidates using machine learning methods. The formation of the slush-like polar state at the nanoscale in cation-doped BaTiO3 films is simulated by phase field simulation and confirmed by aberration-corrected scanning transmission electron microscopy. The large polarization and the delayed polarization saturation lead to greatly enhanced energy density of 80 J/cm3 and transfer efficiency of 85% over a wide temperature range. Such a data-driven design recipe for a slush-like polar state is generally applicable to quickly optimize functionalities of ferroelectric materials.