Shortwave infrared single-pixel spectral imaging based on a GSST phase-change metasurface.

Shortwave infrared (SWIR) spectral imaging obtains spectral fingerprints corresponding to overtones of molecular vibrations invisible to conventional silicon-based imagers. However, SWIR imaging is challenged by the excessive cost of detectors. Single-pixel imaging based on compressive sensing can alleviate the problem but meanwhile presents new difficulties in spectral modulations, which are prerequisite in compressive sampling. In this work, we theoretically propose a SWIR single-pixel spectral imaging system with spectral modulations based on a Ge2Sb2Se4Te1 (GSST) phase-change metasurface. The transmittance spectra of the phase-change metasurface are tuned through wavelength shifts of multipole resonances by varying crystallinities of GSST, validated by the multipole decompositions and electromagnetic field distributions. The spectral modulations constituted by the transmittance spectra corresponding to the 11 phases of GSST are sufficient for the compressive sampling on the spectral domain of SWIR hyperspectral images, indicated by the reconstruction in false color and point spectra. Moreover, the feasibility of optimization on phase-change metasurface via coherence minimization is demonstrated through the designing of the GSST pillar height. The concept of spectral modulation with phase-change metasurface overcomes the static limitation in conventional modulators, whose integratable and reconfigurable features may pave the way for high-efficient, low-cost, and miniaturized computational imaging based on nanophotonics.

Treatment of hospital wastewater by electron beam technology: Removal of COD, pathogenic bacteria and viruses.

The effective treatment of hospital sewage is crucial to human health and eco-environment, especially during the pandemic of COVID-19. In this study, a demonstration project of actual hospital sewage using electron beam technology was established as advanced treatment process during the outbreak of COVID-19 pandemic in Hubei, China in July 2020. The results indicated that electron beam radiation could effectively remove COD, pathogenic bacteria and viruses in hospital sewage. The continuous monitoring date showed that the effluent COD concentration after electron beam treatment was stably below 30 mg/L, and the concentration of fecal Escherichia coli was below 50 MPN/L, when the absorbed dose was 4 kGy. Electron beam radiation was also an effective method for inactivating viruses. Compared to the inactivation of fecal Escherichia coli, higher absorbed dose was required for the inactivation of virus. Absorbed dose had different effect on the removal of virus. When the absorbed dose ranged from 30 to 50 kGy, Hepatitis A virus (HAV) and Astrovirus (ASV) could be completely removed by electron beam treatment. For Rotavirus (RV) and Enterovirus (EV) virus, the removal efficiency firstly increased and then decreased. The maximum removal efficiency of RV and EV was 98.90% and 88.49%, respectively. For the Norovirus (NVLII) virus, the maximum removal efficiency was 81.58%. This study firstly reported the performance of electron beam in the removal of COD, fecal Escherichia coli and virus in the actual hospital sewage, which would provide useful information for the application of electron beam technology in the treatment of hospital sewage.

Nonvolatile Optically Reconfigurable Radiative Metasurface with Visible Tunability for Anticounterfeiting.

Control of thermal emission underpins fundamental science, as it is related to both heat and infrared electromagnetic wave transport. However, realizing nonvolatile reconfigurable thermal emission is challenging due to the inherent complexity or limitation in conventional radiative materials or structures. Here, we experimentally demonstrate a nonvolatile optically reconfigurable mid-infrared coding radiative metasurface. By applying laser pulses, infrared emissive patterns are directly encoded into an ultrathin (∼25 nm) Ge2Sb2Te5 layer integrated into a planar optical cavity with the optically crystallized Ge2Sb2Te5 spots, and the peak spectral emissivity is repeatedly switched between low (∼0.1) and high (∼0.7) values. In addition, the visible scattering patterns are independently modulated with submicron-sized bumps generated by high-power laser pulses. An anticounterfeiting label is demonstrated with spatially different infrared emission and visible light scattering information encoded. This approach constitutes a new route toward thermal emission control and has broad applications in encryption, camouflage, and so on.

Compressive single-pixel hyperspectral imaging using RGB sensors.

Hyperspectral imaging that obtains the spatial-spectral information of a scene has been extensively applied in various fields but usually requires a complex and costly system. A single-pixel detector based hyperspectral system mitigates the complexity problem but simultaneously brings new difficulties on the spectral dispersion device. In this work, we propose a low-cost compressive single-pixel hyperspectral imaging system with RGB sensors. Based on the structured illumination single-pixel imaging configuration, the lens-free system directly captures data by the RGB sensors without dispersion in the spectral dimension. The reconstruction is performed with a pre-trained spatial-spectral dictionary, and the hyperspectral images are obtained through compressive sensing. In addition, the spatial patterns for the structured illumination and the dictionary for the sparse representation are optimized by coherence minimization, which further improve the reconstruction quality. In both spatial and spectral dimensions, the intrinsic sparse properties of the hyperspectral images are made full use of for high sampling efficiency and low reconstruction cost. This work may introduce opportunities for optimization of computational imaging systems and reconstruction algorithms towards high speed, high resolution, and low cost future.

High-efficient photoacoustic generation with an ultrathin metallic multilayer broadband absorber.

Metal nanomaterials have been widely used to generate photoacoustic (PA) signals because of their high optical absorption characteristics. However, the PA conversion efficiency of metal nanomaterials is limited by the single-wavelength absorption at the resonant peak. To mitigate this issue, a three-layer ultrathin film containing a thin PDMS layer sandwiched between two ultrathin chromium films is proposed. This kind of film structure can attain high optical absorbance (>80%) through the visible light range (450-850 nm). The optical absorption characteristics can be easily modulated by varying the thickness of the PDMS layer. Under the same excitation condition, the PA signal generated by this film structure is twice that of an only Cr film and three times that of an only Au film. This film structure is easily fabricated and can operate with lasers having different central wavelengths or even white light sources, leading to its applications in many fields, including photoacoustic communications and audio transducers.

Multispectral camouflage for infrared, visible, lasers and microwave with radiative cooling.

Interminable surveillance and reconnaissance through various sophisticated multispectral detectors present threats to military equipment and manpower. However, a combination of detectors operating in different wavelength bands (from hundreds of nanometers to centimeters) and based on different principles raises challenges to the conventional single-band camouflage devices. In this paper, multispectral camouflage is demonstrated for the visible, mid-infrared (MIR, 3-5 and 8-14 µm), lasers (1.55 and 10.6 µm) and microwave (8-12 GHz) bands with simultaneous efficient radiative cooling in the non-atmospheric window (5-8 µm). The device for multispectral camouflage consists of a ZnS/Ge multilayer for wavelength selective emission and a Cu-ITO-Cu metasurface for microwave absorption. In comparison with conventional broadband low emittance material (Cr), the IR camouflage performance of this device manifests 8.4/5.9 °C reduction of inner/surface temperature, and 53.4/13.0% IR signal decrease in mid/long wavelength IR bands, at 2500 W ∙ m-2 input power density. Furthermore, we reveal that the natural convection in the atmosphere can be enhanced by radiation in the non-atmospheric window, which increases the total cooling power from 136 W ∙ m-2 to 252 W ∙ m-2 at 150 °C surface temperature. This work may introduce the opportunities for multispectral manipulation, infrared signal processing, thermal management, and energy-efficient applications.

Simultaneous coded aperture and dictionary optimization in compressive spectral imaging via coherence minimization.

Coded aperture snapshot spectral imaging (CASSI) reconstructs a hyperspectral image from several two-dimensional (2D) projections via compressive sensing. The reconstruction quality and the sampling efficiency of CASSI can be effectively improved by decreasing the coherence of the underlying sensing matrix. Efforts have been made to minimize the coherence with individual optimization on coded aperture or sparse basis. In this paper, a simultaneous optimization on the system projection and the over-complete dictionary is introduced to minimize the Frobenius norm coherence. The dual-disperser structure and the RGB image sensor are adopted for the lowest coherence in terms of system configuration. The coded aperture and the dictionary are optimized with genetic algorithm and gradient descent respectively, and simultaneous optimization is conducted iteratively. Low coherence of sensing matrix is acquired after the simultaneous optimization, with both reconstruction quality and sampling efficiency significantly improved. Compared to the non-optimized system and state-of-the-art systems with individually optimized coded aperture or dictionary, the simultaneous optimization promotes the peak signal-to-noise ratio by more than 5dB. The coherence minimization via simultaneous optimization on the system matrix and the sparse representation basis may open opportunities for further development of other compressive-sensing-based computational imaging systems.

High-temperature infrared camouflage with efficient thermal management.

High-temperature infrared (IR) camouflage is crucial to the effective concealment of high-temperature objects but remains a challenging issue, as the thermal radiation of an object is proportional to the fourth power of temperature (T4). Here, we experimentally demonstrate high-temperature IR camouflage with efficient thermal management. By combining a silica aerogel for thermal insulation and a Ge/ZnS multilayer wavelength-selective emitter for simultaneous radiative cooling (high emittance in the 5-8 µm non-atmospheric window) and IR camouflage (low emittance in the 8-14 µm atmospheric window), the surface temperature of an object is reduced from 873 to 410 K. The IR camouflage is demonstrated by indoor/outdoor (with/without earthshine) radiation temperatures of 310/248 K for an object at 873/623 K and a 78% reduction in with-earthshine lock-on range. This scheme may introduce opportunities for high-temperature thermal management and infrared signal processing.

Inverse design of an integrated-nanophotonics optical neural network.

Artificial neural networks have dramatically improved the performance of many machine-learning applications such as image recognition and natural language processing. However, the electronic hardware implementations of the above-mentioned tasks are facing performance ceiling because Moore's Law is slowing down. In this article, we propose an optical neural network architecture based on optical scattering units to implement deep learning tasks with fast speed, low power consumption and small footprint. The optical scattering units allow light to scatter back and forward within a small region and can be optimized through an inverse design method. The optical scattering units can implement high-precision stochastic matrix multiplication with mean squared error <10-4 and a mere 4 × 4 µm2 footprint. Furthermore, an optical neural network framework based on optical scattering units is constructed by introducing "Kernel Matrix", which can achieve 97.1% accuracy on the classic image classification dataset MNIST.

Tunable narrowband mid-infrared thermal emitter with a bilayer cavity enhanced Tamm plasmon.

A narrowband thermal emitter exhibits higher energy efficiency and sensitivity in molecule sensing and other mid-infrared (MIR) spectral range applications compared to a blackbody emitter. Most narrowband thermal emitters involving surface plasmons have a relatively low quality factor (Q-factor) and require complex fabrication processes. Here we propose a bilayer cavity-enhanced Tamm plasmon (TP) structure with a high/low refractive index bilayer sandwiched between a metal and distributed Bragg reflector (DBR) to achieve an enhanced Q-factor and maintain higher emittance over a conventional pure DBR-metal TP structure-based emitters. The large optical thickness of the high/low index bilayer cavity aids in increasing the Q-factor (∼172 for emission) of the cavity resonance. Furthermore, a tunable Q-factor is achieved (Q from 172 to 47 for emission) by incorporating phase-changing material Ge2Sb2Te5. This easy-to-fabricate and tunable high Q-factor emitter is competent as a narrowband MIR light source in molecule sensing, typically gas sensing applications.