Cutting-edge mid-wavelength infrared (MWIR) sensing technologies leverage infrared photodetectors, memory units, and computing units to enhance machine vision. Real-time processing and decision-making challenges emerge with the increasing number of intelligent pixels. However, current operations are limited to in-sensor computing capabilities for near-infrared technology, and high-performance MWIR detectors for multi-state switching functions are lacking. Here, we demonstrate a non-volatile MoS₂/black phosphorus (BP) heterojunction MWIR photovoltaic detector featuring a semi-floating gate structure design, integrating near- to mid-infrared photodetection, memory and computing (PMC) functionalities. The PMC device exhibits the property of being able to store a stable responsivity, which varies linearly with the stored conductance state. Significantly, device weights (stable responsivity) can be programmed with power consumption as low as 1.8 fJ, and the blackbody peak responsivity can reach 1.68 A/W for the MWIR band. In the simulation of Faster Region with convolution neural network (CNN) based on the FLIR dataset, the PMC hardware responsivity weights can reach 89% mean Average Precision index of the feature extraction network software weights. This MWIR photovoltaic detector, with its versatile functionalities, holds significant promise for applications in advanced infrared object detection and recognition systems.

A low energy chirp-pulsed radar thermography (CP-RT) was used as a nondestructive inspection technique to detect the subsurface delamination of CFRP composite. Laser intensities were modulated according to a chirp-pulsed radar signal, and the temperature rise is controlled within 2 Degree. The thermal-wave signal was processed by different post-processing characteristic extraction algorithms. These algorithms include time-frequency algorithms (Cross-correlation, CC, fast Fourier transform, FFT, and dual-orthogonal demodulation, DOD) and statistical analysis approaches (Principal component analysis, PCA and PCA based reconstructed independent component analysis, PCA-RICA). The SNRs of defects were employed to evaluate the defect detectability of different post processing algorithms. Two kind of 3D tomography methods were proposed. FFT phase presents a high SNR and has a good correlation with the depth of the defect. FFT based CP-RT has the potential to provide a rapid NDT&E and 3D tomography approach for CFRP with subsurface defects under low energy excitation condition.

In-sensor processing has the potential to reduce the energy consumption and hardware complexity of motion detection and recognition. However, the state-of-the-art all-in-one array integration technologies with simultaneous broadband spectrum image capture (sensory), image memory (storage) and image processing (computation) functions are still insufficient. Here, macroscale (2 × 2 mm²) integration of a rippled-assisted optoelectronic array (18 × 18 pixels) for all-day motion detection and recognition. The rippled-assisted optoelectronic array exhibits remarkable uniformity in the memory window, optically stimulated non-volatile positive and negative photoconductance. Importantly, the array achieves an extensive optical storage dynamic range exceeding 10⁶, and exceptionally high room-temperature mobility up to 406.7 cm² V⁻¹ s⁻¹, four times higher than the International Roadmap for Device and Systems 2028 target. Additionally, the spectral range of each rippled-assisted optoelectronic processor covers visible to near-infrared (405 nm–940 nm), achieving function of motion detection and recognition.

Automated fiber placement (AFP) is an advanced manufacturing method for composites, which is especially suitable for large-scale composite components. However, some manufacturing defects inevitably appear in the AFP process, which can affect the mechanical properties of composites. This work aims to investigate the recent works on manufacturing defects and their online detection techniques during the AFP process. The main content focuses on the position defect in conventional and variable stiffness laminates, the relationship between the defects and the mechanical properties, defect control methods, the modeling method for a void defect, and online detection techniques. Following that, the contributions and limitations of the current studies are discussed. Finally, the prospects of future research concerning theoretical and practical engineering applications are pointed out.

Present vision restoration technologies have substantial constraints that limit their application in the clinical setting. In this work, we fabricated a subretinal nanoprosthesis using tellurium nanowire networks (TeNWNs) that converts light of both the visible and near-infrared–II spectra into electrical signals. The broad-spectrum coverage is made possible by a combination of narrow bandgaps, strong absorption, and engineered asymmetries. Implanted into blind mice, the TeNWNs restored pupillary reflexes and enabled visually cued learning under visible and near-infrared 1550-nanometer light. In nonhuman primates, TeNWNs elicited robust retina-derived neural responses, confirming biocompatibility and feasibility. By restoring lost photosensitivity and extending vision to near-infrared, this nanoprosthesis offers a promising approach for restoring vision.

Paint removal is an important part of ship and marine engineering ship processing. Aluminum alloy is extremely vital in the field of shipbuilding, due to its high strength and strong corrosion resistance ability. Therefore, the cleaning quality of aluminum alloy is a key factor in the service life of the ship. In this paper, the research about continuous wave (CW) laser cleaning technique is employed to clean the paint on the substrate of aluminum alloy. The track width and depth of laser ablated craters are measured to study the removal rates. The analysis of CW laser cleaning is performed to explain the removal process that is theoretically based on the cleaning model, temperature, and the thermal stress profiles. The parametric and morphological studies indicate that the cleaned surface of aluminum alloy could be achieved at proper parameters. The performance of the laser cleaned surface at an intensity of 11.9 W/cm² has better corrosion resistance and surface roughness. Therefore, the experimental results were considered to provide more completed and further understandings of interaction mechanism between the laser and paint on the aluminum alloy substrate, which could make some contributions to the development of laser manufacturing.