High-performance infrared photodetectors based on InAs/InAsSb/AlAsSb superlattice for 3.5 µm cutoff wavelength spectra

High-performance infrared p-i-n photodetectors based on InAs/InAsSb/AlAsSb superlattices on GaSb substrate have been demonstrated at 300K. These photodetectors exhibit 50% and 100% cut-off wavelength of ∼3.2 µm and ∼3.5 µm, respectively. Under -130 mV bias voltage, the device exhibits a peak responsivity of 0.56 A/W, corresponding to a quantum efficiency (QE) of 28%. The dark current density at 0 mV and -130 mV bias voltage are 8.17 × 10−2 A/cm2 and 5.02 × 10−1 A/cm2, respectively. The device exhibits a saturated dark current shot noise limited specific detectivity (D*) of 3.43 × 109 cm·Hz1/2/W (at a peak responsivity of 2.5 µm) under -130 mV of applied bias

Prediction of paperboard properties based on on-line process data and infrared imaging

In papermaking, online measurement of product properties is crucial for process control. However, current practices are limited to QCS scanner measurements, offering only partial coverage. The introduction of infrared imaging provides full coverage temperature measurements but leaves other properties unmeasured. This study aims to predict these properties using available data from QCS scanners and infrared imaging and construct a full coverage prediction. This work focuses on the prediction of two properties: moisture and grammage. The analysis revealed distinct relationships between and within properties. For example, the strong correlation between temperature and moisture makes a full coverage prediction of moisture especially promising. Meanwhile, the weak non-linear relationship between temperature and grammage makes the prediction of grammage challenging, but still with feasibility. These findings led to the proposal of two prediction models: a linear regression model with a moving window for moisture prediction and a CNN-BiLSTM model for grammage prediction. Both models share the same essential idea of a scanner-infrared data replacement trick. However, the inability to synchronize scanner and infrared data prevents the evaluation of full-scale predictions. Despite this limitation, the proposed approaches show promise, particularly for moisture prediction. Further investigation is warranted, especially for grammage prediction, once the synchronization challenge is resolved

Prediction of paperboard properties based on on-line process data and infrared imaging

In papermaking, online measurement of product properties is crucial for process control. However, current practices are limited to QCS scanner measurements, offering only partial coverage. The introduction of infrared imaging provides full coverage temperature measurements but leaves other properties unmeasured. This study aims to predict these properties using available data from QCS scanners and infrared imaging and construct a full coverage prediction. This work focuses on the prediction of two properties: moisture and grammage. The analysis revealed distinct relationships between and within properties. For example, the strong correlation between temperature and moisture makes a full coverage prediction of moisture especially promising. Meanwhile, the weak non-linear relationship between temperature and grammage makes the prediction of grammage challenging, but still with feasibility. These findings led to the proposal of two prediction models: a linear regression model with a moving window for moisture prediction and a CNN-BiLSTM model for grammage prediction. Both models share the same essential idea of a scanner-infrared data replacement trick. However, the inability to synchronize scanner and infrared data prevents the evaluation of full-scale predictions. Despite this limitation, the proposed approaches show promise, particularly for moisture prediction. Further investigation is warranted, especially for grammage prediction, once the synchronization challenge is resolved

Design of an off-axis near-eye AR display system based on a full-color freeform holographic optical element

In this Letter, we propose a design and fabrication method for a full-color augmented reality (AR) optical system based on a freeform holographic optical element (HOE). A point-by-point design method is proposed to generate the starting point of the system. Based on the preliminarily optimized system, the recording systems of the full-color HOE are designed. A joint optimization is conducted for all the systems, simultaneously considering the overall imaging performance, the diffraction efficiency, the constraints, and fabrication. A prototype is designed and fabricated to validate the feasibility and effectiveness of the proposed method.</jats:p

Design of off-axis reflective imaging systems based on freeform holographic elements

Holographic optical element (HOE) can be used in many areas in optics due to its characteristics of thin structure, flexible wavefront reconstruction/control ability and angular/wavelength selectivity. In this paper, we propose a design method of off-axis reflective imaging systems based on freeform HOEs, which are fabricated by freeform wavefronts. The freeform HOEs offer many degrees of design freedom and can correct the aberrations in nonsymmetric imaging systems. The initial imaging system with freeform HOEs is generated using a point-by-point design approach, and is used for the preliminary design of the imaging system and the freeform recording system of each HOE. Then a joint optimization is conducted for all the systems, simultaneously considering the imaging performance, the diffraction efficiency, the system constraints and fabrication to get the final design results. To validate the feasibility and effectiveness of the proposed method, an off-axis reflective head-up display system with good performance based on freeform HOEs is designed and fabricated. Detailed procedures of the design and development process of the prototype are demonstrated.</jats:p

Design of off-axis three-mirror freeform optical system with wide field of view

In order to obtain a wider imaging field of view, freeform surface is used to design a large field of view space optical imaging system. The system uses an off-axis three-mirror optical structure with focal length of 1600 mm, F number of 8, and field of view angle of 20&deg;&times;1&deg;. Because of the large field of view, the image quality of general aspheric optimization design system cannot meet the requirements. In order to improve the freedom of system design, the Zernike polynomial freeform surface is applied to the tertiary mirror of the system, which enables the sagittal field of view to reach 20&deg; further widening the imaging field of view. Degrees of freedom are increased effectively by the addition of the freeform surface. After optimization design, the optical transfer function of the system is better than 0.5 at 63 lp/mm, and the diffusion spot is optimized into Airy circle. The system energy concentration is high, and the imaging quality is close to the diffraction limitation. &copy; 2019 SPIE.</p