In this paper, we introduce our latest progress in the colloidal quantum dot enhanced color conversion layer for micro LEDs. Different methods of how to deploy colloidal quantum dots can be discussed and reviewed. The necessity of the using color conversion layer can be seen and color conversion efficiency of such layer can be calculated from the measured spectrum. A sub-pixel size of 5 micron of colloidal quantum dot pattern can be demonstrated in array format.

In flat panel display (FPD) lithography, a high resolution and large depth of focus (DOF) are required. The demands for high throughput have necessitated the use of large glass plates and exposure areas, thereby increasing focal unevenness and reducing process latitude. Thus, a large DOF is needed, particularly for high-resolution lithography. To manufacture future high-definition displays, 1.0μm line and space (L/S) is predicted to be required, and a technique to achieve this resolution with adequate DOF is necessary. To improve the resolution and DOF, resolution enhancement techniques (RETs) have been introduced. RETs such as off-axis illumination (OAI) and phase-shift masks (PSMs) have been widely used in semiconductor lithography, which utilizes narrowband illumination. To effectively use RETs in FPD lithography, modification for broadband illumination is required because FPD lithography utilizes such illumination as exposure light. However, thus far, RETs for broadband illumination have not been studied. This study aimed to develop techniques to achieve 1.0μm L/S resolution with an acceptable DOF. To this end, this paper proposes a method that combines our previously developed RET, namely, divided spectrum illumination (DSI), with an attenuated PSM (Att. PSM). Theoretical observations and simulations present the design of a PSM for broadband illumination. The transmittance and phase shift, whose degree varies according to the wavelength, are determined in terms of aerial image contrast and resist loss. The design of DSI for an Att. PSM is also discussed considering image contrast, DOF, and illumination intensity. Finally, the exposure results of 1.0μm L/S using DSI and PSM techniques are shown, demonstrating that a PSM greatly improves the resist profile, and DSI enhances the DOF by approximately 30% compared to conventional OAI. Thus, DSI and PSMs can be used in practical applications for achieving 1.0μm L/S with sufficient DOF.

Liquid crystal (LC) device has high tunability with low power consumption and it is important not only in visible region but also in terahertz region. In this study, birefringence and absorption losses of hydrogen-bonded LC was estimated at 2.5 THz. Our results indicate that introduction of alkoxy chain to hydrogen-bonded LC is effective to increase birefringence in terahertz region. These results indicate that hydrogen-bonded LCs are a strong candidate for future terahertz devices because of their excellent properties in the terahertz region.

A line display that utilizes saccade has been proposed. When an observer moves his or her eyes on a one-dimensional fixed line display, two-dimensional information is perceived on the retina. In this paper, a high speed flashing line display was developed using a CPLD and PIC microcontroller. The flashing period was reduced to 20 µs, which was less than half that of our previous system. The relationship between the flashing frequency and the optimum distance that can be perceived with the least distortion was clarified. The results show that the higher the flashing frequency is, the more information can be perceived from a farther position. Calculated values, which were based on the relationship between the flashing period and the width of the light source, were almost identical with measured values at the flashing frequencies from 3.3 kHz to 10 kHz. Due to short flashing period, the developed line display not only was visible at distance of 15 m or more, which is suitable for outdoor use, but also realized 16 gray levels.

We have utilized single-pixel imaging and deep-learning to solve the privacy-preserving problem in gesture recognition for interactive display. Silhouette images of hand gestures were acquired by use of a display panel as an illumination. Reconstructions of gesture images have been performed by numerical experiments on single-pixel imaging by changing the number of illumination mask patterns. For the training and the image restoration with deep learning, we prepared reconstructed data with 250 and 500 illuminations as datasets. For each of the 250 and 500 illuminations, we prepared 9000 datasets in which original images and reconstructed data were paired. Of these data, 8500 data were used for training a neural network (6800 data for training and 1700 data for validation), and 500 data were used to evaluate the accuracy of image restoration. Our neural network, based on U-net, was able to restore images close to the original images even from reconstructed data with greatly reduced number of illuminations, which is 1/40 of the single-pixel imaging without deep learning. Compared restoration accuracy between cases using shadowgraph (black on white background) and negative-positive reversed images (white on black background) as silhouette image, the accuracy of the restored image was lower for negative-positive-reversed images when the number of illuminations was small. Moreover, we found that the restoration accuracy decreased in the order of rock, scissor, and paper. Shadowgraph is suitable for gesture silhouette, and it is necessary to prepare training data and construct neural networks, to avoid the restoration accuracy between gestures when further reducing the number of illuminations.

Image resolution under the effect of color speckle was successfully measured for a raster-scan mobile projector, using the modified contrast modulation method. This method was based on the eye-diagram analysis for distinguishing the binary image signals, black-and-white line pairs. The image resolution and the related metrics, illuminance, chromaticity, and speckle contrast were measured at the nine regions on the full-frame area projected on a standard diffusive reflectance screen. The nonuniformity data over the nine regions were discussed and analyzed.

Machine learning, especially deep learning, is dramatically changing the methods associated with optical thin-film inverse design. The vast majority of this research has focused on the parameter optimization (layer thickness, and structure size) of optical thin-films. A challenging problem that arises is an automated material search. In this work, we propose a new end-to-end algorithm for optical thin-film inverse design. This method combines the ability of unsupervised learning, reinforcement learning and includes a genetic algorithm to design an optical thin-film without any human intervention. Furthermore, with several concrete examples, we have shown how one can use this technique to optimize the spectra of a multi-layer solar absorber device.