Organic Semiconducting Luminophores for Near-Infrared Afterglow,Chemiluminescence, and Bioluminescence Imaging

Optical imaging has played a pivotal role in deciphering in vivo bioinformatics but is limited by shallow penetration depth and poor imaging performance owing to interfering tissue autofluorescence induced by concurrent photoexcitation. The emergence of near-infrared (NIR) self-luminescence imaging independent of real-time irradiation has timely addressed these problems. There are two main kinds of self-luminescent agents, namely inorganic and organic luminophores. Inorganic luminophores usually suffer from long-term biotoxicity concerns resulting from potential heavy-metal ions leakage and nonbiodegradability, which hinders their further translational application. In contrast, organic luminophores, especially organic semiconducting luminophores (OSLs) with good biodegradable potential, tunable design, and outstanding optical properties, are preferred in biological applications. This review summarizes the recent progress of OSLs used in NIR afterglow, chemiluminescence, and bioluminescence imaging. Molecular manipulation and nanoengineering approaches of OSLs are discussed, with emphasis on strategies that can extend the emission wavelength from visible to NIR range and amplify luminescence signals. This review concludes with a discussion of current challenges and possible solutions of OSLs in the self-luminescence field.     

Improving accuracy of automatic optical inspection with machine learning

Electronic devices require the printed circuit board(PCB)to support the whole structure,but the assembly of PCBs suffers from welding problem of the electronic components such as surface mounted devices(SMDs)resistors.The automated optical inspection(AOI)machine,widely used in industrial production,can take the image of PCBs and examine the welding issue.However,the AOI machine could commit false negative errors and dedicated technicians have to be employed to pick out those misjudged PCBs.This paper proposes a machine learning based method to improve the accuracy of AOI.In particular,we propose an adjacent pixel RGB value based method to pre-process the image from the AOI machine and build a customized deep learning model to classify the image.We present a practical scheme including two machine learning procedures to mitigate AOI errors.We conduct experiments with the real dataset from a production line for three months,the experimental results show that our method can reduce the rate of misjudgment from 0.3%–0.5%to 0.02%–0.03%,which is meaningful for thousands of PCBs each containing thousands of electronic components in practice.     

Fabrication of high-efficiency Yb:Y2O3 laser ceramics without photodarkening

High-efficiency Yb:Y₂O₃ laser ceramics were fabricated using the vacuum-sintering plus hot isostatic pressing (HIP) without sintering additives. High-purity well-dispersed nanocrystalline Yb:Y₂O₃ powder was synthesized using a modified co-precipitation method in-house. The green bodies were first vacuum sintered at a temperature as low as 1430°C and then HIPed at 1450°C. Finally, the samples were air annealed at 800°C for 10 h. Although no sintering aids were used, full density of the samples with excellent optical homogeneity and an inline transmission of 80% at 400 nm could be obtained. Moreover, photodarkening phenomenon was not detected in the ceramics. Preliminary laser experiment with the fabricated ceramics in a two-mirror cavity has demonstrated 32 W continuous-wave (CW) output at ∼1077 nm with an optical-to-optical conversion efficiency of 58.2%. To the best of our knowledge, this is so far the highest CW output power and optical-to-optical conversion efficiency achieved with the Yb³⁺-doped sesquioxide ceramics in a simple two-mirror cavity.     

Design,preparation, and characterization of new high-refractive index hybrid organic–inorganic polysiloxanes: Innovative coatings for optoelectronic applications

The current demand for high-refractive index materials is very high due to their importance in optoelectronic applications. Such materials already exist in the market, but they present many disadvantages. They might contain toxic metals; their preparation can be challenging or produce high quantity of waste. Consequently, there is an urgent need to produce new friendly coatings with high-refractive index. Hybrid organic–inorganic polysiloxanes can offer a solution to this problem. They can be easily prepared from nontoxic alkoxy silanes using the sol–gel chemistry process. Herein, a series of new hybrid polysiloxanes are synthesized from the monomer 1–(2–(triethoxysilyl)ethyl)triphenylsilane and other silanes. The preparation of the macromolecules is optimized at both stages of the sol–gel process. The polymers are characterized by gel permeation chromatography and NMR spectroscopy. Spin coating of the materials on silicon wafers, followed by film thickness and refractive index measurements, indicates that the new polysiloxanes can have refractive indexes as high as 1.6 with thicknesses varying from 2200 to 3700 nm. Consequently, it is expected that the new materials described in this report are valuable for optoelectronic applications such as high-dielectric constant (high-k) gate oxides, interlayer high-k dielectrics, or high-refractive index abrasion resistant coatings.     

Structure–Function Relationship of Retinal Ganglion Cells in Multiple Sclerosis

The retinal ganglion cells (RGC) may be considered an easily accessible pathophysiological site of degenerative processes in neurological diseases, such as the RGC damage detectable in multiple sclerosis (MS) patients with (HON) and without a history of optic neuritis (NON). We aimed to assess and interrelate RGC functional and structural damage in different retinal layers and retinal sites. We included 12 NON patients, 11 HON patients and 14 healthy controls for cross-sectional multifocal pattern electroretinography (mfPERG) and optical coherence tomography (OCT) measurements. Amplitude and peak times of the mfPERG were assessed. Macula and disc OCT scans were acquired to determine macular retinal layer and peripapillary retinal nerve fiber layer (pRNFL) thickness. In both HON and NON patients the foveal N2 amplitude of the mfPERG was reduced compared to controls. The parafoveal P1 peak time was significantly reduced in HON only. For OCT, parafoveal (pfGCL) and perifoveal (pGCL) ganglion cell layer thicknesses were decreased in HON vs. controls, while pRNFL in the papillomacular bundle sector (PMB) showed reductions in both NON and HON. As the mfPERG derived N2 originates from RGC axons, these findings suggest foveal axonal dysfunction not only in HON, but also in NON patients.     

Robust optical flow estimation via edge preserving filtering

It is known that optical flow estimation techniques suffer from the issues of ill-defined edges and boundaries of the moving objects. Traditional variational methods for optical flow estimation are not robust to handle these issues since the local filters in these methods do not hold the robustness near the edges. In this paper, we propose a non-local total variation NLTV-$L^1$ optical flow estimation method based on robust weighted guided filtering. Specifically, first, the robust weighted guided filtering objective function is proposed to preserve motion edges. The proposed objective function is based on the linear model which is computationally efficient and edge-preserving in complex natural scenarios. Second, the proposed weighted guided filtering objective function is incorporated into the non-local total variation NLTV-$L^1$ energy function. Finally, the novel NLTV-$L^1$ optical flow method is performed using the coarse-to-fine process. Additionally, we modify some state-of-the-art variational optical flow estimation methods by the robust weighted guided filtering objective function to verify the performance on Middlebury, MPI-Sintel, and Foggy Zurich sequences. Experimental results show that the proposed method can preserve edges and improve the accuracy of optical flow estimation compared with several state-of-the-art methods.     

BCLA CLEAR - Effect of contact lens materials and designs on the anatomy and physiology of the eye

This paper outlines changes to the ocular surface caused by contact lenses and their degree of clinical significance. Substantial research and development to improve oxygen permeability of rigid and soft contact lenses has meant that in many countries the issues caused by hypoxia to the ocular surface have largely been negated. The ability of contact lenses to change the axial growth characteristics of the globe is being utilised to help reduce the myopia pandemic and several studies and meta-analyses have shown that wearing orthokeratology lenses or soft multifocal contact lenses can reduce axial length growth (and hence myopia).However, effects on blinking, ptosis, the function of Meibomian glands, fluorescein and lissamine green staining of the conjunctiva and cornea, production of lid-parallel conjunctival folds and lid wiper epitheliopathy have received less research attention. Contact lens wear produces a subclinical inflammatory response manifested by increases in the number of dendritiform cells in the conjunctiva, cornea and limbus. Papillary conjunctivitis is also a complication of all types of contact lenses. Changes to wear schedule (daily disposable from overnight wear) or lens materials (hydrogel from SiHy) can reduce papillary conjunctivitis, but the effect of such changes on dendritic cell migration needs further study. These changes may be associated with decreased comfort but confirmatory studies are needed. Contact lenses can affect the sensitivity of the ocular surface to mechanical stimulation, but whether these changes affect comfort requires further investigation.In conclusion, there have been changes to lens materials, design and wear schedules over the past 20+ years that have improved their safety and seen the development of lenses that can reduce the myopia development. However, several changes to the ocular surface still occur and warrant further research effort in order to optimise the lens wearing experience.     

Development of surface reconstruction algorithms for optical interferometric measurement

Optical interferometry is a powerful tool for measuring and characterizing areal surface topography in precision manufacturing. A variety of instruments based on optical interferometry have been developed to meet the measurement needs in various applications, but the existing techniques are simply not enough to meet the ever-increasing requirements in terms of accuracy, speed, robustness, and dynamic range, especially in on-line or on-machine conditions. This paper provides an in-depth perspective of surface topography reconstruction for optical interferometric measurements. Principles, configurations, and applications of typical optical interferometers with different capabilities and limitations are presented. Theoretical background and recent advances of fringe analysis algorithms, including coherence peak sensing and phase-shifting algorithm, are summarized. The new developments in measurement accuracy and repeatability, noise resistance, self-calibration ability, and computational efficiency are discussed. This paper also presents the new challenges that optical interferometry techniques are facing in surface topography measurement. To address these challenges, advanced techniques in image stitching, on-machine measurement, intelligent sampling, parallel computing, and deep learning are explored to improve the functional performance of optical interferometry in future manufacturing metrology.