50 Years of Image Analysis

Diagnostics and Therapy Guanying Chen,‡,† Indrajit Roy,†,§ Chunhui Yang,*,‡ and Paras N. Prasad*,† †Institute for Lasers, Photonics, and Biophotonics and Department of Chemistry, University at Buffalo, State University of New York, Buffalo, New York 14260, United States ‡School of Chemical Engineering and Technology, Harbin Institute of Technology, Harbin, Heilongjiang 150001, China Department of Chemistry, University of Delhi, Delhi 110007, India

Nanochemistry and Nanomedicine for Nanoparticle-based Diagnostics and Therapy

Visible-light persistent phosphors are being widely used as self-sustained night-vision materials because of their sufficiently strong and long afterglow (>10 h) and their ability to be excited by sunlight as well as room light. In contrast, persistent phosphors for near-infrared (NIR) wavelengths are lacking. Here we report a series of Cr(3+)-doped zinc gallogermanate NIR persistent phosphors that exhibit strong emission at 650-1,000 nm, extending beyond the typical 690-750 nm, and with a super-long afterglow of more than 360 h. These new NIR persistent phosphors are all-weather materials that can be rapidly, effectively and repeatedly charged by natural sunlight in almost all kinds of outdoor environment. Seconds to minutes of sunlight activation can result in more than two weeks of persistent NIR light emission. This new series of NIR persistent materials have potential applications in night-vision surveillance, solar energy utilization and in vivo bio-imaging.

Sunlight-activated long-persistent luminescence in the near-infrared from Cr 3+ -doped zinc gallogermanates

Owing to the unique mechanism of photoelectron storage and release, long persistent phosphorescence, also called long persistent luminescence or long lasting afterglow/phosphorescence, plays a pivotal role in the areas of spectroscopy, photochemistry, photonics and materials science. In recent years, more research has focused on the manipulation of the morphology, operational wavebands and persistent duration of long persistent phosphors (LPPs). These desired achievements stimulated the growing interest in designing bio-labels, photocatalysts, optical sensors, detectors and photonic devices. In this review, we present multidisciplinary research on synthetic methods, afterglow mechanisms, characterization techniques, materials system, and applications of LPPs. First, we introduce the recent developments in LPPs for the synthesis of nanoparticles from the aspects of particle sizes, monodispersity and homogeneity based on the urgent application of bio-imaging. In the later sections, we present the possible mechanisms, which involve the variation of trap distribution during the trapping and de-trapping process, complicated photo-ionization reaction of trap site levels and impurity centers together with their corresponding migration kinetics of carriers. Meanwhile, we emphasize the characterization techniques of defects, used to qualitatively or quantitatively describe the types, concentrations and depths of the traps. This review article also highlights the recent advances in suggested LPPs materials with a focus on the LPPs' hosts and optically active centers as well as their control, tuning and intrinsic links. We further discuss the classification of LPPs based on the different emission and excitation wavebands from the ultraviolet to the near-infrared region along with an overview of the activation mode of afterglow. Afterwards, we provide an exhibition of new products towards diverse application fields, including solar energy utilization, bio-imaging, diagnosis, and photocatalysts. Finally, we summarize the current achievements, discuss the problems and provide suggestions for potential future directions in the aforementioned parts.

Long persistent phosphors—from fundamentals to applications

Because of the interesting and multifunctional properties, recently, ZnO nanostructures are considered as excellent material for fabrication of highly sensitive and selective gas sensors. Thus, ZnO nanomaterials are widely used to fabricate efficient gas sensors for the detection of various hazardous and toxic gases. The presented review article is focusing on the recent developments of NO2 gas sensors based on ZnO nanomaterials. The review presents the general introduction of some metal oxide nanomaterials for gas sensing application and finally focusing on the structure of ZnO and its gas sensing mechanisms. Basic gas sensing characteristics such as gas response, response time, recovery time, selectivity, detection limit, stability and recyclability, etc are also discussed in this article. Further, the utilization of various ZnO nanomaterials such as nanorods, nanowires, nano-micro flowers, quantum dots, thin films and nanosheets, etc for the fabrication of NO2 gas sensors are also presented. Moreover, various factors such as NO2 concentrations, annealing temperature, ZnO morphologies and particle sizes, relative humidity, operating temperatures which are affecting the NO2 gas sensing properties are discussed in this review. Finally, the review article is concluded and future directions are presented.

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Zinc Oxide Nanostructures for NO2 Gas–Sensor Applications: A Review

In conventional photostimulable storage phosphors, the optical information written by x-ray or ultraviolet irradiation is usually read out as a visible photostimulated luminescence (PSL) signal under the stimulation of a low-energy light with appropriate wavelength. Unlike the transient PSL, here we report a new optical read-out form, photostimulated persistent luminescence (PSPL) in the near-infrared (NIR), from a Cr(3+)-doped LiGa₅O₈ NIR persistent phosphor exhibiting a super-long NIR persistent luminescence of more than 1,000 h. An intense PSPL signal peaking at 716 nm can be repeatedly obtained in a period of more than 1,000 h when an ultraviolet-light (250-360 nm) pre-irradiated LiGa₅O₈:Cr(3+) phosphor is repeatedly stimulated with a visible light or a NIR light. The LiGa₅O₈:Cr(3+) phosphor has promising applications in optical information storage, night-vision surveillance, and in vivo bio-imaging.

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Photostimulated near-infrared persistent luminescence as a new optical read-out from Cr³⁺-doped LiGa₅O₈.

The estimation and prediction of state-of-health (SOH) and state-of-charge (SOC) of Lithium-ion batteries are two main functions of the battery management system (BMS). In order to reduce the computation cost and enable deployment of the BMS on the low-cost hardware, a Lebesgue-sampling-based extended Kalman filter (LS-EKF) is developed to estimate the SOH and SOC. An LS-EKF is able to eliminate unnecessary computations, especially when the states change slowly. In this paper, the SOH is first estimated and the remaining useful life is predicted by the LS-EKF. Then, the estimated SOH is used as the initial battery capacity for SOC estimation and prediction. The SOH and SOC estimation and prediction are calculated repeatedly in the whole battery service life. The proposed method is verified with the application to the capacity degradation of the Lithium-ion battery. The results show that the LS-EKF-based algorithm has a good performance in SOH and SOC estimation and prediction in terms of accuracy and computation cost.

A Battery Management System With a Lebesgue-Sampling-Based Extended Kalman Filter

Near infrared (NIR; 660−1300 nm) long-persistent phosphorescence from Cr3+ ions with persistence time of more than 1 hour was realized in La3Ga5GeO14:Cr3+ phosphor (with or without co-dopants such as Li+, Zn2+, Ca2+, Mg2+ and Dy3+). The NIR phosphorescence can be effectively achieved under UV illumination (~240−360 nm) but is barely achieved by blue light (~480 nm) irradiation, even though the blue light excitation are effective to the NIR fluorescence. The NIR phosphorescence mechanisms were discussed by measuring the irradiation energy dependence of the phosphorescence intensity.

Near Infrared Long-Persistent Phosphorescence in La 3 Ga 5 GeO 14 :Cr 3+ Phosphor

Traditional fault diagnosis and prognosis (FDP) approaches are based on periodic sampling, i.e., samples are taken and algorithms are executed both in a periodic manner. As the volume of sensor data and complexity of algorithms keep increasing, the bottleneck of FDP is mainly the limited computational resources, which is particularly true for distributed applications where FDP functions are deployed on microcontrollers and embedded systems with limited computation resources. This paper introduces the concept of Lebesgue sampling (LS) in FDP and proposes a LS-based FDP (LS-FDP) framework. In the proposed LS-FDP, a novel diagnostic philosophy of “execution only when necessary” is developed in computation cost reduction. For prognosis, different from traditional approaches in which the prognostic horizon is on the time axis, the proposed approach defines the prognostic horizon on the fault state axis. With a reduced prognostic horizon, the LS-FDP naturally benefits the uncertainty management. The goal of this paper is to create the fundamental knowledge for LS-FDP solutions that are cost efficient, capable for the deployment on systems with limited computation sources, and supportive to the trend of distributed FDP schemes in complex systems. The design and implementation of particle-filter-based LS-FDP are presented with experimental results on lithium-ion batteries to verify the effectiveness of the proposed approaches.

Lebesgue-Sampling-Based Diagnosis and Prognosis for Lithium-Ion Batteries

Lebesgue-sampling-based fault diagnosis and prognosis (LS-FDP) is developed with the advantage of less computation requirement and smaller uncertainty accumulation. Same as other diagnostic and prognostic approaches, the accuracy and precision of LS-FDP are significantly influenced by the parameters and uncertainties in the diagnostic and prognostic models. To improve performance of LS-FDP, this paper introduces an online model parameter adaptation scheme, which is realized by a recursive least square method with a forgetting factor. In addition, uncertainty of remaining useful life (RUL) prediction is managed by adjusting the model noises through a short-term prediction and correction loop. To verify the proposed parameter adaptation and noise adjustment methods, they are designed and implemented in a particle-filtering-based LS-FDP algorithm with applications to Li-ion batteries. Experimental results show that the proposed approach has significant improvement on both battery capacity estimation and RUL prediction.

Wuzhao Yan

Papers

Photostimulated near-infrared persistent luminescence as a new optical read-out from Cr³⁺-doped LiGa₅O₈.

A Battery Management System With a Lebesgue-Sampling-Based Extended Kalman Filter

Near Infrared Long-Persistent Phosphorescence in La 3 Ga 5 GeO 14 :Cr 3+ Phosphor

Lebesgue-Sampling-Based Diagnosis and Prognosis for Lithium-Ion Batteries

Uncertainty Management in Lebesgue-Sampling-Based Diagnosis and Prognosis for Lithium-Ion Battery