Wavelet denoising of fiber optic monitoring signals in permafrost regions.

To address the noise issue in fiber optic monitoring signals in frozen soil areas, this study employs wavelet denoising techniques to process the fiber optic signals. Since existing parameter choices for wavelets are typically based on conventional environments, selecting suitable parameters for frozen soil regions becomes crucial. In this work, an index library is constructed based on commonly used wavelet basis functions in civil engineering. An optimal wavelet basis function is objectively selected through specific criteria. Considering the characteristic of small root mean square error in fiber optic signals in frozen soil areas, a multi-index fusion approach is applied to determine the optimal decomposition level. Field observations validate that denoised signals, with parameters set appropriately, can more accurately identify locations where settlement occurs.

Detection of NT-proBNP Using Optical Fiber Back-Reflection Plasmonic Biosensors.

Heart failure (HF) is a clinical entity included in cardiovascular diseases affecting millions of people worldwide, being a leading cause of hospitalization of older adults, and therefore imposing a substantial economic burden on healthcare systems. HF is characterized by dyspnea, fatigue, and edema associated with elevated blood levels of natriuretic peptides, such as N Terminal pro-B-type Natriuretic Peptide (NT-proBNP), for which there is a high demand for point of care testing (POCT) devices. Optical fiber (OF) biosensors offer a promising solution, capable of real-time detection, quantification, and monitoring of NT-proBNP concentrations in serum, saliva, or urine. In this study, immunosensors based on plasmonic uncladded OF tips were developed using OF with different core diameters (200 and 600 µm). The tips were characterized to bulk refractive index (RI), anddetection tests were conducted with NT-proBNP concentrations varying from 0.01 to 100 ng/mL. The 200 µm sensors showed an average total variation of 3.6 ± 2.5 mRIU, an average sensitivity of 50.5 mRIU/ng·mL-1, and a limit of detection (LOD) of 0.15 ng/mL, while the 600 µm sensors had a response of 6.1 ± 4.2 mRIU, a sensitivity of 102.8 mRIU/ng·mL-1, and an LOD of 0.11 ng/mL. Control tests were performed using interferents such as uric acid, glucose, and creatinine. The results show the potential of these sensors for their use in biological fluids.

Polymeric optical fiber biosensor with PAMAM dendrimer-based surface modification and PlGF detection for pre-eclampsia diagnosis.

Pre-eclampsia (PE) is a life-threatening complication that occurs during pregnancy, affecting a large number of pregnant women and newborns worldwide. Rapid, on-site and affordable screening of PE at an early stage is necessary to ensure timely treatment and minimize both maternal and neonatal morbidity and mortality rates. Placental growth factor (PlGF) is an angiogenic blood biomarker used for PE diagnosis. Herein, we report the plasmonic fiber optic absorbance biosensor (P-FAB) strategy for detecting PlGF at femtomolar concentration using polymethyl methacrylate (PMMA) based U-bent polymeric optical fiber (POF) sensor probes. A novel poly(amidoamine) (PAMAM) dendrimer based PMMA surface modification is established to obtain a greater immobilization of the bioreceptors compared to a linear molecule like hexamethylenediamine (HMDA). Plasmonic sandwich immunoassay was realized by immobilizing the mouse anti-PlGF (3H1) on the U-bent POF sensor probe surface and gold nanoparticles (AuNP) labels conjugated with mouse anti-PlGF (6H9). The POF sensor probes could measure PlGF within 30 min using the P-FAB strategy. The limit-of-detection (LoD) was found to be 0.19 pg/mL and 0.57 pg/mL in phosphate-buffered saline and 10× diluted serum, respectively. The clinical sample testing, with eleven positive and eleven negative preeclamptic pregnancy samples, successfully confirmed the accuracy, reliability, specificity, and sensitivity of the P-FAB based POF sensor platform, thereby paving the way for cost-effective technology for PlGF detection and its potential for pre-eclampsia diagnosis.

Deep-learning-based image super-resolution of an end-expandable optical fiber probe for application in esophageal cancer diagnostics.

Significance: Endoscopic screening for esophageal cancer (EC) may enable early cancer diagnosis and treatment. While optical microendoscopic technology has shown promise in improving specificity, the limited field of view (<1 mm) significantly reduces the ability to survey large areas efficiently in EC screening. Aim: To improve the efficiency of endoscopic screening, we propose a novel concept of end-expandable endoscopic optical fiber probe for larger field of visualization and for the first time evaluate a deep-learning-based image super-resolution (DL-SR) method to overcome the issue of limited sampling capability. Approach: To demonstrate feasibility of the end-expandable optical fiber probe, DL-SR was applied on simulated low-resolution microendoscopic images to generate super-resolved (SR) ones. Varying the degradation model of image data acquisition, we identified the optimal parameters for optical fiber probe prototyping. The proposed screening method was validated with a human pathology reading study. Results: For various degradation parameters considered, the DL-SR method demonstrated different levels of improvement of traditional measures of image quality. The endoscopists' interpretations of the SR images were comparable to those performed on the high-resolution ones. Conclusions: This work suggests avenues for development of DL-SR-enabled sparse image reconstruction to improve high-yield EC screening and similar clinical applications.

Blind Polarization Demultiplexing of Shaped QAM Signals Assisted by Temporal Correlations.

While probabilistic constellation shaping (PCS) enables rate and reach adaption with finer granularity [1], it imposes signal processing challenges at the receiver. Since the distribution of PCS-quadrature amplitude modulation (QAM) signals tends to be Gaussian, conventional blind polarization demultiplexing algorithms are not suitable for them [2]. It is known that independently and identically distributed (iid) Gaussian signals, when mixed, cannot be recovered/separated from their mixture. For PCS-QAM signals, there are algorithms such as [3], [4] which are designed by extending conventional blind algorithms used for uniform QAM signals. In these algorithms, an initialization point is obtained by processing only a part of the mixed signal, which have non-Gaussian statistics. In this paper, we propose an alternative method wherein we add temporal correlations at the transmitter, which are subsequently exploited at the receiver in order to separate the polarizations. We will refer to the proposed method as frequency domain (FD) joint diagonalization (JD) probability aware-multi modulus algorithm (pr-MMA), and it is suited to channels with moderate polarization mode dispersion (PMD) effects. Furthermore, we extend our previously proposed JD-MMA [5] by replacing the standard MMA with a pr-MMA, improving its performance. Both FDJD-pr-MMA and JD-pr-MMA are evaluated for a diverse range of PCS (entropy 𝓗) over a first-order PMD channel that is simulated in a proof-of-concept setup. A MMA initialized with a memoryless constant modulus algorithm (CMA) is used as a benchmark. We show that at a differential group delay (DGD) of 10% of symbol period Tsymb and 18 dB SNR/pol., JD-pr-MMA successfully demultiplexes the PCS signals, while CMA-MMA fails drastically. Furthermore, we demonstrate that the newly proposed FDJD-pr-MMA is robust against moderate PMD effects by evaluating it over a DGD of up to 40% of Tsymb. Our results show that the proposed FDJD-pr-MMA successfully equalizes PMD channels with a DGD up to 20% of Tsymb.

Portable ratiometric fluorescence detection of Cu2+and thiram.

Food contaminants pose a danger to human health, but rapid, sensitive and reliable food safety detection methods can offer a solution to this problem. In this study, an optical fiber ratiometric fluorescence sensing system based on carbon dots (CDs) and o-phenylenediamine (OPD) was constructed. The ratiometric fluorescence response of Cu2+and thiram was carried out by the fluorescence resonance energy transfer (FRET) between CDs and 2,3-diaminophenazine (ox-OPD, oxidized state o-phenylenediamine). The oxidation of OPD by Cu2+resulted in the formation of ox-OPD, which quenched the fluorescence of CDs and exhibited a new emission peak at 573 nm. The formation of a [dithiocarbamate-Cu2+] (DTC-Cu2+) complex by reacting thiram with Cu2+, inhibits the OPD oxidation reaction triggered by Cu2+, thus turning off the fluorescence signal of OPD-Cu2+. The as-established detection system presented excellent sensitivity and selectivity for the detection of Cu2+and thiram in the ranges of 1 ∼ 100µM and 5 ∼ 50µM, respectively. The lowest detection limits were 0.392µM for Cu2+and 0.522µM for thiram. Furthermore, actual sample analysis indicated that the sensor had the potential for Cu2+and thiram assays in real sample analysis.

A Wearable Sandwich Heterostructure Multimode Fiber Optic Microbend Sensor for Vital Signal Monitoring.

This work proposes a highly sensitive sandwich heterostructure multimode optical fiber microbend sensor for heart rate (HR), respiratory rate (RR), and ballistocardiography (BCG) monitoring, which is fabricated by combining a sandwich heterostructure multimode fiber Mach-Zehnder interferometer (SHMF-MZI) with a microbend deformer. The parameters of the SHMF-MZI sensor and the microbend deformer were analyzed and optimized in detail, and then the new encapsulated method of the wearable device was put forward. The proposed wearable sensor could greatly enhance the response to the HR signal. The performances for HR, RR, and BCG monitoring were as good as those of the medically approved commercial monitors. The sensor has the advantages of high sensitivity, easy fabrication, and good stability, providing the potential for application in the field of daily supervision and health monitoring.

Soft Polymer Optical Fiber Sensors for Intelligent Recognition of Elastomer Deformations and Wearable Applications.

In recent years, soft robotic sensors have rapidly advanced to endow robots with the ability to interact with the external environment. Here, we propose a polymer optical fiber (POF) sensor with sensitive and stable detection performance for strain, bending, twisting, and pressing. Thus, we can map the real-time output light intensity of POF sensors to the spatial morphology of the elastomer. By leveraging the intrinsic correlations of neighboring sensors and machine learning algorithms, we realize the spatially resolved detection of the pressing and multi-dimensional deformation of elastomers. Specifically, the developed intelligent sensing system can effectively recognize the two-dimensional indentation position with a prediction accuracy as large as ~99.17%. The average prediction accuracy of combined strain and twist is ~98.4% using the random forest algorithm. In addition, we demonstrate an integrated intelligent glove for the recognition of hand gestures with a high recognition accuracy of 99.38%. Our work holds promise for applications in soft robots for interactive tasks in complex environments, providing robots with multidimensional proprioceptive perception. And it also can be applied in smart wearable sensing, human prosthetics, and human-machine interaction interfaces.

Temperature Uncertainty Reduction Algorithm Based on Temperature Distribution Prior for Optical Sensors in Oil Tank Ground Settlement Monitoring.

Ground settlement (GS) in an oil tank determines its structural integrity and commercial service. However, GS monitoring faces challenges, particularly due to the significant temperature differences induced by solar radiation around the tank in daytime. To address this problem, this paper digs out a prior and proposes a temperature uncertainty reduction algorithm based on that. This prior has a spatial Gaussian distribution of temperature around the tank, and numerical simulation and practical tests are conducted to demonstrate it. In addition, combining uniformly packaged sensor probes and the spatial prior of temperature, the temperature uncertainty is verified to be Gaussian-distributed too. Then, the overall temperature uncertainty can be captured by Gaussian fitting and then removed. The practical test verified a 91% reduction rate in temperature uncertainty, and this approach enables GS sensors to effectively perform daytime monitoring by mitigating temperature-related uncertainties.

Photocatalytic Optical Hollow Fiber with Enhanced Visible-light-driven CO2 Reduction.

A visible-light-driven CO2 reduction optical fiber is fabricated using graphene-like nitrogen-doped composites and hollow quartz optical fibers to achieve enhanced activity, selectivity, and light utilization for CO2 photoreduction. The composites are synthesized from a lead-based metal-organic framework (TMOF-10-NH2 ) and g-C3 N4 nanosheet (CNNS) via electrostatic self-assembly. The TMOF-10-NH2 /g-C3 N4 (TMOF/CNNS) photocatalyst with an S-type heterojunction is coated on optical fiber. The TMOF/CNNS coating, which has a bandgap energy of 2.15 eV, has good photoinduced capability at the coating interfaces, high photogenerated electron-hole pair yield, and high charge transfer rate. The conduction band potential of the TMOF/CNNS coating is more negative than that for CO2 reduction. Moreover, TMOF facilitates the CO desorption on its surface, thereby improving the selectivity for CO production. High CO2 photoreduction and selectivity for CO production is demonstrated by the TMOF/CNNS-coated optical fiber with the cladding/core diameter of 2000/1000 µm, 10 wt% TMOF in CNNS, coating thickness of 25 µm, initial CO2 concentration of 90 vol%, and relative humidity of 88% RH under the excitation wavelength of 380-780 nm. Overall, the photocatalytic hollow optical fiber developed herein provides an effective and efficient approach for the enhancement of light utilization efficiency of photocatalysts and selective CO2 reduction.

STNet: A Time-Frequency Analysis-Based Intrusion Detection Network for Distributed Optical Fiber Acoustic Sensing Systems.

Distributed optical fiber acoustic sensing (DAS) is promising for long-distance intrusion-anomaly detection tasks. However, realistic settings suffer from high-intensity interference noise, compromising the detection performance of DAS systems. To address this issue, we propose STNet, an intrusion detection network based on the Stockwell transform (S-transform), for DAS systems, considering the advantages of the S-transform in terms of noise resistance and ability to detect disturbances. Specifically, the signal detected by a DAS system is divided into space-time data matrices using a sliding window. Subsequently, the S-transform extracts the time-frequency features channel by channel. The extracted features are combined into a multi-channel time-frequency feature matrix and presented to STNet. Finally, a non-maximum suppression algorithm (NMS), suitable for locating intrusions, is used for the post-processing of the detection results. To evaluate the effectiveness of the proposed method, experiments were conducted using a realistic high-speed railway environment with high-intensity noise. The experimental results validated the satisfactory performance of the proposed method. Thus, the proposed method offers an effective solution for achieving high intrusion detection rates and low false alarm rates in complex environments.

Optical pH Sensor Based on a Long-Period Fiber Grating Coated with a Polymeric Layer-by-Layer Electrostatic Self-Assembled Nanofilm.

An optical fiber pH sensor based on a long-period fiber grating (LPFG) is reported. Two oppositely charged polymers, polyethylenimine (PEI) and polyacrylic acid (PAA), were alternately deposited on the sensing structure through a layer-by-layer (LbL) electrostatic self-assembly technique. Since the polymers are pH sensitive, their refractive index (RI) varies when the pH of the solution changes due to swelling/deswelling phenomena. The fabricated multilayer coating retained a similar property, enabling its use in pH-sensing applications. The pH of the PAA dipping solution was tuned so that a coated LPFG achieved a pH sensitivity of (6.3 ± 0.2) nm/pH in the 5.92-9.23 pH range. Only two bilayers of PEI/PAA were used as an overlay, which reduces the fabrication time and increases the reproducibility of the sensor, and its reversibility and repeatability were demonstrated by tracking the resonance band position throughout multiple cycles between different pH solutions. With simulation work and experimental results from a low-finesse Fabry-Perot (FP) cavity on a fiber tip, the coating properties were estimated. When saturated at low pH, it has a thickness of 200 nm and 1.53 ± 0.01 RI, expanding up to 310 nm with a 1.35 ± 0.01 RI at higher pH values, mostly due to the structural changes in the PAA.

3D Printing of Glass Micro-Optics with Subwavelength Features on Optical Fiber Tips.

Integration of functional materials and structures on the tips of optical fibers has enabled various applications in micro-optics, such as sensing, imaging, and optical trapping. Direct laser writing is a 3D printing technology that holds promise for fabricating advanced micro-optical structures on fiber tips. To date, material selection has been limited to organic polymer-based photoresists because existing methods for 3D direct laser writing of inorganic materials involve high-temperature processing that is not compatible with optical fibers. However, organic polymers do not feature stability and transparency comparable to those of inorganic glasses. Herein, we demonstrate 3D direct laser writing of inorganic glass with a subwavelength resolution on optical fiber tips. We show two distinct printing modes that enable the printing of solid silica glass structures ("Uniform Mode") and self-organized subwavelength gratings ("Nanograting Mode"), respectively. We illustrate the utility of our approach by printing two functional devices: (1) a refractive index sensor that can measure the indices of binary mixtures of acetone and methanol at near-infrared wavelengths and (2) a compact polarization beam splitter for polarization control and beam steering in an all-in-fiber system. By combining the superior material properties of glass with the plug-and-play nature of optical fibers, this approach enables promising applications in fields such as fiber sensing, optical microelectromechanical systems (MEMS), and quantum photonics.

Development of an Immunocapture-Based Polymeric Optical Fiber Sensor for Bacterial Detection in Water.

Conventional methods for pathogen detection in water rely on time-consuming enrichment steps followed by biochemical identification strategies, which require assay times ranging from 24 hours to a week. However, in recent years, significant efforts have been made to develop biosensing technologies enabling rapid and close-to-real-time detection of waterborne pathogens. In previous studies, we developed a plastic optical fiber (POF) immunosensor using an optoelectronic configuration consisting of a U-Shape probe connected to an LED and a photodetector. Bacterial detection was evaluated with the immunosensor immersed in a bacterial suspension in water with a known concentration. Here, we report on the sensitivity of a new optoelectronic configuration consisting of two POF U-shaped probes, one as the reference and the other as the immunosensor, for the detection of Escherichia coli. In addition, another methos of detection was tested where the sensors were calibrated in the air, before being immersed in a bacterial suspension and then read in the air. This modification improved sensor sensitivity and resulted in a faster detection time. After the immunocapture, the sensors were DAPI-stained and submitted to confocal microscopy. The histograms obtained confirmed that the responses of the immunosensors were due to the bacteria. This new sensor detected the presence of E. coli at 104 CFU/mL in less than 20 min. Currently, sub-20 min is faster than previous studies using fiber-optic based biosensors. We report on an inexpensive and faster detection technology when compared with conventional methods.

Probe-Type Multi-Core Fiber Optic Sensor for Simultaneous Measurement of Seawater Salinity, Pressure, and Temperature.

In this article, we propose and demonstrate a probe-type multi-core fiber (MCF) sensor for the multi-parameter measurement of seawater. The sensor comprises an MCF and two capillary optical fibers (COFs) with distinct inner diameters, in which a 45° symmetric core reflection (SCR) structure and a step-like inner diameter capillary (SIDC) structure filled with polydimethylsiloxane (PDMS) are fabricated at the fiber end. The sensor is equipped with three channels for different measurements. The surface plasmon resonance (SPR) channel (CHSPR) based on the side-polished MCF is utilized for salinity measurement. The fiber end air cavity, forming the Fabry-Pérot interference (FPI) channel (CHFPI), is utilized for pressure and temperature measurement. Additionally, the fiber Bragg grating (FBG) channel (CHFBG), which is inscribed in the central core, serves as temperature compensation for the measurement results. By combining three sensing principles with space division multiplexing (SDM) technology, the sensor overcomes the common challenges faced by multi-parameter sensors, such as channel crosstalk and signal demodulation difficulties. The experimental results indicate that the sensor has sensitivities of 0.36 nm/‱, -10.62 nm/MPa, and -0.19 nm/°C for salinity, pressure, and temperature, respectively. As a highly integrated and easily demodulated probe-type optical fiber sensor, it can serve as a valuable reference for the development of multi-parameter fiber optic sensors.

Dynamic Measurement of a Cancer Biomarker: Towards In Situ Application of a Fiber-Optic Ball Resonator Biosensor in CD44 Protein Detection.

The accuracy and efficacy of medical treatment would be greatly improved by the continuous and real-time monitoring of protein biomarkers. Identification of cancer biomarkers in patients with solid malignant tumors is receiving increasing attention. Existing techniques for detecting cancer proteins, such as the enzyme-linked immunosorbent assay, require a lot of work, are not multiplexed, and only allow for single-time point observations. In order to get one step closer to clinical usage, a dynamic platform for biosensing the cancer biomarker CD44 using a single-mode optical fiber-based ball resonator biosensor was designed, constructed and evaluated in this work. The main novelty of the work is an in-depth study of the capability of an in-house fabricated optical fiber biosensor for in situ detection of a cancer biomarker (CD44 protein) by conducting several types of experiments. The main results of the work are as follows: (1) Calibration of the fabricated fiber-optic ball resonator sensors in both static and dynamic conditions showed similar sensitivity to the refractive index change demonstrating its usefulness as a biosensing platform for dynamic measurements; (2) The fabricated sensors were shown to be insensitive to pressure changes further confirming their utility as an in situ sensor; (3) The sensor's packaging and placement were optimized to create a better environment for the fabricated ball resonator's performance in blood-mimicking environment; (4) Incubating increasing protein concentrations with antibody-functionalized sensor resulted in nearly instantaneous signal change indicating a femtomolar detection limit in a dynamic range from 7.1 aM to 16.7 nM; (5) The consistency of the obtained signal change was confirmed by repeatability studies; (6) Specificity experiments conducted under dynamic conditions demonstrated that the biosensors are highly selective to the targeted protein; (7) Surface morphology studies by AFM measurements further confirm the biosensor's exceptional sensitivity by revealing a considerable shift in height but no change in surface roughness after detection. The biosensor's ability to analyze clinically relevant proteins in real time with high sensitivity offers an advancement in the detection and monitoring of malignant tumors, hence improving patient diagnosis and health status surveillance.

Insulin biotrapping using plasmofluidic optical fiber chips: A benchmark.

Plasmonic optical fiber-based biosensors are currently in their early stages of development as practical and integrated devices, gradually making their way towards the market. While the majority of these biosensors operate using white light and multimode optical fibers (OFs), our approach centers on single-mode OFs coupled with tilted fiber Bragg gratings (TFBGs) in the near-infrared wavelength range. Our objective is to enhance surface sensitivity and broaden sensing capabilities of OF-based sensors to develop in situ sensing with remote interrogation. In this study, we comprehensively assess their performance in comparison to the gold-standard plasmonic reference, a commercial device based on the Kretschmann-Raether prism configuration. We present their refractive index sensitivity and their capability for insulin sensing using a dedicated microfluidics approach. By optimizing a consistent surface biotrapping methodology, we elucidate the dynamic facets of both technologies and highlight their remarkable sensitivity to variations in bulk and surface properties. The one-to-one comparison between both technologies demonstrates the reliability of optical fiber-based measurements, showcasing similar experimental trends obtained with both the prismatic configuration and gold-coated TFBGs, with an even enhanced limit of detection for the latter. This study lays the foundation for the detection of punctual molecular interactions and opens the way towards the detection of spatially and temporally localized events on the surface of optical probes.

Advancements in optical fiber-based wearable sensors for smart health monitoring.

Healthcare system is undergoing a significant transformation from a traditional hospital-centered to an individual-centered one, as a result of escalating chronic diseases, ageing populations, and ever-increasing healthcare costs,. Wearable sensors have become widely used in health monitoring systems since the COVID-19 pandemic. They enable continuous measurement of important health indicators like body temperature, wrist pulse, respiration rate, and non-invasive bio fluids like saliva and perspiration. Over the last few decades, the development has mostly concentrated on electrochemical and electrical wearable sensors. However, due to the drawbacks of such sensors, such as electronic waste, electromagnetic interference, non-electrical security, and poor performance, researchers are exhibiting a strong interest in optical principle-based systems. Fiber-based optical wearables are among the most promising healthcare systems because of advancements in high-sensitivity, durable, multiplexed sensing, and simple integration with flexible materials to improve wearability and simplicity. We present an overview of recent developments in optical fiber-based wearable sensors, focusing on two mechanisms: wavelength interrogation and intensity modulation for the detection of body temperature, pulse rate, respiration rate, body movements, and biomedical noninvasive fluids, with a thorough examination of their benefits and drawbacks. This review also focuses on improving working performance and application techniques for healthcare systems, including the integration of nanomaterials and the usage of the Internet of Things (IoT) with signal processing. Finally, the review concludes with a discussion of the future possibilities and problems for optical fiber-based wearables.

Mass-manufacturable scintillation-based optical fiber dosimeters for brachytherapy.

Scintillation-based fiber dosimeters are a powerful tool for minimally invasive localized real-time monitoring of the dose rate during Low Dose Rate (LDR) and High Dose Rate (HDR) brachytherapy (BT). This paper presents the design, fabrication, and characterization of such dosimeters, consisting of scintillating sensor tips attached to polymer optical fiber (POF). The sensor tips consist of inorganic scintillators, i.e. Gd2O2S:Tb for LDR-BT, and Y2O3:Eu+4YVO4:Eu for HDR-BT, dispersed in a polymer host. The shape and size of the tips are optimized using non-sequential ray tracing simulations towards maximizing the collection and coupling of the scintillation signal into the POF. They are then manufactured by means of a custom moulding process implemented on a commercial hot embossing machine, paving the way towards series production. Dosimetry experiments in water phantoms show that both the HDR-BT and LDR-BT sensors feature good consistency in the magnitude of the average photon count rate and that the photon count rate signal is not significantly affected by variations in sensor tip composition and geometry. Whilst individual calibration remains necessary, the proposed dosimeters show great potential for in-vivo dosimetry for brachytherapy.

Ratiometric Fluorescence Optical Fiber Enabling Operando Temperature Monitoring in Pouch-Type Battery.

Thermal characteristics are essential for improving the performance and monitoring the status of Li-ion batteries (LIBs). However, it is a challenge to design efficient and facile sensing materials for the detection of the in situ temperature of a working LIB. Herein, a ratiometric fluorescence optical fiber is developed and real-time temperature monitoring is performed with a measurement accuracy of 0.12 °C, and the feasibility based on this polymer optical fiber composed of NaLaTi2 O6 :Yb/Er phosphors is verified in a pouch-type battery. During the charging and discharging cycles, the in situ temperature is instantaneously conveyed, revealing the internal situation of LIBs. This article further dwells on the thermal characteristics in constant current (CC)/constant voltage charging and CC discharging processes at different C-rates and the battery failure when operated at low temperatures (0 °C). This work demonstrates an innovative strategy for operando solitary temperature monitoring conducted by ratiometric fluorescence optical fiber.