Operando optical fiber monitoring of nanoscale and fast temperature changes during photo-electrocatalytic reactions

In Situ and Continuous Decoding Hydrogen Generation in Solar Water-Splitting Cells

Photoelectrochemical (PEC) water splitting is gaining recognition as an effective method for producing green hydrogen. However, the absence of in situ, continuous decoding hydrogen generation tools hampers a detailed understanding of the physics and chemistry involved in hydrogen generation within PEC systems. In this article, we present a quantitative, spatiotemporally resolved optical sensor employing a fiber Bragg grating (FBG) to probe hydrogen formation and temperature characteristics in the PEC system. Demonstrating this principle, we observed hydrogen formation and temperature changes in a novel cappuccino cell using a BiVO4/TiO2 photoanode and a Cu2O/CuO/TiO2 photocathode. Our findings demonstrate that FBG sensors can probe dynamic hydrogen formation at 0.5 s temporal resolution; these sensors are capable of detecting hydrogen concentrations as low as 0.6 mM. We conducted in situ and continuous monitoring of hydrogen and temperature to ascertain various parameters: the rate of hydrogen production at the photocathode surface, the time to reach hydrogen saturation, the distribution of hydrogen and temperature, and the rate of hydrogen transfer in the electrolyte under both external bias and unbiased voltage conditions. These results contribute valuable insights into the design and optimization of PEC water-splitting devices, advancing the in situ comprehensive monitoring of PEC water-splitting processes.

Operando Decoding of Surface Chemical and Thermal Events in Photoelectrocatalysis via a Lab-Around-Microfiber Sensor

Operando decoding of the key parameters of photo-electric catalysis provides reliable information for catalytic effect evaluation and catalytic mechanism exploration. However, to capture the details of surface-localized and rapid chemical and thermal events at the nanoscale in real-time is highly challenging. A promising approach based on a lab-around-microfiber sensor capable of simulating photo-electric catalytic reactions on the surface of optical fibers as well as monitoring reactant concentration changes and catalytic heat generation processes is demonstrated. Due to the penetration depth of submicron size and the fast response ability of the evanescent field, the lab-around-microfiber sensor overcame the difficulty of reading instantaneous surface parameters in the submicron range. This sensor operando dismantled the changes in reactant concentration and temperature on the catalyst surface induced by light and voltage, respectively. It also decoded the impact of catalyst composition on the adsorption efficiency and catalytic efficiency across various wavelengths and determined the synchronized occurrence of pollutant degradation and catalytic thermal effects. Stable correlations between the real-time parameters and catalytic activities are obtained, helping to provide a basic understanding of the catalytic process and mechanism. This approach fills an important gap in the current monitoring methods of catalytic processes and heat production.

High performance few-mode fiber-based light field direction sensing system using deep convolutional neural network: fiber speckle demodulation network (FSDNET)

Precisely sensing the light field direction information plays the essential role in the fields of three-dimensional (3D) imaging, light field sensing, target positioning and tracking, remote sensing, etc. It is thrilling to find that the optical fiber can be used as a sensing component due to its high sensitivity, compact size, and strong resistance to electromagnetic interference. According to the core principle that the few-mode fiber output speckle pattern is sensitive to the change of incident light field direction, the variation characteristics is further investigated in this research study. Based on the simulation and analysis of the fiber transmission characteristics, the output speckle corresponding to the incident light field with the direction in the range of ±6° horizontally and vertically are calculated. Furthermore, a deep convolutional neural network (CNN): fiber speckle demodulation network (FSDNET) is proposed and constructed to establish what we believe to be a novel way to reveal and identify the mapping relationship between the light field direction and the output speckle. The theoretical simulation shows that the mean absolute error (MAE) between the perceived light field directions and the true directions is 0.01°. Then, a light field direction sensing system based on the few-mode fiber is developed. Regarding to the performance of the sensing system, the MAE of the FSDNET for the light field directions that have appeared in the training set is 0.0389°, and for testing set of the unknown directions that have not appeared in the training set, the MAE is 0.0570°. Therefore, the simulation and experimental results prove that high performance sensing of light field direction can be achieved by the proposed few-mode fiber sensing system and the FSDNET.

Advancements in Battery Monitoring: Harnessing Fiber Grating Sensors for Enhanced Performance and Reliability

Batteries play a crucial role as energy storage devices across various industries. However, achieving high performance often comes at the cost of safety. Continuous monitoring is essential to ensure the safety and reliability of batteries. This paper investigates the advancements in battery monitoring technology, focusing on fiber Bragg gratings (FBGs). By examining the factors contributing to battery degradation and the principles of FBGs, this study discusses key aspects of FBG sensing, including mounting locations, monitoring targets, and their correlation with optical signals. While current FBG battery sensing can achieve high measurement accuracies for temperature (0.1 °C), strain (0.1 με), pressure (0.14 bar), and refractive index (6 × 10-5 RIU), with corresponding sensitivities of 40 pm/°C, 2.2 pm/με, -0.3 pm/bar, and -18 nm/RIU, respectively, accurately assessing battery health in real time remains a challenge. Traditional methods struggle to provide real-time and precise evaluations by analyzing the microstructure of battery materials or physical phenomena during chemical reactions. Therefore, by summarizing the current state of FBG battery sensing research, it is evident that monitoring battery material properties (e.g., refractive index and gas properties) through FBGs offers a promising solution for real-time and accurate battery health assessment. This paper also delves into the obstacles of battery monitoring, such as standardizing the FBG encapsulation process, decoupling multiple parameters, and controlling costs. Ultimately, the paper highlights the potential of FBG monitoring technology in driving advancements in battery development.

In situ surface turbidity sensor based on localized light scattering from tilted fiber Bragg gratings

We propose a compact fiber-optic sensor for in situ and continuous turbidity monitoring, based on surface optical scattering of polarized evanescent waves from targeted particles. The sensor is composed of a tilted fiber Bragg grating (TFBG) packaged inside a microfluidic capillary. The transmission spectrum of the TFBG provides a fine comb of narrow cladding resonances that are highly sensitive to the turbidity due to the localized light scattering of polarized evanescent waves from the microparticles near the fiber surface (as opposed to traditional bulk/volumetric turbidity measurement). We also propose a transmission spectral area interrogation method and quantify the repeatable correlation between the surface turbidity and the optical spectral area response. We show that the maximum sensitive turbidity response is achieved when the wavelength of the sensing cladding resonance matches the size of surrounding solid particles.

Operando monitoring of dendrite formation in lithium metal batteries via ultrasensitive tilted fiber Bragg grating sensors

Lithium (Li) dendrite growth significantly deteriorates the performance and shortens the operation life of lithium metal batteries. Capturing the intricate dynamics of surface localized and rapid mass transport at the electrolyte-electrode interface of lithium metal is essential for the understanding of the dendrite growth process, and the evaluation of the solutions mitigating the dendrite growth issue. Here we demonstrate an approach based on an ultrasensitive tilted fiber Bragg grating (TFBG) sensor which is inserted close to the electrode surface in a working lithium metal battery, without disturbing its operation. Thanks to the superfine optical resonances of the TFBG, in situ and rapid monitoring of mass transport kinetics and lithium dendrite growth at the nanoscale interface of lithium anodes have been achieved. Reliable correlations between the performance of different natural/artificial solid electrolyte interphases (SEIs) and the time-resolved optical responses have been observed and quantified, enabling us to link the nanoscale ion and SEI behavior with the macroscopic battery performance. This new operando tool will provide additional capabilities for parametrization of the batteries' electrochemistry and help identify the optimal interphases of lithium metal batteries to enhance battery performance and its safety.

High-sensitivity fiber optic temperature sensor based on CTFBG-FPI and Vernier effect

A novel high-sensitivity temperature sensor based on a chirped thin-core fiber Bragg grating Fabry-Perot interferometer (CTFBG-FPI) and the Vernier effect is proposed and demonstrated. With femtosecond laser direct writing technology, two CTFBG-FPIs with different interferometric cavity lengths are inscribed inside a thin-core fiber to form a Vernier effect system. The two FPIs consist of two pairs of CTFBGs with a full width at half maximum (FWHM) of 66.5 nm staggered in parallel. The interferometric cavity lengths of the two FPIs were designed to be 2 mm and 1.98 mm as the reference arm and sensing arm of the sensor, respectively. The temperature sensitivity of this sensor was measured to be -1.084 nm/°C in a range of 40-90°C. This sensor is expected to play a crucial role in precision temperature measurement applications.

Polarization-independent tilted fiber Bragg grating surface plasmon resonance sensor based on spectrum optimization

We experimentally demonstrated polarization multiplexing schemes in a tilted fiber grating (TFBG) to achieve polarization-independent fiber-optic surface plasmon resonance (SPR) sensors. The first used two orthogonal polarized lights separated by a polarization beam splitter (PBS) that are p-polarized in polarization-maintaining fiber (PMF) and precisely aligned with the tilted grating plane, so as to achieve the transmission of p-polarized light in two opposite directions of the Au-coated TFBG to excite SPR. Alternatively, polarization multiplexing was also achieved by exploring two polarization components to achieve the SPR effect through a Faraday rotator mirror (FRM). The SPR reflection spectra are polarization-independent of the light source and any perturbations to fibers, which are explained by the superposition of p- and s-polarized transmission spectra in equal proportions. The spectrum optimization is presented to reduce the proportion of the s-polarization component. A polarization-independent TFBG-based SPR refractive index (RI) sensor with a wavelength sensitivity of 555.14 nm/RIU and an amplitude sensitivity of 1724.92 dB/RIU for small changes is obtained, exhibiting unique advantages of minimizing the polarization alterations by mechanical perturbations.

Decoupling bulk and surface characteristics with a bare tilted fiber Bragg grating

The tilted fiber Bragg grating (TFBG) with dense comb-like resonances offers a promising fiber-optic sensing platform but could suffer from cross sensitivity dependent on bulk and surface environment. In this work, the decoupling of bulk and surface characteristics (indicated by bulk refractive index (RI) and surface-localized binding film) from each other is attained theoretically with a bare TFBG sensor. This is realized with the proposed decoupling approach based on differential spectral responses of cut-off mode resonance and mode dispersion represented as wavelength interval between P- and S-polarized resonances of the TFBG to the bulk RI and surface film thickness. The results demonstrate that with this method the sensing performance for decoupling bulk RI and surface film thickness is comparative to the cases in which either the bulk or surface environment of the TFBG sensor changes, with the bulk and surface sensitivities over 540 nm/RIU and 12 pm/nm, respectively.

Accurate compensation and prediction of the temperature cross-sensitivity of tilted FBG cladding mode resonances

The temperature dependence of core mode resonance has been thoroughly studied in fiber Bragg gratings (FBGs), but it is not the case for cladding mode resonances in multi-resonance gratings such as tilted FBGs (TFBGs). In this work, the temperature sensitivity of ultraviolet written TFBGs in SMF-28 fibers is assessed, demonstrating in the first, to the best of our knowledge, place that a single gauge factor K T =6.25⋅10-6±0.02⋅10-6 ∘ C -1 can be employed to characterize the response to temperature of the resonances over the full spectrum in the 10°-50°C range. Then, a simulation model is obtained, enabling to predict TFBG spectra in the 10°-50°C range with high accuracy. This requires a calibration of the core index and dispersion of the TFBG measured in air at 25°C, and determination of the glass refractive index thermo-optic coefficient (d n/d T=8.46⋅10-6±0.1⋅10-6 ∘ C -1, common to both core and cladding glasses), leading to a mean error on the wavelength position of resonances between 1 and 3 pm. This mean error can be further reduced (less than 1 pm) by considering a linear dependence with temperature of d n/d T. Therefore, this model will enable to completely remove the temperature-induced shifts of all resonances in TFBG sensing applications and measure with great accuracy the variables of interest by using the scaled averages of groups of resonances instead of (less accurate) individual shifts.

Modulating the metal center in MIL-101 for the piezoelectric catalytic synthesis of hydrogen peroxide

Modulation of metal centers is a promising strategy to boost catalytic performance. Two structurally identical MOFs with different metal centers, namely MIL-101(Cr) and MIL-101(Fe), were synthesized. MIL-101(Cr) exhibits superior H₂O₂ yield due to Cr's electron-donating ability. This work helps in developing the rational design and optimization of MOF catalysts for catalytic reactions.

Chloroform-infiltrated photonic crystal fiber with high-temperature sensitivity

The temperature sensor is the core part of the temperature measurement instrument, and its performance directly determines the temperature measurement accuracy. Photonic crystal fiber (PCF) is a new type of temperature sensor with extremely high potential. In this paper, we propose a high-performance, structurally simple, liquid-filled PCF temperature sensor, which is based on a SMF-PCF-SMF (single mode fiber, SMF) sandwich structure. By adjusting the structural parameters of the the PCF, it is possible to obtain optical properties that are superior to those of ordinary optical fibers. This allows for more obvious responsive changes of the fiber transmission mode under small external temperature changes. By optimizing the basic structure parameters, a new PCF structure with a central air hole is designed, and its temperature sensitivity is -0.04696 nm/°C. When filling the air holes of PCFs with temperature-sensitive liquid materials, the response of the optical field against the temperature fluctuations can be effectively enhanced. The Chloroform solution is used to selectively infiltrate the resulting PCF owing to its large thermo-optical coefficient. After comparing various filling schemes, the calculation results show that the highest temperature sensitivity of -15.8 nm/°C is finally realized. The designed PCF sensor has a simple structure, high-temperature sensitivity, and good linearity showing great application potential.

In-Situ Construction Molecular Imprinting Electrocatalyst of Au-MoO3/Graphene for Bisphenol A Determination with Long-Term Stability

Molecular imprinting (MI) technology has been used in electrochemical analysis technology because of its unique selectivity and specificity. In this work, an electrochemical sensor based on in-situ inorganic MI-Au-MoO3/graphene for bisphenol A (BPA) analysis is designed, where MI-MoO3 is hybridized with graphene nanosheets and Au nanoparticles, and BPA is acted as the temple molecular. Differential pulse voltammetry (DPV) was used to evaluate the sensing performance of the MI-Au-MoO3/rGO sensor toward BPA determination and it is about 2.0 times that of NI-Au-MoO3/rGO. The as-constructed sensor presents a wide linear range from 0.01 to 106.04 μM and a low limit of detection of 0.003 μM. It also displays outstanding stability and repeatability up to 20 days, and can be used to analyze the content of BPA in dust leachate and plastic bottle. This sensor offers a promising strategy for environment pollution and food analysis via MI technology.

High-performance multi-parameter fiber sensor by grating-enhanced Mach-Zehnder interference

A multi-parameter dual-core fiber sensor is proposed to realize highly sensitive detection of illumination, temperature, and humidity, separately. Through partial grating etching of a one-side core, the interaction between the core and the external environment is enhanced. Then, combining the Mach-Zehnder effect of the dual core, a higher sensing sensitivity is obtained. Experimental results show the temperature sensitivity is higher than 6.1952 nm/°C. Besides, the humidity and illumination resolution can reach as accurate as 0.041 relative humidity (RH) and 0.025 light units, respectively. To have better multi-parameter sensing and demodulation, the deep learning algorithm of a one-dimensional convolutional neural network (1D-CNN) is used to reach an accuracy of 99.05% with ∼2.00 root mean square error (RMSE). We envision such an excellent multi-parameter sensor can be promising in environmental monitoring and intelligent manufacturing.