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Li L, Wu S, Jin M, Liu F, Zhao J, Huang Y, Feng N, Liu Y. Dielectric-metal hybrid structured LSPR sensor based on graphene oxide amplification for lead ion detection. OPTICS EXPRESS 2024; 32:48252-48266. [PMID: 39876135 DOI: 10.1364/oe.545553] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/21/2024] [Accepted: 12/02/2024] [Indexed: 01/30/2025]
Abstract
The detection of lead ions (Pb2+) is crucial due to its harmful effects on health and the environment. In this article, what we believe to be a novel dielectric-metal hybrid structure localized surface plasmon resonance (LSPR) sensor for ultra-trace detection of Pb2+ is proposed, featuring a zinc sulfide layer, silver nanodisks (Ag-disks), and graphene oxide (GO) covering the Ag-disks. The sensor works by detecting the variation of gold nanoparticles (AuNPs) on its surface when Pb2+ cleaves a substrate strand linked to a DNAzyme, causing the AuNPs modified on the substrate strand to disperse. The LSPR sensor boasts superior performance with a bulk refractive index sensitivity of 714.34 nm/RIU. It also exhibits a log-linear response to Pb2+ concentrations ranging from 10 pM to 100 nM, with a sensitivity of 3.93 nm/log(µM) and a detection limit of 10 pM. This represents a 1.25-fold increase in sensitivity and an order of magnitude lower detection limit compared to the GO-uncoated sensor. The improved performance is due to the abundant reactive groups and expansive surface area of graphene oxide, which facilitate the absorption of biochemical molecules. In addition, the sensor has good specificity and stability, holding significant potential for a variety of practical applications, and paving the way for LSPR sensors in detecting trace heavy metal ions.
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Hu Y, Jiang S, Huang Z, Guo Y, Qian S, Chen X, Geng Y, Liu S. Optical characterization sensing method of TFBG sensor for battery electromotive force monitoring. OPTICS EXPRESS 2024; 32:28914-28923. [PMID: 39538697 DOI: 10.1364/oe.524031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/18/2024] [Accepted: 07/18/2024] [Indexed: 11/16/2024]
Abstract
In the past few years, fiber optic sensors have demonstrated an amazing ability to detect the state of charge (SOC) and electromotive force (EMF) inside a battery in real-time. However, it remains an enormous challenge to characterize the relationship between the spectral shift of the fiber sensor and the internal EMF change of the battery. Here, we propose a method to monitor the electrolyte during the battery discharge process using the integral spectrum of a tiny tilted fiber Bragg grating (TFBG) sensor. The relationship between the fiber optic transmission spectrum and battery EMF was established by using this method. The results show that a TFBG sensor implanted in a lead-acid battery enables rapid EMF detection with a sensitivity of 1.16 × 105 (nm·dBm) /V. This technology provides a fiber optic precision solution for battery operating conditions and has excellent potential for detecting battery failures using traditional EMF methods.
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Li Y, Wang L, Song Y, Wang W, Lin C, He X. Functional Optical Fiber Sensors Detecting Imperceptible Physical/Chemical Changes for Smart Batteries. NANO-MICRO LETTERS 2024; 16:154. [PMID: 38499708 PMCID: PMC10948733 DOI: 10.1007/s40820-024-01374-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/05/2023] [Accepted: 02/01/2024] [Indexed: 03/20/2024]
Abstract
The battery technology progress has been a contradictory process in which performance improvement and hidden risks coexist. Now the battery is still a "black box", thus requiring a deep understanding of its internal state. The battery should "sense its internal physical/chemical conditions", which puts strict requirements on embedded sensing parts. This paper summarizes the application of advanced optical fiber sensors in lithium-ion batteries and energy storage technologies that may be mass deployed, focuses on the insights of advanced optical fiber sensors into the processes of one-dimensional nano-micro-level battery material structural phase transition, electrolyte degradation, electrode-electrolyte interface dynamics to three-dimensional macro-safety evolution. The paper contributes to understanding how to use optical fiber sensors to achieve "real" and "embedded" monitoring. Through the inherent advantages of the advanced optical fiber sensor, it helps clarify the battery internal state and reaction mechanism, aiding in the establishment of more detailed models. These advancements can promote the development of smart batteries, with significant importance lying in essentially promoting the improvement of system consistency. Furthermore, with the help of smart batteries in the future, the importance of consistency can be weakened or even eliminated. The application of advanced optical fiber sensors helps comprehensively improve the battery quality, reliability, and life.
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Affiliation(s)
- Yiding Li
- Institute of Nuclear and New Energy Technology, Tsinghua University, Beijing, 100084, People's Republic of China
| | - Li Wang
- Institute of Nuclear and New Energy Technology, Tsinghua University, Beijing, 100084, People's Republic of China.
| | - Youzhi Song
- Institute of Nuclear and New Energy Technology, Tsinghua University, Beijing, 100084, People's Republic of China
| | - Wenwei Wang
- National Engineering Research Center of Electric Vehicles, Beijing Institute of Technology (BIT), Beijing, 100081, People's Republic of China
- Shenzhen Automotive Research Institute of BIT (Shenzhen Research Institute of National Engineering Research Center of Electric Vehicles), Shenzhen, 518118, People's Republic of China
| | - Cheng Lin
- National Engineering Research Center of Electric Vehicles, Beijing Institute of Technology (BIT), Beijing, 100081, People's Republic of China
| | - Xiangming He
- Institute of Nuclear and New Energy Technology, Tsinghua University, Beijing, 100084, People's Republic of China.
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Arcadio F, Noël L, Del Prete D, Maniglio D, Seggio M, Soppera O, Cennamo N, Bossi AM, Zeni L. Soft molecularly imprinted nanoparticles with simultaneous lossy mode and surface plasmon multi-resonances for femtomolar sensing of serum transferrin protein. Sci Rep 2023; 13:11210. [PMID: 37433901 DOI: 10.1038/s41598-023-38262-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Accepted: 07/05/2023] [Indexed: 07/13/2023] Open
Abstract
The simultaneous interrogation of both lossy mode (LMR) and surface plasmon (SPR) resonances was herein exploited for the first time to devise a sensor in combination with soft molecularly imprinting of nanoparticles (nanoMIPs), specifically entailed of the selectivity towards the protein biomarker human serum transferrin (HTR). Two distinct metal-oxide bilayers, i.e. TiO2-ZrO2 and ZrO2-TiO2, were used in the SPR-LMR sensing platforms. The responses to binding of the target protein HTR of both sensing configurations (TiO2-ZrO2-Au-nanoMIPs, ZrO2-TiO2-Au-nanoMIPs) showed femtomolar HTR detection, LODs of tens of fM and KDapp ~ 30 fM. Selectivity for HTR was demonstrated. The SPR interrogation was more efficient for the ZrO2-TiO2-Au-nanoMIPs configuration (sensitivity at low concentrations, S = 0.108 nm/fM) than for the TiO2-ZrO2-Au-nanoMIPs one (S = 0.061 nm/fM); while LMR was more efficient for TiO2-ZrO2-Au-nanoMIPs (S = 0.396 nm/fM) than for ZrO2-TiO2-Au-nanoMIPs (S = 0.177 nm/fM). The simultaneous resonance monitoring is advantageous for point of care determinations, both in terms of measurement's redundancy, that enables the cross-control of the measure and the optimization of the detection, by exploiting the individual characteristics of each resonance.
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Affiliation(s)
- Francesco Arcadio
- Department of Engineering, University of Campania "L. Vanvitelli", Via Roma 29, Aversa, Italy
| | - Laurent Noël
- CNRS, IS2M UMR 7361, University of Upper-Alsace, 68100, Mulhouse, France
- Université de Strasbourg, 67000, Strasbourg, France
| | - Domenico Del Prete
- Department of Engineering, University of Campania "L. Vanvitelli", Via Roma 29, Aversa, Italy
| | - Devid Maniglio
- Department of Industrial Engineering, University of Trento, Via Sommarive 34, 38123, Trento, Italy
| | - Mimimorena Seggio
- Department of Biotechnology, University of Verona, Strada Le Grazie 15, 37134, Verona, Italy
| | - Olivier Soppera
- CNRS, IS2M UMR 7361, University of Upper-Alsace, 68100, Mulhouse, France
- Université de Strasbourg, 67000, Strasbourg, France
| | - Nunzio Cennamo
- Department of Engineering, University of Campania "L. Vanvitelli", Via Roma 29, Aversa, Italy
| | - Alessandra Maria Bossi
- Department of Biotechnology, University of Verona, Strada Le Grazie 15, 37134, Verona, Italy.
| | - Luigi Zeni
- Department of Engineering, University of Campania "L. Vanvitelli", Via Roma 29, Aversa, Italy.
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