摘要
与传统的传感器设备阵列相比,由于结构更为简单,具有广泛检测兼容性的光纤系统逐渐成为分布式监测的有力候选者。然而,受工作机制的限制,大多数光纤传感器仍局限于对折射率等物理参数进行探测,一种用于环境化学监测的全光纤分布式传感系统亟待研发。本工作中,我们向化学气相沉积法生长的石墨烯光子晶体光纤(Gr-PCF)中引入了一种化学传感机制。初步结果表明,石墨烯光子晶体光纤可以选择性地检测浓度为ppb级的二氧化氮气体,并在液体中表现出离子敏感性。石墨烯光子晶体光纤与光纤通信系统的波分、时分复用技术结合后,将为实现分布式光学传感环境问题提供巨大的潜力和机会。
Compared to traditional sensor device arrays, optical fiber systems capable of wide-range detection are gradually emerging as strong candidates for distributed monitoring owing to their simplified structure. However, the working mechanism of optical fiber sensors limits their use to the detection of physical parameters such as refractive index and is an obstacle for the detection of small doses of molecules by optical fiber systems. Several researchers have focused on this aspect to endow sensitivity to these optical fibers for gas or liquid molecules. By deliberately destroying the fiber structure, strong interactions between the evanescent field of optical fibers and the target materials, such as microfibers, D-shaped fiber, etc. can be achieved. Assisted by the surface plasmon resonance techniques, such configurations can exhibit highly enhanced sensitivity to a change in the refractive index caused by gas or liquid molecules. Two-dimensional materials are an excellent candidate as coating materials due to their high specific surface area, which also guarantees a large sensing response and simultaneously minimizes any side effects by suppressing the propagating mode of optical fibers. However, owing to the obstacles in optical fiber engineering and device fabrication, the abovementioned functional 2D sensors are still limited to sample-scale fabrication, and their mass-production has not yet been realized. An all-fiber distributed sensing system with high single-spot sensitivity is still difficult to fabricate. Here, we propose a new configuration of a grid-distributed environmental optical fiber sensing by introducing low-pressure chemical vapor deposition(LPCVD)-grown graphene photonic crystal fiber(PCF) into the optical fiber sensing system. We successfully synthesized monolayer and/or bilayer graphene in the air holes of PCF. By fusing the graphene PCF(Gr-PCF) to a single mode optical fiber, we fabricated an all-optical-fiber sensing system. Preliminary experiments suggest that Gr-PCF can selectively detect NO2 gas at ppb-level and exhibit ionic sensitivity in liquids. The ability to detect NO2 gas is attributed to the graphene layer’s interaction among light-mode and adsorbed molecules: adsorption-induced additional hole-doping caused a shift in the Fermi level of graphene and eventually modulated its light absorption, leading to changes in the light intensity signals. We believe that the sensor can be extended to other kinds of gases and liquids, considering the affinity of graphene toward various molecules. In view of practical optical sensors, our design is compatible with the time domain or wavelength domain multiplexing techniques of optical fiber communication systems. Because CVD-based synthesis can be used to realize mass production, the design proposed herein shall be one of the answers to the distributed optical fiber environmental sensors.
作者
尚念泽
程熠
敖申
姑力米热
李梦文
王晓愚
洪浩
李泽晖
张晓艳
符汪洋
刘开辉
刘忠范
Nianze Shang;Yi Cheng;Shen Ao;Gulimire Tuerdi;Mengwen Li;Xiaoyu Wang;Hao Hong;Zehui Li;Xiaoyan Zhang;Wangyang Fu;Kaihui Liu;Zhongfan Liu(State Key Laboratory for Mesoscopic Physics,Academy for Advanced Interdisciplinary Studies,Peking University,Beijing 100871,China;Beijing Graphene Institute(BGI),Beijing 100095,China;Center for Nanochemistry,College of Chemistry and Molecular Engineering,Peking University,Beijing 100871,China;School of Material Science and Engineering,Tsinghua University,Beijing 100084,China;Frontiers Science Center for Nano-optoelectronics,Collaborative Innovation Center of Quantum Matter,School of Physics,Peking University,Beijing 100871,China)
出处
《物理化学学报》
SCIE
CAS
CSCD
北大核心
2022年第12期236-242,共7页
Acta Physico-Chimica Sinica
基金
国家自然科学基金(52025023,51991342,52021006,11888101)
广东省重点研发计划(2020B010189001,2019B010931001,2018B030327001)
中国科学院战略重点研究计划(XDB33000000)
北京市自然科学基金(JQ19004)
广东省珠江人才招聘计划(2019ZT08C321)资助项目。