ACS Sensors最新文献

{"title":"γ-Graphyne as a Functional 2D Nanoarchitectonics for Room-Temperature Chemiresistive-Potentiometric Sensing Interfaces.","authors":"Utkarsh Kumar,Pei-Ying Wu,Chun-En Lin,Zu-Yin Deng,Ren-Jang Wu,Kuen-Lin Chen,Wen-Min Huang,Chiu-Hsien Wu","doi":"10.1021/acssensors.5c01507","DOIUrl":"https://doi.org/10.1021/acssensors.5c01507","url":null,"abstract":"The development of highly selective gas sensors operating at room temperature with detection capabilities in the parts-per-billion (ppb) range is one of fundamental and technological interest across diverse fields. Conventional sensor arrays often suffer from signal instability, large device footprints, and high fabrication costs. The emergence of two-dimensional (2D) materials has enabled new paradigms in chemiresistive sensing, leveraging their quantum confinement, high surface-to-volume ratio, and tunable electronic structure. In this study, we present, for the first time, a high-performance chemiresistive sensor based on chemically exfoliated γ-graphyne, a carbon allotrope with sp-sp2-hybridized bonding and an extended π-conjugated system. The material's cross-linked layered structure introduces spatially varying local potential gradients, which enhance charge carrier modulation upon gas molecule adsorption. First-principles density functional theory (DFT) calculations were employed to optimize the graphyne synthesis pathway and to model adsorption energies and charge transfer dynamics. Real-time detection of NO2 gas at room temperature demonstrates exceptional sensor performance, with a measured response of 1.05 at 25 ppb and an estimated detection limit as low as 0.45 ppb. The device exhibits rapid response (53 s) and recovery (185 s) times, governed by gas-adsorbate interactions and carrier scattering mechanisms. Theoretical models reveal that adsorption of NO2 induces significant modulation of the local density of states and carrier concentration in graphyne, enhancing its chemiresistive response. Furthermore, we integrated machine learning algorithms with the experimental sensor output to establish a robust gas classification framework. Classifiers trained on sensor data exhibit 100% accuracy across varying concentrations (15-100 ppb) of NO2 and high selectivity for other interfering gases, validating the discriminatory power of the sensor. This synergistic approach combining quantum mechanical modeling, charge transport physics, and data-driven learning algorithms opens new avenues for designing next-generation miniaturized gas sensors with ultrahigh sensitivity and selectivity.","PeriodicalId":24,"journal":{"name":"ACS Sensors","volume":"39 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145203477","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Synergistic Enhancement of NO2 Sensing via Pd-Sensitized Oxygen Vacancy Engineering in WO3 Nanoplates","authors":"Jiangbin Guo, Xiao Chang, Wenyang Zheng, Jun Zhang, Xianghong Liu","doi":"10.1021/acssensors.5c01952","DOIUrl":"https://doi.org/10.1021/acssensors.5c01952","url":null,"abstract":"The strategic integration of metal catalysts with atomic defects in functional materials offers a promising pathway to tailor desired properties. In this study, we demonstrate a high-performance NO₂ gas sensor utilizing Pd-sensitized, oxygen vacancy-rich WO₃ nanoplates. Pd nanoparticles were precisely deposited on WO₃ via atomic layer deposition (ALD), which not only enhanced the oxygen vacancy (O_v) concentration but also optimized the electronic structure of the material. The resulting Pd-WO₃-O_v sensor exhibited a significantly improved response of 84.57 to 10 ppm of NO₂─3.5 times higher than pristine WO₃. The synergistic interplay between Pd catalysts and oxygen vacancies was found to simultaneously lower the operating temperature and amplify both the sensitivity and response speed. Density functional theory (DFT) calculations further confirmed that oxygen vacancies facilitate robust Pd–WO₃ interactions, elucidating the mechanism behind the enhanced performance. This work provides a novel design strategy for developing advanced gas sensors through defect and catalyst engineering.","PeriodicalId":24,"journal":{"name":"ACS Sensors","volume":"214 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145203982","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Constructing S-Scheme Charge Migration in a Self-Assembled In2O3/WO3 Heterojunction for Photothermal-Driven Dual-Gas Detection","authors":"Jianyu Ling, Tao Zhang, Dongchang Li, Hongpeng Zhang, Yu Tong, Linhu Jin, Xiaoyu Ji, Kewei Zhang, Mingzhe Zhang","doi":"10.1021/acssensors.5c02363","DOIUrl":"https://doi.org/10.1021/acssensors.5c02363","url":null,"abstract":"Increased safe and environmental awareness in production processes necessitates an ever-growing demand for efficient detection of ethanol/n-butanol/diesel fuel blends (clean energy) in rapid, real time. However, the forces between multiplexed organic molecules in complex environments induce a decrease in the flash point, thus requiring sensors with high selectivity and low-temperature detection capabilities. In this study, an In₂O₃/WO₃ multilevel heterojunction is assembled by utilizing the electrostatic interaction between the hydroxyl group of In(OH)₃ and WS₂. The material achieves dual detection of ethanol and n-butanol under the excitation of light and temperature fields. It also possesses fast response/recovery times, excellent selectivity, and good long-term stability. The WO₃ has a defect-rich (002) exposed surface in the In₂O₃/WO₃ heterojunction, and the special electronic structure of the heterojunction induces carrier migration at the S-scheme heterointerface under photothermal activation, which promotes the generation of more reactive oxygen species (O₂^–, O^–) from the sensing material. The special chemical reaction of the sensor between oxygen anions and the target gas at room temperature (RT) and 120 °C is the basis for the realization of dual-selective detection of ethanol and n-butanol. The sensing mechanism of the WO₃/In₂O₃ heterojunction for ethanol/n-butanol has been systematically investigated based on energy band structure analysis and in situ Raman spectroscopic characterization. This work focuses on the potential of metal oxide-based S-scheme heterojunctions for high-performance gas sensor applications.","PeriodicalId":24,"journal":{"name":"ACS Sensors","volume":"25 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145203983","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Introducing Single Pd Atoms into a Two-Dimensional Metal–Organic Framework for Enhanced Benzene Vapor Detection","authors":"Zhiheng Ma, Panzhe Qiao, Xiaowu Wang, Xin Jia, Ou Wang, Jiaqiang Xu, Aihua Zhong","doi":"10.1021/acssensors.5c01398","DOIUrl":"https://doi.org/10.1021/acssensors.5c01398","url":null,"abstract":"We report the design and synthesis of a two-dimensional porphyrinic metal–organic framework (MOF), Al-TCPP-Pd, which incorporates atomically dispersed palladium sites for ultrasensitive benzene vapor detection. Compared with pristine Al-TCPP and Al-TCPP-Al analogs, Al-TCPP-Pd exhibits superior performance with an actual detection limit of 1 ppb (logic LOD is 0.48 ppb) and a response value that is four times higher than Al-TCPP at 1 ppm benzene concentration. This remarkable sensitivity is attributed to a synergistic mechanism involving geometric confinement within the MOF’s rectangular pores and π-electron channel enhancement induced by Pd coordination. The sensor also shows excellent selectivity against aromatic and nonaromatic interfering gases, strong resistance to humidity, and long-term operational stability over 180 days. Through <i>in situ</i> Raman, quasi-<i>in situ</i> XPS, and Grand Canonical Monte Carlo simulations, it is revealed that the superior detection performances are attributed to the increased adsorption energies and preferential benzene localization in Pd-activated pores. These results underscore the effectiveness of noble metal single-atom functionalization in enhancing MOF-based sensor performance and offer a modular framework for designing.","PeriodicalId":24,"journal":{"name":"ACS Sensors","volume":"8 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145203981","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Printable OECT for Simple Integration in Nitrocellulose-Based Assays.","authors":"Martina Cicolini,Ali Solgi,Lorenzo Vigna,Alberto Ballesio,Simone Marasso,Matteo Cocuzza,Hans Kleemann,Francesca Frascella,Lucia Napione","doi":"10.1021/acssensors.5c01893","DOIUrl":"https://doi.org/10.1021/acssensors.5c01893","url":null,"abstract":"Paper-based biosensors hold significant promise for point-of-care (POC) diagnostic applications. Among these, lateral flow assays (LFAs) are particularly appealing due to their ease of use, portability, and low cost. However, their limited sensitivity and qualitative output set drawbacks on their reliability and widespread application. In response to the growing need for rapid and consistent diagnostic and monitoring tools, Organic Electrochemical Transistors (OECTs) have emerged as powerful devices in biochemical sensing applications because of their high sensitivity, low operating voltage, and compatibility with a biological environment. In this work, we developed a printable OECT for biochemical sensing on a commercial cellulose membrane, commonly used as a detection substrate in LFA-based rapid tests. Constituting a self-standing, passive microfluidic platform, the system was designed to transport and interact with liquid samples, while ensuring a contamination-free zone for the active components. Inside a dry area delimited by a hydrophobic barrier, the OECT components include dispense-printed silver electrodes, a polystyrenesulfonate-doped poly(3,4-ethylenedioxy-thiophene) (PEDOT:PSS) channel and gate, and a solid-state electrolyte (SSE) layer. Outside the dry area, a PEDOT:PSS extended gate alone interacts with the analyte in the liquid sample, preventing channel contamination and enhancing the system stability. We investigated the effect of dopamine (DA) oxidation at the extended gate interface on the device response and observed variations in the transfer characteristics, transconductance and Ion/Ioff ratio, obtaining a limit of detection of 0.01 mM. With a maximum transconductance of approximately 4 mS, our system shows potential for the integration of an easy-to-fabricate device into an affordable biochemical assay, providing quantitative results at the point-of-care site to complement and reinforce the typical colorimetric response of LFAs.","PeriodicalId":24,"journal":{"name":"ACS Sensors","volume":"4 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2025-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145194911","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Aromatic Amino Acid Dipeptide-Mediated Bacterial Imprinted Electrochemiluminescence Sensor with Cytochrome-Accelerated Electron Transfer for Ultrasensitive Detection of Staphylococcus aureus.","authors":"Xin Wang,Qiuyu Ding,Xufeng Zang,Jinmei Zu,Bo Cui,Yishan Fang","doi":"10.1021/acssensors.5c01773","DOIUrl":"https://doi.org/10.1021/acssensors.5c01773","url":null,"abstract":"In this study, a novel biosensing platform based on aromatic amino acid dipeptide-boosted bacterial imprinted electrochemiluminescence technology was successfully constructed for the efficient detection of Staphylococcus aureus. The sensor employs copper/europium metal-organic frameworks (Cu/Eu-MOFs) as the ECL substrate, demonstrating excellent and stable luminescence. Notably, the aromatic dipeptide Cyclo(-Gly-Trp) was used as a functional monomer, primarily binding to cytochrome P450 in S. aureus membrane proteins via hydrophobic interactions. This interaction facilitates NADPH-dependent electron transfer, activating subsequent electron transport (ET) pathways and significantly accelerating charge transfer in this region. As well, comparative studies confirmed that the aromatic dipeptide substantially enhances electron transfer, leading to a stronger ECL signal than systems lacking aromatic amino acids. With good linearity in the range of 101-108 CFU/mL and a detection limit as low as 3.36 CFU/mL (S/N = 3), this sensor provides an innovative solution for rapid screening of food-contaminated microorganisms with the advantages of high specificity and ease of operation.","PeriodicalId":24,"journal":{"name":"ACS Sensors","volume":"38 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2025-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145194913","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Rapid Quantification of Virus-Like Particles via Gold Nanoparticle Sensors and Dark-Field Differential Dynamic Microscopy.","authors":"Sina Salimi,Pierre-Luc Latreille,Hu Zhang,Daria C Boffito,Jochen Arlt,Vincent A Martinez,Xavier Banquy","doi":"10.1021/acssensors.5c02121","DOIUrl":"https://doi.org/10.1021/acssensors.5c02121","url":null,"abstract":"We present a novel diagnostic platform using differential dynamic microscopy (DDM) to quantify viral load in salivary samples. This method leverages gold nanoparticle-based sensors that form heteroaggregates with virus-like particles (VLPs), designed to mimic viruses. The sensors were sequentially functionalized with biotin, streptavidin, and biotinylated angiotensin-converting enzyme 2, while VLPs were functionalized with streptavidin and the spike S1 receptor-binding domain of SARS-CoV-2 as the model virus. Viral load is quantified by tracking changes in the sensor nanoparticle dynamics during their interactions with VLPs. Initially optimized in buffer and subsequently adapted for salivary samples, the assay leverages dark-field DDM to remove possible interference from unbound VLPs. This approach enables the quantification of VLPs that were otherwise undetectable by dark-field DDM alone, by exploiting the slower diffusion of nanosensor-VLP heteroaggregates, achieving a detection limit of 9 × 103 VLPs/mL (20 pg/mL), within clinically relevant viral loads. The platform requires minimal sample preparation, a 5 min incubation, and no fluorescent labeling or washing steps. With only a conventional microscope and camera, this rapid assay provides quantitative results in 10-15 min. This proof-of-concept offers an accessible tool for rapid and precise viral load quantification in laboratory settings with potential for point-of-care applications through setup miniaturization. With its simplicity, speed, and sensitivity, this platform represents a promising advancement in infectious disease diagnostics.","PeriodicalId":24,"journal":{"name":"ACS Sensors","volume":"7 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2025-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145194930","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Machine Learning-Integrated Electrochemical Sensors for Accurate and Continuous Free Chlorine Monitoring.","authors":"Mayano Yamanouchi,Yasufumi Yokoshiki,Masakazu Dohi,Takashi Tokuda,Shinji Koh,Takeshi Watanabe","doi":"10.1021/acssensors.5c02634","DOIUrl":"https://doi.org/10.1021/acssensors.5c02634","url":null,"abstract":"Accurate and continuous monitoring of free chlorine concentrations is essential for ensuring water safety in applications such as drinking water disinfection and food sanitation. Traditional methods for free chlorine detection, including colorimetry and photometry, often involve complex sample preparation and lack real-time monitoring capabilities. Electrochemical sensors provide a promising alternative; however, their long-term accuracy is affected by pH variations, electrode surface conditions, and impurity accumulation. In this study, we developed a machine learning-integrated electrochemical sensor using a glassy carbon (GC) electrode to measure current-potential relationships for free chlorine detection. An automated measurement system was constructed to acquire large datasets across varying pH values and free chlorine concentrations, thereby enabling robust model training. The effects of electrode surface conditions were mitigated by integrating voltammogram data obtained from a chlorine-free background solution (base solution) alongside the target voltammogram data into the machine learning model. The trained model was cross-validated and further tested on real samples collected from a vegetable washing factory. The free chlorine concentrations, measured by an iodine photometric sensor, were used as reference values. The calibration system significantly enhanced the estimation accuracy across all test conditions. In real-sample evaluations, the machine learning model successfully estimated free chlorine levels, despite variations in the base solution parameters and the presence of impurities. These results demonstrate the feasibility of integrating machine learning with electrochemical sensing for accurate and continuous monitoring of free chlorine.","PeriodicalId":24,"journal":{"name":"ACS Sensors","volume":"31 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2025-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145189443","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Resilient MEMS Sensor Array-AI System for DGA-Based Transformer Fault Monitoring in High-H2 Environments.","authors":"Ze Zhang,Yining Zhang,Tengfei Li,Cheng Zhang,Zongchang Luo,Bofeng Luo,Bing Tian,Yulong Zhao,Hairong Wang","doi":"10.1021/acssensors.5c02569","DOIUrl":"https://doi.org/10.1021/acssensors.5c02569","url":null,"abstract":"MOS gas sensors offer significant potential for real-time dissolved gas analysis (DGA) in power transformer monitoring. However, their performance is often degraded in high-hydrogen (H2) environments due to cross-interference, which impairs detection accuracy and limits practical deployment. To overcome these challenges, we propose a co-optimized sensing framework that integrates a MEMS-based hybrid sensor array with a CNN-LSTM-AM deep learning model. The hybrid array combines Pd-Au and MOS sensors to exploit their complementary gas-response behaviors, enabling reliable hydrocarbon detection even under H2 saturation. On the algorithmic side, a 1D convolutional neural network (CNN) extracts subtle gas features from saturated MOS signals, while the LSTM-based attention mechanism (LSTM-AM) compensates for Pd-Au sensor drift by learning temporal dependencies. To further enhance robustness, a smooth-label training method is introduced to reduce prediction instability during abrupt concentration transitions. Experimental results demonstrate that our framework achieves a mean squared error (MSE) of 0.0020 on a custom datset (D1), outperforming the UCI-TGS benchmark by 87.3% (MSE: 0.0157). Moreover, the smooth-label strategy reduces prediction variance by 50% compared to conventional labeling. This integrated hardware-algorithm system not only improves Pd-Au sensor performance and reduces training loss by half but also provides an accurate and robust solution for real-time DGA, contributing to enhanced diagnostic reliability in smart grid applications.","PeriodicalId":24,"journal":{"name":"ACS Sensors","volume":"93 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2025-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145194901","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Plasmon-Induced Graphene/Silicon Schottky Junctions for Ultrasensitive Gas Sensing.","authors":"Katarzyna Drozdowska,Janusz Smulko,Tesfalem Welearegay,Lars Österlund,Sergey Rumyantsev","doi":"10.1021/acssensors.5c01920","DOIUrl":"https://doi.org/10.1021/acssensors.5c01920","url":null,"abstract":"Modulating metal oxide-based gas sensors with light is emerging as an alternative to enhance their sensitivity and selectivity. Plasmonic gas sensors based on excitation of the localized surface plasmon resonance (LSPR) in noble metals have recently shown promising properties. The classic approach of incorporating LSPR in sensors is to measure changes in the optical properties of the plasmonic material that depend on the surrounding local environment, i.e., an optical sensor device. The less common approach is to utilize chemiresistive sensors that consist of a gas-sensitive material (like graphene) decorated with plasmonic nanoparticles and employ solely electrical measurements for sensing data acquisition. This work demonstrates a chemiresistive gas sensor graphene/silicon Schottky junction decorated with palladium nanoparticles (PdNPs) that exhibit LSPR in the UV light range. We demonstrate a method of recording responses of plasmonic gas sensors based only on their DC characteristic measurements, which is simplified compared to optical and spectroscopic methods. Supported by the DC characteristics recorded under different UV wavelengths (255 nm, 275 nm, 355 nm), we show that the highest sensitivity to NO2 and NH3 is obtained for plasmonic resonant wavelength excitation of the PdNPs occurring at about 275 nm. The LSPR-modulated sensor response is nearly 14 times greater for NO2 gas compared to NH3 and exhibits a sensitivity toward NO2 gas with an ultralow detection limit of 4 ppb, thus showing that both the selectivity and sensitivity of plasmonic chemiresistive gas sensors can be significantly enhanced by LSPR-tuned light modulation.","PeriodicalId":24,"journal":{"name":"ACS Sensors","volume":"7 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2025-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145194912","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}