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基于表面增强拉曼光谱技术对不同产地酱香型白酒的鉴别研究 认领 引用 被引量：2
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作者 向玲 贾俊杰 +7 位作者 毛雪婷 刘晓彤 牛曼思 屠婷瑶 吴美霞 佘远斌 王松涛 沈才洪 《分析测试学报》 CAS CSCD 北大核心 2026年第1期77-87,共11页
该研究采用表面增强拉曼散射(SERS)技术结合感官品评手段,对61款酱香型白酒进行系统分析。通过主成分分析(PCA)和正交偏最小二乘法-判别分析(OPLS-DA),构建了基于SERS的酱香型白酒产地与品质鉴别模型。实验结果表明,61款酱香型白酒的SER... 该研究采用表面增强拉曼散射(SERS)技术结合感官品评手段,对61款酱香型白酒进行系统分析。通过主成分分析(PCA)和正交偏最小二乘法-判别分析(OPLS-DA),构建了基于SERS的酱香型白酒产地与品质鉴别模型。实验结果表明,61款酱香型白酒的SERS谱图在主要特征峰上表现出高度一致性,主要包括880、1 050、1 100、1 270、1 450 cm-1等乙醇特征峰。SERS谱图结合PCA和OPLS-DA模型,能够有效区分不同产地及等级的酱香型白酒,2 100、1 750、1 100 cm-1附近位置是区分不同产地和品质酱香型白酒的主要拉曼特征峰。感官品评结果进一步揭示苦味、涩味、麻味、辣味是区分不同产地酱香型白酒的关键口感属性。对比分析表明,SERS技术结合OPLS-DA模型在区分不同产地和等级酱香型白酒方面表现出优于传统感官品评的鉴别能力。该方法为酱香型白酒产地溯源和品质鉴别提供了新的技术路径,具有重要的潜在应用价值。 展开更多
关键词 酱香型白酒 表面增强拉曼光谱 化学计量学 感官品评 鉴别模型 产地
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基于拉曼光谱“先筛后养”策略在功能微生物资源挖掘中的应用 认领 引用 被引量：1
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作者 刘佳 任义尚 +1 位作者 许拉 荆晓艳 《生物技术通报》 EI CAS CSCD 北大核心 2026年第5期63-75,共13页
随着微生物研究的深入,传统的“先养后筛”策略在应对复杂环境样本和挖掘功能微生物时暴露出显著的局限性。以肠道和自然环境样本为例,由于99%以上的原核生物无法在实验室条件下培养,大量具有重要功能的微生物尚未被发现和研究。针对这... 随着微生物研究的深入,传统的“先养后筛”策略在应对复杂环境样本和挖掘功能微生物时暴露出显著的局限性。以肠道和自然环境样本为例,由于99%以上的原核生物无法在实验室条件下培养,大量具有重要功能的微生物尚未被发现和研究。针对这一挑战,提出了基于单细胞拉曼光谱(SCRS)结合重水(D2O)代谢标记的“先筛后养”策略。该策略采用原位无标记的单细胞拉曼光谱分析,可快速筛选出具有特定代谢活性的微生物细胞,随后对这些细胞进行精准培养与鉴定。通过SCRS检测细胞对D2O的同化速率,可高效筛选具备特定功能(如溶磷、降解污染物等)的微生物个体。本文综述了该策略的关键技术及应用实例,并详细分析其在微生物功能挖掘方面的优势,指出该策略在提高筛选通量、灵敏度和活性保持率等方面具有显著潜力。同时,探讨了自动化、AI辅助识别、多组学融合以及基因组驱动培养基设计等发展趋势。最后,展望了该策略在微生物资源库构建、耐药性监测等领域的应用前景。旨在为微生物功能筛选与高通量分选技术提供系统性参考,以推动单细胞拉曼技术在微生物学研究与应用中的广泛应用。 展开更多
关键词 单细胞拉曼光谱 拉曼激活细胞分选 单细胞高通量分选 单细胞培养 重水代谢标记 “先筛后养”策略 功能筛选 微生物资源
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不同变质程度煤分子结构表征的拉曼光谱分峰拟合方法研究 认领 引用
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作者 李焕同 谢兴杰 +3 位作者 张谦 胡家兴 邹晓艳 李雨阳 《岩矿测试》 CAS CSCD 北大核心 2026年第2期458-474,共17页
针对煤分子结构解析的需求,拉曼光谱作为一种快速无损的碳材料表征技术,因其对碳结构有序度的高敏感性被广泛应用于表征煤分子结构。通过拉曼光谱分峰拟合优化,揭示煤分子结构演化规律,支撑低碳利用与标准体系构建。然而由于对煤结构的... 针对煤分子结构解析的需求,拉曼光谱作为一种快速无损的碳材料表征技术,因其对碳结构有序度的高敏感性被广泛应用于表征煤分子结构。通过拉曼光谱分峰拟合优化,揭示煤分子结构演化规律,支撑低碳利用与标准体系构建。然而由于对煤结构的理解存在差异,不同研究中采用的拟合峰数和函数差异显著,影响了拉曼光谱数据在煤分子结构表征中的可比性和可靠性。本文旨在探究不同拟合方式对煤的拉曼光谱相关特征峰的拟合效果。基于拟合优度(R2)及前人对煤结构特征的认知,确定了最优拟合峰数和函数,并系统比较了高斯(Gaussian)、洛伦兹(Lorentzian)、高斯-洛伦兹混合(Gaussian-Lorentzian)、福格特(Voigtian)和皮尔逊Ⅶ(PearsonⅦ)函数的拟合性能,对样品拉曼光谱的一级模(1000~1800 cm-1)进行拟合。结果表明:Gaussian、Lorentzian和Voigtian函数均能获得对称峰与非对称峰的较高拟合优度(R2>0.9964),在拟合对称峰时,Gaussian函数优于Lorentzian函数;而在拟合非对称峰时,Lorentzian函数表现更优。此外,不同变质程度样品的最优拟合方法存在显著差异,煤系石墨的拉曼光谱一级模拟合三个峰(D1、G、D2),高煤阶煤拟合四个峰(D4、D1、D3、G),两者采用Gaussian-Lorentzian或Voigtian函数可获得最优拟合(R2>0.9979);高灰煤拟合四个峰(D4、D1、D3、G),采用PearsonⅦ函数拟合效果最佳(R2>0.9983);热解煤焦拟合十个峰(低于900℃),采用Voigtian和Gaussian-Lorentzian函数的拟合效果最优(R2>0.9967)。本研究评估了拟合函数类型与拟合峰数对煤拉曼光谱特征峰的拟合优度。拟合函数的选择依赖于峰型对称性,煤结构的复杂度决定最优拟合策略,为煤拉曼光谱的定量分峰拟合提供了解决方案。 展开更多
关键词 拉曼光谱 分峰拟合优化 函数类型 非对称峰 不同变质程度煤 高灰煤 热解煤焦
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内标校准与多变量建模的煤气多组分拉曼检测 认领 引用
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作者 郭松杰 李俊楷 +6 位作者 邱选兵 田亚莉 张其生 东占萃 李伟 宋黎明 李传亮 《光学精密工程》 EI CAS CSCD 北大核心 2026年第12期1817-1829,共13页
针对转炉、焦炉等复杂工况下煤气多组分(H2,CO,CH4等)在线检测中,拉曼光谱信号易受气压波动、激光功率漂移及光路传输效率变化等多源干扰影响,导致浓度反演精度下降的问题,本文提出一种基于内标校准与多变量联合建模的煤气多组分... 针对转炉、焦炉等复杂工况下煤气多组分(H2,CO,CH4等)在线检测中,拉曼光谱信号易受气压波动、激光功率漂移及光路传输效率变化等多源干扰影响,导致浓度反演精度下降的问题,本文提出一种基于内标校准与多变量联合建模的煤气多组分拉曼光谱分析方法。首先,以煤气中普遍存在且化学性质稳定的CO2作为内标参考组分,构建内标比Ri以消除系统增益的共模干扰;其次,定义系统增益校准算子Sfactor,实现对气压、散射光强等系统状态变量的实时表征;最后,将内标比、气压、散射光强及系统增益校准算子等参数共同作为输入特征,采用LightGBM算法建立多变量非线性回归模型,对H2,CO,CH4三种组分浓度进行高精度反演。实验结果表明,所提出的多变量联合模型对H2,CO,CH4的均方根误差(RMSE)均低于0.09%,平均绝对百分比误差(MAPE)均低于0.6%,与仅采用原始光谱数据或单一内标比的模型相比,RMSE整体降幅约为37%~63%。该方法有效补偿了气压与散射光强变化带来的非线性干扰,显著提升了复杂工况下煤气多组分拉曼光谱的浓度反演精度,为工业煤气在线检测提供了可行方案。 展开更多
关键词 拉曼光谱 煤气 内标 多变量联合建模 机器学习
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Timeshare surface-enhanced Raman scattering platform with sensitive and quantitative mode 认领 引用
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作者 Qianqian Ding Xueyan Chen +4 位作者 Yunlu Jia Hong Liu Xiaochen Zhang Ningtao Cheng Shikuan Yang 《Opto-Electronic Advances》 SCIE EI CAS CSCD 2026年第1期65-74,共10页
The sensitivity and quantification capability of surface-enhanced Raman scattering(SERS)substrates are mutually exclusive,because the ultrasensitive SERS sites(hottest spots)necessary for the sensitivity will signific... The sensitivity and quantification capability of surface-enhanced Raman scattering(SERS)substrates are mutually exclusive,because the ultrasensitive SERS sites(hottest spots)necessary for the sensitivity will significantly magnify the SERS signals of the analyte molecules and thus each of these molecules will be miscounted to be hundreds during the quantification process.We demonstrate a concept to circumvent the above contradiction by engineering a timeshare SERS platform capable of working at the quantitative or the sensitive mode on demand.The timeshare SERS platform was constructed by transferring a monolayer gold nanosphere film onto elastic substrates(e.g.,hydrogel).The volume change of the hydrogel could adjust the inter-nanosphere distance,dynamically controlling the formation or extinction of the SERS hottest spots on the same SERS substrate without influencing the spatial distribution of the analyte molecules.The timeshare SERS platform without the SERS hottest spots showed strong quantification capability,while when equipped with a substantial number of the SERS hottest spots exhibited ultrahigh sensitivity.We demonstrated quantitative and ultrasensitive detection of various analyte molecules using the quantitative and the sensitive mode of the timeshare SERS platform,respectively.We opened an avenue towards designing SERS substrates with both high sensitivity and strong quantification capability. 展开更多
关键词 timeshare SERS platform sensing quantification hydrogel gold nanosphere
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Deep Learning-Driven Surface-Enhanced Raman Scattering-Lateral Flow Immunoassay With Au Nanostars for High-Accuracy Respiratory Virus Detection 认领 引用
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作者 Shuai Zhao Yan-Yan Li +7 位作者 Cheng-Long Lin Mei-Mei Xu Wei-Da Zhang Dan Li Yu-Si Peng Masaki Tanemura Tian-Shuo Zhao Yong Yang 《Rare Metals》 SCIE EI CAS CSCD 2026年第2期492-505,共14页
The high accuracy in surface-enhanced Raman scattering-lateral flow immunoassays(SERS-LFIAs)is critical for reliable pointof-care testing(POCT)in clinical diagnostics.Conventional approaches are often affected by samp... The high accuracy in surface-enhanced Raman scattering-lateral flow immunoassays(SERS-LFIAs)is critical for reliable pointof-care testing(POCT)in clinical diagnostics.Conventional approaches are often affected by sampling variability and uneven distribution of immunoprobes,leading to unreliable signal fluctuations.To address this challenge,we developed a highperformance SERS-LFIA strip based on gold nanostars(Au NSs)and integrated it with an artificial intelligence(AI)-powered diagnostic framework.Specifically,Au NSs with exceptional SERS enhancement were synthesized via an optimized“twostep”method and utilized as nanoprobes to construct an influenza B(FluB)SERS-LFIA strip for performance validation.A novel large-area Raman scanning technique was then employed to generate intensity maps depicting the immunoprobe distribution around the test(T)line.A deep residual neural network(ResNet-18)was subsequently applied to analyze these SERS images,minimizing subjective interpretation and significantly improving accuracy.The optimized framework achieved 100%training accuracy and 95%validation accuracy,significantly outperforming conventional peak intensity analysis and support vector machine(SVM)-based full-spectrum discrimination methods.The Au NSs-based SERS-LFIA platform and the optimized ResNet-18 model were integrated into a portable Raman spectrometer to create an automated diagnostic system.To further evaluate the stability and versatility of the system,the detection target was switched to influenza A(FluA)by altering the capture and detection antibodies.This reengineered system demonstrated a 95%accuracy rate in testing 40 simulated human clinical samples.Our work establishes a machine learning-enhanced,automated SERS-LFIA system that leverages Au NSs for superior signal enhancement and utilizes deep learning for robust image analysis.This integrated approach provides a scalable and high-performance POCT framework,paving the way for automated clinical diagnostics. 展开更多
关键词 automated diagnosis system deep learning gold nanostars ResNet-18 SERS-LFIA
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SERS传感器在粮食真菌毒素检测中应用的研究进展 认领 引用
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作者 尹丽梅 田秀梅 +4 位作者 马立鑫 郭志明 邹小波 GONG Yunyun 蔡健荣 《食品工业科技》 EI CAS 北大核心 2026年第6期485-495,共11页
粮食中真菌毒素的污染普遍存在,且常表现为多种真菌毒素的混合污染。基于表面增强拉曼光谱(Surfaceenhanced Raman Spectroscopy,SERS)技术的传感方法已被广泛应用于真菌毒素的检测研究。本文首先系统性地综述了基于溶液反应体系的SERS... 粮食中真菌毒素的污染普遍存在,且常表现为多种真菌毒素的混合污染。基于表面增强拉曼光谱(Surfaceenhanced Raman Spectroscopy,SERS)技术的传感方法已被广泛应用于真菌毒素的检测研究。本文首先系统性地综述了基于溶液反应体系的SERS传感器在单一真菌毒素和多种真菌毒素检测中的研究和应用进展,指出纳米间隙构建、磁性探针富集、内标校正及酶循环放大策略是实现SERS传感器检测性能提升的有效途径。其次,详细阐述了基于免疫层析试纸的SERS传感器在真菌毒素快速检测研究中的进展,并分别阐释了双金属纳米材料、磁性复合纳米材料及三维膜状纳米材料在多重检测、抗基质干扰及信号稳定性方面的技术优势和最新进展。最后指出了制备拉曼信号强、性能稳定、重复性良好、成本低廉的SERS增强基底和降低样本基质干扰是解决SERS传感器实用性的技术关键,明确了SERS传感器标准化、智能化及多场景集成应用的发展趋势,为真菌毒素SERS传感器的研发和应用提供借鉴和参考。 展开更多
关键词 真菌毒素 表面增强拉曼光谱(SERS) 免疫传感器 适配体传感器 侧向流免疫分析
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拉曼光谱的荧光抑制方法及其在皮肤和化妆品分析中的应用 认领 引用
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作者 陈云霞 王佳荣 +5 位作者 朱建宇 林诗雯 刘雅楠 马晓悦 席广成 刘娟 《生物化学与生物物理进展》 SCIE CAS CSCD 北大核心 2026年第7期1914-1926,共13页
在皮肤与化妆品研究领域,拉曼光谱凭借无损、快速、分子特异性强、受水分干扰较小等优势,已广泛应用于皮肤屏障功能评估、经皮吸收、化妆品真伪鉴定与质量控制等方面。然而,皮肤内源性发色团(如结构蛋白、代谢辅酶、黑色素)与化妆品外... 在皮肤与化妆品研究领域,拉曼光谱凭借无损、快速、分子特异性强、受水分干扰较小等优势,已广泛应用于皮肤屏障功能评估、经皮吸收、化妆品真伪鉴定与质量控制等方面。然而,皮肤内源性发色团(如结构蛋白、代谢辅酶、黑色素)与化妆品外源性组分(如着色剂、化学防晒剂、香精)在激光激发下常产生远强于拉曼信号的荧光背景,严重制约了该技术的应用与推广。近年来,随着光电技术和人工智能算法的快速发展,荧光抑制技术已从单一手段发展为样品处理(光漂白、表面增强拉曼光谱)、信号采集(长波长激发法、共聚焦拉曼光谱技术、移频激发差分拉曼光谱法)与数据处理(多项式拟合、惩罚最小二乘、小波变换等)3个层面协同的多层级策略。本文系统梳理了2类荧光干扰的来源与机理,并分别评述了3类主要抑制方法或技术的原理、优势与局限。在此基础上,本文聚焦皮肤屏障功能评估、经皮吸收、化妆品质量控制及便携化检测等典型应用场景,探讨了目前荧光抑制方法的选择与应用现状,并展望了未来发展方向。 展开更多
关键词 拉曼光谱 荧光抑制 皮肤 化妆品
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Characterization of main strains of ARC inoculant via machine learning-assisted single-cell Raman spectroscopy 认领 引用
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作者 Jie Kang Feng Wei +7 位作者 Xi Shen Ao Liu Jingjing Dou Shujie Zhang Jinli Hu Liangxiao Zhang Qi Zhang Peiwu Li 《Oil Crop Science》 CAS CSCD 2026年第2期113-116,共4页
ARC inoculant(A,aflatoxin prevention and control;R,Rhizobia nodulation induction;C,Coupling)is a brandnew inoculant with coupling function that enhances legume quality and nitrogen fixation.Comprehensive characterizat... ARC inoculant(A,aflatoxin prevention and control;R,Rhizobia nodulation induction;C,Coupling)is a brandnew inoculant with coupling function that enhances legume quality and nitrogen fixation.Comprehensive characterization of its key functional strains is critical for establishing a quality-control framework for the inoculant's formulation.Here,we constructed a characteristic spectral dataset comprising over 63,000 single-cell Raman spectra of the constituent strains by employing Ramanome technology.Six machine learning-based predictive models were developed and compared for the constituent strains,while the Linear Discriminant Analysis(LDA)model demonstrated the best performance,with a classification accuracy exceeding 92.4%.This work provides a unique spectral fingerprint for ARC inoculant and will directly aid its application in sustainable agricultural production. 展开更多
关键词 Symbiotic nitrogen fixation Legume ARC inoculant Single-cell Raman spectra Machine learning models Quality-control framework
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A Novel Raman Spectrometer using Bessel-like Laser Beam for Homogeneous Phases and Interface Detections 认领 引用
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作者 Ning Chen Yuhui Li +3 位作者 Tianle Zhang Jin Yang Xiaoguo Zhou Shilin Liu 《Chinese Journal of Chemical Physics》 SCIE EI CAS CSCD 2026年第3期318-327,I0004-I0006,共10页
Bessel beams,often referred to as“nondiffractive”light,have been successfully applied in numerous fields.In this study,we integrated a Bessel beam as the illumination source into a Raman spectrometer to enhance the ... Bessel beams,often referred to as“nondiffractive”light,have been successfully applied in numerous fields.In this study,we integrated a Bessel beam as the illumination source into a Raman spectrometer to enhance the detection of homogeneous phases and interfaces.By simulating optical path systems,we optimized the setup to fully utilize the multi-pixel array and maximize detection sensitivity.Compared to a conventional Gaussian-beam Raman spectrometer in the 90°-scattered configuration,the upgraded Raman spectrometer employing a Bessel-like beam demonstrated a nearly 6-fold improvement in sensitivity.Additionally,it significantly suppressed background scattering interferences in the low-frequency range,thus enhancing the clarity and accuracy of spectral data.Furthermore,the capability of this spectrometer for real-space Raman imaging of heterogeneous phase interfaces was verified.This advancement not only improves the sensitivity and precision of Raman measurements but also expands the potential applications of Raman spectroscopy in studying complex systems,such as interfaces and phase boundaries,with high spatial and spectral resolution. 展开更多
关键词 Raman spectroscopy Raman imaging Interface Bessel beam Gaussian beam
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基于一维卷积神经网络-长短期记忆网络(1DCNN-LSTM)协同模型驱动的中红外-拉曼融合光谱鉴别石菖蒲/水菖蒲 认领 引用
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作者 刘英慧 丁盈 +4 位作者 李林岚 陈玉秀 方磊 蒋跃平 刘海涛 《中国无机分析化学》 CAS 北大核心 2026年第2期281-291,共11页
针对近缘中药饮片因形态相似导致的鉴别难题,本文以石菖蒲与水菖蒲为研究对象,提出了一种基于一维卷积神经网络-长短期记忆网络(1DCNN-LSTM)融合模型的中红外(ATR模式)-拉曼光谱鉴别技术。通过标准正态变量变换(SNV)和Savitzky-Golay(SG... 针对近缘中药饮片因形态相似导致的鉴别难题,本文以石菖蒲与水菖蒲为研究对象,提出了一种基于一维卷积神经网络-长短期记忆网络(1DCNN-LSTM)融合模型的中红外(ATR模式)-拉曼光谱鉴别技术。通过标准正态变量变换(SNV)和Savitzky-Golay(SG)平滑进行光谱预处理,并将中红外与拉曼原始光谱直接串联以构建高维融合数据,在此基础上建立了包含传统机器学习(SVM)、单一深度学习模型(1DCNN、LSTM)以及本研究提出的数据级融合(亦称早期融合)+1DCNN-LSTM模型的对比体系,以系统评估融合策略的有效性。结果显示,数据级融合结合1DCNN-LSTM模型取得了卓越的鉴别性能,测试集准确率达96.2%,显著优于其他对照模型。本研究证实:直接利用原始光谱的完整信息进行端到端深度学习,能够有效捕捉近缘中药的细微差异;中红外-拉曼的光谱信息互补性与1DCNN-LSTM“局部特征提取+长程依赖捕捉”的协同优势,为解决近缘易混淆中药的鉴别问题提供了一种简洁、高效且具有良好可迁移性的方法框架,符合中药质量控制精准化与标准化的需求。 展开更多
关键词 石菖蒲 水菖蒲(藏菖蒲) 中红外光谱 拉曼光谱 1DCNN-LSTM 多光谱融合 近缘中药鉴别
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基于深度学习目标检测-显微拉曼光谱法的微塑料自动检测 认领 引用
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作者 梁维新 宋玉梅 +2 位作者 廖振伟 雷永乾 郭鹏然 《分析测试学报》 CAS CSCD 北大核心 2026年第7期1581-1588,共8页
开发了一种基于深度学习目标检测—显微拉曼光谱的微塑料自动检测方法。该方法将微塑料截留于金属滤膜上,通过目标检测模型识别捕捉疑似微塑料,经坐标转换后自动进行拉曼定性分析。结果表明:实验训练的基于YOLOv8n的微塑料目标检测模型... 开发了一种基于深度学习目标检测—显微拉曼光谱的微塑料自动检测方法。该方法将微塑料截留于金属滤膜上,通过目标检测模型识别捕捉疑似微塑料,经坐标转换后自动进行拉曼定性分析。结果表明:实验训练的基于YOLOv8n的微塑料目标检测模型的精确率、召回率、mAP@0.5均在90%以上,mAP@0.5∶0.95达74%,具有良好目标定位和识别能力;建立的基于优化权重命中质量指数(HQI)算法的微塑料拉曼图谱识别模型对7种微塑料的分类准确率为100%;通过微塑料目标检测模型和拉曼图谱识别模型的联用可实现微塑料自动检测,该方法的尺寸检出限为100μm,对实际水体中微塑料的加标回收率大于90%,相对标准偏差(RSD)在10%以内,显示了良好的准确度和精密度。该方法可应用于水中微塑料的快速、自动、准确检测。 展开更多
关键词 微塑料自动检测 YOLOv8 深度学习目标检测模型 拉曼图谱识别模型
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磁性纳米材料Fe3O4/SiO2/Ag的合成及SERS检测氯霉素 认领 引用
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作者 吴睿 王玉琳 +3 位作者 刘存芳 熊海涛 张晟瑞 杜全超 《贵金属》 CAS 北大核心 2026年第1期37-43,共7页
氯霉素(CAP)是一种广谱抗生素,过量使用氯霉素会影响人体健康和生态环境。本文通过共沉淀法合成磁性的Fe3O4纳米颗粒,在其表面负载二氧化硅(SiO2),形成Fe3O4/SiO2。并以硅烷偶联剂(KH-550)为桥梁,将纳米银负载在Fe_(3... 氯霉素(CAP)是一种广谱抗生素,过量使用氯霉素会影响人体健康和生态环境。本文通过共沉淀法合成磁性的Fe3O4纳米颗粒,在其表面负载二氧化硅(SiO2),形成Fe3O4/SiO2。并以硅烷偶联剂(KH-550)为桥梁,将纳米银负载在Fe3O4/SiO2上,形成Fe3O4/SiO2/Ag复合纳米材料。采用X射线粉末衍射(XRD)、红外光谱(IR)法、紫外-可见吸收光谱(UV-Vis)法等技术对该材料进行表征。将制备的Fe3O4/SiO2/Ag磁性复合纳米材料作为表面增强拉曼光谱(SERS)基底,用于对氯霉素的分析检测。结果显示:在1.0×10-10~1.0×10-3mol/L浓度范围内呈现良好的线性关系,标准曲线方程为I=48199-4386 lgc,相关系数R2=0.9758。检出限为0.6×10-11 mol/L,RSD=7.2%。本方法用于对水中氯霉素的检测,表明其具有一定的应用潜力。对SERS增强机理,包括电磁场增强和电荷转移增强,进行了探究。 展开更多
关键词 磁性材料 银纳米粒子 表面增强拉曼光谱 氯霉素 检测
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Progress in Surface-Enhanced Raman Scattering-Based Volatile Organic Compounds Detection:Materials,Application,and Prospects 认领 引用
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作者 Yuening Wang Lin Qiu +9 位作者 Jian Yu Wen Ma Xiaoyu Song Mingjian Zhang Yujiao Xie Aochi Liu Li Sun Xiangyu Meng Jie Lin Xiaotian Wang 《Rare Metals》 SCIE EI CAS CSCD 2026年第3期14-35,共22页
The detection of volatile organic compounds(VOCs)holds significant implications in environmental monitoring and disease diagnosis.Traditional gas detection technologies are constrained by complex operation and high co... The detection of volatile organic compounds(VOCs)holds significant implications in environmental monitoring and disease diagnosis.Traditional gas detection technologies are constrained by complex operation and high cost,thereby failing to satisfy real-time detection demands.Surface-enhanced Raman scattering(SERS)provides a noble approach for trace VOCs detection,as it possesses single-molecule sensitivity,rapid response,and the ability to analyze chemical structures without being affected by water molecules.Researchers have successfully achieved precise identification of trace VOCs through the meticulous design of SERS substrates,demonstrating excellent application potential in practical detection.This review comprehensively summarizes the research progress and application of SERS technology in VOCs detection,covering the structural design of SERS substrates and the transformation of actual gas detection methods.Specifically,three core substrate structures include noble metal nanostructures,porous semiconductor composite nanostructures,and noble metal-semiconductor composite porous nanostructures that combine the advantages of both were delved into deeply.Furthermore,it also provides a detailed account of the technological innovations in VOCs detection based on SERS technology,expanding the application scope of SERS technology.Nevertheless,the SERS technology still faces significant challenges in VOC gas detection,including nonspecific adsorption in complex matrices,insufficient long-term substrate stability,the need to simultaneously identify multiple components in a mixed gas,etc.This review summarizes the current challenges in detail and looks forward to future research directions and development prospects. 展开更多
关键词 noble metal noble metal-semiconductor semiconductor SERS VOCs
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Multi-point scanning Raman spectroscopy analysis of evolution of carbon structure and inherent minerals of metallurgical coke during heating process 认领 引用
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作者 Ya-Qi Gao Chong Zou +2 位作者 Yuan She Zheng-Yan Huang Jia-Yao Qin 《Journal of Iron and Steel Research International》 SCIE EI CSCD 2026年第6期380-396,共17页
The complexity of the internal environment of a blast furnace has limited the exploration of the microscopic reaction mechanisms of metallurgical coke.Some of the traditional detection methods often focus on average v... The complexity of the internal environment of a blast furnace has limited the exploration of the microscopic reaction mechanisms of metallurgical coke.Some of the traditional detection methods often focus on average value,neglecting the structural heterogeneity of coke.The changes of coke in a CO2 atmosphere at temperatures ranging from 1000 to 1500℃ were investigated using multi-point micro-Raman spectroscopy.The results indicate that,with the increasing temperature,the defect-related parameters of two tested samples decreased by 63.8%and 39.2%,respectively.The interlayer spacing of graphite and the thickness of microcrystalline stacking demonstrate a linear correlation with the Raman defect index,thus offering a precise approach for monitoring the graphitization process.Surface scanning micro-Raman spectroscopy indicated that minerals experienced dynamic migration,which was characterized by an“increase-decrease-increase”pattern.Moreover,in comparison with single-point detection,the quantity of surface scanning sampling increased.Simultaneously,the variance rose from 0.097 to 0.499,which reflects the authenticity of the samples.Finally,the changes of carbon structure and inherent mineral content and distribution are visually revealed by mapping method.This method effectively provides a high-resolution microstructural scale for the quality evaluation of blast furnace coke. 展开更多
关键词 Blast furnace Micro-Raman spectroscopy Coke Mineral Mapping
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基于拉曼光谱表征防晒化妆品微观结构稳定性的研究 认领 引用
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作者 谢宇 何国山 +4 位作者 区耀彬 谭建华 谢嘉颖 吕歆玥 席绍峰 《分析测试学报》 CAS CSCD 北大核心 2026年第1期190-196,共7页
基于显微拉曼光谱技术,建立了一种快速、实时、直接表征防晒化妆品中成分分布的方法。采用DXR3xi显微拉曼光谱仪,以显微镜直接观察样品微观形态,评价样品的均匀性;对样品中存在的较大聚集物或明显结晶体进行拉曼光谱定点扫描,结合仪器... 基于显微拉曼光谱技术,建立了一种快速、实时、直接表征防晒化妆品中成分分布的方法。采用DXR3xi显微拉曼光谱仪,以显微镜直接观察样品微观形态,评价样品的均匀性;对样品中存在的较大聚集物或明显结晶体进行拉曼光谱定点扫描,结合仪器内置拉曼谱库以及自建16种常见防晒剂的标准谱库进行成分匹配剖析;同时,通过对样品进行区域拉曼扫描,并对已知特定成分(如防晒剂、表面活性剂等)的特征光谱进行区域相关性分析,可准确表征这些特定成分在样品中的分布情况,以全面评价样品微观结构的稳定性。此方法已成功运用于膏霜乳类防晒化妆品的稳定性评价,并剖析了苯基苯并咪唑磺酸、鲸蜡醇磷酸酯钾等晶体析出,为防晒化妆品的稳定性研究提供了方法参考。 展开更多
关键词 拉曼光谱 防晒化妆品 结晶 面扫描
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Spectroelectrochemical Measurement Method of In Situ Surface-Enhanced Raman Spectroscopy for Various Electrode Materials Using a Transmission-Type Plasmonic Sensor 认领 引用
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作者 Masahiro Kunimoto Hikaru Shoji +3 位作者 Masahiro Yanagisawa Masayuki Morita Takeshi Abe Takayuki Homma 《Energy & Environmental Materials》 SCIE EI CAS CSCD 2026年第1期368-374,共7页
A versatile spectroelectrochemical measurement method of surface-enhanced Raman scattering spectroscopy is developed,and its capability is assessed in an actual electrochemical system.The spectroelectrochemical cell c... A versatile spectroelectrochemical measurement method of surface-enhanced Raman scattering spectroscopy is developed,and its capability is assessed in an actual electrochemical system.The spectroelectrochemical cell consists of a plasmonic sensor with metal nanoparticles and a wire-type working electrode.The advantages of this method over conventional surface-enhanced Raman scattering methods are as follows:1)surface-enhanced Raman scattering for electrode materials that show little plasmon resonance;and 2)measurement without undesirable influences on the physical and chemical states of the electrode surface and transport phenomena of reaction species.During the measurement,the sensor contacts the working electrode wire at a single point,allowing the surface-enhanced Raman scattering signal to be obtained from the interfacial area of the working electrode surface without significantly disturbing the mass transfer of the reaction species.As plasmon-active metal nanoparticles are modified on the sensor surface in advance,destructive and complicated pretreatment processes on the working electrode are not required.The method is applied to the in situ analysis of electrolyte decomposition reactions in a Li metal battery to reveal the potential of each decomposition product of an organic solvent containing Li.The obtained surface-enhanced Raman scattering spectrum corresponding to the voltammogram reveals the pathway for obtaining decomposition products,such as Li2CO3.In particular,Li2O2was clearly detected with our setup.It is also revealed from the setup that the Ni electrode surface,in contrast to the Cu,does not hold a stable Li-containing composite layer.Such in situ chemical information will contribute to the effective interfacial design of high-performance batteries. 展开更多
关键词 in situ analysis Li ion battery plasmonic sensor surface enhanced Raman scattering
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TMO-based SERS:Dual enhancement mechanisms and multi-functional analytical applications 认领 引用
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作者 Xiaoyu Song Lei Xu +5 位作者 Xiangyu Meng Yuening Wang Mingjian Zhang Aochi Liu Jie Lin Xiaotian Wang 《Chinese Journal of Structural Chemistry》 SCIE CAS CSCD 2026年第2期152-166,共15页
Surface-enhanced Raman scattering(SERS)spectroscopy based on transition metal oxide(TMO)substrates has emerged as a frontier research area,offering distinctive advantages in chemical stability,cost-effectiveness,and t... Surface-enhanced Raman scattering(SERS)spectroscopy based on transition metal oxide(TMO)substrates has emerged as a frontier research area,offering distinctive advantages in chemical stability,cost-effectiveness,and tunable optoelectronic properties compared to conventional noble metal substrates.This review systematically clarifies the dual enhancement mechanisms of TMO-based SERS including charge transfer(CT)resonance at the molecule-semiconductor interface and electromagnetic field amplification induced by localized surface plasmon resonance(LSPR);the two work synergistically to achieve signal amplification.In practical applications,TMO enable multi-scenario analysis via the controllable defect engineering-interfacial CT synergistic mechanism in SERS technology.These scenarios include ultrasensitive detection of biomarkers,dynamic tracking of cellular metabolism,real-time monitoring of environmental pollutants,and mechanistic analysis of catalytic reaction pathways.Nevertheless,critical challenges persist,particularly regarding quantitative reproducibility and long-term stability under operational conditions.This review focuses on discussing the SERS enhancement mecha-nisms of TMO,summarizing their diverse analytical applications across multiple fields,and briefly addressing existing limitations,aiming to provide insights for further advancement in TMO-based SERS research. 展开更多
关键词 Transition metal oxides Surface-enhanced Raman scattering Enhancement mechanisms Defect engineering Analytical applications
Synthesis of reusable and portable SERS sandpaper based on liquid-liquid interface self-assembly method for stable and ultrasensitive detection of S-fenvalerate in foods 认领 引用
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作者 Yingfang Zhang Chen Chen +4 位作者 Xinyue Wang Xuguang Qiao Ximo Wang Geoffrey I.N.Waterhouse Zhixiang Xu 《Food Science and Human Wellness》 SCIE CAS CSCD 2026年第1期327-334,共8页
Herein,a reusable and portable surface-enhanced Raman spectroscopy(SERS)sandpaper was successfully synthesized for the sensitive detection of S-fenvalerate in foods.Commercial sandpapers were decorated with Ag@SiO2@Au... Herein,a reusable and portable surface-enhanced Raman spectroscopy(SERS)sandpaper was successfully synthesized for the sensitive detection of S-fenvalerate in foods.Commercial sandpapers were decorated with Ag@SiO2@Au nanoarrays via a liquid-liquid interface self-assembly method.The capacity of sandpaper to float directly on the cyclohexane-water interface allows nanoarrays to be formed directly on it,thereby minimizing stacking issues typically associated with nanoarray assemblies and significantly enhancing the sensitivity of S-fenvalerate detection.Moreover,the SERS sandpaper was reusable and portable due to its strong adhesion of the nanoarrays.Under optimized testing conditions,the developed SERS sandpaper method was capable of detecting S-fenvalerate,demonstrating a strong linear response within a concentration range of 10–7–103μmol/L,with a limit of detection of 1.92×10−8μmol/L.The analysis of spiked food samples containing S-fenvalerate using the developed SERS sandpaper afforded excellent recoveries(92.2%−109.7%).Additionally,the SERS sandpaper was successfully applied to quantify S-fenvalerate in real food samples,with results consistent with analyses conducted using gas chromatography. 展开更多
关键词 Surface-enhanced Raman spectroscopy Liquid-liquid interface self-assembly Reusable and portable SERS sandpaper S-Fenvalerate detection
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散射光中的隐秘指纹——拉曼光谱 认领 引用
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作者 王京 祁雪 +3 位作者 李琰 温志慧 冯占恒 邱晓航 《大学化学》 CAS 2026年第4期280-288,共9页
拉曼散射是散射光中的“异能者”,它能够精准地反映出物质内部的结构信息,就宛如物质专属的“身份指纹”,隐秘在茫茫的光影信号中,悄然揭开微观世界的神秘面纱。拉曼光谱检测凭借自身的高超本领,在日常生活的大舞台上大放异彩,在食品药... 拉曼散射是散射光中的“异能者”,它能够精准地反映出物质内部的结构信息,就宛如物质专属的“身份指纹”,隐秘在茫茫的光影信号中,悄然揭开微观世界的神秘面纱。拉曼光谱检测凭借自身的高超本领,在日常生活的大舞台上大放异彩,在食品药品成分检测、考古探秘、文物修复、刑侦破案、环境污染监测等工作中都留下了它的“身影”。为促进公众科学认知,本研究设计了四个典型实验模块:塑料材质检测、珠宝玉器鉴定、危险液体安检以及光谱仪自组装实践。通过选取生活中常见的样品和具有代表性的应用场景,直观地阐释拉曼散射现象与物质结构特征的关联性,旨在搭建专业科技与公众认知之间的桥梁,推动光谱分析技术的科普化进程。 展开更多
关键词 拉曼 散射光 塑料 玉石 液体安检 自组建拉曼光谱仪
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