Spectroscopy Sensor Research Articles

Development of aptamer surface-enhanced Raman spectroscopy sensor based on Fe3O4@Pt and Au@Ag nanoparticles for the determination of acetamiprid.

As a common chlorinated nicotinic pesticide with high insecticidal activity, acetamiprid has been widely used for pest control. However, the irrational use of acetamiprid will pollute the environment and thus affect human health. Therefore, it is crucial to develop a simple, highly sensitive, and rapid method for acetamiprid residue detection. In this study, the capture probe (Fe3O4@Pt-Aptamer) was connected with the signal probe (Au@DTNB@Ag CS-cDNA) to form an assembly with multiple SERS-enhanced effects. Combined with magnetic separation technology, a SERS sensor with high sensitivity and stability was constructed to detect acetamiprid residue. Based on the optimal conditions, the SERS intensity measured at 1333cm-1 is in relation to the concentration of acetamiprid in the range 2.25 × 10-9-2.25 × 10-5M, and the calculated limit of detection (LOD) was 2.87 × 10-10M. There was no cross-reactivity with thiacloprid, clothianidin, nitenpyram, imidacloprid, and chlorpyrifos, indicating that this method has good sensitivity and specificity. Finally, the method was applied to the detection of acetamiprid in cucumber samples, and the average recoveries were 94.19-103.58%, with RSD < 2.32%. The sensor can be used to analysereal samples with fast detection speed, high sensitivity, and high selectivity.

Low-Cost Recognition of Plastic Waste Using Deep Learning and a Multi-Spectral Near-Infrared Sensor.

This work presents an approach for the recognition of plastics using a low-cost spectroscopy sensor module together with a set of machine learning methods. The sensor is a multi-spectral module capable of measuring 18 wavelengths from the visible to the near-infrared. Data processing and analysis are performed using a set of ten machine learning methods (Random Forest, Support Vector Machines, Multi-Layer Perceptron, Convolutional Neural Networks, Decision Trees, Logistic Regression, Naive Bayes, k-Nearest Neighbour, AdaBoost, Linear Discriminant Analysis). An experimental setup is designed for systematic data collection from six plastic types including PET, HDPE, PVC, LDPE, PP and PS household waste. The set of computational methods is implemented in a generalised pipeline for the validation of the proposed approach for the recognition of plastics. The results show that Convolutional Neural Networks and Multi-Layer Perceptron can recognise plastics with a mean accuracy of 72.50% and 70.25%, respectively, with the largest accuracy of 83.5% for PS plastic and the smallest accuracy of 66% for PET plastic. The results demonstrate that this low-cost near-infrared sensor with machine learning methods can recognise plastics effectively, making it an affordable and portable approach that contributes to the development of sustainable systems with potential for applications in other fields such as agriculture, e-waste recycling, healthcare and manufacturing.

Potential powered EC-SERS for sensitive detection of acetamiprid

Surface-enhanced Raman spectroscopy (SERS) is a powerful tool for rapid and sensitive detection of pesticide residues in food, and the applied potential regulated SERS technique can be endowed with a higher sensitivity. In this work, we developed an electrochemical-surface enhanced Raman spectroscopy (EC-SERS) sensor for the rapid detection of acetamiprid (AAP) in vegetables. AuNPs/ITO were prepared via in-situ electrodeposition of gold nanoparticles (AuNPs) on an indium tin oxide (ITO) both as a SERS substrate and working electrode. By adding AAP into an in-situ Raman electrolytic cell with an applied electrochemical potential (+0.3 V), the SERS intensity was enhanced by 4-fold and the characteristic signal was linearly related to the concentration of AAP. Under the optimal conditions, the EC-SERS method exhibited a linear detection range from 0.05 to 50 μM, with a limit of detection (LOD, 3S/M) of 0.02 μM. Simultaneously, based on density functional theory (DFT), the adsorption characteristics of AAP on AuNPs/ITO were studied in the presence of electric field. The method was finally confirmed by HPLC-MS for the detection of real samples, revealing its potential application in food safety.

Control of a dual-mode scramjet flow path utilizing optical emission spectroscopy

Shock train leading edge (STLE) location control within a Dual-Mode Scramjet (DMSJ) flow path was demonstrated using an optical emission spectroscopy (OES) sensor for control feedback. Emission from electronically excited chemical species, OH⁎ and C2⁎, was observed within the combustor and used for feedback to control the STLE within the DMSJ isolator. An optical emission sensor was used to experimentally demonstrate STLE control using a Proportional-Integral (PI) controller. Feedback using this sensor was compared the traditional approach of using wall pressure sensors. Utilizing an OES sensor for feedback proved to be an effective method to estimate and control the STLE location and provided a smoother response than when utilizing discrete wall-based pressure measurements that tended to discretize the estimated STLE location. Characteristic Model-Based All-Coefficient Adaptive Control (ACAC) was also implemented and compared to the PI controller response using the OES signal as feedback. Plant changes were introduced in the form of mass addition downstream of the combustor and a reduction of fuel valve response. Experiments showed that the ACAC and PI controllers behave similarly both during nominal operation and with plant changes, though the ACAC controller tended to command the fuel valve more efficiently. This paper presents the first experimental demonstration of closed-loop control of the STLE location within a scramjet flow path when using OES sensor feedback. This is also the first demonstration of adaptive control of STLE location utilizing OES sensor feedback.

Assessment of silver-based calcium silicate hydrate as a novel SERS sensor

This study aims at synthesizing a novel Surface-Enhanced Raman Spectroscopy (SERS) sensor based on a nanostructured substrate, calcium silicate hydrate (C-S-H), the main hydration product of Portland cement. The procedure involves first the incorporation of silver within the nanostructure of the gel (C-S-Ag-H) and second the modification of the surface of pellets of the newly synthesized material by laser irradiation at 532 nm or 355 nm. The assessment of the SERS activity revealed no amplification of the organic molecule rhodamine B (RdB) signal, used as a probe, on the C-S-Ag-H before laser irradiation. However, after laser irradiation, the SERS effect was comparable to that of reference colloidal Ag nanoparticles (NPs). This SERS response is attributed to an increase in the concentration of metallic silver on the surface of the C-S-Ag-H pellets upon laser irradiation and material ablation as revealed by X-ray Photoelectron Spectroscopy (XPS). Further enhancement of the SERS signals was induced by depositing colloidal Ag NPs on the irradiated pellets, giving rise to interparticle hot spots where the electromagnetic field is further intensified.

Emission Spectroscopy-Based Sensor System to Correlate the In-Cylinder Combustion Temperature of a Diesel Engine to NOx Emissions.

Due to a rising importance of the reduction of pollutant, produced by conventional energy technologies, the knowledge of pollutant forming processes during a combustion is of great interest. In this study the in-cylinder temperature, of a near series diesel engine, is examined with a minimal invasive emission spectroscopy sensor. The soot, nearly a black body radiator, emits light, which is spectrally detected and evaluated with a modified function of Planck's law. The results show a good correlation between the determined temperatures and the NOx concentration, measured in the exhaust gas of the engine, during a variety of engine operating points. A standard deviation between 25 K and 49 K was obtained for the in-cylinder temperature measurements.

Preparation of Flower-like Nanosilver Based on Bioderived Caffeic Acid for Raman Enhancement and Dye Degradation.

In this study, a simple, green, and low-cost room temperature synthesis of broccoli-like silver nanoflowers (AgNF) with a particle size of about 300-500 nm was developed using plant-derived caffeic acid as a reducing agent and polyvinylpyrrolidone as a dispersant under ultrasound assistance. The flower clusters covered by small nanocrystals of 20-50 nm significantly enhance the electromagnetic field signals. AgNF was deposited on the surface of silicon wafers as a surface-enhanced Raman spectroscopy sensor for the detection of probe molecules such as rhodamine 6G (R6G) and malachite green with high sensitivity, homogeneity, and reproducibility. AgNF was deposited on cotton fabrics in the form of composites to catalyze the degradation of dye pollutants such as R6G, MG, and methyl orange in the presence of sodium borohydride. 0.1 g of AgNF/cotton fabric could assist 15 mmol/L NaBH4 to achieve over 90% degradation of various dyes as well as a high concentration of dyes in 12 min with good reusability and recyclability. The AgNF synthesized in this work can not only monitor the type and amounts of pollutants (dyes) in wastewater but also catalyze the rapid degradation of dyes, which is expected to be valuable for industrial applications.

A continuous-wave spectroscopic singlet oxygen sensor for photodynamic therapy dosimetry: Preclinical studies in a murine model of actinic keratosis

SignificanceSinglet oxygen (1O2), a type of reactive oxygen species, destroys cancer cells during photodynamic therapy (PDT). Inter-patient variations in tissue oxygen levels, dose of photosensitizer (PS), and fluence of light can affect 1O2 generation and result in suboptimal treatment efficacy in the clinic. ApproachHere, we describe a high throughput spectrometer system based on computational spectroscopy for real-time measurement of PS levels and 1O2 luminescence during PDT. The dosimeter provides a direct real-time measurement of 1O2 production in continuous-wave mode. Data were obtained from in-vitro protoporphyrin IX (PpIX) phantoms, and from in-vivo studies in mice with actinic keratosis (AK, an early form of squamous cell carcinoma) using the dosimeter. ResultsData indicated a correlation between 1O2 levels and treatment outcome (lesion shrinkage/clearance). ConclusionsThis study provides additional evidence for a correlation between 1O2 generation and AK treatment response, suggesting that 1O2 dosimetry could have utility in the dermatology clinic.

Revolutionizing plasmonic platform via magnetic field-assisted confined ultrafast laser deposition of high-density, uniform, and ultrafine nanoparticle arrays

The remarkable capabilities of 2D plasmonic surfaces in controlling optical waves have garnered significant attention. However, the challenge of large-scale manufacturing of uniform, well-aligned, and tunable plasmonic surfaces has hindered their industrialization. To address this, we present a groundbreaking tunable plasmonic platform design achieved through magnetic field (MF) assisted ultrafast laser direct deposition in air. Through precise control of metal nanoparticles (NPs), with cobalt (Co) serving as the model material, employing an MF, and fine-tuning ultrafast laser parameters, we have effectively converted coarse and non-uniform NPs into densely packed, uniform, and ultrafine NPs (∼3 nm). This revolutionary advancement results in the creation of customizable plasmonic ‘hot spots,’ which play a pivotal role in surface-enhanced Raman spectroscopy (SERS) sensors. The profound impact of this designable plasmonic platform lies in its close association with plasmonic resonance and energy enhancement. When the plasmonic nanostructures resonate with incident light, they generate intense local electromagnetic fields, thus vastly increasing the Raman scattering signal. This enhancement leads to an outstanding 2–18 fold boost in SERS performance and unparalleled sensing sensitivity down to 10−10 M. Notably, the plasmonic platform also demonstrates robustness, retaining its sensing capability even after undergoing 50 cycles of rinsing and re-loading of chemicals. Moreover, this work adheres to green manufacturing standards, making it an efficient and environmentally friendly method for customizing plasmonic ‘hot spots’ in SERS devices. Our study not only achieves the formation of high-density, uniform, and ultrafine NP arrays on a tunable plasmonic platform but also showcases the profound relation between plasmonic resonance and energy enhancement. The outstanding results observed in SERS sensors further emphasize the immense potential of this technology for energy-related applications, including photocatalysis, photovoltaics, and clean water, propelling us closer to a sustainable and cleaner future.

Simultaneous SERS Sensing of Cysteine and Homocysteine in Blood Based on the CBT-Cys Click Reaction: Toward Precisive Diagnosis of Schizophrenia.

At present, there is a lack of sufficiently specific laboratory diagnostic indicators for schizophrenia. Serum homocysteine (Hcy) levels have been found to be related to schizophrenia. Cysteine (Cys) is a demethylation product in the metabolism of Hcy, and they always coexist with highly similar structures in vivo. There are few reports on the use of Cys as a diagnostic biomarker for schizophrenia in collaboration with Hcy, mainly because the rapid, economical, accurate, and high-throughput simultaneous detection of Cys and Hcy in serum is highly challenging. Herein, a click reaction-based surface-enhanced Raman spectroscopy (SERS) sensor was developed for simultaneous and selective detection of Cys and Hcy. Through the efficient and specific CBT-Cys click reaction between the probe containing cyan benzothiazole and Cys/Hcy, the tiny methylene difference between the molecular structures of Cys and Hcy was converted into the difference between the ring skeletons of the corresponding products that could be identified by plasmonic silver nanoparticle enhanced molecular fingerprint spectroscopy to realize discriminative detection. Furthermore, the SERS sensor was successfully applied to the detection in related patient serum samples, and it was found that the combined analysis of Cys and Hcy can improve the diagnostic accuracy of schizophrenia compared to a single indicator.

Second sensor to improve near-infrared spectroscopy flap monitor utility: A prospective study.

This study assesses whether use of continuous noninvasive near-infrared spectroscopy (NIRS) sensor on head and neck free flap (FF) with a second sensor on nonoperated tissue improves distinction between systemic hypoperfusion and FF compromise. Single-institution, prospective study of patients undergoing head and neck FF reconstruction from December 2018 to April 2020. FFs were continuously monitored using NIRS on a monitor paddle with a second (control) sensor on the shoulder. Crude StO2 and percent change in StO2 were compared between the FF and control sensors on each patient, and percent change and percent difference between the control and the monitor paddle were documented to assess for congruity. Sentinel events (e.g., hypotension and hematoma) were documented to assess the association with change in StO2. These events and timing of StO2 changes were noted to assess associations with change in StO2. A total of 48 patients had complete data. Donor sites included 35 soft-tissue FFs and 13 fibula FFs. Average StO2 was 73.7 ± 5.5 for FFs and 71.4 ± 5.0 for control sensors. There were seven sentinel events during the study. At the time of the events, StO2 dropped significantly more for the FF than the control sensor (FF = 52.2% drop; control = 6.2% drop; p = .016). NIRS signal denoted change prior to changes in implantable arterial Doppler in all cases. The addition of a second sensor when using NIRS as a primary modality for FF monitoring may improve distinction between FF compromise events and systemic hypoperfusion. By increasing accuracy of the monitor, there is a potential for decreased resident burden and decreased use of higher level of care nursing, which could reduce overall costs.

Freshness evaluation of grouper fillets by inexpensive e-Nose and spectroscopy sensors

Estimating the freshness of fish is a crucial aspect linked to its overall quality. In our research, a rapid freshness sensing system was designed for predicting the freshness of grouper (Epinephelus coioides) fillets throughout their storage period. This system incorporated ten gas sensors (assembled as e-nose) and 18-wavebands spectroscopy chip. Grouper fillet each was placed inside of the sensing device and stored at a temperature of 10 ± 2℃ for a duration of 72 h with sensor signal acquired hourly. In total 292 data points were collected. The true freshness of the grouper fillets represented by K value and total volatile basic nitrogen (T-VBN), was determined by HPLC and colorimetric method. Machine learning algorithms, including multiple linear regression (MLR), partial least squares regression (PLSR), and support vector regression (SVR), were employed to construct predictive models based on the data form both sensors and instrumental analysis. Among these models, MLR observed superior performance in predicting K value and T-VBN, achieving root mean square errors (RMSE) of 5.959 and 1.473, along with R2 of 0.914 and 0.932, respectively. The sensing system exhibited great predicting capabilities for assessing fish freshness.

Mid-infrared all-fiber light-induced thermoelastic spectroscopy sensor based on hollow-core anti-resonant fiber

In this article, a mid-infrared all-fiber light-induced thermoelastic spectroscopy (LITES) sensor based on a hollow-core anti-resonant fiber (HC-ARF) was reported for the first time. The HC-ARF was applied as a light transmission medium and gas chamber. The constructed all-fiber structure has merits of low loss, easy optical alignment, good system stability, reduced sensor size and cost. The mid-infrared transmission structure can be utilized to target the strongest gas absorption lines. The reversely-tapered SM1950 fiber and the HC-ARF were spatially butt-coupled with a V-shaped groove between the two fibers to facilitate gas entry. Carbon monoxide (CO) with an absorption line at 4291.50 cm−1 (2.33 µm) was chosen as the target gas to verify the sensing performance. The experimental results showed that the all-fiber LITES sensor based on HC-ARF had an excellent linear response to CO concentration. Allan deviation analysis indicated that the system had excellent long-term stability. A minimum detection limit (MDL) of 3.85 ppm can be obtained when the average time was 100 s

Two-component intra-cavity photoacoustic spectroscopy sensor using Y-shaped photoacoustic cell with two resonant cavities

In this paper, an intra-cavity photoacoustic spectroscopy (PAS) gas sensing system based on a 3D printed Y-shaped PAS cell with two longitudinal resonant cavities is designed for two-component detection. The sensor embeds the Y-shaped photoacoustic cell in the resonator of fiber ring laser for the intra-cavity gas detection, improving the laser power in the gas detection. The two resonant cavities of the Y-type PAS cell are formed into C-band and the L-band lasers, guaranteeing the laser stable output of C-band and the L-band. Comparing with the conventional dual-wavelength laser, the dual-wavelength laser scheme proposed in the paper eliminates the model competition and possesses much higher laser stability. A dedicated wavelength modulator is used to control the fiber bragger grating (FBG) to generate the stress change, and then scan the absorption peaks of the corresponding gases. The second harmonic (2f) PAS signal is used to calculate the gas concentration. The acetylene (C2H2) and carbon dioxide (CO2) were detected based on the frequency division multiplexing (FDM) technique using two resonant cavities. A microphone is used to simultaneously detect the photoacoustic signals of two resonance cavities. A demodulation frequency with a frequency intervals of 100 Hz ensures there is no cross-interference in demodulation of signals from each resonant cavity. The trace detection of C2H2 and CO2 was realized at normal temperature and pressure. The PAS signal intensity was further improved by optimizing the modulation amplitude and incident laser power. The minimum detection limits (MDLs) and the linear fit R-squared values (R2) of C2H2 and CO2 were 529 ppbv, 0.99971, 282 ppmv and 0.99991, respectively. It indicates that the two-component gas sensing system in this paper has good linearity and high sensitivity. It provides a valuable trace gas detection device for multi-component gas detection.

Realtime monitoring of thrombus formation in vivo using a self-reporting vascular access graft

BackgroundChronic kidney disease (CKD) affects 10% of the global population costing over a hundred billion dollars per annum and leading to increased risk of cardiovascular disease. Many patients with CKD require regular haemodialyses. Synthetic arteriovenous grafts (AVG) are increasingly used to provide rapid vascular connection for dialysis. Initially, they have excellent patency rates but are critically limited by neointimal hyperplasia at the venous anastomosis, which drives subsequent thrombosis, graft failure and death.MethodsHere, we describe a system in which electrical impedance spectroscopy sensors are incorporated circumferentially into the wall of a synthetic arteriovenous graft. This is combined with an implantable radiotelemetry system for data transmission outside the patient. The system was tested using monolayers of endothelial and smooth muscle cells as well as swine blood and clots with explanted human carotid artery plaques. Sensor testing was then performed in vitro and the device was implanted in vivo in female swine.ResultsThe device can wirelessly report the accumulation of biological material, both cells and blood. Differences are also detected when comparing controls with pathological atheroma. In swine differences between blockage formation in a graft were remotely obtained and wireless reported.ConclusionsCombining electrical impedance spectroscopy and an implantable radiotelemetry system enables graft surveillance. This has the potential to be used for early detection of venous stenosis and blood clot formation in real-time in vivo. In principle, the concept could apply to other cardiovascular diseases and vascular implantable devices.

Advanced Tuneable Micronanoplatforms for Sensitive and Selective Multiplexed Spectroscopic Sensing via Electro-Hydrodynamic Surface Molecular Lithography.

Micro- and nanopatterning of materials, one of the cornerstones of emerging technologies, has transformed research capabilities in lab-on-a-chip diagnostics. Herein, a micro- and nanolithographic method is developed, enabling structuring materials at the submicron scale, which can, in turn, accelerate the development of miniaturized platform technologies and biomedical sensors. Underpinning it is the advanced electro-hydrodynamic surface molecular lithography, via inducing interfacial instabilities produces micro- and nanostructured substrates, uniquely integrated with synthetic surface recognition. This approach enables the manufacture of design patterns with tuneable feature sizes, which are functionalized via synthetic nanochemistry for highly sensitive, selective, rapid molecular sensing. The development of a high-precision piezoelectric lithographic rig enables reproducible substrate fabrication with optimum signal enhancement optimized for functionalization with capture molecules on each micro- and nanostructured array. This facilitates spatial separation, which during the spectroscopic sensing, enables multiplexed measurement of target molecules, establishing the detection at minute concentrations. Subsequently, this nano-plasmonic lab-on-a-chip combined with the unconventional computational classification algorithm and surface enhanced Raman spectroscopy, aimed to address the challenges associated with timely point-of-care detection of disease-indicative biomarkers, is utilized in validation assay for multiplex detection of traumatic brain injury indicative glycan biomarkers, demonstrating straightforward and cost-effective micro- and nanoplatforms for accurate detection.

Synthesis and Characterization of Indium-Doped SnO2-Based Impedance Spectroscopy Sensor for Real-Time Humidity Sensing Applications

Metallic transition-metal dichalcogenides are emerging as promising electrode materials for applications such as 2D electronic devices owing to their good electrical conductivity. In this study, a high-performance humidity sensor based on NbTe2 electrode material and an indium-doped SnO2 thin film sensing layer was fabricated using a pulsed laser deposition system. The morphology, structural, elemental compositions, and electrical properties of the as-deposited samples were characterized. Additionally, the humidity sensing response of the fabricated sensor with In-doped SnO2 (8:92 wt%) sensing film was evaluated in a wide range of relative humidity at room temperature. The results demonstrated that the humidity sensor based on In-doped SnO2 exhibited a high sensitivity of 103.1 Ω/%RH, fast response and recovery times, a low hysteresis value, good linearity, and repeatability. In addition, the sensor had good long-term stability, with a variation in impedance of less than 3%. The results indicated that the humidity sensor could be suitable for practical humidity sensing applications.

Near-Infrared Off-Axis integrated cavity output spectroscopic sensor system for ammonia leakage measurement in cold store using embedded Multi-Core processor

A near-infrared off-axis integrated cavity output spectroscopic (OA-ICOS) sensor system for ammonia (NH3) leakage detection was developed. A distributed feedback (DFB) laser was used to target the absorption line of NH3 at 6612.167 cm−1. Experiments were conducted to evaluate the performance of the sensor system. When the averaging time is 0.8 s, the detection limit (1σ) of NH3 is ∼ 1.21 parts-per-million by volume (ppmv) using wavelength modulation spectroscopy (WMS). The 10–90 % response time of the NH3 sensor system is ∼ 7.2 s. Based on the developed local monitoring and control platform (LMCP), cloud server, remote monitoring and control end (RMCE), the unattended NH3 leakage detection experiments were carried out in a cold store located in Jilin City. The experimental results confirmed the rapid detection capability of the reported sensor system for NH3 leakage as well as the capability of remote monitoring and control.

Waveguide‐Based On‐Chip Photothermal Spectroscopy for Gas Sensing

AbstractOn‐chip waveguide spectroscopic sensors have attracted considerable attention due to its potential for large‐scale integration. However, existing waveguide gas sensors based on direct absorption spectroscopy (DAS) suffer from limited sensitivity and measurement range. Here waveguide‐based on‐chip photothermal spectroscopy (PTS) is demonstrated for gas detection with high sensitivity and large dynamic range. On‐chip photothermal field due to non‐radiation relaxation of gas molecules and the resulted photothermal phase modulation are analyzed. By selecting chalcogenide glass (ChG) as the core‐layer material and fabricating thermally‐isolated ChG‐on‐SU8 waveguide for thermal field accumulation, a twofold increase in photothermal phase modulation is achieved as compared to ChG‐on‐SiO2 waveguides. Different from the major concern of multi‐path etalon noise in DAS, piezoelectric transducer noise in the interferometer is identified as the main source in this PTS. For a fair comparison, acetylene (C2H2) detection experiments are conducted using PTS and DAS with a 2 cm‐long ChG‐on‐SU8 waveguide. A remarkable sensitivity of 4 parts‐per‐million (ppm) is achieved, which is 16 times better than that of DAS. The dynamic range extends over five orders of magnitude for PTS, ≈3 orders of magnitude larger than that of DAS. Such high performance opens the possibility of fully‐integrated chip‐level sensors for low‐power, light‐weight applications.

Molecularly imprinted polymer-based SERS sensing of transferrin in human serum.

Specific detection of glycoproteins such as transferrin (TRF) related to neurological diseases, hepatoma and other diseases always plays an important role in the field of disease diagnosis. We designed an antibody-free immunoassay sensing method based on molecularly imprinted polymers (MIPs) formed by the polymerization of multiple functional monomers for the sensitive and selective detection of TRF in human serum. In the sandwich surface-enhanced Raman spectroscopy (SERS) sensor, the TRF-oriented magnetic MIP nanoparticles (Fe3O4@SiO2-MIPs) served as capture units to specifically recognize TRF and 4-mercaptophenylboronic acid-functionalized gold nanorods (MPBA-Au NRs) served as SERS probes to label the targets. In order to achieve stronger interaction between the recognition cavities of the prepared MIPs and the different amino acid fragments that make up TRF, Fe3O4@SiO2-MIPs were obtained through polycondensation reactions between more silylating reagents, enhancing the specific recognition of the entire TRF protein and achieving high IF. This sensing method exhibited a good linear response to TRF within the TRF concentration range of 0.01 ng mL-1 to 1 mg mL-1 (R2 = 0.9974), and the LOD was 0.00407 ng mL-1 (S/N = 3). The good stability, reproducibility and specificity of the resulting MIP based SERS sensor were demonstrated. The determination of TRF in human serum confirmed the feasibility of the method in practical applications.