Microfluidic Transport of Hybrid Optoplasmonic Particles for Repeatable SERS Detection

Plasmonic cellulose microfilament assisted SERS detection in microfluidics

Limited by the narrow enhanced area of nanoscale on the metal surface, the sensitivity of surface-enhanced Raman spectroscopy (SERS) detection in solution is usually much lower than the detection in a solid substrate, which is dramatic in microfluidics for online detection. In this work, a cellulose microfilament embraced by Ag nanoparticles, called plasmonic cellulose microfilament, is located in a microchannel for SERS detection in microfluidics. Benefiting from the congestion caused by the plasmonic cellulose microfilament in a microchannel, the trace molecule in the solution is much easier to gather in Ag nanoparticles for Raman enhancement. To obtain high sensitivity, the structure of plasmonic cellulose microfilament is optimized. The SERS spectra collected in this novel microfluidics demonstrate that the plasmonic cellulose microfilament presents a high sensitivity at 10-13 M and good reproducibility in SERS detection. In addition, automatic identification of urea presence or absence was achieved based on deep learning (DL) here. The results show excellent diagnostic accuracy (99 %), which suggests that a fast, label-free urea screening tool can be developed. These results point out this SERS microfluidics with plasmonic cellulose microfilament has a great application prospective in online SERS detection with high sensitivity.

Microfluidics-aided fabrication of 3D micro-nano hierarchical SERS substrate for rapid detection of dual hepatocellular carcinoma biomarkers

The simultaneous analysis of trace amounts of dual biomarkers is crucial in the early diagnosis, treatment, and prognosis of hepatocellular carcinoma (HCC). In this study, we prepared SERS-active hydrogel microparticles (SAHMs) with 3D hierarchical gold nanoparticles (AuNPs) micro-nanostructures by microdroplet technology and in situ synthesis, which demonstrated high reproducibility and sensitivity. Compared with traditional 2D SERS substrates, this newly prepared 3D SERS substrate provided a high density of nano-wrinkled structures and numerous AuNPs. Furthermore, a newly designed SERS-active substrate was proposed for the simultaneous microfluidic detection of AFP and AFU. The Raman signals of sandwich immunocomplexes on the surface of the SAHMs were measured for the trace analysis of these biomarkers. The proposed microfluidic platform achieved AFP and AFU detection in the range of 0.1-100 ng mL-1 and 0.01-100 ng mL-1, respectively, which represents a good response. Indeed, this platform is easy to fabricate, of low cost and has short detection time and comparable detection limits to other methods. As far as we know, this is the first study to achieve the simultaneous detection of AFP and AFU on a microfluidic platform. Therefore, we proposed a new simultaneous detection platform for dual HCC biomarkers that shows strong potential for the early diagnosis of HCC.

SERS and machine learning based effective feature extraction for detection and identification of amphetamine analogs

Surface-enhanced Raman spectroscopy (SERS) is extensively researched in diverse disciplines due to its sensitivity and non-destructive nature. It is particularly considered a potential and promising technology for rapid on-site screening in drug detection. In this investigation, a technique was developed for fabricating nanocrystals of Ag@Au SNCs. Ag@Au SNCs, as the basic material of SERS, can detect amphetamine at concentrations as low as 1 μg/mL. The Ag@Au SNCs exhibits a strong surface plasmon resonance effect, which amplifies molecular signals. The SERS spectra of ten substances, including amphetamine and its analogs, showed a strong peak signal. To establish a qualitative distinction, we examined the Raman spectra and conducted density functional theory (DFT) calculations on the ten aforementioned species. The DFT calculation enabled us to determine the vibrational frequency and assign normal modes, thereby facilitating the qualitative differentiation of amphetamines and its analogs. Furthermore, the SERS spectrum of the ten mentioned substances was analysed using the support vector machine learning algorithm, which yielded a discrimination accuracy of 98.0 %.

Phase Change Materials Meet Microfluidic Encapsulation

Improving the utilization of thermal energy is crucial in the world nowadays due to the high levels of energy consumption. One way to achieve this is to use phase change materials (PCMs) as thermal energy storage media, which can be used to regulate temperature or provide heating/cooling in various applications. However, PCMs have limitations like low thermal conductivity, leakage, and corrosion. To overcome these challenges, PCMs are encapsulated into microencapsulated phase change materials (MEPCMs) capsules/fibers. This encapsulation prevents PCMs from leakage and corrosion issues, and the microcapsules/fibers act as conduits for heat transfer, enabling efficient exchange between the PCM and its surroundings. Microfluidics-based MEPCMs have attracted intensive attention over the past decade due to the exquisite control over flow conditions and size of microcapsules. This review paper aims to provide an overview of the state-of-art progress in microfluidics-based encapsulation of PCMs. The principle and method of preparing MEPCM capsules/fibers using microfluidic technology are elaborated, followed by the analysis of their thermal and microstructure characteristics. Meanwhile, the applications of MEPCM in the fields of building energy conservation, textiles, military aviation, solar energy utilization, and bioengineering are summarized. Finally, the perspectives on MEPCM capsules/fibers are discussed.

Self-Adhesive, Biocompatible, Wearable Microfluidics with Erasable Liquid Metal Plasmonic Hotspots for Glucose Detection in Sweat

Sweat is a noninvasive metabolite that can provide clinically meaningful information about physical conditions without harming the body. Glucose, a vital component in sweat, is closely related to blood glucose levels, and changes in its concentration can reflect the health status of diabetics. We introduce a self-adhesive, wearable microfluidic chip with erasable liquid metal plasmonic hotspots for the precise detection of glucose concentration in sweat. The self-adhesive, wearable microfluidic chip is made from modified polydimethylsiloxane (PDMS) with enhanced stickiness, enabling conformal contact with the skin, and can collect, deliver, and store sweat. The plasmonic hotspots are located inside the microfluidic channel, are generated by synthesizing silver nanostructures on liquid metal, and can be removed in the alkaline solution. It indicates the erasable and reproducible nature of the plasmonic hotspots. The detection method is based on surface-enhanced Raman spectroscopy (SERS), which allows for accurate detection of the glucose concentration. To enhance the sensitive detection of glucose, the SERS substrate is modified by 4-mercaptophenylboronic acid to achieve the limit of detection of 1 ng/L glucose, which is much lower than the physiological conditions (7.2-25.2 μg/L). The developed microfluidic chip is soft, stretchable, and nontoxic, bringing new possibilities to wearable sweat-sensing devices.

Ultrasensitive discrimination of volatile organic compounds using a microfluidic silicon SERS artificial intelligence chip

Current gaseous sensors hardly discriminate trace volatile organic compounds at the ppt level. Herein, we present an integrated platform for simultaneously enabling rapid preconcentration, reliable surface-enhanced Raman scattering, (SERS) detection and automatic identification of trace aldehydes at the ppt level. For rapid preconcentration, we demonstrate that the nozzle-like microfluidic concentrator allows the enrichment of rare gaseous analytes by five-fold in only 0.01 ms. The enriched gas is subsequently captured and detected by an integrated silicon-based SERS chip, which is made of zeolitic imidazolate framework-8 coated silver nanoparticles grown in situ on a silicon wafer. After SERS measurement, a fully connected deep neural network is built to extract faint features in the spectral dataset and discriminate volatile organic compound classes. We demonstrate that six kinds of gaseous aldehydes at 100 ppt could be detected and classified with an identification accuracy of ∼80.9% by using this platform.

SERS Monitored Kinetic Process of Gaseous Thiophenol Compound in Plasmonic MOF Nanoparticles

Benefiting from the electromagnetic enhancement of noble metal nanoparticles (NPs) and the capture ability of organic frameworks, plasmonic metal-organic framework (MOF) structures have greatly promoted the development of gas detection by surface-enhanced Raman spectroscopy (SERS). In those detections, the kinetic process of gaseous molecules in plasmonic-MOF structures has a great influence on SERS spectra, which is still lacking intensive investigation in previous reports. In this work, the kinetic processes of gaseous thiophenol compounds (TPC) in the plasmonic Zeolitic Imidazolate Framework (Ag@ZIF) core-shell NPs are studied by SERS spectra. The experimental data demonstrate that the SERS intensities of gaseous TPC could be enhanced once more in an H₂ mixed gas environment with different functional groups of TPC. Further results reveal that the two-step enhancement of SERS intensities is not only related to the thicknesses of the MOF shell but also affected by the ambient mixed gas. To understand this novel phenomenon, the binding energy between the gaseous molecule and ZIF is calculated based on first-principles computation. In combination with the plasmonic properties of the Ag core, a molecular collision model is introduced here to show the distribution of gaseous TPC molecules in ZIF, which could be responsible for this interesting two-step enhancement of SERS intensities. Furthermore, the H₂ assisted kinetic process of gaseous p-aminothiophenol (PATP) is also analyzed by the classical pseudo-first-order kinetic model, which is consistent with our experimental SERS data. Our work not only reveals the novel phenomenon of plasmonic-MOF structures to improve the gas detection by SERS spectra but also enriches the understanding of the microcosmic process of gaseous molecules in the mixed gas environment to optimize MOF structures for gas capture and storage.

Fabrication of optoplasmonic particles through electroless deposition and the application in SERS-based screening of nodule-involved lung cancer

In this work, a core-satellite optoplasmonic particle containing a silica microsphere covered with gold nanoparticles (AuNPs) was developed through wet chemistry synthesis in aqueous phase. The electroless deposition and galvanic replacement were employed to anchor AuNPs onto silica sphere surface. The escalated as well as expanded electric field enhancement within the dielectric-metallic interface was analyzed through finite difference time domain (FDTD) simulation. The numerical models and the surface-enhancement Raman spectroscopy (SERS) measurements over blood serum both support that the equatorial plane is the preferred collecting plane for improved signal intensity and stability. The nanocomposite emerged lower relative standard deviation (RSD) in repetitive measurement compared to AuNPs. In practice, this hybrid structure was applied for lung cancer diagnosis based on serum SERS spectra analysis of the patients diagnosed with nodules. The prediction with the aid of principal component analysis (PCA) and support-vector machine (SVM) was attempted for the classification of healthy, benign and relatively malignant sample groups. The accuracy of distinguish benign samples from malignant ones reaches over 90%. These advantages make the structure a promising SERS substrate for the early screening of cancer based on the non-invasive biological samples.

Mxenes–Au NP Hybrid Plasmonic 2D Microplates in Microfluidics for SERS Detection

Combined with microfluidics, surface-enhanced Raman spectroscopy (SERS) exhibits huge application prospective in sensitive online detection. In current studies, the design and optimization of plasmonic enhanced structures in microfluidics for SERS detection could be an interesting challenge. In this work, hybrid plasmonic 2D microplates composed of Mxenes (Ti3C2Tx) microplates and in-situ synthesized Au nanoparticles (Au NPs) are fabricated in a microchannel for enhanced structures in SERS microfluidics. Benefiting from the 2D Mxenes microplates with complex distributions, the enhanced areas generated by Au NPs are quite enlarged in a microchannel, which exhibits high sensitivity in SERS detection at 10−10 M for Nile blue (NB) molecules in microfluidics. The mechanism of electromagnetic enhancement (EM) and chemical enhancement (CM) is analyzed. The experimental data indicate the ultrasonic times of Mxenes and the concentration of Au3+ play important roles in the sensitivity of SERS detection, which is confirmed by the simulated electric field distributions. Furthermore, a typical pesticide (thiram) at 100 ppm in water is detected on these SERS microfluidics with hybrid plasmonic enhanced structures, which demonstrates that our work not only strengthens the knowledge of plasmonics but also enlarges the application of SERS.