Spectroscopy Signals Research Articles

Deep neural network: As the novel pipelines in multiple preprocessing for Raman spectroscopy

Raman spectroscopy is a kind of vibrational method that can rapidly and non-invasively gives chemical structural information with the Raman spectrometer. Despite its technical advantages, in practical application scenarios, Raman spectroscopy often suffers from interference, such as noises and baseline drifts, resulting in the inability to acquire high-quality Raman spectroscopy signals, which brings challenges to subsequent spectral analysis. The commonly applied spectral preprocessing methods, such as Savitzky–Golay smooth and wavelet transform, can only perform corresponding single-item processing and require manual intervention to carry out a series of tedious trial parameters. Especially, each scheme can only be used for a specific data set. In recent years, the development of deep neural networks has provided new solutions for intelligent preprocessing of spectral data. In this paper, we first creatively started from the basic mechanism of spectral signal generation and constructed a mathematical model of the Raman spectral signal. By counting the noise parameters of the real system, we generated a simulation dataset close to the output of the real system, which alleviated the dependence on data during deep learning training. Due to the powerful nonlinear fitting ability of the neural network, fully connected network model is constructed to complete the baseline estimation task simply and quickly. Then building the Unet model can effectively achieve spectral denoising, and combining it with baseline estimation can realize intelligent joint processing. Through the simulation dataset experiment, it is proved that compared with the classic method, the method proposed in this paper has obvious advantages, which can effectively improve the signal quality and further ensure the accuracy of the peak intensity. At the same time, when the proposed method is applied to the actual system, it also achieves excellent performance compared with the common method, which indirectly indicates the effectiveness of the Raman signal simulation model. The research presented in this paper offers a variety of efficient pipelines for the intelligent processing of Raman spectroscopy, which can adapt to the requirements of different tasks while providing a new idea for enhancing the quality of Raman spectroscopy signals.

Ratiometric SERS aptasensing for simultaneous quantitative detection of histamine and tyramine in fishes

Herein, a SiO2@Ag NPs core/shell nanoparticles were synthesized to fabricate a surface-enhanced Raman spectroscopy (SERS) sensor for the simultaneous determination of histamine (HIS) and tyramine (TYR) based on specific aptamer recognition and ratiometric strategy. SiO2@Ag NPs with 4-thiosaminophenol (4-ATP) and Nile blue A (NBA) molecules were used as an internal standard (IS) and labeled with aptamers corresponding to HIS and TYR, respectively. Raman reporter molecules ROX and Cy5 labeled complementary DNA (cDNA) were then hybridized with aptamers to form rigid double-stranded DNA. After the HIS and TYR were captured by their aptamers, resulting in the dissociation of cDNA and separated from the SERS substrate. Therefore, the SERS signal intensity at 1503 cm−1 of ROX and 1358 cm−1 of Cy5 tagged on the terminal of cDNA decreased with the concentration of HIS and TYR increasing, while the SERS signal intensity at 1079 cm−1 of 4-APT and 592 cm−1 of NBA on the substrate remain stable. Thus, the concentrations of HIS and TYR can be determined by the I1503/I1079 and I1358/I592 values, respectively. This sensing strategy achieves a lower detection limit of 0.2 ng/mL for HIS and 0.05 ng/mL for TYR, respectively, demonstrating promising applications in sensitive detection of BAs in animal-derived foodstuff.

Calibration of Raman spectroscopy signals for measurements of methane-air tubular flames

Calibration of Raman spectroscopy signals for measurements of methane-air tubular flames

Drying Acoustically Levitated Droplets as Signal-Amplifying Platforms for Ultrasensitive and Multimode Laser Sensing.

Ultrasensitive sensing to trace atomic and molecular analytes has gained interest for its intimate relation to industrial sectors and human lives. One of the keys to ultrasensitive sensing for many analytical techniques lies in enriching trace analytes onto well-designed substrates. However, the coffee ring effect, nonuniform distribution of analytes onto substrates, in the droplet drying process hinders the ultrasensitive and stable sensing onto the substrates. Here, we propose a substrate-free strategy to suppress the coffee ring effect, enrich analytes, and self-assemble a signal-amplifying (SA) platform for multimode laser sensing. The strategy involves acoustically levitating and drying a droplet, mixed with analytes and core-shell Au@SiO2 nanoparticles, to self-assemble an SA platform. The SA platform with a plasmonic nanostructure can dramatically enrich analytes, enabling enormous spectroscopic signal amplification. Specifically, the SA platform can promote atomic detection (cadmium and chromium) to the 10-3 mg/L level by nanoparticle-enhanced laser-induced breakdown spectroscopy and can promote molecule detection (rhodamine 6G) to the 10-11 mol/L level by surface-enhanced Raman scattering. All in all, the SA platform, self-assembled by acoustic levitation, can intrinsically suppress the coffee ring effect and enrich trace analytes, enabling ultrasensitive multimode laser sensing.

Optofluidic Accumulation of Silica Beads on Gel-Based Three-Dimensional SERS Substrate To Enhance Sensitivity Using Multiple Photonic Nanojets.

This paper presents a gel-based three-dimensional (3D) substrate for surface-enhanced Raman spectroscopy (SERS) mediated by photonic nanojets (PNJs) to enhance the sensitivity of SERS detection. The porous structure of the gel-based substrate allowed small molecules to diffuse into the substrate, while the placement of silica beads on the substrate surface resulted in the generation of photonic nanojets during SERS measurements. Because the gel-based SERS substrate had electromagnetic (EM) hot spots along the Z-direction for several tens of microns, the focuses of the PNJs, which were located a few microns away from the substrate surface, could excite the EM hot spots located within the substrate. Our objective was to maximize SERS signal intensity by coating the substrate with a close-packed array of silica beads to enable the generation of multiple PNJs. The bead array was formed using an optical fiber decorated with gold nanorods (AuNRs) to create a temperature gradient in a mixture containing silica beads, thereby enabling their arrangement and deposition in arbitrary locations across the substrate. In experiments, the Raman enhancement provided by multiple PNJs significantly exceeded that provided by single PNJs. The proposed PNJ-mediated SERS method reduced the limit of detection for malachite green by 100 times, compared to SERS results obtained using the same substrate without beads. The proposed enhancement scheme using a gel-based 3D SERS substrate with a close-packed array of silica beads could be utilized to achieve high-sensitivity SERS detection for a variety of molecules in a diverse range of applications.

Electrochemical Surface-Enhanced Raman Spectroscopy for Aniline Adsorbed on Silver Electrodes: A DFT Study of the Anharmonic Effects of Amino Wagging Vibrational Modes

Aniline molecules exhibit a special amino wagging vibrational mode on the surface of the silver electrode. The corresponding Raman peak not only displays enhanced Raman signals in surface-enhanced Raman spectroscopy (SERS) experiments but also shows a shift toward higher wavenumbers. This work adopts a molecule-metal cluster model to investigate the normal Raman spectra of aniline molecules and their SERS spectra adsorbed on silver electrode surfaces by density functional theory (DFT) approaches. Based on the harmonic approximation, the influence of anharmonic effects on the normal Raman and SERS spectra of aniline is further considered. Our calculated results of the anharmonic Raman spectra of free aniline molecules show that their anharmonic effect mainly comes from the amino wagging vibrational mode. Then, the anharmonic Raman spectra of aniline binding to neutral and positively charged silver clusters were calculated and compared with the harmonic Raman spectra. It was found that the coupling effect between vibrational modes also greatly affects the Raman spectral characteristics. Finally, the excited state energy gap and pre-resonance Raman spectra of the aniline–silver cluster complexes are studied, and it is believed that there may be a charge-transfer enhancement mechanism.

Thermalization of open quantum systems using the multiple-Davydov- D2 variational approach

Numerical implementation of an explicit phonon bath requires a large number of oscillator modes in order to maintain oscillators at the initial temperature when modeling energy relaxation processes. An additional thermalization algorithm may be useful in controlling the local temperature. In this paper we extend our previously proposed thermalization algorithm [M. Jaku\v{c}ionis and D. Abramavi\v{c}ius, Phys. Rev. A 103, 032202 (2021) ] to be used with the numerically exact multiple-Davydov-D2 trial wave function for simulation of relaxation dynamics and spectroscopic signals of open quantum systems using the time-dependent Dirac-Frenkel variational principle. By applying it to the molecular aggregate model, we demonstrate how the thermalization approach significantly reduces the numerical cost of simulations by decreasing the number of oscillators needed to explicitly simulate the aggregate's environment fluctuations while maintaining correspondence to the exact population relaxation dynamics. Additionally, we show how the thermalization can be used to find the equilibrium state of the excited molecular aggregate, which is necessary for simulation of the fluorescence and other spectroscopic signals. The thermalization algorithm we present offers the possibility to investigate larger system-bath models than was previously possible using the multiple-Davydov-D2 trial wave function and local heating effects in molecular complexes.

Fabrication of a plasmonic sensor for surface-enhanced Raman spectroscopy using electroless deposition of Ag with hypophosphite

Surface-enhanced Raman spectroscopy (SERS) provides insights into electrode reaction processes due to its high selectivity towards the interface. It is necessary to ensure a stable and inexpensive supply of sensors to make this method more widely applicable. Techniques based on electrochemistry are efficient and suitable for mass manufacturing. In this research, two electroless processes for depositing Ag nanoparticles (NPs) on a glass substrate for sensor fabrication are discussed: one using ascorbic acid, the other hypophosphite. Specifically, the process using hypophosphite was achieved by forming Pd nuclei in the activating process. It turned out that when the ascorbic acid sensor is applied, undesired SERS signals originating from the reductant appear. By contrast, the hypophosphite sensor greatly reduces the unwanted signals. The optimized plasmonic sensor can achieve in situ SERS observation of electrochemical reactions without being restricted by electrode material and morphology.

Penetration-then-growth enables label-free surface-enhanced Raman spectroscopic discrimination of fibrotic cells and kidney tissues

Surface-enhanced Raman spectroscopy (SERS) is a highly efficient optical technique that employs metallic nanostructures to amplify the inherently weak Raman signals. Despite its great potential in obtaining fingerprint spectral information in complex biological samples, examining subtle molecular change in fixed cells/tissues by SERS is difficult because large-sized metal nanoparticle (NPs) can generate strong SERS signals but lack the ability to penetrate into the samples, whereas small-sized NPs can easily infiltrate samples but do not exhibit SERS activity. Herein, we propose a penetration-then-growth strategy for SERS-based detection of molecular change in the fibrogenic process. In the proof of concept study, control and fibrotic cells / mouse kidney tissue sections were initially incubated with ∼15 nm Au NPs which were permeable, and then the deposited NPs were grown up in situ to act as SERS substrates for Raman signal amplification. After NP growth, the Raman signals were dramatically enhanced, enabling fast discrimination of molecular changes occurred during fibrosis, which were indiscernible using conventional Raman spectrum or SERS detected with ∼50 nm Au NPs. This method is simple, fast, and can be readily adapted for inspecting molecular changes in other biological events.

A Simple Method to Fabricate the Highly Sensitive SERS Substrate by Femtosecond Laser-Based 3D Printer

Surface-enhanced Raman spectroscopy (SERS) is a potent technique for analyzing and detecting various targets, including toxic ions, pesticides, and biomarkers, at the single-molecule level. The efficiency of SERS techniques relies heavily on the underlying SERS substrate, which is primarily responsible for the strong induction of localized plasmon resonance on nanostructures. Noble metals such as gold and silver were commonly used to fabricate SERS substrates, leveraging the electromagnetic mechanism (EM) to enhance the Raman signal. However, chemically synthesized nanoparticle-based SERS substrates suffer from low uniformity and reproducibility. Furthermore, the high cost associated with noble metals makes most SERS substrates expensive to produce. In this study, we present a straightforward method for fabricating a highly uniform and reproducible SERS substrate using a femtosecond laser-based 3D printer. Notably, our method offers good cost competitiveness since it requires only a minimal amount of gold coating for the SERS signal. Moreover, the proposed method exhibits exceptional versatility in SERS analysis and detection, catering to numerous targets in the field.

Post-fire assessment of heating temperatures experienced by concrete using short video imaging, hyperspectral imaging and laser-induced breakdown spectroscopy

This study develops rapid post-fire analysis methods to predict the heating temperature to which the concrete was exposed. Short video imaging (SVI), hyperspectral imaging (HSI) and laser-induced breakdown spectroscopy (LIBS) were used for the first time to obtain spectra of concrete after high-temperature exposure (100–800 °C). The differences in colour levels and spectroscopic signals due to varying temperatures were observed. To handle the complex relationship between spectra and temperatures, machine learning models were used to extract meaningful information from spectra for the quantification of temperature. Furthermore, domain knowledge related to concrete composition and LIBS signal was integrated into machine learning to improve quantification performance. The highest coefficients of determination for prediction achieved based on SVI, HSI and LIBS measurements were 91.4, 94.8 and 98.6, respectively. These results demonstrate that SVI, HSI and LIBS can be fast and viable methods for assessing the fire temperature that the concrete has experienced.

Sensitive Determination of Stevioside by Surface-Enhanced Raman Spectroscopy (SERS) Using 4-Mercaptophenylboric Acid Functionalized Silver Nanoparticles (Ag NPs)

Stevioside is an important natural sweetener in food and beverages. There are concerns about its safety, but few methods for its determination. Silver nanoparticles (Ag NPs) functionalized with 4-mercaptophenylboronic acid (4-MPBA) were successfully used to determine stevioside in beverages based upon surface-enhanced Raman spectroscopy (SERS). The Ag NPs self-assemble with 4-MPBA through the covalent interaction of their sulfhydryl groups with the metal particles. Boronic acid groups bonded to 1,2-/1,3-diol groups form cyclic boronic esters with strong affinity and significant specificity for stevioside. The combination of the two leads to an alteration of the 4-MPBA vibrational mode. The change in the orientation of the moiety and the charge transfer resulted in a significant increase of the SERS signal. The substrates showed strong specificity and sensitivity to stevioside in the presence of other sweeteners. Also, the substrate modification conditions were optimized, including the time, ratio, and concentration. The limit of detection (LOD) for stevioside in beverages was 0.210 μmol/L, and the recovery was from 98.4% to 109.4%. In summary, the presented SERS method provides high sensitivity for stevioside.

Physiological Noise Filtering in Functional Near-Infrared Spectroscopy Signals Using Wavelet Transform and Long-Short Term Memory Networks.

Activated channels of functional near-infrared spectroscopy are typically identified using the desired hemodynamic response function (dHRF) generated by a trial period. However, this approach is not possible for an unknown trial period. In this paper, an innovative method not using the dHRF is proposed, which extracts fluctuating signals during the resting state using maximal overlap discrete wavelet transform, identifies low-frequency wavelets corresponding to physiological noise, trains them using long-short term memory networks, and predicts/subtracts them during the task session. The motivation for prediction is to maintain the phase information of physiological noise at the start time of a task, which is possible because the signal is extended from the resting state to the task session. This technique decomposes the resting state data into nine wavelets and uses the fifth to ninth wavelets for learning and prediction. In the eighth wavelet, the prediction error difference between the with and without dHRF from the 15-s prediction window appeared to be the largest. Considering the difficulty in removing physiological noise when the activation period is near the physiological noise, the proposed method can be an alternative solution when the conventional method is not applicable. In passive brain-computer interfaces, estimating the brain signal starting time is necessary.

Tailoring cavity coupled plasmonic substrates for SERS applications

Surface-enhanced Raman spectroscopy (SERS) has been effectively used in biosensing applications due to its high sensitivity and specificity. Enhancing the coupling of light into plasmonic nanostructures can lead to engineered SERS substrates with improved sensitivity and performance. In the current study, we demonstrate a cavity-coupled structure that assists in enhancing the light–matter interaction leading to an improved SERS performance. Using numerical simulations, we demonstrate that the cavity-coupled structures can either enhance or suppress the SERS signal depending on the cavity length and the wavelength of interest. Furthermore, the proposed substrates are fabricated using low-cost large-area techniques. The cavity-coupled plasmonic substrate consists of a layer of gold nanospheres on an indium tin oxide (ITO)-Au-glass substrate. The fabricated substrates exhibit nearly a 9 times improvement in SERS enhancement as compared to the uncoupled substrate. The demonstrated cavity-coupling approach can also be used for enhancing other plasmonic phenomena like plasmonic trapping, plasmon-enhanced catalysis, and nonlinear signal generation.

Understanding the impact of a non-ionic surfactant alkylphenol ethoxylate on surface-enhanced Raman spectroscopic analysis of pesticides on apple surfaces

Pesticide active ingredients (AIs) are often applied with adjuvants to facilitate the stability and functionality of AIs in agricultural practice. The objective of this study is to investigate the role of a common non-ionic surfactant, alkylphenol ethoxylate (APEO), on the surface-enhanced Raman spectroscopic (SERS) analysis of pesticides as well as its impact on pesticide persistence on apple surfaces, as a model fresh produce surface. The wetted areas of two AIs (thiabendazole and phosmet) mixed with APEO were determined respectively to correct the unit concentration applied on apple surfaces for a fair comparison. SERS with gold nanoparticle (AuNP) mirror substrates was applied to measure the signal intensity of AIs with and without APEO on apple surfaces after a short-term (45 min) and a long-term (5 days) exposure. The limit of detection (LOD) of thiabendazole and phosmet using this SERS-based method were 0.861 ppm and 2.883 ppm, respectively. The result showed that APEO decreased the SERS signal for non-systemic phosmet, while increased SERS intensity of systemic thiabendazole on apple surfaces after 45 min pesticide exposure. After 5 days, the SERS intensity of thiabendazole with APEO was higher than thiabendazole alone, and there was no significant difference between phosmet with and without APEO. Possible mechanisms were discussed. Furthermore, a 1% sodium bicarbonate (NaHCO3) washing method was applied to test the impact of APEO on the persistence of the residues on apple surfaces after short-term and long-term exposures. The results indicated that APEO significantly enhanced the persistence of thiabendazole on plant surfaces after a 5-day exposure, while there was no significant impact on phosmet. The information obtained facilitates a better understanding of the impact of the non-ionic surfactant on SERS analysis of pesticide behavior on and in plants and helps further develop the SERS method for studying complex pesticide formulations in plant systems.

Plasmon-Mediated Photoelectrochemical Hot-Hole Oxidation Coupling Reactions of Adenine on Nanostructured Silver Electrodes.

Surface-enhanced Raman spectroscopy (SERS) has been widely applied in the identification and characterization of DNA structures with high efficiency. Especially, the SERS signals of the adenine group have exhibited high detection sensitivity in several biomolecular systems. However, there is still no unanimous conclusion regarding the interpretation of some special kinds of SERS signals of adenine and its derivatives on silver colloids and electrodes. This Letter presents a new photochemical azo coupling reaction for adenyl residues, in which the adenine is selectively oxidized to (E)-1,2-di(7H-purin-6-yl) diazene (azopurine) in the presence of silver ions, silver colloids, and electrodes of nanostructures under visible light irradiation. The product, azopurine, is first found to be responsible for the SERS signals. This photoelectrochemical oxidative coupling reaction of adenine and its derivatives is promoted by plasmon-mediated hot holes and is regulated by positive potentials and pH of solutions, which opens up new avenues for studying azo coupling in the photoelectrochemistry of adenine-containing biomolecules on electrode surfaces of plasmonic metal nanostructures.

Amplification of SERS Signal of Methotrexate Using Beta-Cyclodextrin Modified Silver Nanoparticles

The paper describes the use of native β-cyclodextrin (CD) for the modification of silver nanoparticles (AgNPs) in order to improve the determination of the anticancer drug methotrexate (MTX) using surface-enhanced Raman spectroscopy (SERS). A control experiment with unmodified AgNPs showed that the strong SERS signal of MTX can only be achieved in alkaline media. However, competitive interactions and the strong background signal of human body fluid components significantly challenge MTX determination in real samples. While previous reports propose the use of thorough sample pretreatment (e.g., solid phase extraction), the application of CD-modified AgNPs increases the SERS signal of MTX in neutral media by seven times which enables simplifying the analysis and improving its accuracy by reducing the influence of endogenous components of body fluids. A detailed study of the synthesis conditions (CD concentration and reaction time) and SERS registration conditions (pH, NaCl concentration, dilution of urine samples) was performed to maximize the analytical signal and signal-to-noise ratio. The final assay was tested for MTX determination in artificially spiked samples of real human urine. The results demonstrated that MTX can be determined within the concentration range suitable for therapeutic drug monitoring (20–300 μg mL−1) with satisfactory precision (6–15% RSD), accuracy (95–111% apparent recovery), and limit of detection (0.3 μg mL−1).

Realizing the highly reversible Zn2+ and Na+ dual ions storage in high-crystallinity nickel hexacyanoferrate microcubes for aqueous zinc-ion batteries

Prussian blue analogues (PBAs) with the 3D open framework are regarded as promising cathode candidates for aqueous Zinc ion batteries (ZIBs). Among various PBAs, nickel hexacyanoferrate (NiHCF) has attracted considerable attention because of its high operating voltage and economic merit. However, the cyclability of NiHCF is unsatisfactory due to poor structural stability during Zn2+ ions insertion/deinsertion. Moreover, the ion storage mechanism of NiHCF in aqueous electrolytes has not been fully revealed yet. Herein, high-crystallinity NiHCF (HC-NiHCF) microcubes with improved structural stability and larger crystal plane spacing are synthesized. For the first time, highly reversible Zn2+ ions and Na+ ions co-insertion/extraction are achieved for the HC-NiHCF microcubes in mixed aqueous electrolyte, as evidenced by various observations including two separated discharge plateaus and sequential changes of Na 1s and Zn 2p signals in ex-situ X-ray photoelectron spectroscopy (XPS). As a result, a high specific capacity of 73.9 mAh g−1 is obtained for the HC-NiHCF microcubes at 0.1 A g−1, combined with enhanced cycle stability (75% vs. 16.4%) over 1000 cycles at 2 A g−1. The reversible Zn2+ ions and Na+ ions co-insertion in HC-NiHCF microcubes reveals a new ion storage mechanism of Ni-based PBAs in aqueous electrolytes.

Mirror-Stamping: A new TLC-SERS method for color authentication

Adulteration of natural colorants with artificial ones compromises the authenticity, quality, and safety of food products. It is significant for food companies to check the raw colorant ingredients to avoid potential adulteration. Combining thin-layer chromatography (TLC) and surface-enhanced Raman spectroscopy (SERS) is a promising colorant separation and detection approach. Herein, we developed a novel and simple TLC-SERS approach based on silver mirror-stamping, which was achieved by pressing a layer of aggregated silver nanoparticles on top of the target analytes on the developed TLC chip. The performance of the stamping method was evaluated on the separation and signal enhancement of an adulterated saffron model matrix (saffron and red 40) as compared to the other two methods (mirror-first and mirror-last methods). The results demonstrated that the mirror-stamping method achieved optimal separation performance with strong SERS signals. This can be attributed to the reduced sample disruption and dilution. Therefore, the mirror-stamping approach demonstrates great potential for use in TLC-SERS analysis to rapidly and accurately determine natural colorant authenticity and quality.

The impact of modified polystyrene on lysozyme fibrillation studied by surface-enhanced Raman spectroscopy (SERS)

Nanoplastics could modulate the fibrillation of amyloid proteins. However, many chemical functional groups are adsorbed to change the interfacial chemistry of nanoplastics in the real world. Herein, this study aimed to investigate the effects of polystyrene (PS), carboxyl modified PS (PS-COOH), and amino modified PS (PS-NH2) on the fibrillation of hen egg-white lysozyme (HEWL). Due to the differences in the interfacial chemistry, concentration was considered an essential factor. PS-NH2 (10 μg/mL) could promote the fibrillation of HEWL similar to PS (50 μg/mL) and PS-COOH (50 μg/mL). Moreover, promoting the primary nucleation step of amyloid fibril formation was the primary reason. The differences in spatial conformation of HEWL were characterized by Fourier transform-infrared spectroscopy and surface enhanced Raman spectroscopy (SERS). Strikingly, a particular signal of SERS of HEWL incubated with PS-NH2 at 1610 cm−1 was found due to the interaction between amino group of PS-NH2 and tryptophan (or tyrosine) of HEWL. Therefore, a new perspective was provided to understand the regulation of interfacial chemistry of nanoplastics on the fibrillation of amyloid proteins. Additionally, this study suggested that SERS could be a powerful method to investigate the interactions between proteins and nanoparticles.