Computational chromatography: A machine learning strategy for demixing individual chemical components in complex mixtures.

Surface-enhanced Raman spectroscopy (SERS) holds exceptional promise as a streamlined chemical detection strategy for biological and environmental contaminants compared with current laboratory methods. Priority pollutants such as polycyclic aromatic hydrocarbons (PAHs), detectable in water and soil worldwide and known to induce multiple adverse health effects upon human exposure, are typically found in multicomponent mixtures. By combining the molecular fingerprinting capabilities of SERS with the signal separation and detection capabilities of machine learning (ML), we examine whether individual PAHs can be identified through an analysis of the SERS spectra of multicomponent PAH mixtures. We have developed an unsupervised ML method we call Characteristic Peak Extraction, a dimensionality reduction algorithm that extracts characteristic SERS peaks based on counts of detected peaks of the mixture. By analyzing the SERS spectra of two-component and four-component PAH mixtures where the concentration ratios of the various components vary, this algorithm is able to extract the spectra of each unknown component in the mixture of unknowns, which is then subsequently identified against a SERS spectral library of PAHs. Combining the molecular fingerprinting capabilities of SERS with the signal separation and detection capabilities of ML, this effort is a step toward the computational demixing of unknown chemical components occurring in complex multicomponent mixtures.

Probing Oxidation Mechanisms in Plasmonic Catalysis: Unraveling the Role of Reactive Oxygen Species.

Plasmon-induced oxidation has conventionally been attributed to the transfer of plasmonic hot holes. However, this theoretical framework encounters challenges in elucidating the latest experimental findings, such as enhanced catalytic efficiency under uncoupled irradiation conditions and superior oxidizability of silver nanoparticles. Herein, we employ liquid surface-enhanced Raman spectroscopy (SERS) as a real-time and in situ tool to explore the oxidation mechanisms in plasmonic catalysis, taking the decarboxylation of p-mercaptobenzoic acid (PMBA) as a case study. Our findings suggest that the plasmon-induced oxidation is driven by reactive oxygen species (ROS) rather than hot holes, holding true for both the Au and Ag nanoparticles. Subsequent investigations suggest that plasmon-induced ROS may arise from hot carriers or energy transfer mechanisms, exhibiting selectivity under different experimental conditions. The observations were substantiated by investigating the cleavage of the carbon-boron bonds. Furthermore, the underlying mechanisms were clarified by energy level theories, advancing our understanding of plasmonic catalysis.

Monitoring Hot Holes in Plasmonic Catalysis on Silver Nanoparticles by Using an Ion Label.

Energetic carriers generated by localized surface plasmon resonance (LSPR) provide an efficient way to drive chemical reactions. However, their dynamics and impact on surface reactions remain unknown due to the challenge in observing hot holes. This makes it difficult to correlate the reduction and oxidation half-reactions involving hot electrons and holes, respectively. Here we detect hot holes in their chemical form, Ag(I), on a Ag surface using surface-enhanced Raman scattering (SERS) of SO32- as a hole-specific label. It allows us to determine the dynamic correlations of hot electrons and holes. We find that the equilibrium of holes is the key factor of the surface chemistry, and the wavelength-dependent plasmonic chemical anode refilling (PCAR) effect plays an important role, in addition to the LSPR, in promoting the electron transfer. This method paves the way for visualizing hot holes with nanoscale spatial resolution toward the rational design of a plasmonic catalytic platform.

Molecular-Sieving Label-Free Surface-Enhanced Raman Spectroscopy for Sensitive Detection of Trace Small-Molecule Biomarkers in Clinical Samples.

Small-molecule biomarkers are ubiquitous in biological fluids with pathological implications, but major challenges persist in their quantitative analysis directly in complex clinical samples. Herein, a molecular-sieving label-free surface-enhanced Raman spectroscopy (SERS) biosensor is reported for selective quantitative analysis of trace small-molecule trimetazidine (TMZ) in clinical samples. Our biosensor is fabricated by decorating a superhydrophobic monolayer of microporous metal-organic frameworks (MOF) shell-coated Au nanostar nanoparticles on a silicon substrate. The design strategy principally combines the hydrophobic surface-enabled physical confinement and preconcentration, MOF-assisted molecular enrichment and sieving of small molecules, and sensitive SERS detection. Our biosensor utilizes such a "molecular confinement-and-sieving" strategy to achieve a five orders-of-magnitude dynamic detection range and a limit of detection of ≈0.5 nM for TMZ detection in either urine or whole blood. We further demonstrate the applicability of our biosensing platform for longitudinal label-free SERS detection of the TMZ level directly in clinical samples in a mouse model.

A Statistical Route to Robust SERS Quantitation Beyond the Single-Molecule Level.

Single-molecule surface-enhanced Raman spectroscopy (SM-SERS) holds great potential to revolutionize ultratrace quantitative analysis. However, achieving quantitative SM-SERS is challenging because of strong intensity fluctuation and blinking characteristics. In this study, we reveal the relation P = 1 - e-α between the statistical SERS probability P and the microscopic average molecule number α in SERS spectra, which lays the physical foundation for a statistical route to implement SM-SERS quantitation. Utilizing SERS probability calibration, we achieve quantitative SERS analysis with batch-to-batch robustness, extremely wide detection range of concentration covering 9 orders of magnitude, and ultralow detection limit far below the single-molecule level. These results indicate the physical feasibility of robust SERS quantitation through statistical route and certainly open a new avenue for implementing SERS as a practical analysis tool in various application scenarios.

Plasmonic Nanotrenches with 1 nm Nanogaps for Surface-Enhanced Raman Scattering-Based Screening of His-Tagged Proteins.

This study represents a highly sensitive and selective approach to protein screening using surface-enhanced Raman scattering (SERS) facilitated by octahedral Au nanotrenches (OANTs). OANTs are a novel class of nanoparticles characterized by narrow, trench-like excavations indented into the eight facets of a Au octahedron. This unique configuration maximizes electromagnetic near-field focusing as the gap distance decreases to ∼1 nm. Owing to geometrical characteristics of the OANTs, near-field focusing can be maximized through the confinement and reflectance of light trapped within the trenches. We used Ni ions and molecular linkers to confer selective binding affinity for His-tagged proteins on the surfaces of the OANTs for SERS-based protein screening. Remarkably, SERS-based protein screening with the surface-modified OANTs yielded outstanding screening capabilities: 100% sensitivity and 100% selectivity in distinguishing His-tagged human serum albumin (HSA) from native HSA. This highlights the significantly enhanced protein screening capabilities achieved through the synergistic combination of SERS and the OANTs.

Patterned Gold Nanoparticle Superlattice Film for Wearable Sweat Sensors.

Nanoparticle superlattices are beneficial in terms of providing strong and uniform signals in analysis owing to their closely packed uniform structures. However, nanoparticle superlattices are prone to cracking during physical activities because of stress concentrations, which hinders their detection performance and limits their analytical applications. In this work, template printing methods were used in this study to prepare a patterned gold nanoparticle (AuNP) superlattice film. By adjustment of the size of the AuNP superlattice domain below the critical size of fracture, the mechanical stability of the AuNP superlattice domain is improved. Thus, long-term sustainable high-performance signal output is achieved. The patterned AuNP superlattice film was used to construct a wearable sweat sensor based on surface-enhanced Raman scattering (SERS). The designed sensor showed promise for long-term reliable use in actual scenarios in terms of recommending water replenishment, monitoring hydration states, and tracking the intensity of activity.

Yolk-Shell Hierarchical Pore Au@MOF Nanostructures: Efficient Gas Capture and Enrichment for Advanced Breath Analysis.

Surface-enhanced Raman scattering (SERS) offers a promising, cost-effective alternative for the rapid, sensitive, and quantitative analysis of potential biomarkers in exhaled gases, which is crucial for early disease diagnosis. However, a major challenge in SERS is the effective detection of gaseous analytes, primarily due to difficulties in enriching and capturing them within the substrate's "hotspot" regions. This study introduces an advanced gas sensor combining mesoporous gold (MesoAu) and metal-organic frameworks (MOFs), exhibiting high sensitivity and rapid detection capabilities. The MesoAu provides abundant active sites and interconnected mesopores, facilitating the diffusion of analytes for detection. A ZIF-8 shell enveloping MesoAu further enriches target molecules, significantly enhancing sensitivity. A proof-of-concept experiment demonstrated a detection limit of 0.32 ppb for gaseous benzaldehyde, indicating promising prospects for the rapid diagnosis of early stage lung cancer. This research also pioneers a novel approach for constructing hierarchical plasmonic nanostructures with immense potential in gas sensing.

Detection of Helicobacter pylori Infection in Human Gastric Fluid Through Surface-Enhanced Raman Spectroscopy Coupled With Machine Learning Algorithms.

Diagnostic methods for Helicobacter pylori infection include, but are not limited to, urea breath test, serum antibody test, fecal antigen test, and rapid urease test. However, these methods suffer drawbacks such as low accuracy, high false-positive rate, complex operations, invasiveness, etc. Therefore, there is a need to develop simple, rapid, and noninvasive detection methods for H. pylori diagnosis. In this study, we propose a novel technique for accurately detecting H. pylori infection through machine learning analysis of surface-enhanced Raman scattering (SERS) spectra of gastric fluid samples that were noninvasively collected from human stomachs via the string test. One hundred participants were recruited to collect gastric fluid samples noninvasively. Therefore, 12,000 SERS spectra (n = 120 spectra/participant) were generated for building machine learning models evaluated by standard metrics in model performance assessment. According to the results, the Light Gradient Boosting Machine algorithm exhibited the best prediction capacity and time efficiency (accuracy = 99.54% and time = 2.61 seconds). Moreover, the Light Gradient Boosting Machine model was blindly tested on 2,000 SERS spectra collected from 100 participants with unknown H. pylori infection status, achieving a prediction accuracy of 82.15% compared with qPCR results. This novel technique is simple and rapid in diagnosing H. pylori infection, potentially complementing current H. pylori diagnostic methods.

Charged Amino Acid Substitutions Affect Conformation of Neuroglobin and Cytochrome c Heme Groups.

Neuroglobin (Ngb) is a cytosolic heme protein that plays an important role in protecting cells from apoptosis through interaction with oxidized cytochrome c (Cyt c) released from mitochondria. The interaction of reduced Ngb and oxidized Cyt c is accompanied by electron transfer between them and the reduction in Cyt c. Despite the growing number of studies on Ngb, the mechanism of interaction between Ngb and Cyt c is still unclear. Using Raman spectroscopy, we studied the effect of charged amino acid substitutions in Ngb and Cyt c on the conformation of their hemes. It has been shown that Ngb mutants E60K, K67E, K95E and E60K/E87K demonstrate changed heme conformations with the lower probability of the heme planar conformation compared to wild-type Ngb. Moreover, oxidized Cyt c mutants K25E, K72E and K25E/K72E demonstrate the decrease in the probability of methyl-radicals vibrations, indicating the higher rigidity of the protein microenvironment. It is possible that these changes can affect electron transfer between Ngb and Cyt c.

DNA Origami-Engineered Plasmonic Nanoprobes for Targeted Cancer Imaging.

Plasmonic nanomaterials bearing targeting ligands are of great interest for surface-enhanced Raman scattering (SERS)-based bioimaging applications. However, the practical utility of SERS-based imaging strategies has been hindered by the lack of a straightforward method to synthesize highly sensitive SERS-active nanostructures with high yield and efficiency. In this work, leveraging DNA origami principles, we report the first-in-class design of a SERS-based plasmonically coupled nanoprobe for targeted cancer imaging (SPECTRA). The nanoprobe harnesses a cancer cell targeting DNA aptamer sequence and vibrational tag with stretching frequency in the cell-silent Raman window. Through the integration of aptamer sequence specific for DU145 cells, we show the unique capabilities of SPECTRA for targeted imaging of DU145 cells. Our results demonstrate that the scalability, cost-effectiveness, and reproducibility of this method of fabrication of SERS nanoprobes can serve as a versatile platform for creating nanoprobes with broad applications in the fields of cancer biology and biomedical imaging.

Unusual Raman Enhancement Effect of Ultrathin Copper Sulfide.

In surface-enhanced Raman spectroscopy (SERS), 2D materials are explored as substrates owing to their chemical stability and reproducibility. However, they exhibit lower enhancement factors (EFs) compared to noble metal-based SERS substrates. This study demonstrates the application of ultrathin covellite copper sulfide (CuS) as a cost-effective SERS substrate with a high EF value of 7.2 × 104 . The CuS substrate is readily synthesized by sulfurizing a Cu thin film at room temperature, exhibiting a Raman signal enhancement comparable to that of an Au noble metal substrate of similar thickness. Furthermore, computational simulations using the density functional theory are employed and time-resolved photoluminescence measurements are performed to investigate the enhancement mechanisms. The results indicate that polar covalent bonds (Cu─S) and strong interlayer interactions in the ultrathin CuS substrate increase the probability of charge transfer between the analyte molecules and the CuS surface, thereby producing enhanced SERS signals. The CuS SERS substrate demonstrates the selective detection of various dye molecules, including rhodamine 6G, methylene blue, and safranine O. Furthermore, the simplicity of CuS synthesis facilitates large-scale production of SERS substrates with high spatial uniformity, exhibiting a signal variation of less than 5% on a 4-inch wafer.

Plasmonic Dodecahedral-Walled Elongated Nanoframes for Surface-Enhanced Raman Spectroscopy.

Here, elongated pseudohollow nanoframes composed of four rectangular plates enclosing the sides and two open-frame ends with four ridges pointing at the tips for near-field focusing are reported. The side facets act as light-collecting domains and transfer the collected light to the sharp tips for near-field focusing. The nanoframes are hollow inside, allowing the gaseous analyte to penetrate through the entire architecture and enabling efficient detection of gaseous analytes when combined with Raman spectroscopy. The resulting nanostructures are named Au dodecahedral-walled nanoframes. Synthesis of the nanoframes involves shape transformation of Au nanorods with round tips to produce Au-elongated dodecahedra, followed by facet-selective Pt growth, etching of the inner Au, and regrowth steps. The close-packed assembly of Au dodecahedral-walled nanoframes exhibits an attomolar limit of detection toward benzenethiol. This significant enhancement in SERS is attributed to the presence of a flat solid terrace for a large surface area, sharp edges and vertices for strong electromagnetic near-field collection, and open frames for effective analyte transport and capture. Moreover, nanoframes are applied to detect chemical warfare agents, specifically mustard gas simulants, and 20 times higher sensitivity is achieved compared to their solid counterparts.

Quantitative Detection of Thyroid-Stimulating Hormone in Patient Samples with a Nanomechanical Single-Antibody Spectro-Immunoassay.

Functional disorders of the thyroid remain a global challenge and have profound impacts on human health. Serving as the barometer for thyroid function, thyroid-stimulating hormone (TSH) is considered the single most useful test of thyroid function. However, the prevailing TSH immunoassays rely on two types of antibodies in a sandwich format. The requirement of repeated incubation and washing further complicates the issue, making it unable to meet the requirements of the shifting public health landscape that demands rapid, sensitive, and low-cost TSH tests. Herein, a systematic study is performed to investigate the clinical translational potential of a single antibody-based biosensing platform for the TSH test. The biosensing platform leverages Raman spectral variations induced by the interaction between a TSH antigen and a Raman molecule-conjugated TSH antibody. In conjunction with machine learning, it allows TSH concentrations in various patient samples to be predicted with high accuracy and precision, which is robust against substrate-to-substrate, intra-substrate, and day-to-day variations. It is envisioned that the simplicity and generalizability of this single-antibody immunoassay coupled with the demonstrated performance in patient samples pave the way for it to be widely applied in clinical settings for low-cost detection of hormones, other molecular biomarkers, DNA, RNA, and pathogens.

One-Stop Plasmonic Nanocube-Excited SERS Immunoassay Platform of Multiple Cardiac Biomarkers for Rapid Screening and Progressive Tracing of Acute Myocardial Infarction.

Rapid and precise acute myocardial infarction (AMI) diagnosis is essential for preventing patient death. In addition, the complementary roles of creatine kinase muscle brain (CK-MB) and cardiac troponin I (cTnI) cardiac biomarkers in the early and late stages of AMI demand their simultaneous detection, which is difficult to implement using conventional fluorescence and electrochemical technologies. Here, a nanotechnology-based one-stop immuno-surface-enhanced Raman scattering (SERS) detection platform is reported for multiple cardiac indicators for the rapid screening and progressive tracing of AMI events. Optimal SERS is achieved using optical property-based, excitation wavelength-optimized, and high-yield anisotropic plasmonic gold nanocubes. Optimal immunoassay reaction efficiencies are achieved by increasing immobilized antibodies. Multiple simultaneous detection strategies are implemented by incorporating two different Raman reports with narrow wavenumbers corresponding to two indicators and by establishing a computational SERS mapping process to accurately detect their concentrations, irrespective of multiple enzymes in the human serum. The SERS platform precisely estimated AMI onset and progressive timing in human serum and made rapid AMI identification feasible using a portable Raman spectrometer. This integrated platform is hypothesized to significantly contribute to emergency medicine and forensic science by providing timely treatment and observation.

2D TiS2-Nanosheet-Coated Concave Gold Arrays with Triple-Coupled Resonances as Sensitive SERS Substrates.

Herein, a hybrid substrate for surface-enhanced Raman scattering (SERS) is fabricated, which couples localized surface plasmon resonance (LSPR), charge transfer (CT) resonance, and molecular resonance. Exfoliated 2D TiS2 nanosheets with semimetallic properties accelerate the CT with the tested analytes, inducing a remarkable chemical mechanism enhancement. In addition, the LSPR effect is coupled with a concave gold array located underneath the thin TiS2 nanosheet, providing a strong electromagnetic enhancement. The concave gold array is prepared by etching silicone nanospheres assembled on larger polystyrene nanospheres, followed by depositing a gold layer. The LSPR intensity near the gold layer can be adjusted by changing the layer thickness to couple the molecular and CT resonances, in order to maximize the SERS enhancement. The best SERS performance is recorded on TiS2-nanosheet-coated plasmonic substrates, with a detectable methylene blue concentration down to 10-13 m and an enhancement factor of 2.1 × 109 and this concentration is several orders of magnitude lower than that of the TiS2 nanosheet (10-11 m) and plasmonic substrates (10-9 m). The present hybrid substrate with triple-coupled resonance further shows significant advantages in the label-free monitoring of curcumin (a widely applied drug for treating multiple cancers and inflammations) in serum and urine.

Tip-based Lithography with a Sacrificial Layer.

The fabrication of a highly controlled gold (Au) nanohole (NH) array via tip-based lithography is improved by incorporating a sacrificial layer-a tip-crash buffer layer. This inclusion mitigates scratches during the nano-indentation process by employing a 300 nm thick poly(methyl methacrylate) layer as a sacrificial layer on top of the Au film. Such a precaution ensures minimal scratches on the Au film, facilitating the creation of sub-50 nm Au NHs with a 15 nm gap between the Au NHs. The precision of this method exceeds that of fabricating Au NHs without a sacrificial layer. Demonstrating its versatility, this Au NH array is utilized in two distinct applications: as a dry etching mask to form a molybdenum disulfide hole array and as a catalyst in metal-assisted chemical etching, resulting in conical-shaped silicon nanostructures. Additionally, a significant electric field is generated when Au nanoparticles (NPs) are placed within the Au NHs. This effect arises from coupling electromagnetic waves, concentrated by the Au NHs and amplified by the Au NPs. A notable result of this configuration is the enhancement factor of surface-enhanced Raman scattering, which is an order of magnitude greater than that observed with just Au NHs and Au NPs alone.

NIR-II Surface-Enhanced Raman Scattering Nanoprobes in Biomedicine: Current Impact and Future Directions.

The field of second near-infrared (NIR-II) surface-enhanced Raman scattering (SERS) nanoprobes has made commendable progress in biomedicine. This article reviews recent advances and future development of NIR-II SERS nanoprobes. It introduces the fundamental principles of SERS nanoprobes and highlights key advances in the NIR-II window, including reduced tissue attenuation, deep penetration, maximized allowable exposure, and improved photostability. The discussion of future directions includes the refinement of nanoprobe substrates, emphasizing the tailoring of optical properties of metallic SERS-active nanoprobes, and exploring non-metallic alternatives. The intricacies of designing Raman reporters for the NIR-II resonance and the potential of these reporters to advance the field are also discussed. The integration of artificial intelligence (AI) into nanoprobe design represents a cutting-edge approach to overcome current challenges. This article also examines the emergence of deep Raman techniques for through-tissue SERS detection, toward NIR-II SERS tomography. It acknowledges instrumental advancements like improved charge-coupled device sensitivity and accelerated imaging speeds. The article concludes by addressing the critical aspects of biosafety, ease of functionalization, compatibility, and the path to clinical translation. With a comprehensive overview of current achievements and future prospects, this review aims to illuminate the path for NIR-II SERS nanoprobes to innovate diagnostic and therapeutic approaches in biomedicine.

Phase-Tunable Molybdenum Boride Ceramics as an Emerging Sensitive and Reliable SERS Platform in Harsh Environments.

Traditional surface-enhanced Raman scattering (SERS) sensors rely heavily on the use of plasmonic noble metals, which have limitations due to their high cost and lack of physical and chemical stability. Hence, it is imperative to explore new materials as SERS platforms that can withstand high temperatures and harsh conditions. In this study, the SERS effect of molybdenum boride ceramic powders is presented with an enhancement factor of 5 orders, which is comparable to conventional noble metal substrates. The molybdenum boride powders synthesized through liquid-phase precursor and carbothermal reduction have ß-MoB, MoB2, and Mo2B5 phases. Among these phases, ß-MoB demonstrates the most significant SERS activity, with a detection limit for rhodamine 6G (R6G) molecules of 10-9 m. The impressive SERS enhancement can be attributed to strong molecule interactions and prominent charge interactions between R6G and the various phases of molybdenum boride, as supported by theoretical calculations. Additionally, Raman measurements show that the SERS activity remains intact after exposure to high temperature, strong acids, and alkalis. This research introduces a novel molybdenum boride all-ceramic SERS platform capable of functioning in harsh conditions, thereby showing the promising of boride ultrahigh-temperature ceramics for detection applications in extreme environments.

Multi-Biomarker Profiling for Precision Diagnosis of Lung Cancer.

Multi-biomarker analysis can enhance the accuracy of the single-biomarker analysis by reducing the errors caused by genetic and environmental differences. For this reason, multi-biomarker analysis shows higher accuracy in early and precision diagnosis. However, conventional analysis methods have limitations for multi-biomarker analysis because of their long pre-processing times, inconsistent results, and large sample requirements. To solve these, a fast and accurate precision diagnostic method is introduced for lung cancer by multi-biomarker profiling using a single drop of blood. For this, surface-enhanced Raman spectroscopic immunoassay (SERSIA) is employed for the accurate, quick, and reliable quantification of biomarkers. Then, it is checked the statistical relation of the multi-biomarkers to differentiate between healthy controls and lung cancer patients. This approach has proven effective; with 20 µL of blood serum, lung cancer is diagnosed with 92% accuracy. It also accurately identifies the type and stage of cancer with 87% and 85%, respectively. These results show the importance of multi-biomarker analysis in overcoming the challenges posed by single-biomarker diagnostics. Furthermore, it markedly improves multi-biomarker-based analysis methods, illustrating its important impact on clinical diagnostics.