Direct Bottom-Up In Situ Growth: A Paradigm Shift for Studies in Wet-Chemical Synthesis of Gold Nanoparticles.

Plasmonic gold nanoparticles have been used increasingly in solid-state systems because of their applicability in fabricating novel sensors, heterogeneous catalysts, metamaterials, and thermoplasmonic substrates. While bottom-up colloidal syntheses take advantage of the chemical environment to control size, shape, composition, surface chemistry, and crystallography of the nanostructures precisely, it can be challenging to assemble nanoparticles rationally from suspension onto solid supports or within devices. In this Review, we discuss a powerful recent synthetic methodology, bottom-up in situ substrate growth, which circumvents time-consuming batch presynthesis, ligand exchange, and self-assembly steps by applying wet-chemical synthesis to form morphologically controlled nanostructures on supporting materials. First, we briefly introduce the properties of plasmonic nanostructures. Then we comprehensively summarize recent work that adds to the synthetic understanding of in situ geometrical and spatial control (patterning). Next, we briefly discuss applications of plasmonic hybrid materials prepared by in situ growth. Overall, despite the vast potential advantages of in situ growth, the mechanistic understanding of these methodologies remains far from established, providing opportunities and challenges for future research.

Potential Alignment in Tandem Catalysts Enhances CO2-to-C2H4 Conversion Efficiencies.

The in-tandem catalyst holds great promise for addressing the limitation of low *CO coverage on Cu-based materials for selective C2H4 generation during CO2 electroreduction. However, the potential mismatch between the CO-formation catalyst and the favorable C-C coupling Cu catalyst represents a bottleneck in these types of electrocatalysts, resulting in low tandem efficiencies. In this study, we propose a robust solution to this problem by introducing a wide-CO generation-potential window nickel single atom catalyst (Ni SAC) supported on a Cu catalyst. The selection of Ni SAC was based on theoretical calculations, and its excellent performance was further confirmed by using in situ IR spectroscopy. The facilitated carbon dimerization in our tandem catalyst led to a ∼370 mA/cm2 partial current density of C2H4, corresponding to a faradic efficiency of ∼62%. This performance remained stable and consistent for at least ∼14 h at a high current density of 500 mA/cm2 in a flow-cell reactor, outperforming most tandem catalysts reported so far.

Investigating Plasmonic Catalysis Kinetics on Hot-Spot Engineered Nanoantennae.

Strong hot-spots can facilitate photocatalytic reactions potentially providing effective solar-to-chemical energy conversion pathways. Although it is well-known that the local electromagnetic field in plasmonic nanocavities increases as the cavity size reduces, the influence of hot-spots on photocatalytic reactions remains elusive. Herein, we explored hot-spot dependent catalytic behaviors on a highly controlled platform with varying interparticle distances. Plasmon-meditated dehalogenation of 4-iodothiophenol was employed to observe time-resolved catalytic behaviors via in situ surface-enhanced Raman spectroscopy on dimers with 5, 10, 20, and 30 nm interparticle distances. As a result, we show that by reducing the gap from 20 to 10 nm, the reaction rate can be sped up more than 2 times. Further reduction in the interparticle distance did not improve reaction rate significantly although the maximum local-field was ∼2.3-fold stronger. Our combined experimental and theoretical study provides valuable insights in designing novel plasmonic photocatalytic platforms.

Coupling Nano and Atomic Electric Field Confinement for Robust Alkaline Oxygen Evolution.

The alkaline oxygen evolution reaction (OER) is a promising avenue for producing clean fuels and storing intermittent energy. However, challenges such as excessive OH- consumption and strong adsorption of oxygen-containing intermediates hinder the development of alkaline OER. In this study, we propose a cooperative strategy by leveraging both nano-scale and atomically local electric fields for alkaline OER, demonstrated through the synthesis of Mn single atom doped CoP nanoneedles (Mn SA-CoP NNs). Finite element method simulations and density functional theory calculations predict that the nano-scale local electric field enriches OH- around the catalyst surface, while the atomically local electric field improves *O desorption. Experimental validation using in situ attenuated total reflection infrared and Raman spectroscopy confirms the effectiveness of the nano-scale and atomically electric fields. Mn SA-CoP NNs exhibit an ultra-low overpotential of 189 mV at 10 mA cm-2 and stable operation over 100 hours at ~100 mA cm-2 during alkaline OER. This innovative strategy provides new insights for enhancing catalyst performance in energy conversion reactions.

Highly Selective Monomethylation of Amines with CO2 /H2 via Ag/Al2 O3 as a Catalyst.

The selective synthesis of monomethylated amines with CO2 is particularly challenging because the formation of tertiary amines is thermodynamically more favorable. Herein, a new strategy for the controllable synthesis of N-monomethylated amines from primary amines and CO2 /H2 is explored. First-principle calculations reveal that the dissociation of H2 via an heterolytic route reduces the reactivity of methylated amines and thus inhibit successive methylation. In situ DRIFTS proves the process of formation and decomposition of ammonium salt by secondary amine reversible binding with H+ on the Ag/Al2 O3 catalyst, thereby reducing its reactivity. Meanwhile, the energy barrier for the rate-determining step of monomethylation was much lower than that of overmethylation (0.34 eV vs. 0.58 eV) means amines monomethylation in preference to successive methylation. Under optimal reaction conditions, a variety of amines were converted to the corresponding monomethylated amines in good to excellent yields, and more than 90 % yield of product was obtained.

Atomically Local Electric Field Induced Interface Water Reorientation for Alkaline Hydrogen Evolution Reaction.

The slow water dissociation process in alkaline electrolyte severely limits the kinetics of HER. The orientation of H2 O is well known to affect the dissociation process, but H2 O orientation is hard to control because of its random distribution. Herein, an atomically asymmetric local electric field was designed by IrRu dizygotic single-atom sites (IrRu DSACs) to tune the H2 O adsorption configuration and orientation, thus optimizing its dissociation process. The electric field intensity of IrRu DSACs is over 4.00×1010  N/C. The ab initio molecular dynamics simulations combined with in situ Raman spectroscopy analysis on the adsorption behavior of H2 O show that the M-H bond length (M=active site) is shortened at the interface due to the strong local electric field gradient and the optimized water orientation promotes the dissociation process of interfacial water. This work provides a new way to explore the role of single atomic sites in alkaline hydrogen evolution reaction.

Combined miRNA and SERS urine liquid biopsy for the point-of-care diagnosis and molecular stratification of bladder cancer.

BACKGROUND: Bladder cancer (BC) has the highest per-patient cost of all cancer types. Hence, we aim to develop a non-invasive, point-of-care tool for the diagnostic and molecular stratification of patients with BC based on combined microRNAs (miRNAs) and surface-enhanced Raman spectroscopy (SERS) profiling of urine. METHODS: Next-generation sequencing of the whole miRNome and SERS profiling were performed on urine samples collected from 15 patients with BC and 16 control subjects (CTRLs). A retrospective cohort (BC = 66 and CTRL = 50) and RT-qPCR were used to confirm the selected differently expressed miRNAs. Diagnostic accuracy was assessed using machine learning algorithms (logistic regression, naïve Bayes, and random forest), which were trained to discriminate between BC and CTRL, using as input either miRNAs, SERS, or both. The molecular stratification of BC based on miRNA and SERS profiling was performed to discriminate between high-grade and low-grade tumors and between luminal and basal types. RESULTS: Combining SERS data with three differentially expressed miRNAs (miR-34a-5p, miR-205-3p, miR-210-3p) yielded an Area Under the Curve (AUC) of 0.92 ± 0.06 in discriminating between BC and CTRL, an accuracy which was superior either to miRNAs (AUC = 0.84 ± 0.03) or SERS data (AUC = 0.84 ± 0.05) individually. When evaluating the classification accuracy for luminal and basal BC, the combination of miRNAs and SERS profiling averaged an AUC of 0.95 ± 0.03 across the three machine learning algorithms, again better than miRNA (AUC = 0.89 ± 0.04) or SERS (AUC = 0.92 ± 0.05) individually, although SERS alone performed better in terms of classification accuracy. CONCLUSION: miRNA profiling synergizes with SERS profiling for point-of-care diagnostic and molecular stratification of BC. By combining the two liquid biopsy methods, a clinically relevant tool that can aid BC patients is envisaged.

Fermi Level Equilibration at the Metal-Molecule Interface in Plasmonic Systems.

We highlight a new metal-molecule charge transfer process by tuning the Fermi energy of plasmonic silver nanoparticles (AgNPs) in situ. The strong adsorption of halide ions upshifts the Fermi level of AgNPs by up to ∼0.3 eV in the order Cl- < Br- < I-, favoring the spontaneous charge transfer to aligned molecular acceptor orbitals until charge neutrality across the interface is achieved. By carefully quantifying, experimentally and theoretically, the Fermi level upshift, we show for the first time that this effect is comparable in energy to different plasmonic effects such as the plasmoelectric effect or hot-carriers production. Moreover, by monitoring in situ the adsorption dynamic of halide ions in different AgNP-molecule systems, we show for the first time that the catalytic role of halide ions in plasmonic nanostructures depends on the surface affinity of halide ions compared to that of the target molecule.

Heteroatoms Induce Localization of the Electric Field and Promote a Wide Potential-Window Selectivity Towards CO in the CO2 Electroreduction.

Carbon dioxide electroreduction (CO2 RR) is a sustainable way of producing carbon-neutral fuels. Product selectivity in CO2 RR is regulated by the adsorption energy of reaction-intermediates. Here, we employ differential phase contrast-scanning transmission electron microscopy (DPC-STEM) to demonstrate that Sn heteroatoms on a Ag catalyst generate very strong and atomically localized electric fields. In situ attenuated total reflection infrared spectroscopy (ATR-IR) results verified that the localized electric field enhances the adsorption of *COOH, thus favoring the production of CO during CO2 RR. The Ag/Sn catalyst exhibits an approximately 100 % CO selectivity at a very wide range of potentials (from -0.5 to -1.1 V, versus reversible hydrogen electrode), and with a remarkably high energy efficiency (EE) of 76.1 %.

SERS-based liquid biopsy of saliva and serum from patients with Sjögren's syndrome.

In this preliminary study, we employed surface-enhanced Raman scattering (SERS) of saliva and serum samples for diagnosing Sjogren's syndrome (SjS), a systemic autoimmune disease characterized by dryness of the mouth and eyes. The saliva and serum samples from n = 29 patients with SjS and n = 21 controls were deproteinized with methanol and then the SERS spectra were acquired using silver nanoparticles synthesized by reduction with hydroxylamine hydrochloride. In the case of both saliva and serum, the SERS spectra were dominated by similar bands attributed to purine metabolites such as uric acid, xanthine, and hypoxanthine. Principal component analysis-linear discriminant analysis (PCA-LDA) models built from SERS spectra of saliva and serum yielded an overall classification accuracy of 94% and 98%, respectively. These results suggest that the SERS analysis of saliva and serum is able to capture the complex biochemical perturbations that accompany the onset of SjS, a strategy which could be translated in the future into a novel point-of-care diagnosis method. Graphical abstract.

SERS assessment of the cancer-specific methylation pattern of genomic DNA: towards the detection of acute myeloid leukemia in patients undergoing hematopoietic stem cell transplantation.

In this label-free surface-enhanced Raman scattering (SERS) study of genomic DNA, we demonstrate that the cancer-specific DNA methylation pattern translates into specific spectral differences. Thus, DNA extracted from an acute myeloid leukemia (AML) cell line presented a decreased intensity of the 1005 cm-1 band of 5-methylcytosine compared to normal DNA, in line with the well-described hypomethylation of cancer DNA. The unique methylation pattern of cancer DNA also influences the DNA adsorption geometry, resulting in higher adenine SERS intensities for cancer DNA. The possibility of detecting cancer DNA based on its SERS spectrum was validated on peripheral blood genomic DNA samples from n = 17 AML patients and n = 17 control samples, yielding an overall classification of 82% based on the 1005 cm-1 band of 5-methylcytosine. By demonstrating the potential of SERS in assessing the methylation status in the case of real-life DNA samples, the study paves the way for novel methods of diagnosing cancer. Graphical abstract.

Knee osteoarthritis grading by resonant Raman and surface-enhanced Raman scattering (SERS) analysis of synovial fluid.

In this preliminary study on synovial fluid (SF), knee osteoarthritis (OA) grading of n = 23 patients was accomplished by combining two methods: resonant Raman spectroscopy, and surface-enhanced Raman scattering (SERS) of native proteins acquired with iodide-modified silver nanoparticles and a laser emitting at 633 nm. Based on principal component analysis-linear discriminant analysis (PCA-LDA), the SERS spectra of proteins enabled the classification of low-grade and high-grade OA groups with an accuracy of 91%. Resonant Raman spectra of SF, recorded with laser excitation at 532 nm, exhibited carotenoid-associated bands that were less intense in the case of high-grade knee OA patients. Based on the resonant Raman spectra, the grading of OA patients was accomplished with an accuracy of 74%. Concatenating SERS and Raman spectral information increased the classification accuracy between the two groups to 100%. These results demonstrate the potential of Raman and SERS as a point-of-care method for aiding OA grading.

Raman spectroscopy applications in rheumatology.

Raman spectroscopy is a type of vibrational spectroscopy based on the inelastic scattering of photons, which has attracted much attention due to its potential clinical application in rheumatology. In this review, we discuss the typical spectral features of cartilage, bone, synovial fluid, and pathologic crystal deposits, as well as methods of amplifying the Raman signal of biofluids such as drop-coating deposition Raman spectroscopy. Further, applications of Raman and drop-coating deposition Raman spectroscopy in osteoarthritis are described, highlighting the clinical potential of these methods. We also discuss the role of Raman and related techniques in analyzing pathologic crystals such as monosodium urate, calcium pyrophosphate dihydrate, and hydroxyapatite. The results presented in this review demonstrate that Raman spectroscopy has grown past the stage of proof-of-concept, especially in the case of pathologies involving crystal depositions such as gout and calcium pyrophosphate deposition disease , for which the method has been validated on large number of samples. As the medical community becomes more and more aware of Raman spectroscopy, it is envisioned that it will become a standard technique in the near future.

SERS-based quantification of albuminuria in the normal-to-mildly increased range.

The lack of an accurate point-of-care detection system for microalbuminuria represents an important unmet medical need that contributes to the morbidity and mortality of patients with kidney diseases. In this proof-of-concept study, we used SERS spectroscopy to detect urinary albumin concentrations in the normal-to-mildly increased albuminuria range, a strategy that could be useful for the early diagnosis of renal impairment due to uncontrolled hypertension, cardiovascular disease or diabetes. We analyzed 27 urine samples by SERS, using iodide-modified silver nanoparticles and we could discriminate between groups with high and low albumin concentrations with an overall accuracy of 89%, 93% and 89%, using principal component analysis-linear discriminant analysis and cut-off values of 3, 6 and 10 µg mL-1 for urinary albumin concentrations, respectively. We achieved a detection limit of 3 µg mL-1 for human serum albumin based on the 1002 cm-1 SERS band, attributed to the ring breathing vibration of phenylalanine. Our detection limit is similar to that of the immunoturbidimetric assays and around one order of magnitude below the detection limit of urinary dipsticks used to detect microalbuminuria. We used principal least squares regression for building a spectral model for quantifying albumin. Using an independent prediction set, the R2 and root mean squared error of prediction between predicted and reference values of human serum albumin concentrations were 0.982 and 2.82, respectively. Here, we show that direct SERS spectroscopy has the sensitivity required for detecting clinically relevant concentrations of urinary albumin, a strategy that could be used in the future for the point-of-care screening of microalbuminuria.

Interface-Dependent Selectivity in Plasmon-Driven Chemical Reactions.

Plasmonic nanoparticles can drive chemical reactions powered by sunlight. These processes involve the excitation of surface plasmon resonances (SPR) and the subsequent charge transfer to adsorbed molecular orbitals. Nonetheless, controlling the flow of energy and charge from SPR to adsorbed molecules is still difficult to predict or tune. Here, we show the crucial role of halide ions in modifying the energy landscape of a plasmon-driven chemical reaction by carefully engineering the nanoparticle-molecule interface. By doing so, the selectivity of plasmon-driven chemical reactions can be controlled, either enhancing or inhibiting the metal-molecule charge and energy transfer or by regulating the vibrational pumping rate. These results provide an elegant method for controlling the energy flow from plasmonic nanoparticles to adsorbed molecules, in situ, and selectively targeting chemical bonds by changing the chemical nature of the metal-molecule interface.

Boosting Nitrogen Activation via Ag Nanoneedle Arrays for Efficient Ammonia Synthesis.

Electrocatalytic N2 reduction reaction (eNRR) provides a promising carbon-neutral and sustainable ammonia-synthesizing alternative to the Haber-Bosch process. However, the nonpolar N2 has significant thermodynamic stability and requires ultrahigh energy to break down the N≡N bond. Here, we report the construction of local enhanced electric fields (LEEFs) by Ag nanoneedle arrays to promote N≡N fracture thus assisting the eNRR. The LEEFs could induce charge polarization on nitrogen atoms and reduce the energy barrier in the N2 first-protonation step. The detected N─N and N─H intermediates prove the cleavage of the N≡N bond and the hydrogenation of N2 by LEEFs. The increased LEEFs lead to logarithmic growth rates for the targeted eNRR and exponential growth rates for the unavoidable competitive hydrogen evolution reaction. Thus, regulation and tuning of LEEFs to ∼4 × 104 kV m-1 endows the raise of eNRR to the summit, achieving high ammonia selectivity with a Faradaic efficiency of 72.3 ± 4.0%.

SERS Liquid Biopsy Profiling of Serum for the Diagnosis of Kidney Cancer.

Renal cancer (RC) represents 3% of all cancers, with a 2% annual increase in incidence worldwide, opening the discussion about the need for screening. However, no established screening tool currently exists for RC. To tackle this issue, we assessed surface-enhanced Raman scattering (SERS) profiling of serum as a liquid biopsy strategy to detect renal cell carcinoma (RCC), the most prevalent histologic subtype of RC. Thus, serum samples were collected from 23 patients with RCC and 27 controls (CTRL) presenting with a benign urological pathology such as lithiasis or benign prostatic hypertrophy. SERS profiling of deproteinized serum yielded SERS band spectra attributed mainly to purine metabolites, which exhibited higher intensities in the RCC group, and Raman bands of carotenoids, which exhibited lower intensities in the RCC group. Principal component analysis (PCA) of the SERS spectra showed a tendency for the unsupervised clustering of the two groups. Next, three machine learning algorithms (random forest, kNN, naïve Bayes) were implemented as supervised classification algorithms for achieving discrimination between the RCC and CTRL groups, yielding an AUC of 0.78 for random forest, 0.78 for kNN, and 0.76 for naïve Bayes (average AUC 0.77 ± 0.01). The present study highlights the potential of SERS liquid biopsy as a diagnostic and screening strategy for RCC. Further studies involving large cohorts and other urologic malignancies as controls are needed to validate the proposed SERS approach.

SERS liquid biopsy in breast cancer. What can we learn from SERS on serum and urine?

SERS analysis of biofluids, coupled with classification algorithms, has recently emerged as a candidate for point-of-care medical diagnosis. Nonetheless, despite the impressive results reported in the literature, there are still gaps in our knowledge of the biochemical information provided by the SERS analysis of biofluids. Therefore, by a critical assignment of the SERS bands, our work aims to provide a systematic analysis of the molecular information that can be achieved from the SERS analysis of serum and urine obtained from breast cancer patients and controls. Further, we compared the relative performance of five different machine learning algorithms for breast cancer and control samples classification based on the serum and urine SERS datasets, and found comparable classification accuracies in the range of 61-89%. This result is not surprising since both biofluids show striking similarities in their SERS spectra providing similar metabolic information, related to purine metabolites. Lastly, by carefully comparing the two datasets (i.e., serum and urine) we show that it is possible to link the misclassified samples to specific metabolic imbalances, such as carotenoid levels, or variations in the creatinine concentration.

SERS-based DNA methylation profiling allows the differential diagnosis of malignant lymphadenopathy.

This study highlights the potential of surface-enhanced Raman scattering (SERS) to differentiate between B-cell lymphoma (BCL), T-cell lymphoma (TCL), lymph node metastasis of melanoma (Met) and control (Ctr) samples based on the specific SERS signal of DNA extracted from lymph node tissue biopsy. Differences in the methylation profiles as well as the specific interaction of malignant and non-malignant DNA with the metal nanostructure are captured in specific variations of the band at 1005 cm-1, attributed to 5-methylcytosine and the band at 730 cm-1, attributed to adenine. Thus, using the area ratio of these two SERS marker bands as input for univariate classification, an area under the curve (AUC) of 0.70 was achieved in differentiating between malignant and non-malignant DNA. In addition, DNA from the BCL and TCL groups exhibited differences in the area of the SERS band at 730 cm-1, yielding an AUC of 0.84 in differentiating between these two lymphadenopathies. Lastly, using multivariate data analysis techniques, an overall accuracy of 94.7% was achieved in the differential diagnosis between the BCL, TCL, Met and Ctr groups. These results pave the way towards the implementation of SERS as a novel tool in the clinical setting for improving the diagnosis of malignant lymphadenopathy.

SERS-Based Evaluation of the DNA Methylation Pattern Associated With Progression in Clonal Leukemogenesis of Down Syndrome.

Here we show that surface-enhanced Raman scattering (SERS) analysis captures the relative hypomethylation of DNA from patients with acute leukemia associated with Down syndrome (AL-DS) compared with patients diagnosed with transient leukemia associated with Down syndrome (TL-DS), an information inferred from the area under the SERS band at 1005 cm-1 attributed to 5-methycytosine. The receiver operating characteristic (ROC) analysis of the area under the SERS band at 1005 cm-1 yielded an area under the curve (AUC) of 0.77 in differentiating between the AL-DS and TL-DS groups. In addition, we showed that DNA from patients with non-DS myeloproliferative neoplasm (non-DS-MPN) is hypomethylated compared to non-DS-AL, the area under the SERS band at 1005 cm-1 yielding an AUC of 0.78 in separating between non-DS-MPN and non-DS-AL. Overall, in this study, the area of the 1005 cm-1 DNA SERS marker band shows a stepwise decrease in DNA global methylation as cells progress from a pre-leukemia to a full-blown acute leukemia, highlighting thus the potential of SERS as an emerging method of analyzing the methylation landscape of DNA in the context of leukemia genesis and progression.