Discrimination between hydrogen bonding and protonation in the spectra of a surface-enhanced Raman sensor

Molecular Self-Assembly and Adsorption Structure of 2,2'-Dipyrimidyl Disulfides on Au(111) Surfaces

The effects of solution concentration and pH on the formation and surface structure of 2-pyrimidinethiolate (2PymS) self-assembled monolayers (SAMs) on Au(111) via the adsorption of 2,2'-dipyrimidyl disulfide (DPymDS) were examined using scanning tunneling microscopy (STM) and X-ray photoelectron spectroscopy (XPS). STM observations revealed that the formation and structural order of 2PymS SAMs were markedly influenced by the solution concentration and pH. 2PymS SAMs formed in a 0.01 mM ethanol solution were mainly composed of a more uniform and ordered phase compared with those formed in 0.001 mM or 1 mM solutions. SAMs formed in a 0.01 mM solution at pH 2 were composed of a fully disordered phase with many irregular and bright aggregates, whereas SAMs formed at pH 7 had small ordered domains and many bright islands. As the solution pH increased from pH 7 to pH 12, the surface morphology of 2PymS SAMs remarkably changed from small ordered domains to large ordered domains, which can be described as a (4√2 × 3)R51° packing structure. XPS measurements clearly showed that the adsorption of DPymDS on Au(111) resulted in the formation of 2PymS (thiolate) SAMs via the cleavage of the disulfide (S-S) bond in DPymDS, and most N atoms in the pyrimidine rings existed in the deprotonated form. The results herein will provide a new insight into the molecular self-assembly behaviors and adsorption structures of DPymDS molecules on Au(111) depending on solution concentration and pH.

Surface-Enhanced Raman Scattering-Based Surface Chemotaxonomy: Combining Bacteria Extracellular Matrices and Machine Learning for Rapid and Universal Species Identification

Rapid, universal, and accurate identification of bacteria in their natural states is necessary for on-site environmental monitoring and fundamental microbial research. Surface-enhanced Raman scattering (SERS) spectroscopy emerges as an attractive tool due to its molecule-specific spectral fingerprinting and multiplexing capabilities, as well as portability and speed of readout. Here, we develop a SERS-based surface chemotaxonomy that uses bacterial extracellular matrices (ECMs) as proxy biosignatures to hierarchically classify bacteria based on their shared surface biochemical characteristics to eventually identify six distinct bacterial species at >98% classification accuracy. Corroborating with in silico simulations, we establish a three-way inter-relation between the bacteria identity, their ECM surface characteristics, and their SERS spectral fingerprints. The SERS spectra effectively capture multitiered surface biochemical insights including ensemble surface characteristics, e.g., charge and biochemical profiles, and molecular-level information, e.g., types and numbers of functional groups. Our surface chemotaxonomy thus offers an orthogonal taxonomic definition to traditional classification methods and is achieved without gene amplification, biochemical testing, or specific biomarker recognition, which holds great promise for point-of-need applications and microbial research.

Water-phase synthesis of Au and Au-Ag nanowires and their SERS activity

Metal nanowires (NWs) with a diameter of a few nanometers have attracted considerable attention as a promising one-dimensional nanomaterial due to their inherent flexibility and conductive properties and their weak plasmon absorption in the visible region. In a previous paper, we reported the synthesis of ultrathin 1.8 nm-diameter Au NWs using toluene-solubilized aqueous solutions of a long-chain amidoamine derivative (C18AA). This study investigates the effect of different organic solvents solubilized in C18AA aqueous solutions on the morphology of the Au products and demonstrates that solubilizing methylcyclohexane yields thick 2.7 nm-diameter Au NWs and 3.3 nm-diameter Au-Ag alloy NWs. Further, the surface-enhanced Raman scattering sensitivity of ultrathin Au NWs, thick Au NWs, and thick Au-Ag alloy NWs were assessed using 4-mercaptopyridine and found that their enhancement factors are 10⁴-10⁵ and the order is Au-Ag NWs > thick Au NWs > ultrathin Au NWs.

Inducing Ring Complexation for Efficient Capture and Detection of Small Gaseous Molecules Using SERS for Environmental Surveillance

Gas-phase surface-enhanced Raman scattering (SERS) remains challenging due to poor analyte affinity to SERS substrates. The reported use of capturing probes suffers from concurrent inconsistent signals and long response time due to the formation of multiple potential probe-analyte interaction orientations. Here, we demonstrate the use of multiple non-covalent interactions for ring complexation to boost the affinity of small gas molecules, SO₂ and NO₂ , to our SERS platform, achieving rapid capture and multiplex detection down to 100 ppm. Experimental and in-silico studies affirm stable ring complex formation, and kinetic investigations reveal a 4-fold faster response time compared to probes without stable ring complexation capability. By synergizing spectral concatenation and support vector machine regression, we achieve 91.7 % accuracy for multiplex quantification of SO₂ and NO₂ in excess CO₂ , mimicking real-life exhausts. Our platform shows immense potential for on-site exhaust and air quality surveillance.

Real-time Tracking and Sensing of Cu+ and Cu2+ with a Single SERS Probe in the Live Brain: Toward Understanding Why Copper Ions Were Increased upon Ischemia

The imbalance of Cu⁺ and Cu²⁺ in the brain is closely related to neurodegenerative diseases. However, it still lacks of effective analytical methods for simultaneously determining the concentrations of Cu⁺ and Cu²⁺ . Herein, we created a novel SERS probe (CuSP) to real-time track and accurately quantify extracellular concentrations of Cu⁺ and Cu²⁺ in the live brain. The present CuSP probe demonstrated specific ability for recognition of Cu⁺ and Cu²⁺ in a dual-recognition mode. Then, a microarray consisting of 8 CuSP probes with high tempo-spatial resolution and good accuracy was constructed for tracking and simultaneously biosensing of Cu⁺ and Cu²⁺ in the cerebral cortex of living brain. Using our powerful tool, it was found that that the concentrations of Cu²⁺ and Cu⁺ were increased by ≈4.26 and ≈1.80 times upon ischemia, respectively. Three routes were first discovered for understanding the mechanisms of the increased concentrations of Cu⁺ and Cu²⁺ during ischemia.

Quantitative characterisation of the ring normal modes. Pyridine as a study case

In the present work, the vibrational normal modes (NM) of pyridine were revisited. Quantum Chemical calculations were performed to help understand the true nature of some ring related vibrational normal modes (RNM) and how they may be correlated with the electronic structure on the ring. The 27 vibrational normal modes were decomposed into the molecular internal coordinates, and the interest was focused on 7 of them, involving the in-plane ring motion. The electronic structure was analysed through frontier Molecular Orbitals (MO), maps of Molecular Electrostatic Potential surfaces (MEPs) and Natural Bond Orbital (NBO) analysis in a dynamic manner, wherein, each vibration was scanned. The present investigation is aimed to provide the Reader with a quantitative characterisation of the RNMs of pyridine.

In Situ Differentiation of Multiplex Noncovalent Interactions Using SERS and Chemometrics

Probing changes of noncovalent interactions is crucial to study the binding efficiencies and strengths of (bio)molecular complexes. While surface-enhanced Raman scattering (SERS) offers unique molecular fingerprints to examine such interactions in situ, current platforms are only able to recognize hydrogen bonds because of their reliance on manual spectral identification. Here, we differentiate multiple intermolecular interactions between two interacting species by synergizing plasmonic liquid marble-based SERS platforms, chemometrics, and density functional theory. We demonstrate that characteristic 3-mercaptobenzoic acid (probe) Raman signals have distinct peak shifts upon hydrogen bonding and ionic interactions with tert-butylamine, a model interacting species. Notably, we further quantify the contributions from each noncovalent interaction coexisting in different proportions. As a proof-of-concept, we detect and categorize biologically important nucleotide bases based on molecule-specific interactions. This will potentially be useful to study how subtle changes in biomolecular interactions affect their structural and binding properties.

An Open Source, Iterative Dual-Tree Wavelet Background Subtraction Method Extended from Automated Diffraction Pattern Analysis to Optical Spectroscopy

Background subtraction is a general problem in spectroscopy often addressed with application-specific techniques, or methods that introduce a variety of implementation barriers such as having to specify peak-free regions of the spectrum. An iterative dual-tree complex wavelet transform-based background subtraction method (DTCWT-IA) was recently developed for the analysis of ultrafast electron diffraction patterns. The method was designed to require minimal user intervention, to support streamlined analysis of many diffraction patterns with complex overlapping peaks and time-varying backgrounds, and is implemented in an open-source computer program. We examined the performance of DTCWT-IA for the analysis of spectra acquired by a range of optical spectroscopies including ultraviolet-visible spectroscopy (UV-Vis), X-ray photoelectron spectroscopy (XPS), and surface-enhanced Raman spectroscopy (SERS). A key benefit of the method is that the user need not specify regions of the spectrum where no peaks are expected to occur. SER spectra were used to investigate the robustness of DTCWT-IA to signal-to-noise levels in the spectrum and to user operation, specifically to two of the algorithm parameter settings: decomposition level and iteration number. The single, general DTCWT-IA implementation performs well in comparison to the different conventional approaches to background subtraction for UV-Vis, XPS, and SERS, while requiring minimal input. The method thus holds the same potential for optical spectroscopy as for ultrafast electron diffraction, namely streamlined analysis of spectra with complex distributions of peaks and varying signal levels, thus supporting real-time spectral analysis or the analysis of data acquired from different sources.

Hydrogel Microdomain Encapsulation of Stable Functionalized Silver Nanoparticles for SERS pH and Urea Sensing

Conceptual and commercial examples of implantable sensors have been limited to a relatively small number of target analytes, with a strong focus on glucose monitoring. Recently, surface-enhanced Raman spectroscopy (SERS) pH sensors were demonstrated to track acid-producing enzymatic reactions targeting specific analytes. We show here that SERS pH tracking in the basic regime is also possible, and can be used to monitor urea concentration. To accomplish this, we developed a hydrogel consisting of polyelectrolyte multilayer microcapsules containing a SERS-sensitive pH reporter (4-mercapopyridine capped silver nanoparticles modified with bovine serum albumin). This pH sensing material exhibited a sensitive Raman scattering response to a wide range of pH from 6.5-9.7. By incorporating urease into the hydrogel matrix, the new sensor was capable of distinguishing urea concentrations of 0, 0.1, 1, and 10 mM. We also found that bovine serum albumin (BSA) prevented severe aggregation of the nanoparticle-based pH sensor, which improved sensing range and sensitivity. Furthermore, BSA safeguarded the pH sensor during the encapsulation procedure. Together, the combination of materials represents a novel approach to enabling optical sensing of reactions that generate pH changes in the basic range.