Principal Component Analysis of Surface-Enhanced Raman Scattering Spectra Revealing Isomer-Dependent Electron Transport in Spiropyran Molecular Junctions: Implications for Nanoscale Molecular Electronics

A facile paper-based chromatography coupled Au nanodendrite on nickel foam for application in separation and SERS measurement

A simple paper-based chromatography coupling with nickel foam decorated Au nanodendrite (PP-AuND/NiF) was fabricated for simultaneous separation and surface-enhanced Raman scattering (SERS) detection of Rhodamine-6G (R6G) from a mixture of analytes. The three-dimensional porous nickel foam (NiF) was employed as a sampling diffusion platform, and AuND with a high surface active area beneficial for SERS efficiency was electro-deposited directly onto the NiF frame. The structure of AuND/NiF was characterized by X-ray diffraction and scanning electron microscopy. The AuND/NiF could detect R6G at 0.1 nM, and the enhancement factor was 1.84 x 106. The AuND/NiF was durable, with a slight signal decrease after 6 m of drop-testing. Also, upon three days of exposure to ambient air, the signal droped only 3.35 %. Subsequently, the PP-AuND/NiF was constructed by directly situating AuND/NiF on a paper strip, serving as a sample in and out to AuND/NiF. A mixture of two SERS active compounds, namely 2-Naphthalenethiol (2-NpSH) and Rhodamine 6G (R6G), was prepared in ethanol: water (1:1) solution to evaluate PP-AuND/NiF separation capability. Raman measurements along different distances of AuND/NiF were performed, and the signal of 2-NpSH was dismissed after 3.0 mm, while R6G's signals were observed throughout AuND/NiF. In general, the PP-AuND/NiF demonstrated effective separation and SERS measurement of analytes in a mixture, which could be applicable for more complex samples in the future, especially in clinical analysis.

An Orthogonal Conductance Pathway in Spiropyrans for Well-Defined Electrosteric Switching Single-Molecule Junctions

While a multitude of studies have appeared touting the use of molecules as electronic components, the design of molecular switches is crucial for the next steps in molecular electronics. In this work, single-molecule devices incorporating spiropyrans, made using break junction techniques, are described. Linear spiropyrans with electrode-contacting groups linked by alkynyl spacers to both the indoline and chromenone moieties have previously provided very low conductance values, and removing the alkynyl spacer has resulted in a total loss of conductance. An orthogonal T-shaped approach to single-molecule junctions incorporating spiropyran moieties in which the conducting pathway lies orthogonal to the molecule backbone is described and characterized. This approach has provided singlemolecule conductance features with good correlation to molecular length. Additional higher conducting states are accessible using switching induced by UV light or protonation. Theoretical modeling demonstrates that upon (photo)chemical isomerization to the merocyanine, two cooperating phenomena increase conductance: release of steric hindrance allows the conductance pathway to become more planar (raising the mid-bandgap transmission) and a bound state introduces sharp interference near the Fermi level of the electrodes similarly responding to the change in state. This design step paves the way for future use of spiropyrans in single-molecule devices and electrosteric switches.

Surface-Enhanced Raman Spectroscopy-Based Detection of Micro-RNA Biomarkers for Biomedical Diagnosis Using a Comparative Study of Interpretable Machine Learning Algorithms

Surface-enhanced Raman spectroscopy (SERS) has wide diagnostic applications due to narrow spectral features that allow multiplex analysis. We have previously developed a multiplexed, SERS-based nanosensor for micro-RNA (miRNA) detection called the inverse molecular sentinel (iMS). Machine learning (ML) algorithms have been increasingly adopted for spectral analysis due to their ability to discover underlying patterns and relationships within large and complex data sets. However, the high dimensionality of SERS data poses a challenge for traditional ML techniques, which can be prone to overfitting and poor generalization. Non-negative matrix factorization (NMF) reduces the dimensionality of SERS data while preserving information content. In this paper, we compared the performance of ML methods including convolutional neural network (CNN), support vector regression, and extreme gradient boosting combined with and without NMF for spectral unmixing of four-way multiplexed SERS spectra from iMS assays used for miRNA detection. CNN achieved high accuracy in spectral unmixing. Incorporating NMF before CNN drastically decreased memory and training demands without sacrificing model performance on SERS spectral unmixing. Additionally, models were interpreted using gradient class activation maps and partial dependency plots to understand predictions. These models were used to analyze clinical SERS data from single-plexed iMS in RNA extracted from 17 endoscopic tissue biopsies. CNN and CNN-NMF, trained on multiplexed data, performed most accurately with RMSElabel = 0.101 and 9.68 × 10-2, respectively. We demonstrated that CNN-based ML shows great promise in spectral unmixing of multiplexed SERS spectra, and the effect of dimensionality reduction on performance and training speed.

Light-driven modulation of electrical conductance with photochromic switches: bridging photochemistry with optoelectronics

Photochromic conducting molecules have emerged because of their unique capacity to modulate electrical conductivity upon exposure to light, toggling between high and low conductive states. This unique amalgamation has unlocked novel avenues for the application of these materials across diverse areas in optoelectronics and smart materials. The fundamental mechanism underpinning this phenomenon is based on the light-driven isomerization of conjugated π-systems which influences the extent of conjugation. The photoisomerization process discussed here involves photochromic switches such as azobenzenes, diarylethenes, spiropyrans, dimethyldihydropyrenes, and norbornadiene. The change in the degree of conjugation alters the charge transport in both single molecules and bulk states in solid samples or solutions. This article discusses a number of recent examples of photochromic conducting systems and the challenges and potentials of the field.

Intermolecular and Electrode-Molecule Bonding in a Single Dimer Junction of Naphthalenethiol as Revealed by Surface-Enhanced Raman Scattering Combined with Transport Measurements

Electron transport through noncovalent interaction is of fundamental and practical importance in nanomaterials and nanodevices. Recent single-molecule studies employing single-molecule junctions have revealed unique electron transport properties through noncovalent interactions, especially those through a π-π interaction. However, the relationship between the junction structure and electron transport remains elusive due to the insufficient knowledge of geometric structures. In this article, we employ surface-enhanced Raman scattering (SERS) synchronized with current-voltage (I-V) measurements to characterize the junction structure, together with the transport properties, of a single dimer and monomer junction of naphthalenethiol, the former of which was formed by the intermolecular π-π interaction. The correlation analysis of the vibrational energy and electrical conductance enables identifying the intermolecular and molecule-electrode interactions in these molecular junctions and, consequently, addressing the transport properties exclusively associated with the π-π interaction. In addition, the analysis achieved discrimination of the interaction between the NT molecule and the Au electrode of the junction, i.e., Au-π interactions through-π coupling and though-space coupling. The power density spectra support the noncovalent character at the interfaces in the molecular junctions. These results demonstrate that the simultaneous SERS and I-V technique provides a unique means for the structural and electrical investigation of noncovalent interactions.

Label-free detection and discrimination of respiratory pathogens based on electrochemical synthesis of biomaterials-mediated plasmonic composites and machine learning analysis

Seasonal outbreaks of respiratory viral infections remain a global concern, with increasing morbidity and mortality rates recorded annually. Timely and false responses contribute to the widespread of respiratory pathogenic diseases owing to similar symptoms at an early stage and subclinical infection. The prevention of emerging novel viruses and variants is also a big challenge. Reliable point-of-care diagnostic assays for early infection diagnosis play a critical role in the response to threats of epidemics or pandemics. We developed a facile method for specifically identifying different viruses based on surface-enhanced Raman spectroscopy (SERS) with pathogen-mediated composite materials on Au nanodimple electrodes and machine learning (ML) analyses. Virus particles were trapped in three-dimensional plasmonic concave spaces of the electrode via electrokinetic preconcentration, and Au films were simultaneously electrodeposited, leading to the acquisition of intense and in-situ SERS signals from the Au-virus composites for ultrasensitive SERS detection. The method was useful for rapid detection analysis (<15 min), and the ML analysis for specific identification of eight virus species, including human influenza A viruses (i.e., H1N1 and H3N2 strains), human rhinovirus, and human coronavirus, was conducted. The highly accurate classification was achieved using the principal component analysis-support vector machine (98.9%) and convolutional neural network (93.5%) models. This ML-associated SERS technique demonstrated high feasibility for direct multiplex detection of different virus species for on-site applications.

Near-field circular dichroism of single molecules

Near-field images of molecules provide information about their excited orbitals, giving rise to photonic and chemical functions. Such information is crucial to the elucidation of the full potential of molecules as components in functional materials and devices at the nanoscale. However, direct imaging inside single molecules with a complex structure in the near-field is still challenging because it requires in situ observation at a higher resolution than the molecular scale. Here, using a proven theoretical method that has demonstrated sub-nanoscale resolution based on photoinduced force microscopy (PiFM) experiment [Nat. Commun.12, 3865 (2021)10.1038/s41467-021-24136-2], we propose an approach to obtaining the near-field imaging with spatial patterns of electronic transitions of single molecules. We use an extended discrete dipole approximation method that incorporates microscopic nonlocal optical response of molecules and demonstrate that PiFM can visualize circular-dichroism signal patterns at sub-nanometer scale for both optically allowed and forbidden transitions. The result will open the possibility for the direct observation of complex spatial patterns of electronic transitions in a single molecule, providing insight into the optical function of single molecules and helping realize new functional materials and devices.