Ultra-sensitive SERS detection of perfluorooctanoic acid based on self-assembled p-phenylenediamine nanoparticle complex

Rapid detection of perfluorooctanoic acid by surface enhanced Raman spectroscopy and deep learning

Perfluorooctanoic acid (PFOA) has received increasing concerns in recent years due to its wide distribution and potential toxicity. Existing detection techniques of PFOA require complex pre-treatment, therefore often taking several hours. Here, we developed a rapid PFOA detection mode to detect approximate concentrations of PFOA (ranging from 10-15 to 10-3 mol/L) in deionized water, and detecting one sample takes only 20 min. The detection mode was achieved using a deep learning model trained by a large surface enhanced Raman spectra dataset, based on the agglomeration of PFOA with crystal violet. In addition, transfer learning approach was used to fine tune the model, the fine-tuned model was generalizable across water samples with different impurities and environments to determine whether meet the safety standards of PFOA, the accuracy was 96.25 % and 94.67 % for tap water and lake water samples, respectively. The mechanism and specificity of the detection mode were further confirmed by molecular dynamics simulation. Our work provides a promising solution for PFOA detection, especially in the context of the increasingly widespread application of PFOA.

"Partner" cellulose gel with "dialysis" function: Achieve the integration of filtration-enrichment-SERS detection

Hydrogel and aerogel materials have garnered significant attention in constructing effective surface-enhanced Raman spectroscopy (SERS) substrates due to their excellent adsorption capabilities, high specific surface area, and abundant chemical groups. However, in liquids with complex compositions, non-specific adsorption of macromolecules can lead to surface scaling and pore clogging of the substrate material, limiting the selective enrichment and SERS detection of target molecules. To address this, an innovative aerogel-chimeric hydrogel material (CH@S-CNF/SA/Ag NPs) was developed. The aerogel component, with its high specific surface area and electronegative properties, functions as a SERS "chip" for adsorption and detection of target molecules. Simultaneously, the mesoporous structure of the hydrogel "shell" effectively filters macromolecules from the solution. These CH@S-CNF/SA/Ag NPs were utilized as SERS substrate materials for detecting urine from healthy individuals and patients with chronic kidney disease stage 5 (CKD5). When combined with machine learning algorithms, the detection accuracy reached 99.50%. This work represents a significant advancement in the specific adsorption and SERS detection of small molecules in complex biological samples such as urine and blood.

Generic method for the detection of short & long chain PFAS extended to the lowest concentration levels of SERS capability

The detection of the highly toxic per- and polyfluoroalkyl substances, PFAS, constitutes a challenging task in terms of developing a generic method that could be rapid and applicable simultaneously to both long and short-chain PFAS at ppt concentration level. In the present study, the method introduced by the USA Environmental Protection Agency, EPA, to detect surfactants, using methylene blue, MB, which is identified an ideal candidate for PFAS-MB ion pairing, is extended at the lowest concentration range by a simple additional step that involves the dissociation of the ion pairs in water. In this work, Surface Enhanced Raman Scattering, SERS, is applied via Ag nanocolloidal suspensions to probe MB and indirectly either/or both short-chain (perfluorobutyric acid, PFBA) and long-chain (perfluoloctanoic acid, PFOA) PFAS downt to 5 ppt. This method, which can be further optimized to sub-ppt level via a custom-made SERS-PFAS dedicated Raman system, offers the possibility to be applied to either specific PFAS (both short and long-chain) in a targeted analysis or to total PFAS in a non-targeted analysis at very low detection limits, following any type of MB detection method in aqueous solutions and obviously with any type of SERS substrate.

Dual-mode electrochemical and SERS detection of PFAS using functional porous substrate

Human activity is the cause of the continuous and gradual grooving of environmental contaminants, where some released toxic and dangerous compounds cannot be degraded under natural conditions, resulting in a serious safety issue. Among them are the widely occurring water-soluble perfluoroalkyl and polyfluoroalkyl substances (PFAS), sometimes called "forever chemicals" because of the impossibility of their natural degradation. Hence, a reliable, expressive, and simple method should be developed to monitor and eliminate the risks associated with these compounds. In this study, we propose a simple, express, and portable detection method for water-soluble fluoro-alkyl compounds (PFOA and GenX) using mutually complementary methods: electrochemical impedance spectroscopy (EIS) and surface-enhanced Raman spectroscopy (SERS). To implement our method, we developed special substrates based on porous silicon with a top-deposited plasmon-active Au layer by subsequently grafting -C6H4-NH2 chemical moieties to provide surface affinity toward negatively charged water-soluble PFAS. Subsequent EIS utilization allows us to perform semiquantitative detection of PFOA and GenX up to 10-10 M concentration because surface entrapping of PFAS leads to a significant increase in the electrode-electrolyte charge-transfer resistance. However, distinguishing by EIS whether even PFAS were entrapped was impossible, and thus the substrates were subsequently subjected to SERS measurements (allowed by surface plasmon activity due to the presence of a porous Au layer), clearly indicating the appearance of characteristic C-F vibration bands.

Novel Conductive and Redox-Active Molecularly Imprinted Polymer for Direct Quantification of Perfluorooctanoic Acid

This study developed a novel molecularly imprinted polymer (MIP) that is both conductive and redox-active for directly quantifying perfluorooctanoic acid (PFOA) electrochemically. We synthesized the monomer 3,4-ethylenedioxythiophene-2,2,6,6-tetramethylpiperidinyloxy (EDOT-TEMPO) for electropolymerization on a glassy carbon electrode using PFOA as a template, which was abbreviated as PEDOT-TEMPO-MIP. The redox-active MIP eliminated the need for external redox probes. When exposed to PFOA, both anodic and cathodic peaks of MIP showed a decreased current density. This observation can be explained by the formation of a charge-assisted hydrogen bond between the anionic PFOA and MIP's redox-active moieties (TEMPO) that hinder the conversion between the oxidized and reduced forms of TEMPO. The extent of the current density decrease showed excellent linearity with PFOA concentrations, with a method detection limit of 0.28 ng·L-1. PEDOT-TEMPO-MIP also exhibited high selectivity toward PFOA against other per- and polyfluoroalkyl substances (PFAS) at environmentally relevant concentrations. Our results suggest electropolymerization of MIPs was highly reproducible, with a relative standard deviation of 5.1% among three separate MIP electrodes. PEDOT-TEMPO-MIP can also be repeatedly used with good stability and reproducibility for PFOA detection. This study provides an innovative platform for rapid PFAS quantification using redox-active MIPs, laying the groundwork for developing compact PFAS sensors.

Polymerization-Induced Hierarchical Hybrid Particles from Siloxane Emulsification Endowing Polyurethane Composite Coating with Superhydrophobicity, Thermal Insulation, and Fluorescence

Hierarchically structural particles (HSPs) are highly regarded as favorable nanomaterials for superhydrophobic coating due to their special multiscale structure and surface physicochemical properties. However, most of the superhydrophobic coatings constructed from HSPs are monofunctional, constraining their broader applications. Moreover, traditional methods for constructing HSPs mostly rely on complicated chemical routes and template removal. Herein, we propose an innovative strategy (one-pot method) for producing multifunctional hierarchical hybrid particles (HHPs). Polysilsesquioxane (PSQ), generated from hydrolysis condensation of methyltriethoxylsilane, is used as the sole stabilizer to anchor on the surface of styrene and short fluoroalkyl compound tridecafluorooctyl acrylate comonomers droplets, forming a mesoporous PSQ shell. Subsequently, the comonomers inside of the shell perform restricted polymerization to generate the HHP due to the driving of the mesoporous capillary force. The HHP is then mixed with waterborne polyurethane (WPU) to develop a robust nanocomposite coating (WPU-HHP). Through the deliberate design of the HHP components, the WPU-HHP coating has thermal insulation, photoluminescence properties, and the ability to achieve a wettability transition during abrasion. Our research has achieved the integration of multifunctionality in one waterborne hybrid system, broadening the application areas of nanocomposite coatings.

Lanthanide metal-organic framework-based surface molecularly imprinted polymers ratiometric fluorescence probe for visual detection of perfluorooctanoic acid with a smartphone-assisted portable device

Perfluorooctanoic acid (PFOA) poses a threat to the environment and human health due to its persistence, bioaccumulation, and reproductive toxicity. Herein, a lanthanide metal-organic framework (Ln-MOF)-based surface molecularly imprinted polymers (SMIPs) ratiometric fluorescence probe (Eu/Tb-MOF@MIPs) and a smartphone-assisted portable device were developed for the detection of PFOA with high selectivity in real water samples. The integration of Eu/Tb MOFs as carriers not only had highly stable multiple emission signals but also prevented deformation of the imprinting cavity of MIPs. Meanwhile, the MIPs layer preserved the fluorescence of Ln-MOF and provided selective cavities for improved specificity. Molecular dynamics (MD) was employed to simulate the polymerization process of MIPs, revealing that the formation of multiple recognition sites was attributed to the establishment of hydrogen bonds between functional monomers and templates. The probe showed a good linear relationship with PFOA concentration in the range of 0.02-2.8 μM, by giving the limit of detection (LOD) of 0.98 nM. Additionally, The red-green-blue (RGB) values analysis based on the smartphone-assisted portable device demonstrated a linear relationship of 0.1-2.8 μM PFOA with the LOD of 3.26 nM. The developed probe and portable device sensing platform exhibit substantial potential for on-site detecting PFOA in practical applications and provide a reliable strategy for the intelligent identification of important targets in water environmental samples.

Decoding PFAS contamination via Raman spectroscopy: A combined DFT and machine learning investigation

In this study, density function theory (DFT) is employed to compute Raman spectra of 40 important Perfluoroalkyl substances (PFASs) as listed in Draft Method 1633 by U.S. Environmental Protection Agent. A systematic comparison of their spectral features is conducted, and Raman peaks and vibrational modes are identified. The Raman spectral regions for the main chemical bonds (such as C-C, CF2 & CF3, O-H) and main functional groups (such as -COOH, -SO3H, -C2H4SO3H, and -SO2NH2) are identified and compared. The impacts of branching location in isomer, molecular chain length, and functional groups on the Raman spectra are analyzed. Particularly, the isomers of PFOA alter the peak locations slightly in wavenumber regions of 200 - 800 and 1000 - 1400 cm-1, while for PFOS, spectral features in the 230 - 360, 470 - 680, and 1030 - 1290 cm-1 regions exhibit significant difference. The carbon chain length can significantly increase the number of Raman peaks, while different functional groups give significantly different peak locations. To facilitate differentiation, a spectral database is constructed by introducing controlled noise into the DFT-computed Raman spectra. Subsequently, two chemometric techniques, principal component analysis (PCA) and t-distributed stochastic neighbor embedding (t-SNE), are applied to effectively distinguish among these spectra, both for 40 PFAS compounds and the isomers. The findings demonstrate the promising potential of combining Raman spectroscopy with advanced spectral analysis methods to discriminate between distinct PFAS compounds, holding significant implications for improved PFAS detection and characterization methodologies.

Highly Sensitive and Wide-Range Detection of Thiabendazole via Surface-Enhanced Raman Scattering Using Bimetallic Nanoparticle-Functionalized Nanopillars

Thiabendazole (TBZ) is a benzimidazole; owing to its potent antimicrobial properties, TBZ is extensively employed in agriculture as a fungicide and pesticide. However, TBZ poses environmental risks, and excessive exposure to TBZ through various leakage pathways can cause adverse effects in humans. Therefore, a method must be developed for early and sensitive detection of TBZ over a range of concentrations, considering both human and environmental perspectives. In this study, we used silver nanopillar structures (SNPis) and Au@Ag bimetallic nanoparticles (BNPs) to fabricate a BNP@SNPi substrate. This substrate exhibited a broad reaction surface with significantly enhanced surface-enhanced Raman scattering hotspots, demonstrating excellent Raman performance, along with high reproducibility, sensitivity, and selectivity for TBZ detection. Ultimately, the BNP@SNPi substrate successfully detected TBZ across a wide concentration range in samples of tap water, drinking water, juice, and human serum, with respective limits of detection of 146.5, 245.5, 195.6, and 219.4 pM. This study highlights BNP@SNPi as a promising sensor platform for TBZ detection in diverse environments and contributes to environmental monitoring and bioanalytical studies.