Application of FTIR two-dimensional correlation spectroscopy (2D-COS) analysis in characterizing environmental behaviors of microplastics: A systematic review.

Microplastics (MPs) are ubiquitous in the environment, continuously undergo aging processes and release toxic chemical substances. Understanding the environmental behaviors of MPs is critical to accurately evaluate their long-term ecological risk. Generalized two-dimensional correlation spectroscopy (2D-COS) is a powerful tool for MPs studies, which can dig more comprehensive information hiding in the conventional one-dimensional spectra, such as infrared (IR) and Raman spectra. The recent applications of 2D-COS in analyzing the behaviors and fates of MPs in the environment, including their aging processes, and interactions with natural organic matter (NOM) or other chemical substances, were summarized systematically. The main requirements and limitations of current approaches for exploring these processes are discussed, and the corresponding strategies to address these limitations and drawbacks are proposed as well. Finally, new trends of 2D-COS are prospected for analyzing the properties and behaviors of MPs in both natural and artificial environmental processes.

Two-Dimensional Correlation Spectroscopy (2D-COS) Tracking of the Formation of Selected Transition Metal Compounds Cu(II) and Cd(II) With Cinchonine and Their Impact on Model Components of Erythrocytes.

Cinchonine is a quinoline alkaloid known for its antimalarial properties. Due to the advantages of using compounds of metal ions with alkaloids, a copper(II) compound with cinchonine was synthesized, and, for comparative purposes, a cadmium(II) compound with cinchonine. During the synthesis, the emerging interactions between the metal ion and cinchonine were studied. After crystallization, it was examined how the obtained compounds would interact with the model blood component, hematoporphyrin IX. Ultraviolet-visible (UV-Vis) spectroscopy, Raman spectroscopy, and attenuated total reflection Fourier transform infrared spectroscopy (ATR FT-IR) were used in the study. In the case of monitoring the synthesis, the best method turned out to be UV-Vis spectroscopy, combined with the possibility of two-dimensional correlation spectroscopy (2D-COS), which enabled the identification of peaks characteristic of the interactions of the cinchonine quinoline ring with metal ions. In turn, the obtained Raman spectra showed shifts of individual bands and changes in their intensity, and 2D-COS showed the sequence of formation of individual interactions, which confirmed the formation of cinchonine compounds with metals. ATR FT-IR also allowed us to compare the spectra of the substrates used in the synthesis with the crystallized compounds and thus confirm the formation of the expected compounds. Bands characteristic of π-π-stacking interactions between the quinoline ring and the tetrapyrrole ring of hematoporphyrin IX were also observed. Observed interaction with a model blood component may be important when designing drugs for antimalarial therapy.

Can Two-Dimensional Correlation Spectroscopy (2D-COS) Indicate Biocompatible Material?

Carbon nanofibers are a new type of carbon materials. One of the methods of obtaining them is the carbonization of a polymer precursor. They are attractive in many areas, including medicine, due to the possibility of modifying their properties in a wide range. For example, the conditions of the carbonization process result in the creation of materials with designed structures and surface parameters. In the current work, the nanoprecursor was polyacrylonitrile (PAN) fibers. Two types of carbon fibers obtained by carbonization of the PAN precursor at 1000 °C were tested. The first electrospun carbon nanofibers (ESCNFs) were cytotoxic, while the second ESCNF-f were biocompatible after functionalization. The parameters obtained from Raman tests did not clearly discriminate between the tested materials. Multiwavelength Raman studies, analyzed using the two-dimensional correlation spectroscopy (2D-COS), treating the laser energy as an external disturbance, showed a difference between both fibrous structures. 2D-COS indicates that structures resembling graphite systems, devoid of disordered carbon forms, are nontoxic.

Simultaneous Measurement of Two-Trace Two-Dimensional (2T2D) Near-Infrared (NIR) Asynchronous Correlation Spectra and Small-Angle X-ray Scattering (SAXS) to Characterize Thermally Aged Polypropylene (PP).

In this study, a new system was developed to carry out simultaneous near-infrared (NIR) and small-angle X-ray scattering (SAXS) measurements. Aged polypropylene (PP) was examined with the NIR-SAXS system to demonstrate how it can be utilized to derive pertinent information about the polymer structure. Pairs of SAXS profiles and NIR spectra of PP in its initial state and after aging were measured to derive an in-depth understanding of the aging phenomenon. The SAXS profiles of the PP samples showed a clear shift of the SAXS peak to the lower q direction induced by the thermal aging, indicating an increase in the length of the long-period structure. Two-trace two-dimensional (2T2D) asynchronous correlation spectra derived from NIR spectra clearly revealed that the aging treatment leads to a substantial increase in the spectral intensity of the regularity bands representing the longer helix present in a folded lamellar structure. In other words, it suggests that the long helix structure is more abundantly present than the short helix structure in the aged PP than in the initial PP. By combining the information derived from the SAXS profiles and NIR spectra, the details of the aging-induced variation were clearly determined. Namely, aging causes additional crystallization of the PP by developing more helical structures, which involves an increase in the lamellar thickness as well as a decrease in the amorphous region. The growth of the rigid crystalline phase restricts the elastic deformation in the amorphous structure, which eventually induces the deterioration of PP by making the polymer hard but brittle. Such observation, in turn, implies that retarding or accelerating the crystallized structure of PP substantially works to control the progress of aging.

Analysis of the Adsorption Behavior of Phenanthrene on Microplastics Based on Two-Dimensional Correlation Spectroscopy.

Microplastics (MPs), an emerging pollutant, widely co-occur with polycyclic aromatic hydrocarbons (PAHs) in the environment. Therefore, the interaction between MPs and PAHs has been the focus of much attention in recent years. In this study, three types of MPs, i.e., polypropylene, polystyrene, and poly(vinyl chloride), with the same main chain were selected as the adsorbents, with phenanthrene (PHE) as the representative PAHs. The adsorption mechanisms were explored from the perspective of the molecular spectral level using a combination of Fourier transform infrared spectroscopy (FT-IR) with a two-dimensional correlation technique. The adsorption kinetics results showed that the adsorption of PHE on the three MPs was dominated by chemisorption. However, the FT-IR analysis results indicated that no new covalent bond was created during the adsorption process. Based on the above research, a generalized two-dimensional (2D) correlation spectral technique was employed to investigate the sequence of functional group changes during the adsorption process for different MPs. Furthermore, the hybrid 2D correlation spectral technique explored the effect of side groups attached to the main chain molecules of MPs on adsorption. The results showed that for all three MPs, the functional groups in the side chain have a higher affinity for PHE, which is due to their higher hydrophobicity. This study provides a feasible way to analyze the adsorption of pollutants on MPs, and the results are important for understanding the adsorption interaction between PAHs and MPs in the aquatic environment.

Ultrasensitive detection of trace Hg(â ¡) in acidic conditions using DMABR loaded on sepiolite: Function, application and mechanism studies.

Fast and real-time detection of trace Hg(Ⅱ) by fluorescent probes under acidic conditions is urgently required due to the high toxicity and accessibility to creatures and human being. However, fluorescent probes for Hg(Ⅱ) detection in environmental samples are rarely reported due to the protonation potential of acidic mercury sources. In this study, the SD probe was developed by 5-(p-dimethylaminobenzylidene) rhodanine (DMABR) loaded on sepiolite by hydrothermal treatment, and showed excellent Hg(Ⅱ) detection performances for mercury sources at pH 4-10 due to buffering ability of the hyperconjugated lactam rings. Sepiolite functioned as the support skeleton to decrease intermolecular transition, and thus increased the sensitivity. At pH 4, the SD probe showed high selectivity and sensitivity for Hg(Ⅱ) among various species, with low LOD and binding constant of 4.78 × 10-9 M and 1.34 × 106 M-1, respectively. Through DFT calculations, MAS 1H NMR and 2D-COS analysis, the detection mechanism was demonstrated as SN1 substitution of the spontaneous leaving H on amino groups in the transient state during tautomeric equilibrium, rather than the expected high-affinity sulphydryl. Additionally, the SD probe exhibited promising potential in quantifying water-soluble and bioavailable Hg(Ⅱ) in acidic polluted soil and water samples. Moreover, real-time detection was realized by paper-based strips.

Rheo-Optical Near-Infrared (NIR) Characterization of Styrene-Butadiene Rubber (SBR) Using Two-Trace Two-Dimensional (2T2D) Correlation Analysis.

A rheo-optical characterization technique based on the combination of near-infrared (NIR) spectroscopy and tensile testing was applied for the first time to an actual rubber sample based on styrene-butadiene rubber (SBR) including silica filler. When SBR samples were subjected to mechanical deformation, changes in the NIR spectral features were readily captured. Two-trace two-dimensional (2T2D) correlation analysis was then applied to the sets of NIR spectra to clearly reveal the subtle but pertinent difference between the NIR spectral features of the initial and deformed SBR. The initial deformation of the sample induces greater deformation of the soft butadiene groups than of the hard styrene groups. The inclusion of the silica filler and a coupling agent (CA) essentially develops firm links between the silica and butadiene via the CA to restrict the displacement of the butadiene during the tensile deformation of the system. The development of such linkage requires even more mechanical force to deform the SBR, which, in turn, improves Young's modulus of the rubber system. Asynchronous correlation spectra of SBR with no silica filler revealed that, during the deformation of the SBR, the butadiene groups were initially deformed, and this feature was then replaced by the predominant deformation of the hard styrene groups. On the other hand, this correlation feature became somewhat unclear when a similar analysis was applied to the SBR sample with silica filler, revealing subtle differences in interaction between individual comonomer functional groups distributed randomly along the copolymer chain and CA.

Efficient adsorption of hexavalent chromium in water by torrefaction biochar from lignin-rich kiwifruit branches: The combination of experiment, 2D-COS and DFT calculation.

A biochar (KBC) enriched with O functional groups was prepared by torrefaction using lignin-rich kiwifruit branches (KBM) as a raw material, which was characterized, and then KBC was used to adsorb hexavalent chromium (Cr6+) from water. The results showed that KBC contained more functional groups compared to KBM. The maximum adsorption of Cr6+ by KBC could reach 143.64 mg·g-1 and also had better adsorption performance than other adsorbents reported in some other reports. Cr6+ absorption by KBC was mainly a mechanism of electrostatic interaction and adsorption-reduction coupling. FTIR and XPS revealed that -OH, -COOH, CO and CC on KBC participated in Cr6+ adsorption and new groups (C=O) were generated during the process of adsorption, which implied that a redox reaction occurred. 2D-COS and DFT calculations showed that the order of functional groups on KBC interacting with Cr6+ was -OCH3 > -COOH > -OH > phenolic hydroxyl, and the binding tightness of the different functional groups to Cr6+ was -OCH3 (the shortest displacement of both groups after the adsorption) > -COOH > -OH > phenolic hydroxyl. KBC has good regeneration performance, and it is a good adsorbent for Cr6+.

New insight into the spatio-temporal patterns of functional groups of hotspot inside the composting aggregates by synchrotron-based FTIR in hyperthermophilic composting.

Hyperthermophilic composting (HTC) is a recently developed and highly promising organic fraction of municipal solid waste (OFMSW) treatment technology. Investigation of organic matter (OM) dynamics in compost particle is thus crucial for the understanding of humification of HTC process. Herein, this work aimed to study the chemical and structural changes of OM at the molecular level during HTC of OFMSW using EEM and SR-FTIR analyses. Additionally, two-dimensional correlation spectroscopy (2D-COS) was also utilized to probe and identify the changes in chemical constituents and functional groups of organic compounds on the surface of compost particles during different composting periods. Results show that SR-FTIR can detect fine-scale (~µm) changes in functional groups from the edges to the interior of compost particles during different composting periods by mapping the particles in situ. In the hyperthermophilic stage (day 9), the extracted µ-FTIR spectrum reveals a distinct boundary between anaerobic and aerobic regions within the compost particle, with a thickness of anaerobic zone (1460 cm-1) of approximately 30 µm inside the particle's core. This provides direct evidence of anaerobic trends at compost microscales level within compost particles. 2D-COS analysis indicated that organic functional groups gradually agglomerated in the order of 1330 > 2930 > 3320 > 1600 > 1030 > 895 cm-1 to the core skeleton of cellulose degradation residues, forming compost aggregates with well physicochemical properties. Overall, the first combination of SR-FTIR and EEM provides complementary explanations for the humification mechanism of HTC, potentially introducing a novel methodology for investigating the environmental behaviors and fates of various organic contaminants associated with OM during the in-situ composting biochemical process.

Research of 2D-COS with metabolomics modifications through deep learning for traceability of wine.

To tackle the difficulty of extracting features from one-dimensional spectral signals using traditional spectral analysis, a metabolomics analysis method is proposed to locate two-dimensional correlated spectral feature bands and combine it with deep learning classification for wine origin traceability. Metabolomics analysis was performed on 180 wine samples from 6 different wine regions using UPLC-Q-TOF-MS. Indole, Sulfacetamide, and caffeine were selected as the main differential components. By analyzing the molecular structure of these components and referring to the main functional groups on the infrared spectrum, characteristic band regions with wavelengths in the range of 1000-1400 nm and 1500-1800 nm were selected. Draw two-dimensional correlation spectra (2D-COS) separately, generate synchronous correlation spectra and asynchronous correlation spectra, establish convolutional neural network (CNN) classification models, and achieve the purpose of wine origin traceability. The experimental results demonstrate that combining two segments of two-dimensional characteristic spectra determined by metabolomics screening with convolutional neural networks yields optimal classification results. This validates the effectiveness of using metabolomics screening to determine spectral feature regions in tracing wine origin. This approach effectively removes irrelevant variables while retaining crucial chemical information, enhancing spectral resolution. This integrated approach strengthens the classification model's understanding of samples, significantly increasing accuracy.

Novel Developments and Progress in Two-Dimensional Correlation Spectroscopy (2D-COS).

This first of the two-part series of the comprehensive survey review on the progress of the two-dimensional correlation spectroscopy (2D-COS) field during the period 2021-2022, covers books, reviews, tutorials, novel concepts and theories, and patent applications that appeared in the last two years, as well as some inappropriate use or citations of 2D-COS. The overall trend clearly shows that 2D-COS is continually growing and evolving with notable new developments. The technique is well recognized as a powerful analytical tool that provides deep insights into systems in many science fields.

Diverse Applications of Two-Dimensional Correlation Spectroscopy (2D-COS).

This second of the two-part series of a comprehensive survey review provides the diverse applications of two-dimensional correlation spectroscopy (2D-COS) covering different probes, perturbations, and systems in the last two years. Infrared spectroscopy has maintained its top popularity in 2D-COS over the past two years. Fluorescence spectroscopy is the second most frequently used analytical method, which has been heavily applied to the analysis of heavy metal binding, environmental, and solution systems. Various other analytical methods including laser-induced breakdown spectroscopy, dynamic mechanical analysis, differential scanning calorimetry, capillary electrophoresis, seismologic, and so on, have also been reported. In the last two years, concentration, composition, and pH are the main effects of perturbation used in the 2D-COS fields, as well as temperature. Environmental science is especially heavily studied using 2D-COS. This comprehensive survey review shows that 2D-COS undergoes continuous evolution and growth, marked by novel developments and successful applications across diverse scientific fields.

Mid-Infrared Dispersion Spectroscopy as a Tool for Monitoring Time-Resolved Chemical Reactions on the Examples of Enzyme Kinetics and Mutarotation of Sugars.

Ongoing technological advancements in the field of mid-infrared (MIR) spectroscopy continuously yield novel sensing modalities, offering capabilities beyond traditional techniques like Fourier transform infrared spectroscopy (FT-IR). One such advancement is MIR dispersion spectroscopy, utilizing a tunable quantum cascade laser and Mach-Zehnder interferometer for liquid-phase analysis. Our study assesses the performance of a custom MIR dispersion spectrometer at its current development stage, benchmarks its performance against FT-IR, and validates its potential for time-resolved chemical reaction monitoring. Unlike conventional methods of IR spectroscopy measuring molecular absorptions using intensity attenuation, our method detects refractive index changes (phase shifts) down to a level of 6.1 × 10-7 refractive index units (RIU). This results in 1.5 times better sensitivity with a sevenfold increase in analytical path length, yielding heightened robustness for the analysis of liquids compared to FT-IR. As a case study, we monitor the catalytic activity of invertase with sucrose, observing the formation of resultant monosaccharides and their progression toward thermodynamic equilibrium. Anomalous refractive index spectra of reaction mixtures, with substrate concentrations ranging from 2.5 to 25 g/L, are recorded, and analyzed at various temperatures, yielding Michaelis-Menten kinetics findings comparable to the literature. Additionally, the first-time application of two-dimensional correlation spectroscopy on the recorded dynamic dispersion spectra correctly identifies the mutarotation of reaction products (glucose and fructose). The results demonstrate high precision and sensitivity in investigating complex time-dependent chemical reactions via broadband refractive index changes.

A Spectroscopic Method for Distinguishing Two Novel Sandwich-Type Tungsten Oxide Cluster Compounds.

This study introduces two novel sandwich-type tungsten-oxygen cluster compounds synthesized by hydrothermal methods, H4(C6H12N2H2)3{Na(H2O)2[Mn2(H2O)(GeW9O34)]}2 (Compound 1) and H2(C6H12N2H2)3.5{Na3(H2O)4[Co2(H2O)(GeW9O34)]2}·17H2O (Compound 2). The two compounds comprise cluster anions [GeW9O34]10- coordinated with transition metal atoms, either Mn or Co, and are stabilized by organic ligands. These compounds are crystallized in the hexagonal crystal system and P63/m space group. The two compounds were characterized through various techniques. Fourier transform infrared (IR) spectroscopy showed absorption peaks of anionic backbone vibrations of the Keggin cluster at 500-1000 cm-1, IR spectral peaks of δ(N-H) and νas(C-N) of the ligand triethylenediamine at 1000-2000 cm-1, and IR spectral peaks of the ligand νas(N-H) and νas(O-H) of water at 3000-3500 cm-1. Despite similar one-dimensional (1D) IR spectra due to the same cluster anions and similar molecular structures, the two compounds exhibited distinct responses in two-dimensional correlation spectroscopy with IR under magnetic and thermal perturbations. Under magnetic perturbation, Compound 1 showed a strong response peak for νas(W-Ob-W), while Compound 2 exhibited a strong response peak for νas(W=Od), possibly linked to differing magnetic particles. Similarly, Compound 1 displayed a strong response peak under thermal perturbation for νas(W-Oc-W). In contrast, Compound 2 showed a strong response peak for νas(W=Od); these results may be attributed to the different hydrogen bonding connections between the two compounds, which affect the groups in distinct ways through vibration and transmit these vibrations to the W-O bonds. The research presented in this paper expands the theoretical and experimental data of 2D correlation IR spectroscopy.

Beef muscle discrimination based on two-trace two-dimensional correlation spectroscopy (2T2D COS) combined with snapshot visible-near infrared multispectral imaging.

The purpose of this work was to assess the potential of 2T2D COS PLS-DA (two-trace two-dimensional correlation spectroscopy and partial least squares discriminant analysis) in conjunction with Visible Near infrared multispectral imaging (MSI) as a quick, non-destructive, and precise technique for classifying three beef muscles -Longissimus thoracis, Semimembranosus, and Biceps femoris- obtained from three breeds - the Blonde d'Aquitaine, Limousine, and Aberdeen Angus. The experiment was performed on 240 muscle samples. Before performing PLS-DA, spectra were extracted from MSI images and processed by SNV (Standard Normal Variate), MSC (Multivariate Scattering Correction) or AREA (area under curve equal 1) and converted in synchronous and asynchronous 2T2D COS maps. The results of the study highlighted that combining synchronous and asynchronous 2T2D COS maps before performing PLS-DA was the best strategy to discriminate between the three muscles (100% of classification accuracy and 0% of error).

Integrating portable NIR spectrometry with deep learning for accurate Estimation of crude protein in corn feed.

This study investigates the challenges encountered in utilizing portable near-infrared (NIR) spectrometers in agriculture, specifically in developing predictive models with high accuracy and robust generalization abilities despite limited spectral resolution and small sample sizes. The research concentrates on the near-infrared spectra of corn feed, utilizing spectral processing techniques and CNNs to precisely estimate crude protein content. Five preprocessing methods were implemented alongside two-dimensional (2D) correlation spectroscopy, resulting in the development of both one-dimensional (1D) and 2D regression models. A comparative analysis of these models in predicting crude protein content demonstrated that 1D-CNNs exhibited superior predictive performance within the 1D category. For the 2D models, CropNet and CropResNet were utilized, with CropResNet demonstrating more accurate and superior predictive capabilities. Overall, the integration of 2D correlation spectroscopy with suitable preprocessing techniques in deep learning models, particularly the 2D CropResNet, proved to be more precise in predicting the crude protein content in corn feed. This finding emphasis the potential of this approach in the portable spectrometer market.

Patterns of Cross-Peaks in Two-Dimensional Correlation Spectra to Probe Intermolecular Interactions Described by Two Reversible Reactions.

Two-dimensional correlation spectroscopy is used to investigate the intermolecular interaction between two substances dissolved in the same solutions, where the intermolecular interaction is described by two reversible reactions producing two supramolecular aggregates. The severe overlappings expected among the characteristic peaks of the original solute and aggregates make conventional one-dimensional spectra difficult to accurately reflect the physiochemical nature of the intermolecular interaction. The double asynchronous orthogonal sample design (DAOSD) approach is utilized to analyze the simulated data for proof-of-principle demonstration. The patterns of cross-peaks are much more complex compared with the intermolecular interaction described by only a single reaction. Four major groups of cross-peaks with characteristic patterns observed in the pair of DAOSD asynchronous spectra are systematically analyzed and classified. Further analysis of the spectral feature of the cross-peaks of the DAOSD asynchronous spectra is helpful to exact additional information concerning the variation of the peak position and peak width of the aggregates compared with those of the original solute. The result is important to reveal the physicochemical nature of intermolecular interaction between the solutes (e.g., changes in conformation, dynamical behavior, etc.). The pattern of cross-peaks in the corresponding 2D asynchronous spectra may become rather complex when the peak position, peak width, and peak intensity of two supramolecular aggregates change simultaneously. Further work using artificial intelligence techniques to interpret the complex cross-peaks is still being carried out.

Applying fluorescence spectroscopy coupled with Gaussian band fitting to reveal dynamic variation process of humus fractions from riparian soils along an urbanized river.

Humus, an important fraction of soil organic matter, play an environmental role on nutrients, organic and inorganic pollutants in riparian zones of urbanized rivers. In this study, dynamic variation process of humus fractions from riparian soils was revealed along Puhe River. Composite soil samples of four depths were collected from four land-uses, i.e., eco-conservation area (ECA), industrial area (INA), urban/town area (UTA), rural/agricultural area (RAA). Based on synchronous fluorescence spectra coupled with Gaussian band fitting, fulvic/humic acid predominantly contained tyrosine-like (TYLF), tryptophan-like (TRLF), microbial-like (MLF), fulvic-like (FLF) and humic-like (HLF) substances within each soil profile. TRLF, MLF and FLF (89.43-90.30 %) are the representative components in fulvic-acid, while MLF and HLF (52.81-59.97 %) in humic-acid. Phenolic, carboxylic and humified materials were present in both humus. According to 2-dimensitonal correlation spectroscopy and canonical correlation analysis, fulvic/humic acid within the ECA soil profile could be mainly derived from the degradations of terrestrial plant metabolites and residuals. Within the INA, fulvic-acid could be associated with treated/untreated wastewater, which entered the river and flew into the riparian during high flow period; whereas humic-acid could be relative to the terrestrials. Fulvic-acid had the same source as humic-acid in the UTA, which might be concerned with scattered domestic sewage and livestock wastewater, rather than the fluvial water. Furthermore, the source of fulvic/humic acid in the RAA was the crop metabolites and residuals, apart from the livestock wastewater. Noticeably, the variations of humus fractions in the ECA and RAA roughly occurred in 0-60 cm, while approximately in 20-80 cm in the INA and UTA. This proved that humus fractions in the former were referred to the plant/crop residuals, whereas humus fractions in the latter were those the terrestrials and fluvial water. This study could provide a key support for the construction and restoration of the urbanized riparian zone.

Two-Dimensional (2D) Hybrid Method: Expanding 2D Correlation Spectroscopy (2D-COS) for Time Series Analysis.

We present a concise report on the two-dimensional (2D) hybrid method, an innovative extension of 2D correlation spectroscopy, tailored for quasar light curve analysis. Addressing the challenge of discerning periodic variations against the background of intrinsic "red" noise fluctuations, this method employs cross-correlation of wavelet transform matrices to reveal distinct correlation patterns between underlying oscillations, offering new insights into quasar dynamics.

Ag(I) Ion-Concentration-Dependent Dynamic Mechanism of Thiolactic-Acid-Capped Gold Nanoclusters Revealed by Fluorescence Spectra and Two-Dimensional Correlation Spectroscopy.

Based on fluorescence spectroscopy, being combined with several spectral analysis techniques including principal component analysis (PCA), two-dimensional correlation spectroscopy (2D-COS), and moving window 2D-COS, the study disclosed the structural variations of gold nanoclusters capped by thiolactic acid (AuNCs@TLA) induced by Ag(I) ions. Transmission electron microscopy (TEM) and X-ray photoelectron spectroscopy (XPS) were applied to monitor the morphology evolution of the surface and composition of the nanoclusters induced by Ag(I) ions. Several spectral components, centered at (790, 607) nm, (670, 590) nm, and (740, 670) nm were revealed by 2D-COS analysis, suggesting new luminescent species or groups were generated with the introduction of Ag(I) ions. A two-stage mechanism was revealed for the photoluminescence variations of AuNCs@TLA induced by Ag(I) ion. The first stage was characterized by the emission quench of 790 nm followed by the emerging emission of 607 nm, which was attributed to the anti-galvanic reaction; and the second stage featured by the noticeable growth of the emission's intensity around 670 nm as result of the AuNCs' size effect. The present study will attract more focuses on near-infrared (NIR)-emitted metal nanoclusters and promote their synthesis and utilities.