Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy最新文献

Water is a greatly convenient solvent in Raman spectroscopy. However, non-additive effects sometimes make its signal difficult to subtract. To understand these effects, spectra for clusters of model ions, including transition metal complexes and water molecules, were simulated and analyzed. A combined molecular mechanics/quantum mechanics approach was taken to reveal how relative Raman scattering intensities depend on the distance from the solute and the excitation wavelength. The computations indicate a big effect of solute charge; for example, the sodium cation affects Raman scattering by water to a lesser extent than the chlorine anion. The modeling was able to qualitatively reproduce the experimental observation that a solution of a simple salt may work as a baseline better than pure water in many Raman experiments. For absorbing species, an additional scattering boost occurs due to the resonance effect. Simulations thus provide useful insight into solute-solvent interactions and their effects on measured spectra.

The main objective of this study was to evaluate the potential of near infrared (NIR) spectroscopy and machine learning in detecting microplastics (MPs) in chicken feed. The application of machine learning techniques in building optimal classification models for MPs-contaminated chicken feeds was explored. 80 chicken feed samples with non-contaminated and 240 MPs-contaminated chicken feed samples including polypropylene (PP), polyvinyl chloride (PVC), and polyethylene terephthalate (PET) were prepared, and the NIR diffuse reflectance spectra of all the samples were collected. NIR spectral properties of chicken feeds, three MPs of PP, PVC and PET, MPs-contaminated chicken feeds were firstly investigated, and principal component analysis was carried out to reveal the effect of MPs on spectra of chicken feed. Moreover, the raw spectral data were pre-processed by multiplicative scattering correction (MSC) and standard normal variate (SNV), and the characteristic variables were selected using the competitive adaptive re-weighted sampling (CARS) algorithm and the successive projections algorithm (SPA), respectively. On this basis, four machine learning methods, namely partial least squares discriminant analysis (PLSDA), back propagation neural network (BPNN), support vector machine (SVM) and random forest (RF), were used to establish discriminant models for MPs-contaminated chicken feed, respectively. The overall results indicated that SPA was a powerful tool to select the characteristic wavelength. SPA-SVM model was proved to be optimal in all constructed models, with a classification accuracy of 96.26% for unknow samples in test set. The results show that it is not only feasible to combine NIR spectroscopy with machine learning for rapid detection of microplastics in chicken feed, but also achieves excellent analysis results.

Excessive plastic consumption can pose potential risks to the human respiratory and circulatory systems, leading to various diseases. Therefore, the sensitive detection of plastics holds significant implications for ensuring food safety, environmental protection, and human health. Conducting tests on rivers and drinking water can ensure their compliance with relevant safety standards, thereby mitigating the potential environmental and health risks associated with plastic pollution. In this experiment, we prepared a roseate petal homochiral nanogold (Au RHNs) as a surface-enhanced Raman scattering (SERS) substrate for detecting plastics in the water. Due to the intricate rose petal-like surface and structures with symmetry breaking, which result in a large surface area, the mean enhancement factor (EF) of the Au RHNs was determined to be 8.4696 × 10⁵. The Au RHNs as the SERS substrate were used to test the plastic polyethylene (PE) and polyvinyl chloride (PVC), with the detection limits of 0.0986 mg/mL and 0.0975 mg/mL, respectively. Moreover, the prepared Au RHNs substrate were successfully applied for ananlyzing analyze actual samples (tap water, mineral water, river water), yielding a satisfactory recovery rate. The exceptional performance of Au RHNs as a SERS detection substrate indicated its promising potential for practical detection of plastic samples.

Glioblastoma multiforme (GBM) is the most lethal intracranial tumor with a median survival of approximately 15 months. Due to its highly invasive properties, it is particularly difficult to accurately identify the tumor margins intraoperatively. The current gold standard for diagnosing GBM during surgery is pathology, but it is time-consuming. Under these circumstances, we developed a method combining Raman spectroscopy (RS) with convolutional neural networks (CNN) to distinguish GBM. Analysis of the spectra of normal brain samples (478 spectra) and GBM samples (462 spectra) from 29 in situ intracranial tumor-bearing mice showed that this method identified GBM tissue with 96.8 % accuracy. Subsequently, spectral analysis of 23 normal human brain tissues (223 spectra) versus 21 tissues from patients with pathologically diagnosed GBM (267 spectra) revealed that the accuracy of this method was 93.9 %. Most importantly, for the difference peaks in the spectra of GBM and normal brain tissue, the common difference peaks in the mouse and human spectra were at 750 cm^-1, 1440 cm^-1, and 1586 cm^-1, which emphasized the differences in cytochrome C and lipids between GBM samples and normal brain samples in both mice and human. The preliminary results showed that CNN-assisted RS is simple to operate and can rapidly and accurately identify whether it is GBM tissue or normal brain tissue.

In this work, the interaction behaviour of gold nanoparticles (AuNPs) with o-phenylenediamine (OPD) was studied to ascertain the nanozyme-substrate interaction. The UV-Vis absorption, high-resolution transmission electron microscopy and zeta potential analysis revealed that the electron-rich nitrogen atoms in OPD showed a stronger affinity toward electron-deficient surface, indicating a stronger interaction between nanozyme and substrate molecules. Subsequently, under optimum conditions, AuNPs are used as nanozyme to catalyze the oxidation of OPD in the presence of H₂O₂. The catalyzed product (2,3-diaminophenazine, (DAP)) generated visible colorimetric readout (yellow color) and showed yellow fluorescence upon excitation at 450 nm. The nanozyme-based oxidation reaction of OPD was then applied to detect glutathione (GSH) by colorimetric and fluorometric techniques. The detection principle is based on the fact that GSH being a thiol-containing moiety can readily interact with AuNPs and considerably decrease the catalytic activity of nanoparticles. In the presence of varying concentrations (1-15 µM) of GSH, the formation of DAP is significantly decreased leading to a decrease in the absorbance and fluorescence intensity at 450 nm and 540 nm, respectively. The colorimetric and fluorescence assay for GSH exhibited a limit of detection of 3.42 and 2.01 µM, respectively. Kinetic studies were conducted to elucidate the inhibition mechanism of GSH on the catalytic function of AuNPs. To demonstrate the practical applicability of the nanozyme-based assay, GSH detection in artificial urine samples were carried out.

This study explores the nonlinear optical (NLO) and photophysical properties of newly designed naphthyridine derivatives by density functional theory (DFT). The first hyperpolarizability (β_tot), a key indicator of NLO activity, varies significantly depending on the substituent groups. N-substituted compounds (IUB-N series) generally show lower β_tot values, while compounds with electron donor/acceptor groups (IUB-P series) demonstrate a broader range, with IUB-A-02 achieving the highest β_tot value of 16,362 a.u. due to the presence of two -NH₂ groups. TD-DFT analysis confirms key electronic transitions, mostly from HOMO to LUMO, with absorption wavelengths (λmax) ranging from 349.596 to 440.692 nm for the IUB-P series. The introduction of electron-donor groups considerably boosts absorption, particularly in IUB-P-06, with highest λ_max and oscillator strength (f_o) signifying excellent light absorption capabilities. The calculated light harvesting efficiency (LHE) correlates strongly with f_o values, IUB-N-01 to IUB-N-05 exhibiting higher LHE than the unsubstituted IUB. Additionally, lower radiative lifetimes (τ) for the modified compounds indicate faster decay, useful for applications in photodynamic therapy and fluorescence imaging. Lower transition energy (ΔE) and higher f_o values contributed to greater first hyperpolarizability (β_o). IUB-P-06, with two -NH₂ donor groups, shows the lowest ΔE (2.81 eV) and a correspondingly high β_o (60218.89 a.u.). Whereas IUB-A-02 exhibits the highest β_o (68907.84 a.u.) due to its large dipole moment change (Δμ = -6.37 D). Among N-substituted compounds, IUB-N-01 exhibits the highest charge density. IUB-P-06 has the highest charge density and electron-hole separation due to electron donor/acceptor groups, indicating a higher degree of internal atomic localization. This enhanced charge separation further confirms the superior performance of these compounds in NLO applications. In conclusion, this comprehensive analysis spanning ESP, TD-DFT, TLM, LHE, and TDM demonstrates that the studied naphthyridine derivatives possess promising NLO properties and exhibit strong potential for use in optoelectronics, photovoltaics, photodynamic therapy, and other advanced optical technologies.

Lead ion (Pb²⁺) is a common environmental contaminant, extremely toxic, persistent, and easily adsorbed, concentrated, and enriched by agricultural products. Ingestion of this ion can result in health problems for humans, including neurological disorders, heart disease, brain damage, and mental deficiency. In this research, a sensitive fluorescent biosensing method for detecting Pb²⁺ was developed using DNAzyme as the target recognition element and SYBR Green (SG) fluorescent dye as the signal indicator. Through catalytic action on a strand of DNA with ribo-adenine (rA), the DNAzyme was able to cut it in the presence of Pb²⁺. This led to the removal of intercalation sites for SG molecules, resulting in a decrease in fluorescence response. The newly developed biosensor was capable of identifying Pb²⁺ ions within a range of 0.1-600 µM with a detection limit of 0.018 µM. This label-free fluorescent biosensor proved to be both convenient and efficient in accurately measuring the levels of Pb²⁺ ions in blood serum and milk samples, yielding recovery rates between 96.81 % and 100.00 %. The DNAzyme-based biosensor offers an economical and easy-to-use sensing assay for Pb²⁺ ion.

Neutral radicals have the potential to construct pure organic light-emitting diodes (OLEDs) with internal quantum efficiencies reaching 100%. However, neutral radical luminescent materials with emission wavelengths in the second near-infrared (NIR-II) window are rare. Herein, a serial of neutral donor-bridge-acceptor (D-π-A) type radical derivatives are investigated. The dominant elements influencing the luminescent properties of neutral radicals, such as chemical stability, excited state characteristics, radiative decay rate (k_r) and internal conversion rate (k_IC) constants are taken into consideration. Theoretical calculations reveal that introducing heteroatomic fused-rings into neutral radicals can modulate the chemical stability and result in a red shift of the emission wavelength spectrum. In the presence of charge transfer characteristics, by increasing the effective overlap between the hole and electron wavefunctions, the k_r constants of the neutral D-π-A type radicals increase. In addition, avoiding the geometric relaxation between the lowest excited state (D₁) and the ground state (D₀), as well as reducing electron-vibration coupling and non-adiabatic coupling in the low-frequency region can effectively decrease the k_IC constants. Our study proposes an innovative design approach aiming to develop stable and efficient NIR-II window neutral radical luminescent materials utilizing heteroatomic fused-rings as key elements.

Development of a rapid and sensitive detection method for hazardous dyes attracts considerable research interest. In this work, L-Tryptophan-based Carbon dots were developed as a fluorescence sensor for the detection of Malachite green (MG). Green fluorescent L-Trp-C-dots were synthesized by a simple pyrolysis technique using L-Trp as the starting precursor. L-Trp-C-dots exhibited different quenching responses to MG, and other interfering species, consequently offering a selective strategy to detect MG. The proposed sensor shows a limit of detection (LOD) of 0.06 μM and a limit of quantification (LOQ) of 0.22 μM with in the linearity range of 0 to 60 µM concentration. Additionally, the relative standard deviation (RSD) was found to be below 1.7 %. Furthermore, the recovery of MG from the real-time samples (green peas) was investigated.

The high thermal stability and chemical durability of amide-linked covalent organic frameworks (amide COFs) make them a promising material for a range of new applications. Nevertheless, the low reversibility of the amide bond presents a significant challenge to the direct synthesis of amide-bonded COFs. In this paper, we present a simple method for synthesizing amide COFs. The synthesis of imine-linked COFs was initially achieved through the reaction of 2,4,6-tris(4-aminophenyl)-1,3,5-triazine and 2,5-dimethoxybenzene-1,4-dicarboxaldehyde. Subsequently, amide COFs were synthesized via the oxidation of the imine bond into an amide bond, utilizing ammonium persulfate as the oxidizing agent. Due to the difference of link bond, two COFs separately displayed distinct and significant fluorescence enhancement for Al³⁺ and Ce³⁺, which was highly sensitive and less affected by environmental factors. The strategy offers a novel approach to the convenient and environmentally benign synthesis of amide COFs, which may facilitate their wider applications.