Spectroscopy Spectra Research Articles

Surface-enhanced Raman spectroscopy (SERS) for the diagnosis of acute myocardial infarction (AMI) using blood serum samples.

Acute myocardial infarction (AMI) is a serious medical condition generally known as heart attack, which is caused by the decreased or completely blocked blood flow to a part of the heart muscle. It is a significant cause of both mortality and morbidity throughout the world. Cardiac troponin-I (cTnI) is an important biomarker at different stages of AMI and is one of the most specific and widely used cardiac skeletal muscle proteins. Delays in medical treatment and inaccurate diagnosis might be the main cause of death of AMI patients. To overcome the death rate of AMI patients, early diagnosis of this disease is crucial. In the current study, surface-enhanced Raman spectroscopy (SERS) is employed for the characterization and diagnosis of this disease using blood serum samples from 49 clinically confirmed acute myocardial infarction (AMI) patients and 17 healthy persons. Silver nanoparticles (AgNPs) are used as the SERS substrate for the recognition of characteristic SERS spectral features, differentiating between healthy and AMI-positive samples. The acute myocardial infarction-positive blood serum samples reveal remarkable differences in spectral intensities at 534, 697, 744, 835, 927, 941, 988, 1221, 1303, 1403, 1481, 1541, 1588 and 1694 cm-1. For the differentiation and quantitative analysis of the SERS spectra, multivariate chemometric tools (including principal component analysis (PCA) and partial least squares regression (PLSR)) are employed. A PLSR model established on the basis of differentiating the SERS spectral features is found to be helpful in the prediction of the levels of cardiac troponin-I (cTnI) in the blood serum samples with the root mean square error of calibration (RMSEC) value of 2.98 ng mL-1 and root mean square errors of prediction (RMSEP) value of 3.98 ng mL-1 for S7.

Improved Discrimination of Mass Spectral Isomers Using the High-Dimensional Consensus Mass Spectral Similarity Algorithm.

This study employs a high-dimensional consensus mass spectral (HDCMS) similarity scoring technique to discriminate isomers collected using an electron ionization mass spectrometer. The HDCMS method was previously introduced and applied to the discrimination of mass spectra of constitutional isomers, methamphetamine and phentermine, collected with direct analysis real-time mass spectrometry (DART-MS). The method formulates the problem of discriminating mass spectra in a mathematical Hilbert space and is hence called "high dimensional." It requires replicate mass spectra to build a Gaussian model and evaluate the inner products between these functions. The resulting measurement variability is used as a signature by which to discriminate spectra. In this work, HDCMS is tested on electron impact ionization (EI) mass spectra of 7 terpene and terpene-related (C10H16 and C10H14) isomers with experimental retention indices that differ by less than 30 and with traditional cosine similarity scores greater than 0.9, on a scale of 0 to 1, when compared with at least one other compound in the test set. Using identical instrument parameters, 15 replicate gas chromatography-electron ionization-mass spectrometry (GC-EI-MS) spectra of each isomer were collected and separated into distinct library and query sets. The HDCMS algorithm discriminated each isomer, indicating the method's potential. Because the method requires replicate measurements, observations from a simple heuristic study of the number of replicates required to discriminate these isomers is presented. The paper concludes with a discussion of compound discrimination using HDCMS and the benefits and drawbacks of applying the method to EI-MS data.

Regulated Photocatalytic CO2-to-CH3OH Pathway by Synergetic Dual Active Sites of Interlayer.

Herein, composites of nanosheets with van der Waals contacts are employed to disclose how the interlayer-microenvironment affects the product selectivity of carbon dioxide (CO2) photoreduction. The concept of composites of nanosheets with dual active sites is introduced to manipulate the bonding configuration and promote the thermodynamic formation of methanol (CH3OH). As a prototype, the CoNi2S4-In2O3 composites of nanosheets are prepared, in which high-resolution transmission electron microscopy imaging, X-ray photoelectron spectroscopy spectra, and zeta potential tests confirm the presence of van der Waals contacts rather than chemical bonding between the In2O3 nanosheets and the CoNi2S4 nanosheets within the composite. The fabricated CoNi2S4-In2O3 composites of nanosheets exhibit the detection of the key intermediate *CH3O during CO2 photoreduction through in situ Fourier transform infrared spectra, while the In2O3 nanosheets and CoNi2S4 nanosheets alone do not show this capability, further verified by the density functional theory calculations. Accordingly, the CoNi2S4-In2O3 composites of nanosheets show the ability to produce CH3OH, whereas the CoNi2S4 and In2O3 nanosheets solely generate carbon monoxide products from CO2 photoreduction.

Dual-Mode Sensing of Fe(III) Based on Etching Induced Modulation of Localized Surface Plasmon Resonance and Surface Enhanced Raman Spectroscopy.

Convenient, rapid, highly sensitive and on-site iron determination is important for environmental safety and human health. We developed a sensing system for the detection of Fe(III) in water based on 7-mercapto-4-methylcoumarine (MMC)-stabilized silver-coated gold nanostars (GNS@Ag@MMC), exploiting a redox reaction between the Fe(III) cation and the silver shell of the nanoparticles, which causes a severe transformation of the nanomaterial structure, reverting it to pristine GNSs. This system works by simultaneously monitoring changes in the Localized Surface Plasmon Resonance (LSPR) and Surface-Enhanced Raman Spectroscopy (SERS) spectra as a function of added Fe(III). The proposed sensing system is able to detect the Fe(III) cation in the 1.0 × 10-5-1.5 × 10-4 M range, and its selectivity of the GNS@Ag@MMC sensor toward iron has been verified monitoring the LSPR and the SERS response to other cations with a clear selectivity toward Fe(III).

The impact of cobalt oxide additions and heat treatment on wollastonite for magnetic applications

Magnetic nanocomposite was prepared using the wet chemical precipitation approach with varying amounts of cobaltous oxide (CoO). The concentrations of CoO were 0.5, 3.5, 6.5, and 9.5 g per 100 % wollastonite composition. Samples were sintered separately at 1000 and 1200 °C. X-ray diffraction analysis (XRD) of the sintered parent sample revealed the formation of wollastonite CaSiO3 and larnite Ca2SiO4, as well as a minor silicon oxide SiO2 phase. In CoO-doped samples, Co-åkermanite Ca2CoSi2O7 and other phases were formed. The XRD and scanning electron microscope SEM confirm the samples' submicron and nanocrystalline microstructure. The Fourier transform infrared spectroscopy (FTIR) and Raman spectra (RS) of investigated samples sintered at 1000 and 1200 °C revealed their bond structure. Both analyses confirmed that incorporating CoO into CaSiO3 significantly improved its vibrational modes, reflecting structural modifications. By increasing the cobalt oxide content from 3.5 to 9.5 wt%, the samples attain the ideal paramagnetic state, as demonstrated by the magnetic hysteresis (M − H) curve, which is linearly reversible. Formation of the Ca2CoSi2O7 significantly alters the magnetic characteristics of the samples, whether through increasing the cobalt oxide concentration up to 9.5 wt% or modifying the sintering temperature. This enables the prepared nonocomposites to be suitable for novel magnetic applications.

Biocomposite Scaffolds Based on Chitosan Extraction from Shrimp Shell Waste for Cartilage Tissue Engineering Application.

Chitosan-based scaffolding possesses unique properties that make it highly suitable for tissue engineering applications. Chitosan is derived from deacetylating chitin, which is particularly abundant in the shells of crustaceans. This study aimed to extract chitosan from shrimp shell waste (Macrobrachium rosenbergii) and produce biocomposite scaffolds using the extracted chitosan for cartilage tissue engineering applications. Chitinous material from shrimp shell waste was deproteinized and deacetylated. The extracted chitosan was characterized and compared to commercial chitosan through various physicochemical analyses. The findings revealed that the extracted chitosan shares similar trends in the Fourier transform infrared spectroscopy spectrum, energy dispersive X-ray mapping, and X-ray diffraction pattern to commercial chitosan. Despite differences in the degree of deacetylation, these results underscore its comparable quality. The extracted chitosan was mixed with agarose, collagen, and gelatin to produce the blending biocomposite AG-CH-COL-GEL scaffold by freeze-drying method. Results showed AG-CH-COL-GEL scaffolds have a 3D interconnected porous structure with pore size 88-278 μm, high water uptake capacity (>90%), and degradation percentages in 21 days between 5.08% and 30.29%. Mechanical compression testing revealed that the elastic modulus of AG-CH-COL-GEL scaffolds ranged from 44.91 to 201.77 KPa. Moreover, AG-CH-COL-GEL scaffolds have shown significant potential in effectively inducing human chondrocyte proliferation and enhancing aggrecan gene expression. In conclusion, AG-CH-COL-GEL scaffolds emerge as promising candidates for cartilage tissue engineering with their optimal physical properties and excellent biocompatibility. This study highlights the potential of using waste-derived chitosan and opens new avenues for sustainable and effective tissue engineering solutions.

Computational, molecular docking and spectroscopic insights of drug–drug interaction between Ibuprofen and Paracetamol

The combination of existing drugs or drug–drug interaction enthralls researcher because of their potential applications in multiple diseases and better efficacy. The present work is undertaken to study the interaction between two drugs, Ibuprofen and Paracetamol, using Density Functional Theory and spectroscopic techniques (Infrared and Raman spectroscopy). The molecular modeling of the two drugs indicates their interaction through intermolecular hydrogen bonds (O34-H53-O2 and (O1-H33-O34), which is observed in Natural Bond Orbital and atoms in molecules analysis of the compound (Ibuprofen + Paracetamol). The experimental Raman, Surface Enhanced Raman Spectroscopy and Infrared spectra of the physical mixture (Ibuprofen + Paracetamol) are found close to their computed wavenumbers. The interacting state, that is, Ibuprofen + Paracetamol is optimized using B3LYP/6-31G ++ (d, p) model under density functional theory framework and different computed quantum chemical parameters such as, dipole moment, ionization energy, electron affinity, electrophilicity index, chemical potential, hardness and the Highest Occupied and Lowest Unoccupied Molecular Orbital energies and energy gaps are calculated and compared to the monomer state of the drugs. The lowering of energy gap and increased in dipole moment of combined drug molecules show potency as an effective hybrid drug. The molecular docking study of the combined drug molecule against the 4PH9 receptor shows a better binding affinity with its residues through hydrogen bonding and hydrophobic interaction.

Tracing Microplastic Aging Processes Using Multimodal Deep Learning: A Predictive Model for Enhanced Traceability.

The aging process of microplastics (MPs) affects their surface physicochemical properties, thereby influencing their behaviors in releasing harmful chemicals, adsorption of organic contaminants, sinking, and more. Understanding the aging process is crucial for evaluating MPs' environmental behaviors and risks, but tracing the aging process remains challenging. Here, we propose a multimodal deep learning model to trace typical aging factors of aged MPs based on MPs' physicochemical characteristics. A total of 1353 surface morphology images and 1353 Fourier transform infrared spectroscopy spectra were achieved from 130 aged MPs undergoing different aging processes, demonstrating that physicochemical properties of aged MPs vary from aging processes. The multimodal deep learning model achieved an accuracy of 93% in predicting the major aging factors of aged MPs. The multimodal deep learning model improves the model's accuracy by approximately 5-20% and reduces prediction bias compared to the single-modal model. In practice, the established model was performed to predict the major aging factors of naturally aged MPs collected from typical environment matrices. The prediction results aligned with the aging conditions of specific environments, as reported in previous studies. Our findings provide new insights into tracing and understanding the plastic aging process, contributing more accurately to the environmental risk assessment of aged MPs.

Tandem mass spectral metabolic profiling of 54 actinobacterial strains and their 459 mutants

Natural products encompass a diverse range of compounds with high impact applications in consumer care, agriculture and most notably, therapeutics. However, despite the expansive chemical repertoire indicated in genomic information of microbes, only a small subset can be obtained under laboratory conditions. To increase accessible chemical space and realize Nature’s full chemical potential, a multi-pronged genetic- and cultivation-based strategy has been employed to activate and upregulate natural product biosyntheses in native and heterologous strains. This data descriptor documents a characterized collection of 2,138 liquid chromatography-tandem mass spectrometry (LC/MS-MS) spectra of fermentation extracts from 54 native actinobacterial strains collected from soil and marine environments in Singapore, and their 459 activated mutants in 3 to 5 media. A total of 743 unique metabolites have been identified, with the activated mutants demonstrating an approximately 2-fold expansion in accessible chemical space over wild type strains. Interrogating this expanded chemical diversity with cheminformatic tools can provide direction for the discovery of novel natural products with desirable functional activity.

Breaking New Ground towards Innovative Synthesis of Palladacycles: The Electrochemical Synthesis of a Tetranuclear Thiosemicarbazone-[C,N,S] Palladium(II) Complex.

The electrochemical oxidation of anodic metals (M = nickel and palladium) in an acetonitrile solution of the thiosemicarbazone ligands (E)-2-(1-(4-methoxyphenyl)ethylidene)-N-methylhydrazine-1-carbothioamide (a), (E)-2-(1-(p-tolyl)ethylidene)hydrazine-1-carbothioamide (b), and (E)-N-phenyl-2-(1-(p-tolyl)ethylidene)hydrazine-1-carbothioamide (c) yielded the homoleptic complexes [ML2], 1a, 1b, 1c, and 2c and [M4L4], 2a as air-stable solids. The crystal structures for 1a, 1b, 1c, and 2c show the ligands in a transoid disposition with the [S,S] and [N,N] donor atom pairs occupying cis positions on the nearly square planar coordination plane of the metal. The structure for 2a of S4 symmetry comprises a tetranuclear palladacycle where the metalated ligands are arranged around a central Pd4S4 environment: a crown ring with alternating palladium and sulfur atoms. The latter complex is the first example of an electrochemical preparation of a cyclometalated palladium compound, marking a milestone in the chemistry of such species. The compounds have been fully characterized by elemental microanalysis, mass spectrometry, infrared (IR), and 1H nuclear magnetic resonance (NMR) spectra.

FLIM nanoscopy resolves the structure and preferential adsorption in the co-nonsolvency of PNIPAM microgels in methanol-water

Polymer microgels are swollen macromolecular networks with a typical size of hundred of nanometers to several microns that show an extraordinary open and responsive architecture to different external stimuli, being therefore important candidates for nanobiotechnology and nanomedical applications such as biocatalysis, sensing and drug delivery. It is therefore crucial to understand the delicate balance of physical-chemical interactions between the polymer backbone and solvent molecules that to a high extent determine their responsivity.In particular, the co-nonsolvency effect of poly(N-isopropylacrylamide) in aqueous alcohols is highly discussed, and there is a disagreement between molecular dynamics (MD) simulations (from literature) of the preferential adsorption of alcohol on the polymer chains and the values obtained by several empirical methods that mostly probe the bulk solvent properties.It is our contention that the most efficacious method for addressing this problem requires a nanoscopic method that can be combined with spectroscopy and record fluorescence spectra and super-resolved fluorescence lifetime images of microgels labeled covalently with the solvatochromic dye Nile Red. By employing this approach, we could simultaneously resolve the structure of sub-micron size objects in the swollen and in the collapsed state and estimate the solvent composition inside of them in ▪–▪ mixtures for two very different polymer architectures. We found an outstanding agreement between the MD simulations and our results that estimate a co-solvent molar fraction excess of approximately 3 with a very flat profile in the lateral direction of the microgel.

Enhanced morphological and thermal properties of epoxy composites reinforced with Palm and Prosopis Juliflora fibers

Abstract This study investigates the fabrication and characterization of a hybrid epoxy matrix composite reinforced with Palm and Prosopis Juliflora fibers fabricated using the hand layup technique. Three composite samples were prepared with varying weight percentages of palm and Prosopis Juliflora fiber reinforcements: 5% (Sample A), 10% (Sample B), and 15% (Sample C). Sample B having 10 weight percentage each of Palm fiber and Prosopis Juliflora fiber and 80 weight percentage of Epoxy matrix, exhibited superior performance with a tensile strength of 45.5 MPa and a hardness of 86.5 Shore D. Thermal analysis revealed Sample B’s exceptional thermal stability, with distinct decomposition stages observed through Thermogravimetric Analysis (TGA) and Differential Thermal Analysis (DTA). Void content analysis indicated Sample C had the lowest void content at 4.5%. Energy Dispersive x-ray (EDX) Analysis confirmed homogeneous fiber distribution and strong fiber-matrix adhesion, supported by carbon and oxygen peaks. Fourier-transform infrared spectroscopy (FTIR) spectra showed interactions between functional groups, including alcohols, carboxylic acids, and carbonyl compounds. These findings underscore the composite’s potential for high strength, toughness, and thermal stability applications.

MoⅣ boosted carrier density of MoO3-X for surface-enhanced Raman spectroscopy

Molybdenum oxides (MoO3-X) with the same surface plasmon resonance (SPR) effect as Au/Ag, and occupies an irreplaceable value in SERS detections. MoO3-X SERS substrates with oxygen-rich defects tend to show better SERS performance, but the preparation and characterization of tunable O defects remain challenging. It cannot be ignored that the oxidation state of metal cations is also influenced by O defects. Here, a series of MoO3-X SERS sensors with regulable Mo valence state were fabricated using magnetron sputtering technology. By changing the Mo sputtering power and the O2/Ar2 ratio, the Mo/O element ratio of the substrate can be easily regulated to readjust the O defects. The X-ray Photoelectron Spectroscopy (XPS) and Raman spectra were performed to investigate the change and related relationship between Mo mixed valence state and SERS sensitivity. The abundant incompletely coordinated electrons produced by low valence MoⅣ act as free carriers, increasing the free carrier density of MoO3-X substrates, which is beneficial for the SERS effect. It has also been proven by Hall effect measurement. The SERS measurement shows that the enhancement factor (EF) reached 3.70 × 105, which is exceedingly close to Au/Ag. The MoO2.5 substrate also exhibited a repeatable and consistent response, high stability, and repeatability, which proves the splendid application potential in complex environments.

Phytochemical Constituents, Antimicrobial Activity of Daniellia oliveri, and X-ray Crystal Structure of Polyalthic Acid

Objectives: Daniellia oliveri Rolfe is a well-known plant of Fabaceae family whose previous phytochemical and pharmacological studies led to the identification of triterpenoid, phenol, anthraquinone oxalate with antioxidant, antibacterial and antifungal activities. This study aimed to investigate chemical constituents and evaluate the antimicrobial potency of the root of D. oliveri. Methods: The methanol extract of the root barks of D. oliveri was subjected to silica gel chromatographic separation. The structures of the isolated compounds (1-9) were determined by analyzing their spectrometric and spectroscopic spectra. Single-crystal-Xray analysis was used to establish the absolute skeletal structure of compound 1. Crude extract, fractions and compounds were investigated against four bacteria vis Pseudomonas aeruginosa 27853, Escherichia coli 5, Staphylococcus aureus 25923 and Streptococcus sp . 9619 and, two yeast vis Candida albicans14053 and Candida tropicalis 018 using broth microdilution method. Results: The phytochemical prospection of the methanol extract of D. oliveri allowed the isolation of a naturally crystallized diterpenoid type furolabdane: polyalthic acid 1, as well as eight amorphous compounds (2-9). Among the tested samples, the crude extract, fractions and compounds selectively showed inhibitory effects against the tested microorganisms with MIC values ranging from 4 to 1024 μg/mL. Fraction D1 and compounds 1, 4, 7, 8 and 9 exhibited the broadest antimicrobial effects among fractions and compounds while D5 and compound 1 showed the best activity with MIC values of 16 and 4 μg/mL respectively against E. coli which appeared to be the most sensitive strain . Conclusion: Polyaltic acid (1) showed the best activity with significant MIC value of 4 μg/mL identical to that of ceftazidine against E. coli. The MIC values of the active compounds 1, 4 and 7 are comparable to those of ceftazidime. Then, these compounds from natural origin, could serve as markers in the standardization of Daniellia plant as phytomedicine.

Exploring the Multifunctional aspects of SrBi2-X(CoFe2O4)XNb2O9 Nanocomposite Materials Emphasizing the Structural, Elastic, and Optical Properties

Nanocomposites of SrBi(2-X)(CF)XNb2O9 (SBNCF) (CF=CoFe2O4 for X = 0.0 to 0.5 with a step increment of 0.1) were synthesized using the hydrothermal method and characterized for their structural, morphological, elastic, and optical properties. The incorporation of CF into SrBi2Nb2O9 (SBN) resulted in hybrid composites with tailored properties. X-ray Diffraction (XRD) with Rietveld refinement analysis confirmed the formation of orthorhombic SBN and spinel CF phases. Field Emission Gun Scanning Electron Microscopy (FEG-SEM) revealed that SBN exhibits a plate-like morphology, with the incorporation of CF into the SBN matrix resulting in both plate-like and octahedral-shaped grains. The Brunauer–Emmett–Teller (BET) method was used to determine the pore radius and surface area, both of which were found to have increased, indicating an enhancement in photocatalytic performance. The presence of the constituent elements in the prepared compositions was confirmed by Energy Dispersive Spectroscopy (EDS). Fourier Transform Infrared Spectroscopy (FTIR) spectra were used to determine elastic properties, suggesting potential applications in electronic noise filtering. From Diffuse Reflectance Spectroscopy (DRS), a recognizable semiconducting behavior and band gap bowing were noticed in SBNCF nanocomposites on the obtained energy band gap values (2.20 eV - 1.56 eV) compared to the SBN host matrix (3.16 eV). The materials exhibited strong emission peaks at 470 nm, 528 nm, 584 nm, and 703 nm upon the excitation of 425 nm light using Photoluminescence (PL) spectroscopy. The white emission was predominant at room temperature in all the produced samples and the corresponding color temperature values range from 5865.93 K to 7599.05 K from the CIE diagram. The SBNCF materials are promising candidates in photocatalytic reactions and white light-emitting diodes (w-LEDs) based on their enhanced optical properties.

Computerized Principal Component–Canonical Discriminant Analysis Classification Model for Pollen Grain Identification Using Surface-Enhanced Raman Spectroscopy

Pollen identification and quantification are employed in various applications, and studies have been conducted to achieve precise automated pollen recognition to minimize the manual labor and subjectivity associated with human identification. The objective of the study was to evaluate the potential of surface-enhanced Raman spectroscopy (SERS) properties of pollen grain spectra, specifically within the spectral range of 582–1563 cm–1, using the convective assembly combined principal component–canonical discriminant analysis (PC-CDA) classification model. This research aimed to explore the feasibility of using this approach for the automated identification of pollen in the future. This approach facilitates the optimal arrangement of pollen grains and colloidal silver nanoprobes, thereby enhancing SERS spectra reproducibility using the convective assembly sampling method. Pollen grains can be characterized at a microscopic level without the need for purification-based analysis procedures. The findings demonstrate the possibility of rapid and accurate classification of pollen grains with the PC-CDA detection model with a 99.3% sensitivity, 97.6% specificity, and 98.5% accuracy. Research study indicates that the SERS properties of pollen spectra could serve as a promising method for automated pollen identification using the PC–CDA classification model.

ZnO nanostructures grown from spent batteries: Ambient catalytic aspects and novel mechanistic insights

The present work includes a facile and economic microwave assisted hydrothermal synthesis of Zinc Oxide (ZnO), Diethylene Triamine Pentaacetic Acid (DTPA) stabilized Zinc Oxide (ZD) and DTPA stabilized Silver doped Zinc Oxide (ZAD) nanostructures using Zn from spent alkaline batteries. The synthesised nanostructures were well characterised using electronic, vibrational and X-Ray spectroscopic techniques as well as thermal and microscopic techniques revealing the successful stabilisation of DTPA in ZD and doping of Ag in ZAD. The Fourier Transform Infrared Spectroscopy (FTIR) spectra showed peaks characteristic to the presence of ZnO in the fingerprint region and those to the presence of DTPA. The X-Ray Diffraction Spectroscopy (XRD) pattern of ZnO, ZD and ZAD indicated the hexagonal wurtzite structure of ZnO and face centred cubic metallic Ag in ZAD. The Transmission Electron Microscopy (TEM) images revealed rod shaped morphology for ZnO and spherical morphologies for ZD and ZAD. The nanostructures proved to be efficient catalysts to achieve 100 % degradation of Malachite Green, Crystal Violet and Reactive Blue-21 and their binary mixtures under ambient conditions in presence of Hydrogen peroxide (H2O2). ZAD exhibited relatively rapid degradation with rate constants 0.754 min−1, 0.187 min−1 and 0.0150 min−1 for MG, CV, and RB-21 respectively as well as 99 % reduction in Chemical Oxygen Demand (COD) value of the dye solutions. Scavenging studies and Electron Paramagnetic Resonance (EPR) studies using different spin trapping agents revealed the involvement of singlet oxygen species, hydroxyl radicals (OH.) and superoxide radicals (O2.-) in the degradation process. This work aligns with Sustainable Development Goals 6, 12 and 13.

Surface-enhanced Raman spectroscopy for the characterization of xylanases enzyme

Xylanases are essential hydrolytic enzymes which break down the plant cell wall polysaccharide, xylan composed of D-xylose monomers. Surface-enhanced Raman Spectroscopy (SERS) was utilized for the characterization of interaction of xylanases with xylan at varying concentrations. The study focuses on the application of SERS for the characterization of enzymatic activity of xylanases causing hydrolysis of Xylan substrate with increase in its concentration which is substrate for this enzyme in the range of 0.2% to 1.0%. SERS differentiating features are identified which can be associated with xylanases treated with different concentrations of xylan. SERS measurements were performed using silver nanoparticles as SERS substrate to amplify Raman signal intensity for the characterization of xylan treated with xylanases. Principal Component Analysis (PCA) and Partial Least Square Discriminant Analysis (PLS-DA) were applied to analyze the spectral data to analyze differentiation between the SERS spectra of different samples. Mean SERS spectra revealed significant differences in spectral features particularly related to carbohydrate skeletal mode and O-C-O and C–C–C ring deformations. PCA scatter plot effectively differentiates data sets, demonstrating SERS ability to distinguish treated xylanases samples and the PC-loadings plot highlights the variables responsible for differentiation. PLS-DA was employed as a quantitative classification model for treated xylanase enzymes with increasing concentrations of xylan. The values of sensitivity, specificity, and accuracy were found to be 0.98%, 0.99%, and 100% respectively. Moreover, the AUC value was found to be 0.9947 which signifies the excellent performance of PLS-DA model. SERS combined with multivariate techniques, effectively characterized and differentiated xylanase samples as a result of interaction with different concentrations of the Xylan substrate. The identified SERS features can help to characterize xylanases treated with various concentrations of xylan with promising applications in the bio-processing and biotechnology industries.

A robust 3D nanostructured composite polymer electrolyte with novel dual-ion channels toward solid-state sodium metal batteries

The high energy density and low cost of sodium metal batteries enable them to be the rising star of next-generation batteries. However, the growth of sodium dendrites and the high activity of sodium metal may lead to significant safety risks for liquid sodium metal batteries. Composite polymer electrolytes (CPEs), which combine the advantages of inorganic solid-state electrolyte and solid-state polymer electrolytes, have become a promising candidate to replace liquid electrolytes. In this study, a novel Na-beta-Al2O3/polyacrylonitrile (PAN) CPE with a 3D network nanostructure (NAP) has been synthesized by electrospinning method. NAP membrane provides synergistic dual-ion channels for the migration of sodium ions, exhibiting ionic conductivity of 7.22 × 10−4 S cm−1, a sodium-ion transport number of 0.73, and an electrochemical stabilization window as high as 4.92 V. Compared with pure PAN, NAP presents enhanced mechanical strength, superior electrochemical properties and interfacial stability. NAP-based sodium symmetric cell achieves stable plating and stripping for 800 h. At room temperature, the capacity retention ratios of NAP-based Na3V2(PO4)3//Na cell are 92.02% (0.2 C, 200 cycles) and 73.10% (0.5 C, 1000 cycles), respectively. The capacity retention is 72.49% after 250 cycles at 0.5 C and a high temperature of 60 °C. X-ray photoelectron spectroscopy spectra indicate that solid electrolyte interphase formed in NAP-based battery contains higher NaF component, R–(CO)O–Na content and interfacially favorable organic components, which are beneficial to accelerate the sodium-ion transfer at the interface. This work provides new insights into the construction of 3D nanostructured CPEs with fast ion transport for solid-state sodium metal batteries.

Efficient hole transport layers for silicon heterojunction solar cells by surface plasmonic modification in MoOx/Au NPs/MoOx stacks

This study explores the integration of Au nanoparticles (NPs) into molybdenum oxide (MoOx) thin films to form a MoOx/Au NPs/MoOx (MAM) stack. This stack serves as a hole transport layer (HTL) in silicon heterojunction solar cells, aiming to address the challenges of safety concerns and inefficient carrier transport. Ultraviolet photoelectron spectroscopy and X-ray photoelectron spectroscopy spectra demonstrate that the incorporation of Au NPs notably raises the work function of MAM to 5.85 eV and stabilize Mo6+ concentrations at 94.07%. In addition, Au NPs effectively act as a shield against detrimental interactions with Ag, thereby improving the interfacial stability between the back electrode and HTL. This strategic enhancement facilitates the formation of surface plasmon polaritons, reduces the contact resistance to 41.19 mΩ cm2, and boosts the quantum efficiency by injecting hot electrons and intensifying the surface electric field. These advancements lead to a significant enhancement in the fill factor and short-circuit current, leading to the development of a heterojunction solar cell with an increased efficiency (Eff) from 19.81% to 22.03%. This investigation underscores the transformative potential of engineered nanomaterials in elevating the performance and stability of photovoltaic devices, promoting the wider adoption of renewable energy technologies.