Specific Peak Research Articles

Biosynthesis of zinc oxide nanoparticles using water hyacinth extracts: Characterization, evaluation of antimicrobial and dye removal

In nanobiotechnology, synthesizing metal nanoparticles (NPs) using plant extracts has recently been increasing because of eco-friendly and low-cost methods. For this work, zinc oxide nanoparticles (ZnO NPs) have been synthesized by biosynthesis process using water hyacinth extracts (WHE). The water hyacinth (WH) was chosen because the WH is fast-growing and the most toxic aquatic plant in the world. Therefore, this work aims to apply these WHE to be a precursor in the biosynthesis of ZnO NPs (ZnOBio-NPs) based on the research of a sustainable environment. The ZnO NPs synthesized by the WHE were investigated for their antibacterial and photocatalytic activities. An UV-Vis spectrum showed a specific absorbance peak around 362 nm with an average band gap of 3.22 eV. As the result, TEM analysis revealed a triangle structure with an average size of about 64.05 nm. The peaks of XRD analysis show a hexagonal wurtzite structure. The ZnO NPs synthesized by the WHE showed higher antibacterial activity against S. aureus better than E. coli. It is interesting to note that the ZnOBio-NPs synthesized from the WHE can have an anti P. acnes (JB7) with a minimum inhibitory concentration (MIC) and a minimum bactericidal concentration (MBC) equal to 50 µg∙mL‒1 and 200 µg∙mL‒1, respectively. In addition, the ZnOBio-NPs also can effectively remove more than 90% of the malachite green within 180 minutes with extremely high reuse.

The combined use of serum Raman spectroscopy and D dimer testing for the early diagnosis of acute aortic dissection

ObjectivesAcute aortic dissection (AAD) is an extremely life-threatening medical emergency, often misdiagnosed in its early stages, resulting in prolonged wait times for rescue. This study aims to identify potential serum biomarkers that can assist in the accurate diagnosis of AAD and effectively differentiate it from other conditions causing severe chest pain. MethodsA total of 122 patients with AAD and 129 patients with other severe chest pain disorders were included in the study. Serum samples were analyzed by measuring the peak intensities of Raman spectra. For each measurement, the Raman spectrum was accumulated by two accumulations (3 s per acquisition). Logistic regression and nomogram models were developed using these peak intensities as well as D-dimer levels to predict the occurrence of AAD. The clinical utilities of these models were assessed through receiver operating characteristics (ROC) curve analysis, net reclassification improvement (NRI), integrated discrimination improvement (IDI), and decision curve analysis (DCA) in both training and internal test cohorts. ResultsThe D-dimer levels of AAD patients were significantly increased, as well as higher intensities at specific Raman peaks, including 505 cm−1, 842 cm−1, 947 cm−1, 1254 cm−1, 1448 cm−1, and 1655 cm−1 when compared to non-AAD patients. Conversely, decreased intensities were observed at Raman peaks such as 750 cm−1, 1004 cm−1, 1153 cm−1, 1208 cm−1, and 1514 cm−1 in AAD patients. Least absolute shrinkage and selection operator regression analysis on the training cohort identified eight potential predictors: D-dimer along with intensity measurements at peaks such as 505 cm−1, 750 cm−1, 1153 cm−1, 1208 cm−1, 1254 cm−1, 1448 cm−1, and 1655 cm−1. The combination of these eight potential predictors demonstrated a good discriminatory performance, with an area under the curve (AUC) value of 0.928 in the training cohort and an AUC of 0.936 in the internal test cohort, outperforming the use of D-dimer alone. Furthermore, DCA curve analysis revealed that leveraging this combination of eight potential predictors would provide substantial net benefits for clinical application. Moreover, this combination significantly augmented discrimination power, as evidenced by a continuous NRI of 39.8 % and IDI of 9.95 % in the training cohort, as well as a continuous NRI of 27.1 % and IDI of 9.95 % in the internal test cohort. ConclusionsThe employment of this combination of eight potential predictors effectively rules out AAD to a greater extent. This study presents a promising diagnostic strategy for early detection using optical diagnostic techniques such as Raman spectroscopy.

Use of Raman spectroscopy and PCA for quality evaluation and out-of-specification identification in biopharmaceutical products

Over the past three decades, there was a remarkable growth in the approval of antibody-based biopharmaceutical products. These molecules are notably susceptible to the stresses occurring during drug manufacturing, often leading to structural alterations. A key concern is thus the ability to detect and comprehend these alterations caused by processes, such as aggregation, fragmentation, oxidation levels, as well as the change in protein concentration throughout the process steps, potentially resulting in out-of-spec products.In the present study, Raman spectroscopy, coupled with Principal Component Analysis (PCA), has proven to be an excellent tool for characterizing protein-based products. Notably, it offers the advantages of being minimally invasive, rapid and relatively insensitive to water. Therefore, it was successfully employed to discriminate between various stresses impacting a monoclonal antibody (mAb). The molecule used in this study is a fully human IgG1 fusion protein. Thermal stress was induced by incubating the samples at 50 °C for one month, while oxidative stress was induced by introducing hydrogen peroxide. Additionally, dilutions were performed to explore a broader range of protein concentrations.Specific key bands were identified in the Raman spectra, which facilitated the PCA classification and allowed for their association with distinct changes in the secondary and tertiary structures of the protein. Notably, it was observed that signals corresponding to amino acids exhibited a decrease in intensity with increasing levels of thermal stress, while other alterations were noted in the amide bands. It was shown that changes in the range 2800–3000 cm-1 pertains to the dilution process, while specific peaks of C–H stretching were essential for the discrimination between the oxidative-stressed samples and the thermal and diluted counterparts. Furthermore, the model calibrated on the mAb demonstrated remarkable performance when used to evaluate a different product, e.g. a hormone.

Magnetic energy product and hysteresis behavior of antiperovskite Mn3AlN: Monte Carlo Simulation

In this study, we investigated the magnetic properties, magnetocaloric effect, magnetic energy product, and hysteresis behavior of Mn3AlN antiperovskite using Monte Carlo (MC) simulation techniques. We examined the effect of magnetic field on magnetic behavior. As the magnetic field values h increase, the amplitudes of both the specific heat peaks and the susceptibility also increase. For various external magnetic fields and temperatures, we obtained the adiabatic temperature change and the magnetic entropy change. The compound displayed a direct magnetocaloric effect. Furthermore, the relative cooling power (RCP) values for a magnetic field strength of 60 kOe are 117.54 J/kg. The hysteresis loops were used to calculate the energy product BH. These findings suggest that our material is an excellent fit for magnetic refrigeration and information storage applications.

A highly sensitive SERS substrate of porous membrane-Ag NPs for kidney cancer detection

BackgroundThe substrate employed in surface-enhanced Raman spectroscopy (SERS) constitutes an essential element in the cancer detection methodology. In this research, we introduce a three-dimensional (3D) structured SERS substrate that integrates a porous membrane with silver nanoparticles to enhance SERS spectral signals through the utilization of the aggregation effect of silver nanoparticles. This enhancement is crucial because accurate detection results strongly depend on the intensity of specific peaks in Raman spectroscopy. A highly sensitive SERS substrate can significantly improve the accuracy of detection results. ResultsWe collected 66 plasma samples from individuals with kidney cancer and control individuals, including both bladder cancer patients and healthy individuals. Then, we utilized substrates with and without porous membranes to acquire the SERS spectra of the samples, enabling us to evaluate the enhancement effect of our SERS substrate. The spectral analysis demonstrated enhanced peak intensities in the experimental group (with porous substrate) compared to the control group (without porous substrate). The uniformity and reproducibility of the SERS substrate are also significantly enhanced, which is very helpful for improving the accuracy of detection results. Additionally, the Principal Component Analysis-Linear Discriminant Analysis algorithm (PCA-LDA) was employed to classify the SERS spectra of both groups. In the experimental group, the classification accuracy was 98.5 % for kidney cancer, and 83.3 % for kidney and bladder cancer. Compared to the control group, it improved by 3 % and 12.6 % respectively. SignificantThis indicates that our 3D structured SERS substrate combined with multivariate statistical algorithms PCA-LDA can not only improve the accuracy of SERS detection technology in single cancer detection, but also has great potential in multiple cancer detection. This 3D structured SERS substrate is expected to become a new auxiliary means for cancer detection.

NH3-probe X-ray photoelectron spectroscopy method to characterize solid acidity of clay minerals

Accurate determination of solid acidity is essential for evaluating the catalytic activity of clay minerals. However, the conventional Fourier-transform infrared (FTIR) method using NH3 as the probe encounters challenges in measuring the solid acidity owing to the presence of water on the surface or within interlayer spaces of clay minerals as well as the influence of environmental water during the detection process. To mitigate water interference, a NH3-probe X-ray photoelectron spectroscopy (XPS) approach was adopted as an alternative to the FTIR method for the identification and semi-quantification of solid acidity of clay minerals. Following NH3 adsorption, the types of solid acid sites in clay minerals were identified through the chemical shift in N1s XPS spectra. The ratio of Brønsted and Lewis acid sites in a given sample and the relative concentration of acid sites across different samples were determined by examining the specific N1s peak area ratio. According to the XPS data, the ratios of Brønsted and Lewis acid sites in Ca-montmorillonite (SAz-2) and Na-montmorillonite (SWy-2) were nearly 1:1, whereas that for the illite–smectite mixed-layer mineral (ISCz-1) was 4. The acid site contents in SAz-2 were more than twice those of SWy-2. This work highlights the promising application prospects of the NH3-probe XPS method in solid acidity investigations of clay minerals.

Strategic Model for Yellow Hydrogen Production Using the Metalog Family of Probability Distributions

Storing energy in hydrogen has been recognized by scientists as one of the most effective ways of storing energy for many reasons. The first of these reasons is the availability of technology for producing hydrogen from water using electrolytic methods. Another aspect is the availability of relatively cheap energy from renewable energy sources. Moreover, you can count on the availability of large amounts of this energy. The aim of this article is to support the decision-making processes related to the production of yellow hydrogen using a strategic model which exploits the metalog family of probability distributions. This model allows us to calculate, with accuracy regarding the probability distribution, the amount of energy produced by photovoltaic systems with a specific peak power. Using the model in question, it is possible to calculate the expected amount of electricity produced daily from the photovoltaic system and the corresponding amount of yellow hydrogen produced. Such a strategic model may be appropriate for renewable energy developers who build photovoltaic systems intended specifically for the production of yellow and green hydrogen. Based on our model, they can estimate the size of the photovoltaic system needed to produce the assumed hydrogen volume. The strategic model can also be adopted by producers of green and yellow hydrogen. Due to precise calculations, up to the probability distribution, the model allows us to calculate the probability of providing the required energy from a specific part of the energy mix.

Sonochemical Synthesis of Copper Borates: Effect of Reaction Conditions on the Characteristic Properties

The effect of ultrasonic treatment on liquid-state production and the characteristic features of synthesized powder were studied in liquid-state conditions. In sonochemical synthesis, the operation parameters of mole ratio, reaction temperature, and time were optimized. The synthesis was achieved in moderate conditions such as mole ratio of copper: sodium: boron (Cu: Na: B) 1:2:1, 70°C and 2.5 minutes. The prepared samples were identified as copper borate (Cu(BO2)2) with the powder diffraction file number "00-001-0472". The reaction yields were also increased from 50% to 71.5% with the modification of the experimental procedure. The specific FT-IR peaks were observed at 1090, 985, 872, 781 and 731 cm-1 band values. In the morphological analyses, the agglomerations of multi-angular particles were seen. The results showed the affirmative effects of the possible use of the ultrasonic treatment on both the practical synthesis and the increase of characteristics.

Potential of MALDI-TOF MS biotyping to detect deltamethrin resistance in the dengue vector Aedes aegypti.

Insecticide resistance in mosquitoes is spreading worldwide and represents a growing threat to vector control. Insecticide resistance is caused by different mechanisms including higher metabolic detoxication, target-site modification, reduced penetration and behavioral changes that are not easily detectable with simple diagnostic methods. Indeed, most molecular resistance diagnostic tools are costly and labor intensive and then difficult to use for routine monitoring of insecticide resistance. The present study aims to determine whether mosquito susceptibility status against the pyrethroid insecticides (mostly used for mosquito control) could be established by the protein signatures of legs and/or thoraxes submitted to MALDI-TOF Mass Spectrometry (MS). The quality of MS spectra for both body parts was controlled to avoid any bias due to unconformity protein profiling. The comparison of MS profiles from three inbreeds Ae. aegypti lines from French Guiana (IRF, IR03, IR13), with distinct deltamethrin resistance genotype / phenotype and the susceptible reference laboratory line BORA (French Polynesia), showed different protein signatures. On both body parts, the analysis of whole protein profiles revealed a singularity of BORA line compared to the three inbreeding lines from French Guiana origin, suggesting that the first criteria of differentiation is the geographical origin and/or the breeding history rather than the insecticide susceptibility profile. However, a deeper analysis of the protein profiles allowed to identify 10 and 11 discriminating peaks from leg and thorax spectra, respectively. Among them, a specific peak around 4870 Da was detected in legs and thoraxes of pyrethroid resistant lines compared to the susceptible counterparts hence suggesting that MS profiling may be promising to rapidly distinguish resistant and susceptible phenotypes. Further work is needed to confirm the nature of this peak as a deltamethrin resistant marker and to validate the routine use of MS profiling to track insecticide resistance in Ae. aegypti field populations.

Detection of KPC directly from positive blood cultures by MALDI-TOF: From research to the clinical microbiology laboratory routine

Bloodstream infections (BSI) caused by carbapenem-resistant Gram-negative bacilli (CR-GNB) are a subject of major clinical concern, mainly those associated with carbapenemase-producing isolates. Matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) has been proposed to detect specific β-lactamases, including KPC. We aimed to detect KPC enzyme directly from positive blood cultures using MALDI-TOF MS. Overall, 146 clinical Gram-negative bacilli (46 CR-GNB) recovered from consecutive blood cultures were evaluated. Proteins were extracted using formic acid, isopropyl alcohol, and water and spotted onto a steel target plate using the double-layer sinapinic acid method. The relative ions intensity ≥120 arbitrary units (a.u.) of a peak close to 28,700 m/z indicated the presence of KPC. The results were compared to HRM-qPCR methodology. This specific peak was observed in 11/14 blood bottles with blaKPC positive isolates (78.6% sensitivity), with 3 false-positive results (97.7% specificity). Analysis from colonies reached identical sensitivity (78.6%), but higher specificity (100%). The detection of KPC peaks directly from positive blood cultures using MALDI-TOF MS is feasible and rapid. It's excellent specificity indicates that positive results are consistently associated with the presence of a KPC producer in positive blood culture.

Abstract 151: Single Cell Transcriptional And Epigenetic Map Of Human Coronary Artery Disease In A Multi-ethnic Population

Identifying target genes that are causally linked to coronary artery disease (CAD) remains an elusive problem despite the plethora of CAD genome-wide association study (GWAS) risk loci. Here, we performed single nucleus multiomic (RNA + ATAC) sequencing in 44 human coronary arteries and bulk Hi-C in 16 coronaries from multi-ethnic participants. From sequencing 126,804 nuclei, we identified cell type specific transcriptional signatures, chromatin peaks, and gene regulatory networks through peak to gene linkage analysis. Single-cell quantitative trait loci (QTL) analysis identified cell-specific caQTL’s including cell-type specific caQTLs within CAD GWAS loci. The overlap of CAD GWAS loci with ATAC peaks demonstrated that vascular smooth muscle and endothelial cells harbor the greatest genetic risk. To identify proximal and distal putative target genes for CAD loci in a cell type specific manner, we built a enhancer-gene map by leveraging coronary artery ChiP-seq, cell specific RNA/ATAC-seq, and Hi-C based chromatin contact loops. Using this map, we identified distal target genes linked to CAD GWAS loci. Finally, given the effect of ancestry on CAD GWAS risk interpretation, we leveraged Hi-C data to compare the chromatin architecture in coronary tissue from 8 European Americans vs 8 African Americans. A meta-map, sample level, and local ancestry analysis identified ancestry-specific differences in chromatin looping and topologically associated domains. Collectively, our results provide a cell-type specific transcriptomic and epigenetic map which along with bulk chromatin contacts can be used to interpret and prioritize CAD GWAS candidates and nominate cell specific causal target genes.

Inverse machine learning framework for optimizing gradient honeycomb structure under impact loading

In this study, an inverse design framework was constructed to explore gradient honeycomb structures (HCS) with high impact resistance. By establishing the relationship between the height of the cell and the cell-wall angle, HCS with different gradient modes were designed. The developed machine learning (ML) framework consisted of a forward regression model based on neural network (NN) and an inverse optimization model based on generative adversarial network (GAN). The regression model surrogated finite element analysis (FEA) to rapidly provide corresponding mechanical properties for the generated data of GAN. To ensure that the generated data met the desired design targets, additional physical constraints were incorporated into the generator of the GAN. This ensured that the network output not only consisted of valid data but also exhibited superior impact resistance. The results demonstrated that the trained ML model optimized both specific energy absorption (SEA) and initial peak stress of HCS. It even discovered high-performance gradient designs that outperformed the original data, with a maximum energy absorption 49.5% higher than that of uniform HCS. Moreover, the gradient modes and structural parameters of superior designs were identified, which is of great significance for the gradient design of HCS under impact loading. As a general design approach, this ML framework holds significant potential for the optimization design of metamaterials in other structures or with different mechanical properties.

Exploring the mechanism underlying the antifungal activity of chitosan-based ZnO, CuO, and SiO2 nanocomposites as nanopesticides against Fusarium solani and Alternaria solani

Chitosan-based nanocomposites (CS NCs) are gaining considerable attention as multifaceted antifungal agents. This study investigated the antifungal activity of NCs against two phytopathogenic strains: Fusarium solani (F. solani) and Alternaria solani (A. solani). Moreover, it sheds light on their underlying mechanisms of action. The NCs, CS-ZnO, CS-CuO, and CS-SiO2, were characterized using advanced methods. Dynamic and electrophoretic light scattering techniques revealed their size range (60–170 nm) and cationic nature, as indicated by the positive zeta potential values (from +16 to +22 mV). Transmission electron microscopy revealed the morphology of the NCs as agglomerates formed between the chitosan and oxide components. X-ray diffraction patterns confirmed crystalline structures with specific peaks indicating their constituents. Antifungal assessments using the agar diffusion technique demonstrated significant inhibitory effects of the NCs on both fungal strains (1.5 to 4-fold), surpassing the performance of the positive control, nystatin. Notably, the NCs exhibited superior antifungal potency, with CS-ZnO NCs being the most effective. A. solani was the most sensitive strain to the studied agents. Furthermore, the tested NCs induced oxidative stress in fungal cells, which elevated stress biomarker levels, such as superoxide dismutase (SOD) activity and protein carbonyl content (PCC), 2.5 and 6-fold for the most active CS-CuO in F. solani respectively. Additionally, they triggered membrane lipid peroxidation up to 3-fold higher compared to control, a process that potentially compromises membrane integrity. Laurdan fluorescence spectroscopy highlighted alterations in the molecular organization of fungal cell membranes induced by the NCs. CS-CuO NCs induced a membrane rigidifying effect, while CS-SiO2 and CS-ZnO could rigidify membranes in A. solani and fluidize them in F. solani. In summary, this study provides an in-depth understanding of the interactions of CS-based NCs with two fungal strains, showing their antifungal activity and offering insights into their mechanisms of action. These findings emphasize the potential of these NCs as effective and versatile antifungal agents.

The effects of re-irradiation on the chemical and morphological properties of permanent teeth.

This study aimed to assess the in vitro effects of re-irradiation on enamel and dentin properties, simulating head and neck cancer radiotherapy retreatment. Forty-five human permanent molars were classified into five groups: non-irradiated; irradiated 60Gy, and re-irradiated with doses of 30, 40, and 50Gy. Raman spectroscopy, scanning electron microscopy (SEM), and energy dispersive x-ray spectroscopy (EDS) were employed for analysis. Raman spectroscopy assessed intensity, spectral area, and specific peaks comparatively. Statistical analysis involved Kolmogorov-Smirnov and One-Way ANOVA tests, with Tukey's post-test (significance level set at 5%). Significant changes in irradiated, non-irradiated, and re-irradiated enamel peaks were observed, including phosphate (438nm), hydroxyapatite (582nm), phosphate (960nm), and carbonate (1070nm) (p < 0.05). Re-irradiation affected the entire tooth (p > 0.05), leading to interprismatic region degradation, enamel prism destruction, and hydroxyapatite crystal damage. Dentin exhibited tubule obliteration, crack formation, and progressive collagen fiber fragmentation. EDX revealed increased oxygen percentage and decreased phosphorus and calcium post-reirradiation. It is concluded that chemical and morphological changes in irradiated permanent teeth were dose-dependent, exacerbated by re-irradiation, causing substantial damage in enamel and dentin.

Exploring Challenging Properties of Liquid Metallic Systems through Machine Learning: Liquid La and Li4Pb Systems.

In this machine learning (ML) study, we delved into the unique properties of liquid lanthanum and the Li4Pb alloy, revealing some unexpected features and also firmly establishing some of the debated characteristics. Leveraging interatomic potentials derived from ab initio calculations, our investigation achieved a level of precision comparable to first-principles methods while at the same time entering the hydrodynamic regime. We compared the structure factors and pair distribution functions to experimental data and unearthed distinctive collective excitations with intriguing features. Liquid lanthanum unveiled two transverse collective excitation branches, each closely tied to specific peaks in the velocity autocorrelation function spectrum. Furthermore, the analysis of the generalized specific heat ratio in the hydrodynamic regime investigated with the ML molecular dynamics simulations uncovered a peculiar behavior, impossible to discern with only ab initio simulations. Liquid Li4Pb, on the other hand, challenged existing claims by showcasing a rich array of branches in its longitudinal dispersion relation, including a high-frequency LiLi mode with a nonhydrodynamic optical character that maintains a finite value as q → 0. Additionally, we conducted an in-depth analysis of various transport coefficients, expanding our understanding of these liquid metallic systems. In summary, our ML approach yielded precise results, offering new and captivating insights into the structural and dynamic aspects of these materials.

Development of a highly efficient solubilization method for mass spectrometric analysis of phospholipids in living single cells.

Phospholipids are vital constituents of the cell membrane and aid in signal transduction. Phospholipid profiles vary distinctively with the cell type. Notably, specific phospholipid molecules are present in significantly higher or lower concentrations in cancer cells versus normal cells. In this study, live single-cell mass spectrometry (MS) was developed for analyzing phospholipids at the single-cell level. This method facilitates rapid molecular analysis of cells under microscopic observation. For nanoelectrospray ionization, phospholipids were extracted from single cells isolated in a glass capillary through a high-efficiency process. Cell-derived phosphatidylcholines were detected with high sensitivity when trehalose C14 was added as a solubilizing reagent. Trehalose C14 can solubilize cells at low concentrations owing to its low critical micelle concentration, and exerts minimal matrix effects (such as suppressing ionization and causing peak overlap) in the MS analysis of cellular molecules. Analyses of phospholipids in Raji and HEV0070 cells using the developed method revealed specific peaks of phosphatidylcholine and sphingomyelin in the respective cells. The developed technique not only affords phospholipid profiles at the single-cell level, but also holds promise for identifying biomarkers associated with various diseases, particularly cancer.

A facile synthesis of iron single-atom electrocatalyst for high-performing oxygen reduction reaction and remarkable rechargeable zinc-air battery

Iron-based single-atom catalysts (SACs) are considered to the most promising catalysts to replace Pt for efficient oxygen reduction reaction (ORR). However, the precise synthesis of high-performance SACs and the understanding of their ORR origin remain challenging. In this work, microporous nitrogen-doped carbon with abundant and accessible atomically dispersed N-coordinated Fe sites (Fe-N-C) is prepared by molecular-confined coupling pyrolysis strategy. The Fe-N-C exhibits excellent ORR activities in acid (E1/2 of 0.78 V vs. RHE) and alkaline (E1/2 of 0.91 V vs. RHE) electrolytes. When integrated into a rechargeable aqueous Zinc-air battery (ZAB), both large specific capacity (770 mAh g−1) and high peak power density (240 mW cm−2) are achieved. Remarkably, the as-prepared ZAB presents amazing charge-discharge cycle performance of 1600 h at the large current density, which is 52.5 times of that using Pt/C+RuO2. Furthermore, all-solid-state ZAB delivers ultra-robust cycling stability even under bending. This work may advance a critical step towards the design of rational and controlled preparation of remarkable and ultra-stable catalysts.

Delving into judiciously extracted inexpensive micro-algal dyes for DSSCs: Spectral decipherment and time-oriented extraction systems

The temperature and extraction techniques used for natural dye fabrication in dye-sensitized solar cells have significant implications for the future economy, influencing the efficiency and yield of dye extraction. This study analyzes the optical properties of microalgal dyes, examining reflectance and photo-electron energy scans, alongside emission rates in the UV–visible region, using aqueous methanol and ethanol solvents. Different time-oriented extraction methods, involving heating and a combination of sonication and heating, are assessed for their impact on specific and non-specific dye and pigment peaks. Extended heating periods result in dye degradation, while longer sonication proves efficient at 60 °C. The sonication technique's efficiency exponentially increases with Scenedesmus sp. concentration but not as much with Asterarcys quadricellulare at 60 °C. Asterarcys quadricellulare exhibits higher efficiency with ethanol, especially at 80 °C, and performs comparably with Scenedesmus sp. The optimal heating duration ranges from 10 to 25 min, while sonication is more efficient within 25 to 40 min for both temperatures.

Characterization of hemicellulose‐carboxymethyl cellulose blend films: Enhancement of the physicochemical, thermal, and mechanical properties

AbstractThis study investigates the influence of hemicellulose (Hc) on the chemical composition, thermal stability, mechanical properties, and morphology of carboxymethyl cellulose (CMC). Hc was isolated from oil palm trunk and then added into CMC at 10–30 wt% to prepare Hc‐CMC films via solution casting method. The addition of Hc resulted in reduced visual transparency, rendering the blend films opaque. Fourier transform infrared spectroscopy verified the chemical interaction between Hc and CMC by revealing persistent and robust hydrogen bonding at specific spectral peaks (3483–3045 cm−1). The interaction between Hc and CMC was further indicated by the rougher interfacial structure as revealed in scanning electron microscopy (SEM). Thermal analysis via differential scanning calorimetry and thermogravimetry analysis indicated a decrement in thermal stability as Hc loadings increased in the CMC films. The highest tensile properties were observed in Hc‐CMC blend films at a 20 wt% Hc loading, showcasing notable enhancement about 23%. The 20 wt% Hc‐CMC blend films appeared as more suitable blending composition which having an enhanced physicochemical, thermal, and mechanical properties. This finding underscores its potential applicability in diverse industrial sectors, particularly in packaging applications.

Engineered biosorbents of pomelo (Citrus maxima (Burm.f.) Merr) peels modified with zinc oxide and titanium dioxide for methylene blue dye sorption

The pomelo-doped zinc oxide beads (PZB), pomelo-doped titanium dioxide beads (PTB), and pomelo-doped zinc oxide and titanium dioxide beads (PZTB) were synthesized for sorbing methylene blue (MB) dye. Their characterizations were explored by X-Ray Diffractometer (XRD), Field Emission Scanning Electron Microscopy and Focus Ion Beam (FESEM-FIB), Energy Dispersive X-Ray Spectrometer (EDX), and Fourier Transform Infrared Spectroscopy (FT-IR). In addition, their sorbent efficiencies for sorbing MB dye were investigated through batch experiments, sorbent reusability studies, sorption isotherms, kinetics, and thermodynamic studies. They were crystalline phases presenting the specific peaks of zinc oxide (ZnO) or titanium dioxide (TiO2). Their surfaces had lamella structures with coarse surfaces, and they also found specific structures of ZnO or TiO2 on the surfaces. Zn–O or Ti–O–Ti was also detected in PZB or PTB or, PZTB depending upon metal oxide types added into pomelo beaded sorbents. For batch experiments, they could adsorb MB dye of more than 86%, and PZTB showed the highest MB dye removal efficiency. In addition, they could be reused for more than three cycles with high MB dye sorptions of more than 72%. They corresponded to Freundlich and pseudo-second-order kinetic models. Moreover, the increasing temperature affected their decreasing MB dye sorptions which were exothermic processes.