Chemical Analysis Research Articles

Analyzing a series of ligands against malaria through the application of molecular docking, molecular quantum similarity, and reactivity indices

Background The primary goal of this research is to underscore the significance of molecular docking in the context of malaria drug discovery. Molecular docking plays a crucial role in comprehending the interactions between prospective drugs and the target proteins found in Plasmodium parasites. The study delves into the docking interactions of various compounds, emphasizing the necessity of stabilizing the active site to formulate potent and selective drugs. Methods The research focuses on highlighting compound-specific interactions with residues, stressing the importance of stabilizing the active site to design drugs tailored to specific target proteins. Inhibiting the function of these target proteins disrupts the life cycle of the malaria parasite. Quantum Similarity Analysis, utilizing Overlap and Coulomb operators, is employed to identify electronic similarities. The resulting quantum similarity values guide subsequent chemical reactivity analysis. Global reactivity indices such as chemical potential, hardness, softness, and electrophilicity contribute to drug design by showcasing compound-specific indices that underscore the significance of stability and electrophilicity. Fukui functions are utilized to visualize regions for stabilization, providing insights crucial for potential malaria treatment. Results The enhancement of drug-target binding affinity is observed through stabilizing interactions in the active site. Understanding electrophilicity at the active site emerges as a critical factor in drug design and selectivity. The rational manipulation of electrophilic interactions holds promise for developing potent and selective drugs against malaria. Consequently, the integration of molecular docking, quantum similarity analysis, and chemical reactivity indices offers a comprehensive approach to malaria drug discovery. Conclusions The study identifies potential lead compounds, emphasizing the crucial role of stabilizing the active site. Additionally, it sheds light on electronic considerations vital for the design of effective and resistance-resistant drugs. The insights provided by Fukui functions into regions susceptible to -H bond formation make these compounds promising candidates for malaria treatment.

Portable and Flexible Hydrogel Sensor for On-Site Atrazine Assay on Agricultural Products.

There is growing attention focused toward the problems of ecological sustainability and food safety raised from the abuse of herbicides, which underscores the need for the development of a portable and reliable sensor for simple, rapid, and user-friendly on-site analysis of herbicide residues. Herein, a novel multifunctional hydrogel composite is explored to serve as a portable and flexible sensor for the facile and efficient analysis of atrazine (ATZ) residues. The hydrogel electrode is fabricated by doping graphite-phase carbon nitride (g-C3N4) into the aramid nanofiber reinforced poly(vinyl alcohol) hydrogel via a simple solution-casting procedure. Benefiting from the excellent electroactivity and large specific surface area of the solid nanoscale component, the prepared hydrogel sensor is capable of simple, rapid, and sensitive detection of ATZ with a detection limit down to 0.002 ng/mL and per test time less than 1 min. After combination with a smartphone-controlled portable electrochemical analyzer, the flexible sensor exhibited satisfactory analytical performance for the ATZ assay. We further demonstrated the applications of the sensor in the evaluation of the ATZ residues in real water and soil samples as well as the user-friendly on-site point-of-need detection of ATZ residues on various agricultural products. We envision that this flexible and portable sensor will open a new avenue on the development of next-generation analytical tools for herbicide monitoring in the environment and agricultural products.

Rapid assessment of the main economic value indicators in lupine flour samples using infrared spectroscopy

Background. A calibration model has been developed for rapid assessment of economic value indicators (protein, oil, and quinolizidine alkaloid contents) in the seeds of narrowleaf lupine accessions from VIR using near-infrared spectroscopy, with the help of which it is possible to decide on the further use of the accessions.Materials and methods. Biochemical quality indicators (protein, oil, and quinolizidine alkaloid content) were studied in the seeds of narrowleaf lupine (Lupinus angustifolius L.) grown in 2019 in the northwest of Russia. Calibration models for measuring protein, oil and alkaloids in lupine seeds (62 accessions) were developed using a MATRIX-I IR analyzer (Bruker Optics, Germany). To construct calibration models, we used the values obtained by chemical analysis methods accepted at VIR. The oil content in lupine seeds was assessed by the defatted dry residue technique in Soxhlet extractors, protein by the Kjeldahl method, and quinolizidine alkaloids by gas chromatography coupled with mass spectrometry. All indicators were recalculated on the dry-weight basis.Results and conclusion. Statistical significance of the developed models was verified according to the results of measuring the content of protein, oil and alkaloids in the seeds of the test batch. The protein and oil content data obtained using a calibration curve did not differ significantly from the results of chemical studies, in contrast to alkaloid indicators. Consequently, the developed calibration model for the MATRIX-I IR analyzer can be used for rapid assessment of protein and oil content in narrowleaf lupine flour samples, thus accelerating the process of obtaining data on the main economic value indicators. The analysis does not require reagents and is safe.

Methodological aspects of using NIR spectroscopy to assess biochemical indicators in barley grain

Background. The possibility of applying near-infrared reflectance (NIR) spectroscopy for rapid assessment of various biochemical parameters in barley varieties and forms is discussed. The data obtained by the Biochemistry and Molecular Biology Department of VIR served to construct calibration models for the content of protein, starch, oil, beta-glucans, and total phenolic compounds (PhC) in grain, facilitating further screening of various barley samples.Materials and methods. The chemical composition of grain was studied in naked and covered spring barley (Hordeum vulgare L.) accessions grown in 2022 in the northwest of Russia. Calibration models were developed to measure the content of protein, oil, starch, beta-glucans, and PhC (80 accessions) in barley grain with the Matrix-I IR analyzer (Bruker Optics, Germany). The models were constructed on the basis of the data obtained by conventional techniques of chemical analysis. The protein/ nitrogen content was assessed using the Kjeldahl method, oil according to the method of defatted dry residue modified by S. V. Ruszkovsky, starch by the polarimetric method according to Evers, beta-glucans by gravimetric analysis, and the total PhC content by the Folin–Ciocâlteu method modified by Singleton and Rossi.Results. Statistical significance of the constructed calibration tests was compared with the results of measuring protein, starch, oil, beta-glucan and PhC levels by chemical methods. It was shown that the data of calibration techniques for protein and starch were significant, while the remaining models required improvement.Conclusion. The proposed method helps to preserve valuable source material, increases labor efficiency, and does not require chemical reagents. Scanning each sample makes it possible to obtain data for several indicators at once, with a specified replication and standard deviation.

Biosensor-Based Assessment of Pesticides and Mineral Fertilizers’ Influence on Ecotoxicological Parameters of Soils under Soya, Sunflower and Wheat

Pesticides and fertilizers used in agriculture can negatively affect the soil, increasing its toxicity. In this work, a battery of whole-cell bacterial lux-biosensors based on the E. coli MG1655 strain with various inducible promoters, as well as the natural luminous Vibrio aquamarinus VKPM B-11245 strain, were used to assess the effects of agrochemical soil treatments. The advantages of using biosensors are sensitivity, specificity, low cost of analysis, and the ability to assess the total effect of toxicants on a living cell and the type of their toxic effect. Using the V. aquamarinus VKPM B-11245 strain, the synergistic effect of combined soil treatment with pesticides and mineral fertilizers was shown, which led to an increase in the overall (integral) toxicity of soils higher than that of the individual application of substances. Several probable implementation mechanisms of agrochemical toxic effects have been discovered. DNA damage caused by both SOS response induction and alkylation, oxidative stress due to increased superoxide levels, and damage to cellular proteins and membranes are among them. Thus, the usage of biosensors makes it possible to assess the cumulative effect of various toxicants on living organisms without using expensive chemical analyses.

End-user verification results of two serum separator tubes for clinical chemistry analytes according to CLSI GP34-A and CLSI GP41-A6

Tube manufacturers use different composition of gels and blood clot activator formulations in serum tube production. Our aim was to investigate the within-tube (repeatability) and between-tube variation, concordance between comparison results of BD and VacuSEL tubes. Blood samples were collected from control subjects (n = 20) and patients (n = 30) in accordance with the CLSI GP41-A6 and CLSI GP34-A guidelines. Twenty-three clinical chemistry parameters were analysed via Roche Cobas C702 Chemistry Analyzer on T0 (0 hour) and T24 (24 hour). Mean differences % were compared with Wilcoxon matched pair test. Clinical significance was evaluated based on desirable bias according to total allowable error (TEa). VacuSEL tubes demonstrated acceptable performance for the results of 20 parameters with regards to desirable bias % limits. Lactate dehydrogenase (LD) [mean difference % (%95 confidence intervals (CI) values of BD and VacuSEL tubes at T0 [6.41% (4.80–8.01%)]; sodium (Na) and total protein (TP) at T24 [-0.27% (-0.46 to −0.07%) and −1.39% (-1.87 to −0.91), respectively] were over the desirable bias limits (LD: 4.3%, Na: 0.23% and TP: 1.36%, respectively) but not exceeding total biological variation CV % [Na: 0.5 (0.0–1.0) % and TP: 2.6 (2.3–2.7) %). %95 confidence intervals (CI) of T0 LD values overlap with within-subject biological variation % (CI) limits (LD: 5.2 (4.9–5.4) %). The differences between two tubes were not medically significant and necessarily conclusive. VacuSEL serum tubes presented comparable performance with BD serum tubes.

The use of Tetraselmis chuii as seafood flavoring agent in a vegetable broth

The growing demand of seafood alternatives is driven by concerns on overfishing, marine pollutants and animal welfare in aquaculture and fisheries. Currently, the availability of non-animal-based seafood flavorings on the market is limited, and animal-based seafood flavorings conflict with vegetarian and vegan criteria.The aim of this study is to explore the use of Tetraselmis chuii as a seafood flavoring in a vegetable broth. The flavor of the T. chuii broth was compared with a broth containing vegan fish flavoring based on a yeast extract and two broths containing white fish and lobster flavorings. To evaluate the different broths, the study employs a combination of sensory evaluation by a trained panel, chemical flavor analysis for aroma and umami characteristics, and consumer acceptability tests.Our results indicate that T. chuii effectively imparts a fish and shellfish flavor to the broth, which is less intense compared to the white fish and lobster flavorings. Nevertheless, consumers are equally positive of the aroma and flavor of the T. chuii broth and the animal-based seafood flavorings broths. The chemical flavor analysis of the T. chuii broth identifies volatile organic compounds (VOCs) such as dimethyl sulfide, methanethiol, trimethylamine, and 4-heptenal (Z), which collectively contribute to its distinct seafood aroma.Consumer preference tests show a preference for the seafood aroma of the T. chuii broth over the vegan fish flavoring broth, attributed to the meaty-like off-odor originating from specific VOCs of the yeast extract. In contrast, the vegan fish flavoring broth exhibits a stronger umami taste which is explained by elevated levels of free glutamate and guanosine-5′-monophosphate.This study highlights the potential of T. chuii as innovative seafood flavoring agent to enhance the sensory experience of seafood alternatives, contributing to the ongoing development of sustainable and flavorful non-animal alternatives in the food industry.

Applicability of ChatGPT 3.5 in the development of new analytical procedures

Artificial intelligence (AI) is gradually expanding into various fields of science and research, and chemistry is no exception. Although the use of AI in analytical chemistry is today in its infancy, significant progress and an increasing number of publications can be observed here, too. The emergence of user-friendly AI models, such as ChatGPT 3.5, which can understand human-oriented texts and engage in natural conversations without requiring programming skills, offers undeniable benefits. In this work experiences with the use of ChatGPT in the development of a new analytical procedure are presented. The development of a new method for the extraction and determination of bioactive compounds in plant samples was chosen as a model. The goal was to use AI in as many steps as possible in the development of a new procedure and to verify whether AI can fully plan an experiment, choose the optimal conditions, explain the results and evaluate the environmental friendliness of the developed procedure. What AI can do, how it can be useful for the analyst by relieving him of boring and routine tasks, to what extent it can be trusted and what the analyst must pay attention to were examined. We also explored whether AI, on the basis of experimental results, can write a high-quality scientific paper and therefore stand in for analysts. The role and importance of the analytical chemist and his knowledge, experience and creativity for obtaining the best results is emphasized. We hope that our observations, findings and considerations will interest analytical chemists and help them in their research.

Bridging the green talent gap: a case study of product design education

AbstractThis research examines how sustainable product design education can address the deficit in green talent. It presents a framework for a structured curriculum in product design, with hands-on activities, industry-specific case studies, and best practices in alternative design development. The impact of technologies like additive manufacturing on design is considered. Findings demonstrate that knowledge of technological capabilities, industry specific understanding, and proficiency in analytical tools such as Life Cycle Assessments contribute to sustainable designs mitigating a green talent gap.

Mechanistic insight into the anti-alternaria activity of bimetallic zinc oxide and silver/zinc oxide nanoparticles

Alternaria alternata is an opportunistic phytopathogen that negatively impact the growth and production of a wide variety of host plants. In this study, we evaluated the antifungal potential of biogenic ZnO, and bimetallic silver and zinc oxide (Ag/ZnO) nanoparticles synthesized using seed extract of Abrus precatorious and characterized using different analytical tools. In vitro antifungal potentials of ZnO and Ag/ZnO nanoparticles were carried out using the food poison technique. Morphological and ultrastructure of the A. alternata treated with the nanoparticles were carried out using high resolution scanning and transmission electron microscopy (HRSEM and HRTEM). In addition, changes in polysaccharide production, chitin content and enzymatic (cellulase and lipase) activities of A. alternata were assayed. Double peak signifying a UVmax of 353.88 and 417.25 nm representing Ag and ZnO respectively was formed in the bimetallic nanoparticles. HRSEM and HRTEM results shows agglomerated nanoparticles with particle and crystallite size of 23.94 and 16.84 nm for ZnO nanoparticles, 35.12 and 28.99 nm for Ag/ZnO nanoparticles respectively. In vitro antifungal assay shows a significant concentration-dependent inhibition (p < 0.05) of A. alternata mycelia with highest percentage inhibition of 73.93 % (ZnO nanoparticles) and 68.26 % (Ag/ZnO nanoparticles) at 200 ppm. HRSEM and HRTEM micrographs of the treated A. alternata mycelia shows alteration of the cellular structure, clearance of the cytoplasmic organelles and localization of the nanoparticles within the cell. A. alternata treated with 200 ppm nanoparticles show a significant decrease (p < 0.05) in the polysaccharides and chitin contents, cellulase and lipase activities. The results suggests that ZnO and Ag/ZnO nanoparticles mode of action may be via alteration of the fungal cell wall through the inhibition of polysaccharides, chitin, cellulases and lipases synthesis. ZnO and Ag/ZnO nanoparticles may be a promising tool for the management and control of disease causing fungal phytopathogens.

A novel method for quantitative determination of multiple substances using Raman spectroscopy combined with CWT

The identification of mixed solutions is a challenging and important subject in chemical analysis. In this paper, we propose a novel workflow that enables rapid qualitative and quantitative detection of mixed solutions. We use a methanol-ethanol mixed solution as an example to demonstrate the superiority of this workflow. The workflow includes the following steps: (1) converting Raman spectra into Raman images through CWT; (2) using MobileNetV3 as the backbone network, improved multi-label and multi-channel synchronization enables simultaneous prediction of multiple mixture concentrations; and (3) using transfer learning and multi-stage training strategies for training to achieve accurate quantitative analysis. We compare six traditional machine learning algorithms and two deep learning models to evaluate the performance of our new method. The experimental results show that our model has achieved good prediction results when predicting the concentration of methanol and ethanol, and the coefficient of determination R2 is greater than 0.999. At different concentrations, both MAPE and RSD outperform other models, which demonstrates that our workflow has outstanding analytical capabilities. Importantly, we have solved the problem that current quantitative analysis algorithms for Raman spectroscopy are almost unable to accurately predict the concentration of multiple substances simultaneously. In conclusion, it is foreseeable that this non-destructive, automated, and highly accurate workflow can further advance Raman spectroscopy.

Structural study of a polysaccharide component of nfnB mutant of Shewanella vesiculosa HM13

Shewanella vesiculosa HM13 is a Gram-negative bacterium able to produce a large amount of extracellular membrane vesicles. These nanoparticles carry a major protein P49, the loading of which seems to be influenced by the glycans decorating the membrane. Here we report the structural characterization, using chemical analyses and NMR spectroscopy, of the capsular polysaccharides isolated from the nfnB-mutant strain of S. vesiculosa HM13, which is unable to load P49 on the membrane vesicles. In addition to the polysaccharide corona isolated and characterized from the parental strain, the nfnB-mutant strain released another polysaccharide composed of disaccharide repeating units having the following structure:→4)-β-D-Glc-(1→3)-β-D-GlcNAc-(1→

Pepper mild mottle virus as an effective tool in microbial source tracking for deficient domestic on-site water treatment systems

Pollution from domestic on-site wastewater treatment systems (OWTS) is a significant contaminant pressure in many rural catchments. However, due to their design, and dispersed proliferation, it is difficult to assess their impact. Water testing methodologies employ bacterial culturing methods and chemical analysis which may lose resolution and/or specificity being confounded by diffuse agricultural sources within a rural environment. In this study, we successfully assessed the applicability of Pepper Mild Mottle Virus (PMMoV) as a human faecal source tracker for deficient on-site wastewater treatment systems. The transport of PMMoV was first studied in the effluent of a 30 cm deep soil column which was dosed for 510 days with primary influent from a conventional septic system. The removal of PMMoV through the 30 cm deep soil column was quantified with a 5-day seeding trial employing primary influent mixed with PMMoV sourced from Tabasco pepper product ®. The trial was then carried out at field scale with the seeding solution dosed into an operational percolation trench receiving septic tank effluent which had been instrumented for porewater sampling. Samples were taken at depths of 10 cm, 30 cm, and 50 cm across the length of the trench at distances of 1 m, 7.5 m, and 17.5 m from the inlet of the trench. PMMoV was detected on all days of the trial, with a peak concentration of 1 × 106 found at the rear of the trench on day 2 of the seeding trial. Finally, to assess the effectiveness of PPMoV as a microbial source tracking tool from a water receptor perspective, three rural catchments with high densities of OWTSs were sampled and analysed for hourly variations in biological parameters which included total coliforms, Escherichia coli, PMMoV, and chemical parameters total organic carbon, total nitrogen, and total carbon. PMMoV was detected in all river samples over a 24-hour period, thereby indicating its suitability as a tracer of human wastewater effluent in such environments with multiple diffuse sources.

Machine learning to identify structural motifs in asphaltenes

Asphaltenes are organic compounds that aggregate in crude oil with two dominant molecular architectures: archipelago and continental. Continental architectures possess a single uniform island structure composed of aromatic rings in contrast to archipelago architectures with aromatic cores interconnected through aliphatic chains. The structural composition of asphaltenes varies globally due to geographical differences, posing challenges in their classification due to a lack of uniformity. This study is the first known exploration of using image-based supervised machine learning, particularly ResNet-50, for the binary classification of asphaltenes into continental and archipelago motifs. 255 continental and archipelago models underwent structural augmentations to create a sample size of 1,530 asphaltene structures that is robust enough for accurate results in both the training and testing portions of the machine learning. These augmentations included the repeated addition of carbons until a complete pentane chain was added to a specified carbon on each asphaltene structure. Using Mathematica, supervised ResNet-50 image-based classification was used on both original and augmented structure datasets to classify as either archipelago or continental. The classification was also implemented using topological similarity searching for association between atoms and the distance between them for further molecule identification. This study demonstrates the surprising effectiveness of image-based classification compared to traditional topological feature-based methods. Our results reveal that deep learning techniques, especially image-based approaches, provide novel and insightful ways to differentiate complex molecular structures like asphaltenes, challenging the traditional reliance on topological features alone. This research opens new avenues in chemical analysis and molecular characterization, highlighting the potential of machine learning in complex molecular systems.

Comprehensive investigation of coffee acidity on eight different brewing methods through chemical analyses, sensory evaluation and statistical elaboration

Even if the acids composition and their role in coffee still need to be clarified, acidity is one of the main sought-after features in coffee and it is becoming one of the main quality markers. Hence, the aim of this paper was to evaluate the main parameters influencing coffee acidity with a focus on carboxylic acids. To the best of our knowledge, this is the first study regarding filter coffee prepared from specialty and mainstream coffee, differently roasted and through eight diverse extraction methods. Coffee cup chemical composition in terms of organic and chlorogenic acids, caffein and physicochemical parameters were correlated with perceived sourness and mouthfeel to better understand the influence of extracted compounds on the final beverage acidity. Statistical tools revealed that a major impact of chlorogenic acids emerged in pH and titratable acidity, while the sensorial sourness appeared more correlated with organic acids concentration. Thus, these findings suggests that organic acids could be potential predictors of beverage perceived acidity.

Enhancement of the alloyed CdZnSeS/ZnS quantum dots photoluminescence by thiol ligands capping

Most of the existing hydrophilization techniques for the semiconductor quantum dots (QDs) lead to degradation of photoluminescence (PL). Therefore, for the applying of QDs in the areas requiring their stability in water media (e.g. bio- and chemical analysis, labeling and sensing), it is often necessary to find a balance between high stability, good optical properties, and difficulty of acquiring. This article describes simple, fast, and easy scalable methods for alloyed CdZnSeS/ZnS QDs ligand exchange using 2-mercaptoethanol, thioglycolic, 3-mercaptorpopionic and dihydrolipoic acids. The proposed ligand exchange techniques provide the enhancement of the QDs photoluminescence intensity in contrast to most of other ligand exchange procedures on the QDs surface. In optimized conditions the twofold photoluminescence quantum yield increase compared to the initial hydrophobic CdZnSeS/ZnS QDs was achieved. Hydrophilized nanoparticles maintained colloidal stability for a period more than 13 months. The suggested mechanism of the PL increase is the passivation of the QDs surface with molecules containing a thiol group. The combination of the proposed effective CdZnSeS/ZnS QDs synthesis and modification methods shows the prospect of their implementation as basic luminescent material for a wide range of applications.

Antifungal efficacy of natural antimicrobial substances during the fermentation and storage of hardaliye

Hardaliye is a non-alcoholic traditional fermented beverage produced using black grapes, mustard seeds, sour cherry leaves, and sodium benzoate. In this study, the effect of using plant materials (quince leaves, green tea, mulberry leaves, linden flowers, horseradish roots) as an alternative to sodium benzoate for inhibiting yeast growth to produce additive-free hardaliye was investigated. Hardaliye samples were produced using the selected test materials, microbiological and chemical analyses were performed during fermentation (20 °C for 18 days) and storage (4 °C for 2 months) periods. Additionally, the antifungal effects of test material extracts against Saccharomyces cerevisiae in grape juice and Malt Extract Broth (MEB), as well as the survival of S. cerevisiae in grape juice containing plant materials were examined. Only mustard seed extract had inhibitory and fungicidal effects at 25 mg/mL on S. cerevisiae in MEB among the tested plant material extracts and the effect increased when used in combination with grape juice. The total phenolic contents of the hardaliye samples were in the range of 2119.26–8653.33 mg gallic acid equivalents (GAE)/L, and antioxidant activities were in the range of 30.24–93.15%. The numbers of S. cerevisiae decreased below the detection limit (<1 log CFU/mL) after 1 day in grape juice containing horseradish (5%), mustard seeds (1.5%) or sodium benzoate (0.1%). This study indicated that crushed mustard seeds at increased concentrations (1.5%), mustard seeds water extract (7.5 mg/mL), or horseradish roots (5%) have the potential to be used in the production of hardaliye as an alternative to sodium benzoate.

Determination of phthalate esters contents in different types of cheese produced and consumed in Saudi Arabia

Background: Phthalates’ esters are commonly incorporated into plastic materials to enhance their elasticity, thereby facilitating their migration into food items. Aims: To evaluate the levels of phthalate esters in six distinct varieties of locally produced cheese and sold in Saudi Arabia, at the time of purchase (t=0) and after storage for one and two months. Methods: Six types of local cheeses (Cheddar, Mozzarella, Feta, Cheeseburger slices, Haloumi and Kashkaval) were purchased and analyzed at three different intervals: at the time of purchase (t=0), after one month, and after two months of storage. The Phthalate ester concentrations were determined using indirect gas chromatography with results expressed in mg/kg of cheese. Results: Among the cheese samples analyzed, di(2-ethylhexyl) phthalate (DEHP) was found to be the most prevalent. Halloumi cheese exhibited the highest average concentration of DEHP (4.29 ± 0.51 mg/kg) followed by Mozzarella cheese (3.65 ± 0.46 mg/kg). After two months of storage, more than two-thirds (n=13) of the samples exceeded the permissible limits content of DEHP content while one-third (n=6) and more than half (n=9) exceeded the limits for dibutyl phthalate (DBP) and di-n-octyl phthalate (DNOP), respectively. The levels of phthalates in all cheese types increased with prolonged storage duration with Cheddar cheese exhibiting the highest rate of increase, exceeding fivefold (from 0.34 to 2.29 mg/kg). Conclusion: This study confirms the presence of phthalate in cheese samples, with concentrations varying depending on the cheese type, specific phthalate compound, and storage duration. Heightened consumer awareness regarding cheese storage practices is imperative to mitigate potential health risks associated with phthalate consumption. Keywords: Phthalate, cheese, chemical analysis, content, Saudi Arabia.

Changes in crystallinity of sago palm (Metroxylon sago spp.) waste during cellulose extraction

Changes in crystallinity of sago palm (Metroxylon sago spp.) waste during cellulose extraction

Failure analysis of a forming assembly used in aluminum packaging tubes production

A local company produces aluminum collapsible tubes for the packaging of a medicinal ointment. A tooling subassembly comprised of a plug and a sleeve is used for the forming of its metallic neck is failing repeatably; it causes extended downtimes to the production line. Historical data was collected, and macroscopic examination was performed. A photographic archive was created so the substantial features of the incident to be recorded. Hardness measurements were carried out on specific surfaces of the parts and the steel grades selected for their manufacturing were identified by chemical analysis. Samples were designated and prepared for optical and electron microscopy. The study involved the examination of the microstructure and fracture morphologies of the specimens derived from the failed parts. Conclusions related to the fracture mechanism and failure mode are presented. Relatively wide dimensional tolerances between the forming tools led to lack of concentricity between the plug and the sleeve; provoking malfunction of the forming process and finally lead to the brittle fracture of the die. Furthermore, the frequency of the plug failure should have been an indication of unsuitable material-working hardness combination. Corrective as well as preventive actions are proposed.