Surface Area Measurements Research Articles

A Novel ultrasensitive nitrite ion detection using tungsten trioxide-modified gold electrode

A novel ultrasensitive nitrite ion detection using tungsten trioxide/carbon (WO3/C) modified gold electrode has been studied. The WO3 was synthesized from tungsten metal through chemical methods with selective precipitation techniques. The visual color of the material obtained is bright yellow, indicating WO3 compound. The X-ray diffraction (XRD) diffractogram confirms WO3 compound in monoclinic shaped by showing of the 2θ at 23.205, 23.723, 24.384, 33.426, and 33.911. The characterization using Field Emission Scanning Electron Microscopy (FESEM) showed that the material obtained was a disk-shaped with diameter 150–250 nm and a thickness of 50 nm. The Energy Dispersive X-ray spectroscopy (EDX) also confirms WO3 compound with no impurities. The gold electrode was modified by dip immersion technique where the gold electrode was dipped in a mixture of WO3-carbon paste. The measurement of surface area by cyclic voltammetry shows that the WO3/C modified gold electrode has the highest surface area compared to unmodified gold and C-modified gold electrode, indicating it has more active electron transfer sites. The WO3/C modified gold electrode worked well at pH 7 for the detection of nitrite ion and gave the highest peak current (0.875 V) than the others. The measurement ranges from 1–200 mg/L with no interference from NO3−, SO42−, Zn2+, Fe2+, Pb2+, Cl−, Ca2+, and NH4+ ions. The sensitivity and the LOD of the electrode are 8.86 μA.L.mg−1.cm−2 and 0.8 µg/L, respectively. The proposed method not only exhibits identical precision and accuracy to the standard method in detecting nitrite ions in real samples but also offers the advantages of rapid analysis, uncomplicated pretreatment procedures, environmental friendliness, and economical operation. This performance indicates that the WO3/C modified gold electrode is feasible as an alternative electrode for nitrite ion detection.

Adsorption of Eriochrome Black T on Pseudo Boehmite and Gamma Alumina Synthesized from Drinking Water Treatment Sludge: A Waste-to-Recycling Approach

Eriochrome black T is considered as one of the anionic dyes with potential harmful effects on human health and the environment. Among other processes, adsorption can contribute to the removal of these dyes. In the present study, two adsorbent materials, pseudo-boehmite (γ-AlOOH) and gamma alumina (γ-Al2O3), were synthesized and tested in the removal of the Eriochrome black T molecule (EBT). γ-AlOOH and γ-Al2O3 were obtained by precipitation from NaAlO2 solution at pH = 7, at a temperature of 80 °C, and by the thermal transformation of γ-AlOOH at 800 °C, respectively. In order to gain insights into the structural, chemical, thermal and morphological properties of these materials, numerous analytical techniques were involved, including X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR), differential thermogravimetric–thermal analysis (TGA-DTA), scanning electron microscopy with energy-dispersive spectroscopy (SEM-EDS), and specific surface area measurement using the Brunauer–Emmett–Teller (BET) method. Several adsorption parameters were studied, such as the adsorbent dose, initial concentration, pH, contact time and reaction temperature. The kinetic study showed that EBT adsorption follows the pseudo-second-order model. The Langmuir isotherm model revealed a maximum EBT adsorption capacity of 344.44 mg g−1 and 421.94 mg g−1 for γ-AlOOH and γ-Al2O3, respectively. A textural and structural analysis after adsorption highlighted the effective adsorption of the dye.

Age-related decline in thickness and surface area in the cortical surface and hippocampus: lifespan trajectories and decade-by-decade analyses.

Previous studies on age-related changes in cortical and hippocampal morphology were not designed or able to reveal the complex spatial patterns of changes across the lifespan. To this end, the current study examined these changes in a decade-by-decade manner by comparing consecutive age decades at the vertex-wise level. Additionally, the lifespan trajectories of cortical/hippocampal mean thickness and total surface area were modeled and plotted out to provide an overview of their age-related changes. Using two lifespan datasets (Ntotal = 1378; 18 ≤ age ≤ 100), vertex-wise thickness and surface area measurements were extracted from the cortical and unfolded hippocampal surfaces and analyzed using whole-brain/hippocampus vertex-wise analyses. Lifespan trajectories of cortical/hippocampal mean thickness and total surface area were modeled with generalized additive models for location, scale, and shape. These models revealed fairly linear declines in both cortical measures and inverted U-shaped trajectories for both hippocampal measures. Across the different age decades, the sizes and locations of cortical thinning clusters were highly variable across the age decades. No significant clusters of cortical surface area changes were observed across the age decades. Significant clusters of hippocampal surface area and thickness reduction were not observed until the 70s. Generally, the agreement between datasets on the hippocampal findings was much higher than those of the cortical surface. These findings revealed important nuances in the age-related changes of cortical and hippocampal morphology and cautioned against using lifespan trajectories to infer decade-by-decade changes in the cortical surface and the hippocampus.

Principal component analysis as an efficient method for capturing multivariate brain signatures of complex disorders-ENIGMA study in people with bipolar disorders and obesity.

Multivariate techniques better fit the anatomy of complex neuropsychiatric disorders which are characterized not by alterations in a single region, but rather by variations across distributed brain networks. Here, we used principal component analysis (PCA) to identify patterns of covariance across brain regions and relate them to clinical and demographic variables in a large generalizable dataset of individuals with bipolar disorders and controls. We then compared performance of PCA and clustering on identical sample to identify which methodology was better in capturing links between brain and clinical measures. Using data from the ENIGMA-BD working group, we investigated T1-weighted structural MRI data from 2436 participants with BD and healthy controls, and applied PCA to cortical thickness and surface area measures. We then studied the association of principal components with clinical and demographic variables using mixed regression models. We compared the PCA model with our prior clustering analyses of the same data and also tested it in a replication sample of 327 participants with BD or schizophrenia and healthy controls. The first principal component, which indexed a greater cortical thickness across all 68 cortical regions, was negatively associated with BD, BMI, antipsychotic medications, and age and was positively associated with Li treatment. PCA demonstrated superior goodness of fit to clustering when predicting diagnosis and BMI. Moreover, applying the PCA model to the replication sample yielded significant differences in cortical thickness between healthy controls and individuals with BD or schizophrenia. Cortical thickness in the same widespread regional network as determined by PCA was negatively associated with different clinical and demographic variables, including diagnosis, age, BMI, and treatment with antipsychotic medications or lithium. PCA outperformed clustering and provided an easy-to-use and interpret method to study multivariate associations between brain structure and system-level variables. PRACTITIONER POINTS: In this study of 2770 Individuals, we confirmed that cortical thickness in widespread regional networks as determined by principal component analysis (PCA) was negatively associated with relevant clinical and demographic variables, including diagnosis, age, BMI, and treatment with antipsychotic medications or lithium. Significant associations of many different system-level variables with the same brain network suggest a lack of one-to-one mapping of individual clinical and demographic factors to specific patterns of brain changes. PCA outperformed clustering analysis in the same data set when predicting group or BMI, providing a superior method for studying multivariate associations between brain structure and system-level variables.

Particle Sizing and Surface Area Measurements: A Comparative Assessment of Commercial Air Permeability and Laser Light Diffraction Instruments

Six different commercial powders, finer than 45 μm, were used for examining the effects of particle characteristics on mean particle size and specific surface area. The measurements were carried out using the most commonly used air permeability- and laser light diffraction (scattering) techniques. As the air permeability method has been used as a benchmark for decades in the powder metallurgy (P/M) industry, the physical phenomena that govern the passage of gas through the powder bed under laminar flow conditions were also presented. The experimental data indicate that both methods give similar results for spherical powders. The advantage of laser light systems over gas permeameters is the ability to provide additional information on particle size distribution. Irregularly shaped powders should be analyzed by both techniques, relying on gas permeametry for surface area measurements and on laser light diffraction for the estimation of mean particle size and size distribution. Application of scanning electron microscopy as a complementary technique was found very helpful in the interpretation of data through visualization of individual particles.

Automatic cortical surface parcellation in the fetal brain using attention-gated spherical U-net.

Cortical surface parcellation for fetal brains is essential for the understanding of neurodevelopmental trajectories during gestations with regional analyses of brain structures and functions. This study proposes the attention-gated spherical U-net, a novel deep-learning model designed for automatic cortical surface parcellation of the fetal brain. We trained and validated the model using MRIs from 55 typically developing fetuses [gestational weeks: 32.9 ± 3.3 (mean ± SD), 27.4-38.7]. The proposed model was compared with the surface registration-based method, SPHARM-net, and the original spherical U-net. Our model demonstrated significantly higher accuracy in parcellation performance compared to previous methods, achieving an overall Dice coefficient of 0.899 ± 0.020. It also showed the lowest error in terms of the median boundary distance, 2.47 ± 1.322 (mm), and mean absolute percent error in surface area measurement, 10.40 ± 2.64 (%). In this study, we showed the efficacy of the attention gates in capturing the subtle but important information in fetal cortical surface parcellation. Our precise automatic parcellation model could increase sensitivity in detecting regional cortical anomalies and lead to the potential for early detection of neurodevelopmental disorders in fetuses.

International comparisons in the field of measurement of specific adsorption of gases and specific surface area of solids: the optimal amount to ensure calibration and measurement capabilities

Indicators of the accuracy of measurements of the most important characteristics of the structure of porous and dispersed materials - specific adsorption of gases, specific surface area, specific pore volume and pore size – are considered. The performance of sorbents, catalysts and membranes in the chemical and petroleum industries, including the purification of substances and materials, depends on the values of these characteristics. It has been established that for mutual recognition of national standards and certificates of calibrations and measurements of porosity characteristics of solid substances performed by national metrological institutes, it is required to organize and successfully participate in three international key comparisons under the auspices of the Consultative Committee for Amount of Substance: Metrology in Chemistry and Biology of the International Bureau of Weights and Measures. The results of the participation of national metrology institutes and designated organizations of Germany, China, Japan, Brazil, Turkey and Russia in three international key comparisons in the field of measurements of specific adsorption of gases (nitrogen, argon, krypton) and specific surface area of solids (zeolite, silicon oxides and aluminum) are presented. Carrying out the optimal number of comparisons makes it possible to register in the Key Comparison Database of the International Bureau of Weights and Measures the measuring and calibration capabilities of the national metrological institutes of the participating countries for various matrices in a wide range of measurements of specific adsorption of gases 0.001–25 mol/kg and specific surface area of solids 0.1–1500 m2/g. Based on the results of these three international key comparisons, 18 of broad calibration and measurement capabilities of the Russian participant, the D. I. Mendeleev Institute for Metrology, were entered into the Key Comparison Database; two of these items are currently undergoing examination, including reference materials produced by this institute. A comparative analysis of the results of measurements of the specific surface area of solids using nitrogen and krypton as adsorbates was performed. It has been established that the uncertainty of the measurement results of the specific surface area is significantly less in the case of using krypton as an adsorbate with a specific surface area of less than 1 m2/g, which is due to the higher values of the relative pressure of krypton compared to nitrogen. The use of calibration and testing laboratories in Russia of certified reference materials of sorption properties presented in the Key Comparison Database of the International Bureau of Weights and Measures will ensure metrological traceability in the field of measurements of porosity characteristics.

Towards High-Performance Photo-Fenton Degradation of Organic Pollutants with Magnetite-Silver Composites: Synthesis, Catalytic Reactions and In Situ Insights.

In this study, Fe3O4/Ag magnetite-silver (MSx) nanocomposites were investigated as catalysts for advanced oxidation processes by coupling the plasmonic effect of silver nanoparticles and the ferromagnetism of iron oxide species. A surfactant-free co-precipitation synthesis method yielded pure Fe3O4 magnetite and four types of MSx nanocomposites. Their characterisation included structural, compositional, morphological and optical analyses, revealing Fe3O4 magnetite and Ag silver phases with particle sizes ranging from 15 to 40 nm, increasing with the silver content. The heterostructures with silver reduced magnetite particle aggregation, as confirmed by dynamic light scattering. The UV-Vis spectra showed that the Fe:Ag ratio strongly influenced the absorbance, with a strong absorption band around 400 nm due to the silver phase. The oxidation kinetics of organic pollutants, monitored by in situ luminescence measurements using rhodamine B as a model system, demonstrated the higher performance of the developed catalysts with increasing Ag content. The specific surface area measurements highlighted the importance of active sites in the synergistic catalytic activity of Fe3O4/Ag nanocomposites in the photo-Fenton reaction. Finally, the straightforward fabrication of diverse Fe3O4/Ag heterostructures combining magnetism and plasmonic effects opens up promising possibilities for heterogeneous catalysis and environmental remediation.

IMAC application of extracellular polymeric substances doped composite membranes for α-amylase immobilization and kinetic studies

Immobilized metal affinity chromatography (IMAC), extensively utilized technique in affinity chromatography, has proven to be highly effective in purifying α-amylase, a crucial enzyme in industrial applications. Here, Poly (2-hydroxyethyl methacrylate) (PHEMA) based composite membranes were fabricated using the radical copolymerization technique in a petri dish. Extracellular polymeric materials (EPS) as the metal binding agent. The attachment of Cu2+ ions to the membranes occurred through the utilization of EPSs (Cu2+-EPS). The membranes having Cu2+-EPS (Cu2+-EPS-PM) were subjected to various characterization techniques, including scanning electron microscopy (SEM), attenuated total reflectance-fourier transform infrared spectroscopy (ATR-FTIR), swelling tests, and surface area measurements. The investigation also encompassed the examination of various factors, including pH, initial α-amylase concentration, temperature, and ionic strength, that exert an influence on the adsorption of α-amylase from an aqueous medium. The Cu2+-EPS-PMs demonstrated maximum adsorption capacity with a value of 54.2 mg/g polymer (pH 5.0 sodium acetate buffer, temperature: 25°C, initial α-amylase concentration of 2 mg/mL). Additionally, it has been observed that the enzyme is able to be used in adsorption and desorption cycles on Cu2+-EPS-PM many times. The investigation also focused on examining the impact of pH, temperature, storage, and operational stability over the activities of both free and immobilized α-amylase. The outcomes showed that immobilization had positive effects on activity.

Automated 3-D Computer-Aided Measurement of the Bony Orbit: Evaluation of Correlations among Volume, Depth, and Surface Area.

(1)The study aimed to measure the depth, volume, and surface area of the intact human orbit by applying an automated method of CT segmentation and to evaluate correlations among depth, volume, and surface area. Additionally, the relative increases in volume and surface area in proportion to the diagonal of the orbit were assessed. (2) CT data from 174 patients were analyzed. A ball-shaped mesh consisting of tetrahedral elements was inserted inside orbits until it encountered the bony boundaries. Orbital volume, area depth, and their correlations were measured. For the validation, an ICC was used. (3) The differences between genders were significant (p < 10-7) but there were no differences between sides. When comparing orbit from larger to smaller, a paired sample t-test indicated a significant difference in groups (p < 10-10). A simple linear model (Volume~1 + Gender + Depth + Gender:Depth) revealed that only depth had a significant effect on volume (p < 10-19). The ICCs were 1.0. (4) Orbital volume, depth, and surface area measurements based on an automated CT segmentation algorithm demonstrated high repeatability and reliability. Male orbits were always larger on average by 14%. There were no differences between the sides. The volume and surface area ratio did not differ between genders and was approximately 0.75.

Placental structural adaptation to maternal physical activity and sedentary behavior: findings of the DALI lifestyle study.

Are maternal levels of moderate-to-vigorous physical activity (MVPA) and sedentary time (ST) in obese pregnant women associated with placental structural adaptations for facilitating oxygen delivery to the fetus? Higher maternal MVPA and ST are associated with a higher density of villi, a proxy measure of placental surface area for oxygen delivery to the fetus, without further added placental vessels. Physical activity during pregnancy intermittently reduces uterine blood flow, potentially limiting placental and fetal oxygen supply. The placenta can mount several adaptive responses, including enlargement of the surface area of villi and/or feto-placental vessels to accommodate fetal needs. Early research on the morphology and growth of the placenta with exercise interventions has shown inconsistencies and is lacking, particularly in non-lean pregnant women. This study is a secondary longitudinal analysis of the vitamin D and lifestyle intervention for gestational diabetes prevention (DALI) randomized controlled trial. The prospective study was conducted between 2012 and 2015 in nine European countries at 11 different sites. In this analysis, 92 pregnant women with a BMI ≥ 29 kg/m2 were combined into one cohort. MVPA and percentage of time spent sedentary (% ST) were measured with accelerometers during gestation. Placental sections were immunostained for endothelial cell-specific CD34. Artificial intelligence (AI)-based stereology assessed villous density, number, and cross-sectional area of vessels on whole-slide images and in selected regions comprising peripheral villi only, where the majority of vascular adaptations occur. Expression of pro- and anti-angiogenic factors was quantified using molecular counting analysis. In multivariable regression, higher levels of maternal MVPA (min/day) were associated with a higher density of villi in both whole-slide images (beta 0.12; 95% CI 0.05, 0.2) and selected regions (0.17; CI 0.07, 0.26). Unexpectedly, ST was also positively associated with density of villi (0.23; CI 0.04, 0.43). MVPA and ST were not associated with vessel count/mm2 villous area, vessel area, or pro- and anti-angiogenic factor mRNA expression. All estimates and statistical significance of the sensitivity analyses excluding smokers, women who developed gestational diabetes or pre-eclampsia and/or pregnancy-induced hypertension were similar in the main analysis. The placenta is a complex organ undergoing dynamic changes. While various adjustments were made to account for different maternal contributing factors, in addition to the outcome measures, various other factors could impact oxygen delivery to the fetus. For the first time, we evaluated the association between placental structures quantified using an AI-based approach with objectively measured physical activity and ST at multiple time points in pregnant women with obesity. The observed adaptations contribute to the advancement of our understanding of the hemodynamics and adaptations of the placental unit in response to MVPA and ST. However, our results might not be generalizable to lean pregnant women. The DALI project has received funding from the European Community's 7th Framework Program (FP7/2007-2013) under grant agreement no. 242187. The funders had no role in study design, collection of data, analyses, writing of the article, or the decision to submit it for publication. The authors have no conflicts of interest to declare. ISRCTN70595832.

NRN1 epistasis with BDNF and CACNA1C: mediation effects on symptom severity through neuroanatomical changes in schizophrenia

The expression of Neuritin-1 (NRN1), a neurotrophic factor crucial for neurodevelopment and synaptic plasticity, is enhanced by the Brain Derived Neurotrophic Factor (BDNF). Although the receptor of NRN1 remains unclear, it is suggested that NRN1’s activation of the insulin receptor (IR) pathway promotes the transcription of the calcium voltage-gated channel subunit alpha1 C (CACNA1C). These three genes have been independently associated with schizophrenia (SZ) risk, symptomatology, and brain differences. However, research on how they synergistically modulate these phenotypes is scarce. We aimed to study whether the genetic epistasis between these genes affects the risk and clinical presentation of the disorder via its effect on brain structure. First, we tested the epistatic effect of NRN1 and BDNF or CACNA1C on (i) the risk for SZ, (ii) clinical symptoms severity and functionality (onset, PANSS, CGI and GAF), and (iii) brain cortical structure (thickness, surface area and volume measures estimated using FreeSurfer) in a sample of 86 SZ patients and 89 healthy subjects. Second, we explored whether those brain clusters influenced by epistatic effects mediate the clinical profiles. Although we did not find a direct epistatic impact on the risk, our data unveiled significant effects on the disorder’s clinical presentation. Specifically, the NRN1-rs10484320 x BDNF-rs6265 interplay influenced PANSS general psychopathology, and the NRN1-rs4960155 x CACNA1C-rs1006737 interaction affected GAF scores. Moreover, several interactions between NRN1 SNPs and BDNF-rs6265 significantly influenced the surface area and cortical volume of the frontal, parietal, and temporal brain regions within patients. The NRN1-rs10484320 x BDNF-rs6265 epistasis in the left lateral orbitofrontal cortex fully mediated the effect on PANSS general psychopathology. Our study not only adds clinical significance to the well-described molecular relationship between NRN1 and BDNF but also underscores the utility of deconstructing SZ into biologically validated brain-imaging markers to explore their mediation role in the path from genetics to complex clinical manifestation.

Maize leaves as a precursor for the synthesis of greened silver nanocomposite and nanoparticles

This study is aimed at the synthesis of nanoparticles (NPs) and nanocomposite (NC) using maize leave as precursor. Silver NPs (AgNPs) and AgNCs were synthesized from silver nitrate and maize leave extract using green approach. The maize leave NPs (AgNPs) and the maize leave NCs (AgNCs) were characterized using Fourier Transform infrared (FTIR), scanning electron microscopy (SEM), energy dispersion x-ray (EDX), Brunauer–Emmett–Teller (BET) surface area measurement, and dynamic light scattering (DLS) particle size analysis. The phytochemical analysis revealed the presence of tannin, oxalate, and flavonoids in appreciable quantity, which have proven to be a powerful reducing agent that facilitates the reduction of silver ions for the synthesis of silver NPs and silver nano composites. FTIR revealed that all the peaks identified in AgNPs and AgNCs belong to the characteristic bands of reducing compounds such as flavonoid compounds. The SEM-EDX results showed that the peaks observed from 2.9 to 3.1 Kev in the spectra indicate the presence of elemental silver as it is reduced from Ag+ to Ag. DLS analysis results showed that the average size and polydispersity index (PdI) of the synthesized AgNPs and AgNCs were 42.30 and 68.29 nm, 0.691 and 0.270, respectively. The single point BET surface area (m2/g) obtained for AgNPs and AgNCs were 223.3 and 209.5, respectively. The results showed maize leave as a potential precursor for the preparation of NPs and NCs.

Evaluation and 3D imaging of mineral structure changes of the rabbit (New Zealand) skull during developmental periods.

This study aimed to determine the morphometric measurements anatomically and CT images of skulls of healthy male and female rabbits during postnatal development, to analyse the data statistically and to demonstrate the structural changes in bone. A total of 40 rabbits (20 females and 20 males) were divided into four groups including prepubertal period (group I (0-1 month)), period between adolescence and adulthood (group II (3-5 month)) and later (young adult period as group III (1-3 years) and old adult period as group IV (3-5 years)), with five animals in each group. After the morphometric measurements, the surface area and volume values of the skull were calculated. The skulls were reconstructed using a 3D Slicer (5.0.2), which is used for 3D modelling. The cranial bones in each group were then crushed using a grinder so that the powdered samples were obtained for XRF (X-ray fluorescence technique). The p-value was statistically highly significant between group and gender (p < 0.001). In morphometric measurements, males were generally higher than females. Only PL, GBOC and GNB measurements were higher in females. The p-value between groups (in all measurements), between genders (in TL, GLN, FL, VL, OZB and GBN parameters) and between groups and genders (in TL, DL and VL parameters) was statistically highly significant (p < 0.001). The p-value between the groups, p-value between sexes and p-value between group and sex in Si, P, K, Ca, Ni, Zn, Sr, Sr and Ca/P elements were statistically significant (p < 0.001). Consequently, metric, volume and surface area measurements were taken through 3D modelling of skull bone in prepubertal period (group I), period between adolescence and adulthood (group II) and later (young adult period as group III and old adult period as group IV) of rabbits and the change in the mineral structure during postnatal development and effect of sex on this change were investigated. This might be the first study to assess both metric and mineral changes at four age intervals taken during the life span of rabbits.

New interactive machine learning tool for marine image analysis.

Advancing imaging technologies are drastically increasing the rate of marine video and image data collection. Often these datasets are not analysed to their full potential as extracting information for multiple species is incredibly time-consuming. This study demonstrates the capability of the open-source interactive machine learning tool, RootPainter, to analyse large marine image datasets quickly and accurately. The ability of RootPainter to extract the presence and surface area of the cold-water coral reef associate sponge species, Mycale lingua, was tested in two datasets: 18 346 time-lapse images and 1420 remotely operated vehicle video frames. New corrective annotation metrics integrated with RootPainter allow objective assessment of when to stop model training and reduce the need for manual model validation. Three highly accurate M. lingua models were created using RootPainter, with an average dice score of 0.94 ± 0.06. Transfer learning aided the production of two of the models, increasing analysis efficiency from 6 to 16 times faster than manual annotation for time-lapse images. Surface area measurements were extracted from both datasets allowing future investigation of sponge behaviours and distributions. Moving forward, interactive machine learning tools and model sharing could dramatically increase image analysis speeds, collaborative research and our understanding of spatiotemporal patterns in biodiversity.

Ammonium ion removal from aqueous solutions in the presence of organic compounds, using biochar from banana leaves. Competitive isotherm models

BackgroundIndustrial, e.g. food industrial and domestic wastewaters contain huge amount of compounds causing eutrophication, and should be removed with high cost during wastewater treatment. However, these compounds could be utilized as fertilizers too. Biochar can remove a wide range of pollutants from water, such as ammonium, which can be found in relatively high concentration in dairy wastewaters. However, adsorption performance may be affected by the presence of other wastewater pollutants. Thus, this study aims to determine the efficiency of biochar as an adsorbent of ammonium in aqueous solutions in the presence of some selected organic compounds of typical dairy wastewaters such as bovine serum albumin (BSA), lactose, and acetic acid. Methods: The biochar was produced from banana leaves at 300 °C, modified with NaOH, and characterized by Scanning Electron Microscope – Energy Dispersive X-Ray Spectroscopy (SEM-EDX), Fourier-transform infrared spectra (FTIR) analysis, and specific surface area measurements. Batch experiments were carried out to investigate the ammonium adsorption capacity and the ion competitive adsorption mechanism. Significant Findings: Results show that the surface structure of the biochar derived from banana leaves is different from other biochars previously studied; although the specific surface area is not very considerable and despite having nitrogen within the elemental composition, the biochar studied is capable of adsorbing 2.60 mg NH4+/m2, the highest ammonium removal in 2 h occurs at pH 9 and 500 mg biochar dose. Langmuir model in the monolayer phase analysis fits better for all scenarios and the maximum NH4+ adsorption capacity was 0.97 mg/g without organic compounds. In the multilayer adsorption phase, the isotherm model that best fits the data obtained is the Harkins-Jura model without organic compounds. The presence of organic compounds in the aqueous solution significantly impacts the adsorption of ammonium by biochar since it improves the adsorption capacity (1.132 mg/g BSA, 0.975 mg/g lactose, and 1.874 mg/g acetic acid). The Aranovich-Donohue isotherm model fitted the data obtained during ion competitive adsorption experiments well.

Boosted Bio-Jet production: Unveiling the potential of a one-stage concurrent process of deoxygenation/upgrading versus two-stage sequential processes using Pt/Cl-Al2O3@Ni/ZSM-5 catalysts

Bio-jet fuel production from renewable bioresources is an increasingly attractive approach for mitigating the environmental impacts of aviation. Among the different methods available for deriving bio-jet fuel from fatty acids, catalytic hydroprocessing has emerged as a promising and commercially viable technique. Recent studies have focused on identifying suitable catalysts to produce kerosene-type bio-jet fuel, which can serve as blend stocks for aviation fuel after further cracking and isomerization. In this study, a bi-layer catalyst Pt/Cl-Al2O3@Ni/ZSM-5 catalyst was prepared and characterized using various techniques (including XRD, TEM, NH3–TPD, FTIR, H2–TPR, XPS, surface area, and pore size measurements). The thus-prepared catalyst is tested for bio-jet fuel production from Palm kernel oil (PKO). A novel one-stage process yields a high iso-alkane content with a low freezing point of –57 °C. The proposed Pt/Cl-Al2O3@Ni/ZSM-5 bi-layer catalysts in a one-stage process provided satisfactory results, with a conversion rate of 96%. The primary component of the resulting bio-jet fuel was alkanes in the C8-C16 range, with an isomers/normal-alkane (I/N) ratio of 2 and a proportion of 75.6 wt%. Interestingly, the produced bio-jet fuel using the one-stage strategy has significant potential for use as a blend stock to enhance the properties of traditional jet fuels (Jet A and Jet A-1, JP-5, and JP-8).

Assessment of Potential Use of a Composite Based on Polyester Textile Waste as Packing Elements of a Trickle Bed Bioreactor.

Biological wastewater treatment using trickle bed reactors is a commonly known and used solution. One of the key elements of the proper operation of the trickle bed bioreactor is the appropriate selection of biofilm support elements. The respective properties of the bioreactor packing media used can influence, among other things, the efficiency of the treatment process. In this study, the possibility of polyester waste material usage for the preparation of the biofilm support elements was tested. The following properties were checked: adsorption capacity, swelling, surface morphology, microbicidal properties, as well as the possibility of their use in biological wastewater treatment. The tested elements did not adsorb copper nor showed microbicidal properties for bacterial strains Escherichia coli and Staphylococcus aureus as well as fungal strains Aspergillus niger and Chaetomium globosum. The hydrophilic and rough nature of the element surface was found to provide a friendly support for biofilm formation. The durability of the elements before and after their application in the biological treatment process was confirmed by performing tests such as compressive strength, FTIR analysis, hardness analysis and specific surface area measurement. The research confirmed the applicability of the packing elements based on polyester textile waste to the treatment of textile wastewater. The treatment efficiency of the model wastewater stream was above 90%, while in the case of a stream containing 60% actual industrial wastewater it was above 80%. The proposed solution enables the simultaneous management of textile waste and wastewater treatment, which is consistent with the principles of a circular economy. The selected waste raw material is a cheap and easily available material, and the use of the developed packing elements will reduce the amount of polyester materials ending up in landfills.

On a Dowker-Type Problem for Convex Disks with Almost Constant Curvature

A classical result of Dowker (Bull. Amer. Math. Soc. 50: 120-122, 1944) states that for any plane convex body 𝐾, the areas of the maximum (resp. minimum) area convex 𝑛-gons inscribed (resp. circumscribed) in 𝐾 is a concave (resp. convex) sequence. It is known that this theorem remains true if we replace area by perimeter, or convex 𝑛-gons by disk-𝑛-gons, obtained as the intersection of 𝑛 closed Euclidean unit disks. It has been proved recently that if 𝐶 is the unit disk of a normed plane, then the same properties hold for the area of 𝐶-𝑛-gons circumscribed about a 𝐶-convex disk 𝐾 and for the perimeters of 𝐶-𝑛-gons inscribed or circumscribed about a 𝐶-convex disk 𝐾, but for a typical origin-symmetric convex disk 𝐶 with respect to Hausdorff distance, there is a 𝐶-convex disk 𝐾 such that the sequence of the areas of the maximum area 𝐶-𝑛-gons inscribed in 𝐾 is not concave. The aim of this paper is to investigate this question if we replace the topology induced by Hausdorff distance with a topology induced by the surface area measure of the boundary of 𝐶.

Optimization of Desalination Efficiency and Exploratory Applications of TiO2 Active Site Electrode Enhanced by Activated Carbon and Tween 80 in Capacitive Deionization Technology.

Capacitive deionization (CDI) is an emerging desalination technology for seawater desalination. The development of high-desalination and long-life electrode materials is a research focus in the global water treatment field. In this experiment, Tween T80 was used as a surface activator, and a modified electrode was prepared by facilitating the deposition of TiO2 active sites onto the surface of activated carbon through a sol-gel/hydrothermal two-step synthesis strategy. The morphology and specific surface area of the composite material were analyzed through scanning electron microscopy, specific surface area measurements, and contact angle tests. The results indicated that the sol-gel/hydrothermal two-step synthesis strategy played a crucial role in the homogeneous combination and performance enhancement of the composite material. Under constant voltage mode, when the working voltage was 1.2 V, the desalination capacity of this composite material in a NaCl solution with an initial conductivity of 3000 μS·cm-1 reached 23.8 mg·g-1 (26% higher than materials prepared by conventional sol-gel methods). After 150 cycles, the capacity retention rate was 78%, and the retention capacity was significant (87%). Overall, the results demonstrate the potential of the sol-gel/hydrothermal two-step synthesis strategy in preparing high-performance CDI electrode materials. The modified electrode prepared using this method offers enhanced desalination capacity and durability, making it a promising candidate for seawater desalination and other water treatment applications.