Batch Method Research Articles

Combined absorbent of corn husks and eggshells activated by sodium hydroxide as an adsorbent for Remazol Yellow FG dye in textile waste

Reactive dyes such as Remazol Yellow FG are contaminants that are difficult to degrade in the environment. The adsorption method is an alternative to overcome this problem. Corn husk and eggshells can be adsorbents in adsorption. Corn husk contains an organic compound called cellulose, while eggshells have the main component of calcium carbonate. Corn husks and eggshells have the potential to be adsorbents with different characteristics. This research aimed to determine the optimum conditions for the combined adsorbent of corn husks and eggshells, which included composition comparison, contact time, pH, and application in dye waste. The interactions between Remazol Yellow FG dye in solution and combined adsorbent were conducted in batch method. Based on the research results, the optimum composition of corn husks and eggshells was 1:2, with an optimum contact time of 80 minutes at a pH of 2, resulting in an adsorption capacity of 0.559 mg/g, with an adsorption percentage of 33.95%. Adsorption of Remazol Yellow FG in sewage using combined adsorbents under optimal conditions obtained an adsorption capacity of 36.6579 mg/g with an adsorption percentage of 27.87%. The results demonstrate that the combined adsorbent of corn husks and eggshells is a potentially useful for removing Remazol Yellow FG dye from textile wastewater.

The Influence of Solution Concentration and pH for Removal Indigo Carmine using Banana Stem as a Biosorbent

The textile industry is one sector that generates effluent containing a significant quantity of pollutants, including dyes, and thus has an effect on the environment. Synthetic dyes, which are toxic and difficult to degrade, are utilized extensively in the textile industry. Therefore, a new study utilizes banana stems as a cost-effective biosorbent to remove indigo carmine dye. This research aims to investigate the use of banana stem waste as a bisorobent in batch method to adsorption indigo carmine dye. The optimal concentration and pH values are 2 and 900 mg/L, respectively. The interaction between the indigo carmine dye and the banana stems is suggested by the FTIR analysis. The solution's indigo carmine dye may be adsorbed by banana stem.

THE EFFECT OF CONTACT TIME AND BIOSORBENT TEMPERATURE ON THE ADSORPTION OF INDIGO CARMINE DYES IN KAPOK HUSK BIOSORBENT MODIFIED WITH SNAIL MEAT AND KINETIC STUDY

The use of indigo carmine dye in the textile industry is a source of pollution for the environment. The presence of dye pollutants in the environment can threaten the health of living creatures and the sustainability of the ecosystem. This research uses kapok husk biosorbent modified with snail meat. Previously, research on adsorption was carried out on metals and cationic dyes from kapok husk, then in this research adsorption was carried out using the batch method to adsorb anionic dyes. The biosorbent modification process using snail meat aims to add active sites in the form of functional groups to the biosorbent to optimize the dye adsorption capacity. The contact objective of this research is to determine the heating time and temperature conditions for optimal adsorption of indigo carmine using the batch method. The research results showed that the adsorption capacity was at optimum conditions for the adsorption of indigo carmine at a contact time of 60 minutes and a temperature of 25°C.

Influence of Selected Factors on the Adsorption Layer Structure of Polyamino Acids and Their Block Copolymers at the Solid-Aqueous Solution Interface.

The adsorption mechanism of different polymers containing ionic polyamino acids monomers in the chain structure at the solid-liquid interface was investigated. Initially, the influence of molecular weight and solution pH on simple polyamino acids (poly(L-aspartic acid) and poly(L-lysine) binding was determined. Considering the obtained dependencies, the polymer adsorption layer conformation was proposed in the systems containing block copolymers (both diblock and symmetrical triblock) consisting of polypeptide as well as poly(ethylene glycol) fragments. The presented studies focused on the application of two experimental methods. The polymer adsorption was carried out using the batch method and the adsorbate concentration was determined spectrophotometrically. Then, the turbidimetric measurements were taken. The analysis of the obtained results showed that the adsorption process of block copolymers depends on two factors. Firstly, the solution pH determines both the nature of the interactions of the copolymer structural units with the solid surface and the conformation of the polypeptide chains. The second parameter influencing the adsorption layer structure is the ratio of the lengths of both blocks. Introducing a short PEG fragment into the polymer main chain may improve the polymer adsorption properties by increasing the number of interactions with the adsorbent surface.

Biosorptive removal of cationic dyes from ternary system using a magnetic nanocomposite hydrogel based on modified tragacanth gum

Performance of a magnetic tragacanth gum-crosslinked-poly(acrylic acid) (TG-cl-PAA/Fe3O4) nanocomposite hydrogel in removal of malachite green (MG), thioflavin T (ThT), and rhodamine B (RhB) cationic dyes from single, binary, and ternary systemes were investigated through the batch method. The adsorption parameters, including adsorbent amount, initial concentrations of dyes, pH, and contact time were optimized for all systems. Langmuir and Freundlich models were used for equilibrium adsorption isotherm investigation, and it was found that the Langmuir model is more fitted than those of the Freundlich model, which proved the linearity of the adsorption process. Maximum adsorption capacities (Qm) of TG-cl-PAA/Fe3O4 were calculated for all systems. The Qm for MG, RhB, and ThT dyes in ternary system were obtained as 642.9, 552.6, and 413.6 mgg−1, resepectively. The removal of all dyes in single, binary as well as ternary systems were well-fitted with the pseudo-second-order model that confirm the rate-limiting step might be the chemical adsorption. The developed adsorbent was regenerated through desorption process and reused for several times. It was found that the removal efficiency of adsorbent approximately remains the same for the first three cycles, and after which decreased gradually.

Process of Bacterial Cellulose Production from Tofu Wastewater Without Pretreatment Using Acetobacter xylinum

Bacterial cellulose (BC) is an alternative cellulose source that warrants more investigation due to its limited efficiency and high production costs. This research aims to investigate the generation of bacterial cellulose from tofu wastewater using Acetobacter xylinum without pretreatment. The experiment was run on two media: tofu wastewater with and without additional sugar. The fermentation was run in a dark cabinet using a static batch method in numerous fermenter trays, each with a working volume of 1000 mL. Each experiment used 900 mL of tofu wastewater medium plus an extra 100 mL inoculum (equal to 10% v/v), which was then cultured at room temperature and harvested on days 6, 12, 18, 24, and 30. The weight of nata de soya, BC, and residual sugar were all measured from the samples. The results of the experiments revealed that the best incubation time was 18 days. The fermentation employing tofu wastewater medium with added sugar yielded nata de soya of 227.3 g/L and BC of 32.2 g/L, while the medium without added sugar yielded 103.9 g/L and BC of 9.3 g/L. The medium with added sugar yielded higher BC productivity, 1.79 g/L.day, compared to 0.57 g/L.day in the medium without added sugar. On the other hand, the BC results per sugar consumption were 0.62 g BC/g sugar and 0.36 g BC/g sugar, respectively, for the medium with and without added sugar.

Sustainable removal of hexavalent chromium using graphene oxide - Iron oxide reinforced pectin/polyvinyl alcohol magnetic gel beads

The study investigated removal of hexavalent chromium Cr (VI) from aqueous solution using graphene oxide‑iron oxide reinforced pectin/polyvinyl alcohol magnetic gel beads prepared through co-precipitation and freeze-drying technique. Scanning electron microscopy, X-ray photoelectron spectroscopy, Fourier-transform infrared spectroscopy, X-ray diffraction, vibrating sample magnetometer, N2 adsorption-desorption isotherm, and zeta potential are used for characterization. The surface area of magnetic gel beads calculated by BET method was determined to be 100.95 m2/g, significantly higher than that of GO and GO-Fe3O4. The optimum removal efficiency of GO-Fe3O4/Pec/PVA was assessed by batch method at variables such as pH(1–6), adsorption time(0–180 min), and temperature(25–35 °C). Accordingly, 0.2 g GO-Fe3O4/Pec/PVA dose, pH 2, contact time: 120 min at 25 °C were found to be the optimal conditions, and maximum adsorption capacity of GO, GO-Fe3O4 and GO-Fe3O4/Pec/PVA toward Cr(VI) removal was found to be 39.5, 62.5 and 78.55 mg g−1, respectively. Kinetic and isotherm studies indicate adsorption data follow pseudo-second-order kinetic and Langmuir isotherm models. Thermodynamic studies showed adsorption capacities of adsorbents decreased when temperature increased which indicated adsorption for Cr (VI) was an exothermic process. The activation energies were found to be 34.92, 26.57, and 35.23 KJ mol−1 for GO, GO-Fe3O4, and GO-Fe3O4/Pec/PVA, respectively, which illustrated adsorption of Cr(VI) onto the surface of adsorbents was a physical process. The beads exhibit excellent recoverability and reusability over five cycles. Overall, GO-Fe3O4/Pec/PVA demonstrates exceptional adsorption properties and can serve as an efficient, stable, less toxic, and magnetically separable adsorbent for removal of Cr(VI) from aqueous solution.

Green chemistry approach for stereoselective aldol condensation catalyzed by amino acids under microflow conditions

Over the recent years, the pharmaceutical field has been under significant pressure to adapt to the principles of green chemistry. The industry is facing the challenge of environmental protection and securing people's health while sustaining its fundamental goals of efficiency and selectivity optimization. In this work, the reaction processes optimization has been acheived through the microfluidic approach to the widely used aldol condensation reaction. In accordance with the green chemistry principles, we have found that the best conditions include aqueous ethanol solvent and easily available amino acids used as catalysts. Asymmetric aldol condensation of para-nitrobenzaldehyde with cyclohexanone catalyzed by L-tert-Leu under microfluidic conditions provided the product with high yield and diastereoselectivity (anti/syn = 28:1) and 98% enantiomeric excess. The microfluidic reactor process, compared to the classical batch method (in a flask), provides comparable product yield, while the reaction time was reduced by an order of magnitude. It should be noted that this approach allows to carry out the reactions at low (below zero) temperatures with greater enantioselectivity.

Separation of Boron and Arsenic from Geothermal Water with Novel Gel-Type Chelating Ion Exchange Resins: Batch and Column Sorption-Elution Studies

In this research, the removal of boron and arsenic from geothermal water was examined by using novel N-methyl-d-glucamine functionalized gel-like resins (abbreviated as 1JW and 2JW) synthesized by the membrane emulsification method. The outcomes were compared with those of commercially available boron selective chelating ion exchange resin (Diaion CRB 05). According to the results obtained with the novel resins, it was possible to reduce both boron and arsenic concentrations in geothermal water by using these novel gel-like chelating resins below their permissible levels for agricultural irrigation (<1 mg B/L) and drinking water (<0.01 mg As/L) by using the batch method. The optimum resin concentration required for almost complete boron removal (more than 95%) with the two chelating resins was determined to be 2 g/L. The novel gel-like chelating resins 1JW and 2JW achieved 94% of arsenic removal by using the resin concentration of 8 g/L, while the required resin concentration was 32 g/L for 94% of arsenic removal using commercially available Diaion CRB05 resin. In addition, the column performance characteristics of the novel chelating resins for the separation of boron were studied, and the results were compared to those obtained with Diaion CRB05. According to the column data obtained, the total resin capacities of the Diaion CRB05, 1JW, and 2JW resins were calculated as 6.29, 5.08, and 4.64 mg B/mL-resin, respectively.

Pengaruh Kecepatan Pengadukan dan Waktu Kontak Ampas Kulit Durian (Durio Zibethinus L.) terhadap Penyerapan Ion Logam Tembaga (II) dengan Metode Batch

One of the effective methods in handling the impact of pollution by copper ion is the biosorption method using durian peel powder (Durio Zibethinus L.). The purpose of this research is to determine the optimum absorption conditions and the optimum capacity for absorption of copper metal ions (Cu2+) using the batch method with variations in pH, concentration, stirring speed, contact time, and mass of biosorbent. The results of the research showed that the optimum conditions for the absorption of Cu2+ metal ions were at pH 6, concentration of 220 ppm, stirring speed of 250 rpm, contact time of 90 minutes and mass of biosorbent 0,4 gram was 7,788 mg/g. The adsorption isotherm of Cu2+ metal with durian skin biosorbent (Durio Zibethinus L.) tends to follow the Langmuir isotherm equation with a determinant coefficient (R) of 0,1854. Durian peel powder was characterized by the FTIR instrument, before being activated, after being activated, and after contacting the analyte there were functional groups, namely hydroxyl (O-H), alkene (C=C), carbonyl (C-O), and ether (-COC) groups.

Tyramine Adsorption Using the Modification of Takari Natural Sand-Based Silica with Bovine Serum Albumin (BSA)

In this article, we use a batch method to convey tyramine adsorption by modifying Takari natural sand-based silica with BSA and tyramine adsorption. The research stages include the optimization of adsorbent mass, pH, temperature, determination of the isotherm model, and thermodynamic parameters of tyramine adsorption. The tyramine concentration was determined using UV-Vis. The characterizations carried out were functional groups using FT-IR and surface morphology using SEM. The results of FT-IR characterization demonstrated the success of BSA modification, as observed in the C-H, N-H, and C-N groups, which are the typical functional groups of BSA. The SEM image of SiO2@BSA before tyramine adsorption revealed unevenly sized particles, uneven distribution, and agglomeration, leading to larger particles. The morphology of SiO2@BSA-tyramine appeared to be more uniform, exhibiting a smoother shape with a slightly uneven surface. The optimum pH was 5 (qe=11.74 mg/g), and the optimum temperature was 303 K (qe= 2.47 mg/g). The isotherm study showed that the adsorption adhered to the Redlich-Peterson isotherm model with an R2 value of 0.987 (qe=5.157 mg/g and n =3.759). The thermodynamic study demonstrated ∆Ho = 49.08 kJ/mol, ∆Go =-17.84; -20.05 and -22.26 kJ/mol, and ∆So =0.22 kJ/mol.K. These results indicated that the tyramine adsorption process on SiO2@BSA adsorbent occurred endothermically and spontaneously at the temperature of 303 K, and the adsorption was of a physical-chemical adsorption type.

Effect of oxidated golden shower on the adsorption of diclofenac sodium in wastewater

AbstractThis research aimed to modify activated carbon into oxidated activated carbon because it can effectively remove diclofenac sodium (DCF) and increase the adsorption capability. In this study of the several variations of initial concentration and contact time, those variations affected the optimal result. To determine, the removal efficiency of diclofenac sodium used Golden Shower Activated Carbon based on the contact time variation and the optimum contact time compared to Golden Shower Oxidated Activated Carbon as adsorbent on the batch method and to know the isotherm model and the kinetic model of the adsorbent on the adsorption in diclofenac sodium solution. The pHPZC for GSHAC and GSHOAC were 2.4 and 9.3. The optimum contact time for GSHAC was 225 min with the capacity (qt = 184.71 mg/g). The optimum contact time for GSHOAC was 169 min with the capacity (qt = 188.34 mg/g). The Isotherm model, kinetics model, and the physical characterization of the biosorbent were thoroughly investigated. The isotherm model chosen in the adsorption process for GSHAC and GSHOAC was the Langmuir model (R2 = 0.985 and R2 = 0.973). The pseudo‐second‐order for GSHAC and GSHOAC was confirmed to be a kinetic pseudo‐second‐order model of the adsorption with R2 values of 0.9566 and 0.9986. The model represents that the reaction from the adsorbent to the solution was double the initial concentration. Based on SEM analysis after the adsorption process, it was found that flakes of adsorbent before adsorption had many layers of pores, causing an irregular texture after adsorption showed that GSHAC and GSHOAC were fragmented and had many layers of pores that were closed and tight because it adsorbed DCF.

A composite based on hydroxyapatite biocrystal and poly(aniline-o-phenylenediamine) copolymer for efficient removal of anionic dyes from wastewater

BackgroundAcid dyes in any water source strongly impact its color, blocking sunlight and harming aquatic life. Herein, the technical applicability of a novel composite based on hydroxyapatite and poly(aniline-o-phenylenediamine) for removing dyes from synthetic wastewater was investigated using a batch method. MethodsIn this work, camel bones were used as a source of hydroxyapatite. Camel bones were pretreated in an alkali environment before extracting hydroxyapatite biocrystal (HAP). Subsequently, the extracted HAP was mixed with the poly(aniline-o-phenylenediamine) (PANI@PoPD) co-polymer. Different formulation methods were designed to optimize the tested composite samples' shape, size, structure and composition. Then, the optimized composite was further used as an adsorbent to remove orange G (OG) and thymol blue (TB) dyes from synthetic wastewater. The effects of the composite's dose, pH, dyes’ initial concentration and temperature on the overall performance of the composite were assessed. Statistical tests were then used to test the best experimental conditions to remove target dyes from wastewater. Significant findingsBy keeping the dye concentration constant at 50 mg/L for both OG and TB in wastewater at 25 °C, pH = 2 and 800 rpm of agitation speed in a batch reactor, it was found that the synthesized composite efficiently removes 99% of each dye at optimum dose of 0.5 or 1 g/L with a reaction time close to 30 or to 80 min for OG or TB, respectively. The predictive capacity of two-parameter models, including the Langmuir, Freundlich, Temkin and Dubinin-Radushkevich models, and three-parameter models such as the Redlich-Peterson, Sips and Toth models, was assessed to estimate the collected adsorption data. It was found that the statistical analysis was slightly better when the Temkin model was applied. This indicates that this equation was better suited to represent the experimental data of the adsorption of the OG dye. In contrast, the Redlich-Peterson and Toth models were in better agreement with the experimental results of the TB dye adsorption. Furthermore, thermodynamic parameters associated with each dye adsorption demonstrated its feasibility, while the adsorption kinetic data were found to be better described with the pseudo-second-order kinetics. In addition, the regenerability performances of the tested composite were successfully assessed by reusing the spent composite five consecutive times.

NeutronStream: A Dynamic GNN Training Framework with Sliding Window for Graph Streams

Existing Graph Neural Network (GNN) training frameworks have been designed to help developers easily create performant GNN implementations. However, most existing GNN frameworks assume that the input graphs are static, but ignore that most real-world graphs are constantly evolving. Though many dynamic GNN models have emerged to learn from evolving graphs, the training process of these dynamic GNNs is dramatically different from traditional GNNs in that it captures both the spatial and temporal dependencies of graph updates. This poses new challenges for designing dynamic GNN training frameworks. First, the traditional batched training method fails to capture real-time structural evolution information. Second, the time-dependent nature makes parallel training hard to design. Third, it lacks system supports for users to efficiently implement dynamic GNNs. In this paper, we present NeutronStream, a framework for training dynamic GNN models. NeutronStream abstracts the input dynamic graph into a chronologically updated stream of events and processes the stream with an optimized sliding window to incrementally capture the spatial-temporal dependencies of events. Furthermore, NeutronStream provides a parallel execution engine to tackle the sequential event processing challenge to achieve high performance. NeutronStream also integrates a built-in graph storage structure that supports dynamic updates and provides a set of easy-to-use APIs that allow users to express their dynamic GNNs. Our experimental results demonstrate that, compared to state-of-the-art dynamic GNN implementations, NeutronStream achieves speedups ranging from 1.48X to 5.87X and an average accuracy improvement of 3.97%.

Modeling of bioprocess pre-stages for optimization of perfusion profiles and increased process understanding.

Improving bioprocess efficiency is important to reduce the current costs of biologics on the market, bring them faster to the market, and to improve the environmental footprint. The process intensification efforts were historically focused on the main stage, while intensification of pre-stages has started to gain attention only in the past decade. Performing bioprocess pre-stages in the perfusion mode is one of the most efficient options to achieve higher viable cell densities over traditional batch methods. While the perfusion-mode operation allows to reach higher viable cell densities, it also consumes large amount of medium, making it cost-intensive. The change of perfusion rate during a process (perfusion profile) determines how much medium is consumed, thereby running a process in optimal conditions is key to reduce medium consumption. However, the selection of the perfusion profile is often made empirically, without full understanding of bioprocess dynamics. This fact is hindering potential process improvements and means for cost reduction. In this study, we propose a process modeling approach to identify the optimal perfusion profile during bioprocess pre-stages. The developed process model was used internally during process development. We could reduce perfused medium volume by 25%-45% (project-dependent), while keeping the difference in the final cell within 5%-10% compared to the original settings. Additionally, the model helps to reduce the experimental workload by 30%-70% and to predict an optimal perfusion profile when process conditions need to be changed (e.g., higher seeding density, change of operating mode from batch to perfusion, etc.). This study demonstrates the potential of process modeling as a powerful tool for optimizing bioprocess pre-stages and thereby guiding process development, improving overall bioprocess efficiency, and reducing operational costs, while strongly reducing the need for wet-lab experiments.

Coconut Shell Charcoal Combination with Teakwood Sawdust (CSC-TS): An Effective Low-Cost Adsorbent for the Removal Cr(VI) Ion on Industrial Waste

The main goals of this study were to develop activated carbon (AC) from coconut shell charcoal (CSC) combination with teakwood sawdust (TS), combination of both on this study was known with (CSC-TS) as a pledging alternative treatment for perilous Cr(VI) metal from industrial waste which investigated with Batch method. Both AC treated differently, coconut shell charcoal prepared with three stages include dehydration with microwave assisted at 373 K for 24 hours, carbonization under 773 K for 1 hour and followed by chemical activation using H3PO4 10% for 24 hours. Meanwhile, teakwood sawdust prepared only with two stages include dehydration and chemical activation without carbonization. Batch adsorption process in this study did with the aqueous solutions and applied on batik industrial waste, the functional groups of CSC-TS was characterized using FTIR, furthermore the determination of some parameters in adsorption such as adsorbent ratio, effect of contact time, and the effectiveness optimum condition on batik industrial waste obtained by AAS. Based on FTIR result, several functional groups such as (OH) were detected. Langmuir and Freundlich models were calculated to find out the fit adsorption isotherms where Langmuir models had the greater coefficient correlation value (R2=0,9976) which represented the best isotherm models. The result showed that the Cr(VI) adsorption process was found to be maximum at GT-2,5 with 100 minutes of contact time. The percentage removal of Cr(VI) in aqueous solutions under optimal conditions respectively were 87 and 99% with the maximum Langmuir capacity adsorption was 1,08 mg g-1. The initial concentration of batik industrial waste on upstream and downstream were 0,593 and 0,779 mg L-1 with the percentage removal of Cr(VI) were respectively 72 and 83%. This batch adsorption study confirmed that the contaminant of Cr(VI) on industrial waste can be decreased by low-cost adsorbent CSC-TS.

Acoustofluidics-Assisted Coating of Microparticles.

Microparticles have been applied in many areas, ranging from drug delivery, diagnostics, cosmetics, personal care, and the food industry to chemical and catalytic reactions, sensing, and environmental remediation. Coating further provides additional functionality to the microparticles, such as controlled release, surface modification, bio-fouling resistance, stability, protection, etc. In this study, the conformal coating of microparticles with a positively charged polyelectrolyte (polyallylamine hydrochloride, PAH) by utilizing an acoustofluidic microchip was proposed and demonstrated. The multiple laminar streams, including the PAH solution, were formed inside the microchannel, and, under the traveling surface acoustic wave, the microparticles traversed through the streams, where they were coated with PAH. The results showed that the coating of microparticles can be achieved in a rapid fashion via a microfluidic approach compared to that obtained by the batch method. Moreover, the zeta potentials of the microparticles coated via the microfluidic approach were more uniform. For the unfunctionalized microparticles, the charge reversal occurred after coating, and the zeta potential increased as the width of the microchannel or the concentration of the PAH solution increased. As for the carboxylate-conjugated microparticles, the charge reversal again occurred after coating; however, the magnitudes of the zeta potentials were similar when using the microchannels with different widths or different concentrations of PAH solution.

Automated silylation of flavonoids using 3D printed microfluidics prior to chromatographic analysis: system development.

Flavonoids are a class of secondary plant metabolites with low molecular weights. Most flavonoids are highly polar and unsuitable for gas chromatographic analyses. Derivatization is commonly used to make them amenable to gas chromatography by altering their physicochemical properties. Although highly effective, derivatization techniques introduce extra preparation steps and often use hazardous chemicals. The aim of this study was to automate derivatization (specifically, silylation) by developing 3D printed microfluidic devices in which derivatization of flavonoids can occur. A microfluidic device was designed and 3D printed using clear polypropylene. Quercetin and other flavonoids (TED 13 and ZTF 1016) isolated from plant extracts were silylated with N-tert-butyldimethylsilyl-N-methyltrifluoroacetamide (MTBSTFA) at room temperature both in batch and in continuous flow. All the samples were analyzed using Fourier transform infrared (FTIR) spectroscopy, gas chromatography combined with mass spectrometry (GC-MS), and high-resolution accurate mass spectrometry (HR-MS). Interestingly, the HR-MS results showed that the flow method was about 25 times more efficient than the batch method for quercetin samples. The TED 13 flavonoid was completely derivatized in the flow method compared to the batch method where the reaction was incomplete. Similar results were observed for ZTF 1016, where the flow method resulted in a four times derivatized compound, while the compound was only derivatized once in batch. In conclusion, 3D printed microfluidic devices have been developed and used to demonstrate a semi-automated, inexpensive, and more efficient natural product derivatization method based on continuous flow chemistry as an alternative to the traditional batch method.

Taste Masking Cetirizine Hydrochloride using Ion-exchange Resins

Aim: The scope of the study is to determine the exact drug content present in the dry resinate and the utilization of ion-exchange resin in taste masking highly bitter cetirizine hydrochloride (CTZ). The Amberlite® IRP-69 cross-linked polystyrene was used. Objective: The objectives of this study are drug loading, drug–resin ratios, effect of particle size determination, and qualitative evaluation of taste masking ion-exchange resins. Background: The resinate (drug–resin complex) preparation process was completed by batch method in the ratio of 1:1, 1:2, and 1:3. The loaded drug amount in the resin was evaluated spectrophotometrically by measuring the remaining drug to be loaded in the solution at 278nm. Different sieve sizes of Amberlite® IRP-69 resins were employed to determine the effect of the particle size in drug loading and drug releasing profiles in simulated gastric fluid without enzymes. The X-ray diffractograms of cetirizine hydrochloride, Amberlite® IRP-69, and a mixture of cetirizine hydrochloride with resins (resinate) were obtained by using an X-ray diffractometer. Results: Resinates were developed by using single-batch and double-batch methods. Both of them are giving almost the same results of drug loading into ion-exchange resins. We selected 1:1 drug–resin ratio to see the effect of the particle size on the rate and extent of drug loading and drug releasing from the complex. In the 1:1 drug-to-resin ratio, almost 78% of the drug was involved in the complex after 24 hours; in the case of 2:1 and 3:1 ratios, only 49% and 25% of the drug were involved in the complex, respectively. Conclusion: Among many taste masking methods, the formation of resinates with an ion-exchange resin is simple and inexpensive. The present work reveals that the degree of bitterness of cetirizine hydrochloride is reduced to zero by strong cation-exchange resin. The present study deals on the scope of utilizing ion-exchange resins in taste masking cetirizine hydrochloride (CTZ), a highly bitter drug.

High-order moment closure models with random batch method for efficient computation of multiscale turbulent systems.

We propose a high-order stochastic-statistical moment closure model for efficient ensemble prediction of leading-order statistical moments and probability density functions in multiscale complex turbulent systems. The statistical moment equations are closed by a precise calibration of the high-order feedbacks using ensemble solutions of the consistent stochastic equations, suitable for modeling complex phenomena including non-Gaussian statistics and extreme events. To address challenges associated with closely coupled spatiotemporal scales in turbulent states and expensive large ensemble simulation for high-dimensional systems, we introduce efficient computational strategies using the random batch method (RBM). This approach significantly reduces the required ensemble size while accurately capturing essential high-order structures. Only a small batch of small-scale fluctuation modes is used for each time update of the samples, and exact convergence to the full model statistics is ensured through frequent resampling of the batches during time evolution. Furthermore, we develop a reduced-order model to handle systems with really high dimensions by linking the large number of small-scale fluctuation modes to ensemble samples of dominant leading modes. The effectiveness of the proposed models is validated by numerical experiments on the one-layer and two-layer Lorenz '96 systems, which exhibit representative chaotic features and various statistical regimes. The full and reduced-order RBM models demonstrate uniformly high skill in capturing the time evolution of crucial leading-order statistics, non-Gaussian probability distributions, while achieving significantly lower computational cost compared to direct Monte-Carlo approaches. The models provide effective tools for a wide range of real-world applications in prediction, uncertainty quantification, and data assimilation.