Adsorption of Additives in Cola Beverages: A Safe and Improved Experiment Exploring Beer’s Law and Adsorption Process

A chemistry laboratory experiment is described to introduce undergraduate college students to membrane separation technology. This experiment combines a simple nanowire membrane fabrication and visually indicated molecule separation. The membrane is produced via coprecipitation synthesis followed by a filtration assembly process, which can be carried out with ease within 1 h. Molecule separation using membrane filtration is then illustrated by filtering solutions containing methylene blue (MB), rhodamine B (RhB), and an MB/RhB mixture, respectively. A comparison of the filtration results displays that the membrane preferentially rejects MB molecules, whereas the RhB molecules easily pass through it, leading to an impressive separation efficiency of dissolved MB molecules from the dye mixture solution. The clearly visible color changes occurring before and after filtration trigger students' interest in advanced membrane separation technology and deepen their understanding of the potentials offered by membranes for molecule separation and purification applications. The laboratory experiment can be performed during a 3 h activity with the purpose of (1) exposing students to a new and interesting field of advanced membrane separation technology. It not only (2) familiarizes them with the synthesis and self-assembly of nanowires into membranes, but it also (3) helps them to understand the membrane's important role in molecular separation application.

Section: Introductionmentioning

confidence: 99%

A Simple and Colorful Experiment to Show Nanowire Membrane Construction for Molecule Separation

Zhu

2024

“…35,36 Data processing may develop Microsoft Excel skills, but is typically limited to fitting linearized Langmuir or Freundlich adsorption isotherm models to experimental data, using a linear regression (line of best fit). [28][29][30]36 (We note that effective tutorials in nonlinear model fitting using Microsoft Excel are available for other topics.) 37 Despite the small variety of literature discussed above, we find no discussion of surface complexation modeling (SCM) in the teaching lab.…”

Section: ■ Introductionmentioning

confidence: 99%

“…In some experiments, the adsorbent is first synthesized, ,, offering opportunities for students to consider the physical and chemical properties that make an effective adsorbent. Students develop analytical chemistry skills, using background subtraction and external calibration curves. , Data processing may develop Microsoft Excel skills, but is typically limited to fitting linearized Langmuir or Freundlich adsorption isotherm models to experimental data, using a linear regression (line of best fit). − , (We note that effective tutorials in nonlinear model fitting using Microsoft Excel are available for other topics. )…”

Section: Introductionmentioning

confidence: 99%

Teaching Adsorption Chemistry by Constructing Surface Complexation Models (SCM) in PHREEQC

Bullen,

Landa-Cansigno,

Weiss

2024

Adsorption modeling is important to understand and predict both how water contamination occurs, and how it might be prevented or remediated. Surface complexation models (SCM) help us understand adsorption under changing environmental conditions. This computational class introduces undergraduate students to adsorption and surface complexation and provides a foundation in geochemical modeling using freely available PHREEQC software from USGS. Practical capabilities are developed by (1) performing aqueous speciation reactions, (2) determining the surface charge of suspended metal oxide/mineral powders using potentiometric titration data, (3) calculating pH adsorption edges and adsorption isotherms, (4) applying PHREEQC to answer possible water treatment scenarios, and (5) using Visual Basic coding with loops to generate large data sets. This class is contextualized around arsenic contaminated groundwater and its treatment using iron oxide minerals, with hundreds of millions at risk worldwide (e.g., India, Bangladesh, Mexico). Participants report increases in their understanding of adsorption chemistry and confidence in the application of geochemical models to perform predictive SCM calculations.

“…In 2020, Kovarik et al reviewed laboratory experiments carried out using digital images obtained using smartphones, desktop scanners, and webcams. Since then, several new laboratory experiments involving digital images have been published. − …”

Section: Introductionmentioning

confidence: 99%

Iron Quantification in Dietary Supplements using Four Colorimetric Assays

Filgueiras

Borges

2022

Students determine the iron mass in dietary supplements using four colorimetric assays. These colorimetric assays were selective for Fe3+. It was complexed by thiocyanide, salicylate, gallic acid, and Fe(CN)6 4–, forming blood-red, red, violet, and blue complexes, respectively. The λmax of these complexes were 447, 480, 570, and 700 nm, respectively. These assays were scaled-down, where 1 mL of chromogenic reagent was mixed with 0.1 mL of sample. Salicylic acid, gallic acid, and K4[Fe(CN)6] were harmless and cheap chromogenic reagents that could be used instead of traditional chromogenic reagents such as KSCN and phenanthroline. Quantitative analysis was carried out using absorbance measured at λmax of each assay (standard method) and 96-well-plate digital images obtained with a desktop scanner (proposed method). The matrix effect was investigated by comparing the standard addition curves with the external calibration curves, where no matrix effect was found. Results obtained using the four assays were compared using hypothesis tests such as one-way ANOVA, post-hoc tests, and plots. Investigation of interactions between samples and assays was carried out using two-way ANOVA. Statistical tests were carried out using open-source and graphical user interface programs (JASP and R Commander). The student learning goals of this experiment include comparing multiple assays using hypothesis tests. Learn about the principles of green chemistry, method scale-down, and matrix effect.