Living Physics Portal: Diffusive Transport Labs

Abstract: This module describes the experiments that are done in the diffusion unit. Here the students really see that diffusion is slow, painfully so, that diffusion covers all cells in an expanding circle that increases with the square root of time. Gaussian are a real and actual physical manifestation of this diffusive motion and students can use fiji (ImageJ) and loggerpro to fit the Gaussian function their data and calculate the uncertainty in the standard standard deviation. This hopefully raises students awareness of and appreciation for statistics and error analysis.

Resource Types: Lab, Instructor supplement

Authors:

Mark Reeves

George Washington University

Phoebe Sharp

George Washington University

Pi Nuessle

George Washington University

Rachael Stewart

George Washington University

IBET RAMIREZ-URREA

Woodrow Wilson

GW Group

Living Physics Portal Team

TOPICS

Physics Topics:

Thermo & Stat Mech > Probability > Binomial Distribution, Gaussian Distribution, Probability Density

Life Sciences Topics:

Cross-cutting Biological Concepts > Matter/energy Transfer & Transforms > Material Flow

Human and Animal Physiology > Cardiovascular System > Healthy Cardiovascular Function

Human and Animal Physiology > Respiratory System > Animal Respiratory Variations

Math Topics:

Algebra; Exponentials and Logarithms; Integral Calculus; Probability

FILES Download3

Diffusive Transport > Diffusive Transport Labs

Diffusive Transport Labs

Instructions for Fiji.docx

BrownianMotionProcedure.pdf

Lab6.Diffusion.pdf

Write-Up Takeaways.docx

Sample_data_set_1.6%.docx

Instructions for Fiji.docx

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INSTRUCTOR GUIDE

IMPLEMENTATION

Duration: 4 sessions of 2 hours per session.

Equipment required: Computers / software

Specific equipment needed: cameras, light box (can be a laptop screen), microscopes, petri dishes, pipettes, agarose gel, dye, running buffer for electrophoresis, micron-size polystyrene beads. Optional, bacteria from spoiled milk.

Basic implementation tips & tricks: This material challenges the students in a number of ways. 1) Probability has been operationally introduced in high school, but not as a model-building tool. 2) diffusion of a gas and Brownian motion of individual particles are the same thing. 3) Understanding requires flexible and facile movement between mathematical, graphical, and descriptive representations. 4) Predictions are made from statistical principles - this is counter-intuitive. 5) These ideas are important building blocks for thermal physics and biophysics.

How does this resource fit into the flow of your course? Presentation immediately follows energy conservation and fluid dynamics. The timing is unfortunate in that it comes 2/3 of the way into the first semester, immediately after semester break, when the students are cognitively overloaded and looking forward to the end of the semester. The unit on diffusion is followed by entropy and thermodynamics. The statistical ideas bridge from a single particle dynamics driven by deterministic forces to stochastic motion of large numbers of particles.

PEDAGOGY

Pedagogical approach: Peer Instruction / Think-Pair-Share; Collaborative problem-solving; Conceptually-oriented activities; Context-rich problems; Ranking tasks; SCALE-UP / studio / workshop physics; Mathematically-focused activities; Experimentally-focused activities

Skills / Competencies: Dimensional analysis; Functional dependence; Multiple representations; Estimation; Intuition building; Building models; Evaluating models; Error and uncertainty; Designing experiments; Performing experiments; Analyzing experimental data; Applying physical principles; Interdisciplinarity; Metacognitive skills

What insights or realizations do you hope students gain from this resource? That motion at the molecular motion is random, driven by forces between colliding molecules. Diffusion is slow, scales with the square root of time and is not directed. Even so this mechanism is efficient and leads to Brownian motion and diffusion. These are very different looking manifestations of the same phenomena. The sublinear time dependence means that diffusion is impractically slow at even moderate distance (larger than 10 microns, the diameter of a cell). These are important aspect buried in the mathematical representation, so they need to be emphasized.

Why is this resource useful to life sciences students? Diffusion is biologically important because it harnesses the the thermal energy that is inherent to deliver nutrients, oxygen, and biochemical messengers to cells. In situations where directed motion is needed, other transport mechanism (molecular motors) are invoked. However, in the limiting cases where directionality is not important or distances are short enough that the sublinear time dependence is not an impediment.

DISCUSSION

SUBMISSION DETAILS

License: CC: BY-NC-SA - Attribution, No Commercial uses and Share Alike. Derivative works must have the same license

Last Edit Date: June 29, 2021