Advanced Scientific Visual Communication (ChE 3460) Fall 2022
This fast-paced course will train students to produce professional scientific visual work, suitable for publications, presentations, and communicating to the public. Advanced topics, such as 3D modeling & animation, handling and visualizing large datasets, interactive displays, and 3D printing will be covered. The course will emphasize the importance of producing high quality artwork in scientific communication. Please bring a laptop and mouse to class (and a keyboard is helpful too).
Specific skills taught:
- 3D modeling, animation, and rendering using Blender
- Regular, photorealistic, and nonphotorealistic (NPR) rendering
- 2D layout and compositing using Inkscape
- Python programming for data handling
- Syllabus (click here)
- Mondays/Wednesdays, 3:00-4:15PM
- 309 Benedum Hall
- Prof. Wilmer’s office hours: Wednesdays 11am-noon, Fridays 2pm-3pm
Software tools you will need (besides Powerpoint, these are all free and open source):
Supplemental reference material:
Scientific Grant Proposals
In this course, you pretend that you are helping to create and present a high stakes (i.e., multimillion $$) scientific grant proposal. You can choose from one of the following for grant proposals to work on during the course:
Application of metal-organic frameworks (MOFs) to capture CO2 from the exhaust of coal power plants
While the best long term solutions to global warming are solar, wind, and possibly nuclear energy, in the short term, carbon capture technology added to coal power plants can significantly help reduce emissions. This research proposal describes the use of highly selective adsorbents called metal-organic frameworks (MOFs) to capture CO2 from the exhaust stream of coal power plants. Preliminary large-scale computational screening data, supported by early experimental adsorption data, support our hypothesis that a Zr-based MOF with a void fraction 80% is optimal for CO2 separation applications.
Department of Energy - Requested amount: $5 million USD
Useful references: (Wilmer et al., 2012)
Investigation of gold/palladium nanoparticle catalysts for water treatment applications
Tricholroethylene (TCE) is a widely used industrial solvent that has been found in alarmingly high concentrations in ground water in major cities. Existing treatment technologies, such as activated carbon filters, are limited in their effectiveness for filtering out TCE. Recent research by Nutt et al. suggest that Pd/Au bimetallic nanoparticles may be effective catalysts for safely converting TCE to ethane, which can be easily separated from water. Here we propose to optimize the nanoparticle shape/size/composition and test their effectiveness on a pilot-scale filtration unit using an activated carbon support.
Environmental Protection Agency - Requested amount: $4.5 million USD
Useful references: (Nutt et al., 2006)
Artificial nose for disease detection via large array of surface-acoustic wave sensors
An increasing number of anecdotal reports exist of animals (and even an elderly woman) being able to detect diseases, such as Parkinson’s disease, by smell. However, these reports are difficult to reproduce as it is unknown how the animals, typically dogs, can be trained to detect disease, and there are nonetheless unreliable diagnoses due to communication difficulties. An artificial nose, implemented via an array of thousands of microscale gas sensors, could potentially achieve the sensitivity and selectivity of a dog’s nose while improving on reliability and analyzability. We propose to computationally design an optimal array of surface-acoustic wave (SAW) sensors and then build a small-scale prototype.
National Science Foundation - Requested amount: $3.5 million USD
Useful references: (Surface acoustic wave sensor [Wikipedia])