The nanoHUB is a rich, web-based resource for research, education and collaboration in nanotechnology. The nanoHUB hosts over 1300 resources which will help you learn about nanotechnology, including Online Presentations, Courses, Learning Modules, Podcasts, Animations, Teaching Materials, and more. Most importantly, the nanoHUB offers simulation tools which you can access from your web browser, so you can not only learn about but also simulate nanotechnology devices.
This RU-vid channels contains a select set of the technical presentations available on nanohub.org
13:22 The chart was hard for me to understand and I felt some context was missing. I think the x axis ("time") doesn't really matter here, what matters is the relationship between the concentration of potassium ions and the resting membrane potential which should follow Nernst's equation (assuming that the resting membrane is most permeable to K+, which - as it turns out - it is). Basically, researchers changed the external concentration of potassium ions and measured the resting membrane potential for different K+ ion concentrations. By the way, note the K+ concentration at which the resting membrane potential becomes 0. Also note that - although I don't think this is mentioned in the video - the chart is for the giant squid neuron. You can compare this observation to the earlier chart from 8:35. Great lecture otherwise!!
i am trying to plot result and call the regression function but it shows "TypeError: float() argument must be a string or a real number, not 'dict'", how to fix this error
It seems like larger the difference between u1 and u2 the more current is produced, is that correct? Are the differences in u1 and u2 caused by the type of materials used?
Sorry if this is a basic question, but at 7:30 you talk about electrons going in and electrons going out. Is that because n-type materials have extra electrons and p-type materials have electrons holes? If so, is that center rectangle essentially made up of a series of n-type & p-type materials?
Hi Benjamin, Thank you so much for the tutorial. This is really helpful. However, I encountered an issue when attempting to implement the code. I received the following error message: TypeError: agg function failed [how->mean, dtype->object] while running this code: mastml_df_clean = mastml_df_filtered.groupby("chemicalFormula Clean", as_index=False).mean() Could you please provide some advice on this matter? Thank you.
