First, I feel obligated to mention that stepwise regression is often criticized as a technique. This wikipedia article discusses it.
Second: Yes, I think you are calling the function correctly, to get the terms you want to try.
Third: You might want to get a better understanding of the 'Criterion' you are using. If your goal is for this model to generalize beyond your dataset, I think something like AIC might be a better choice. (I am also a little confused why the function did not just return the full model with all possible terms, since that model gives the max R^2. But that is probably just me not researching the documentation fully.)
Last: Empirically, a model with R^2=0.67 and one with R^2=0.71 are so close to the same (in terms of explained variation) that I would consider them to be basically identical. I would not choose a model based on that difference.
Since this is a physical system, I feel like there should be some rationale about why each term might come in a particular power, and that could help drive the decision.
If you are truly going for only predictive power, you might want to use a machine learning model instead ... although with only 181 data points, I'm not entirely sure that that is the best way to go.
