The Physics of Filter Coffee is a deep dive into the science behind coffee brewing. In the book, renowned astrophysicist Jonathan Gagné brings welcome scientific expertise to coffee making. Not only does the book contain numerous original ideas about coffee brewing, but Jonathan lays to rest many controversial ideas about coffee making.
THIS IS THE GOOD STUFF. If you are serious about making the best coffee possible and get excited by data you need to be reading this book. Probably several times. While the focus on such granular detail as particle size distribution and the hydrophobic qualities of various gooseneck kettles can be intimidating, it is always accompanied by a thorough explanation of all data and processes involved alongside a summary of the most important practical takeaways. I am already planning on reading this again with a set of Post-It Notes.
This book has some very good insights and discusses some interesting variables and techniques that I have previously never considered. However, I feel at times it rapidly changes between being beginner-friendly and difficult to understand for somebody who has experience reading academic papers and scientific literature. In addition, many of the figures and graphs explaining what is happening are hand-drawn which makes them a little harder to understand. All in all, a great book to expand working knowledge of specialty coffee.
Something that rlly freaks me about writing reviews on goodreads is that I can never tell if the medium is encouraging me to provide a serious and helpful description of a text for other potential readers, or leave a silly little message to let my friends know what I'm up to. I realize that this is exactly the same as letterboxd, which for some reason does not give me the same kind of decision paralysis, and I make no excuses. Luckily, this text solves that issue entirely - The Physics of Filter Coffee is a perfect but completely niche text, which will never in a million years be randomly discovered by someone browsing goodreads. This is essentially a short textbook attempting to objectively and where possible, quantifiably, analyze some of the key factors related to cup quality in filter coffee. Lots of lovely matplotlib figures, and some very fun diagrams explaining physical models, though perhaps slightly less calculus than I was hoping for. In short: This is book is perfect for readers of Jonathan Gagné's blog, coffee ad astra, who (aside from the unfortunate friends of those readers) are likely to be the only people ever exposed to the text. The idea of someone stumbling upon a review of this book, without prior knowledge of Gagné, and attempting to decide how to feel about it, genuinely boggles my mind. But basically it's perfect!
The cumulative effort of an individual dedicated to uncovering the minutiae of the world around us--in this case how filter coffee works. The only book of its kind on the subject and brilliantly delivered; Gagne uses their years of blogging to write hard-science (this is at some points akin to a huge paper) in a way that is effortlessly approachable and easy to navigate.
And with this I have fully gone coffee nerd. This book is an excellent resource and learning tool to understand how to brew coffee. The author fully explains things- there are tons of graphs and equations to help illustrate the copious testing they did. If you LOVE coffee and want to better understand the process this is a well done read for you!
Dense. Fulll of great discussion and information. Presented in a really digestible way. This is a book I will be referencing often. My understanding of pour overs and technique has increased exponentially. Thanks B!
This is the best book about coffee that I have ever read. The approach in this book is all about data and mathematical models, just perfect. I found the sections about the grinding of coffee, water chemistry and pouring of water the most interesting. 5.0
I am so glad this absurdly niche book exists. Read if you're unhealthily obsessed with specialty filter coffee AND you love physics, math (like a lot of math), and data analysis.