The use of machine learning techniques in materials research has grown in the last decade from a small niche topic to an entire subfield within materials science & engineering. Indeed, there have been over 2000 papers on the topic of materials machine learning in the year 2023 alone, and over the past decade there has been a 1.67 times yearly growth in the number of papers (Figure ). A 2020 review by Morgan and Jacobs 1 found that not only were the number of papers on the topic exponentially increasing, but that the number of review papers per year on the topic had already reached nearly 40 by 2019. Indeed, there already exist many excellent reviews on various aspects of materials machine learning, including its applications in simulation and modeling , synthesis and characterization , manufacturing , and literature mining . Reviews also exist for specific topics such as structural materials or best practices for research reporting .