2023/11/22 by Pamela Knoll, Bin Ouyang, Oliver Steinbock · 1 voice · 3 citations
Materials Science · Chemistry · Engineering · #Machine Learning in Materials Science #Fullerene Chemistry and Applications #Advanced Memory and Neural Computing
paper · doi:10.1021/acsphyschemau.3c00050
openalex publication_date 2023/11/22 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/16
The universe is a complex fabric of repeating patterns that unfold their beauty in system-specific diversity. The periodic table, crystallography, and the genetic code are classic examples that illustrate how even a small number of rules generate a vast range of shapes and structures. Today, we are on the brink of an AI-driven revolution that will reveal an unprecedented number of novel patterns, many of which will escape human intuition and expertise. We suggest that in the second half of the 21st century, the challenge for Physical Chemistry will be to guide and interpret these advances in the broader context of physical sciences and materials-related engineering. If we succeed in this role, Physical Chemistry will be able to extend to new horizons. In this article, we will discuss examples that strike us as particularly promising, specifically the discovery of high-entropy and far-from-equilibrium materials as well as applications to origins-of-life research and the search for life on other planets.