Non-Technical Summary. Semiconductors are critical components in a wide range of technologies including smart phones, solar cells, and radiation detectors, among many others. Mixed-chalcogen solids are an important class of semiconductors that have at least two negatively charged atoms, or anions, which can arrange themselves in ordered or disordered ways within a crystal. The arrangement of anions strongly impacts the electrical and thermal properties of semiconductors, but scientists do not have reliable tools to predict when or how ordering occurs. To overcome this challenge, researchers at Pennsylvania State University and Portland State University, with support from the Solid State and Materials Chemistry program in NSF’s Division of Materials Research, combine computer modeling, machine learning, and laboratory experiments to develop a framework that can predict atomic ordering. The project outcomes advance scientific knowledge and can be used to design materials with improved properties and atomic-scale precision that is needed for next-generation applications. Additionally, this collaborative project includes hands-on training for graduate students, generates new content for college courses and promotes participation in science through mentoring and community interactions, thereby helping to develop a highly skilled workforce in the chemical and materials sciences. Technical Summary. Metal chalcogenides are a highly tunable class of materials due to the h