Enhanced Assessment of Transition Metal Copper Sulfides via Classification of Density of States Spectra

Understanding how crystal structure influences electronic properties is crucial for discovering new functional materials. In this study, we utilized Kernel Principal Component Analysis (KPCA) to classify and analyze the Density of States (DOS) of transition metal sulfide (TMS) compounds, particularly copper-based sulfides. By mapping high-dimensional DOS data into a lower-dimensional space, we identify clusters corresponding to different crystal systems and detect outliers with significant deviations from their expected groups. These outliers exhibit unusual electronic configurations, suggesting potential applications in semiconductors, thermoelectric devices, and optoelectronic devices. Projected Density of States (PDOS) analysis further reveals how orbital hybridization governs the electronic structure of these materials, highlighting key differences between structurally similar compounds. Additionally, we analyze phase stability through inter-cluster distance measurements, identifying potential phase transformations between closely related structures. The implications for this work in terms of modifying chemistries and generalized DOS predictions are discussed.