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3 papers
Thermodynamic assessment of machine learning models for solid-state synthesis prediction
Jane Schlesinger, Simon Hjaltason, Nathan J. Szymanski +1
Machine learning models have recently emerged to predict whether hypothetical solid-state materials can be synthesized. These models aim to circumvent direct first-principles model…
Origins of chalcogenide perovskite instability
Adelina Carr, Talia Glinberg, Nathan Stull +2
Chalcogenide perovskites, particularly II-IV ABS3 compounds, are a promising class of materials for optoelectronic applications. However, these materials frequently exhibit instabi…
Antibonding and Electronic Instabilities in GdRu2X2 (X = Si, Ge, Sn): A New Pathway Toward Developing Centrosymmetric Skyrmion Materials
Dasuni N. Rathnaweera, Xudong Huai, K. Ramesh Kumar +4
Chemical bonding is key to unlocking the potential of magnetic materials for future information technology. Magnetic skyrmions are topologically protected nano-sized spin textures…