We have performed electronic structure calculations of the interaction of potassium and oxygen with graphite (GR), individually and as coadsorbates. We use up to three graphite planes to represent the graphite surface, but we show that the main physics is correctly described by a single graphite layer. At low coverage the potassium–graphite bond is largely ionic, and the variation of the K–GR bond energy with the lateral position of the K atom in the graphite unit cell is very small. We study the interaction between atomic oxygen and graphite. We find that O binds strongest at the bridge site, but the barrier for diffusion is rather small. The frequency for the perpendicular O–graphite vibrational mode is remarkably low (53 meV), reflecting the relative slow variation of the O–graphite interaction energy with the separation z between the O atom and the graphite surface. We consider the adsorption of O2 on a clean graphite surface and on a graphite surface with a low concentration of potassium. On the clean surface the O2–graphite interaction is found to be repulsive (the weak attractive van der Waals interaction is not included in our theoretical method), in accordance with the extremely low sticking coefficient observed for O2 on clean graphite. When potassium is adsorbed on the graphite surface, O2 chemisorbs at the potassium sites which is consistent with the large sticking coefficient observed for O2 on a potassium covered surface. The energy barrier towards dissociation of O2 on the clean graphite surface is estimated to be similar to that of gas phase O2. For O2 on K/graphite we find that O2 chemisorbs “side-on” K, and that the barrier for dissociation is much smaller than in the gas phase or on the clean graphite surface.

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Solar-energy plays an important role in solving serious environmental problems and meeting highenergy demand. However, the lack of suitable materials hinders further progress of this technology. Here, we present the largest inorganic solar-cell material search to date using density functional theory (DFT) and machine-learning approaches. We calculated the spectroscopic limited maximum efficiency (SLME) using Tran-Blaha modified Becke-Johnson potential for 5097 non-metallic materials and identified 1997 candidates with an SLME higher than 10%, including 934 candidates with suitable convex-hull stability and effective carrier mass. Screening for 2D-layered cases, we found 58 potential materials and performed G0W0 calculations on a subset to estimate the prediction-uncertainty. As the above DFT methods are still computationally expensive, we developed a high accuracy machine learning model to pre-screen efficient materials and applied it to over a million materials. Our results provide a general framework and universal strategy for the design of high-efficiency solar cell materials. The data and tools are publicly 2 distributed at:

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