You will be shown an abstract from a biomedical research paper. Given this abstract, your task is to extract all unique entities of the following types: ["Chemical"].

Please return the output as a JSON object of the format: {"Chemical": ["Arsenic", ...]}. The keys should be entity types and values should be lists of extracted entities belonging to the corresponding type. If you cannot find entities belonging to a specific type, the value should be [].

Only output the JSON object and do not include any additional text.

Abstract:

Quantum-dot-sensitized solar cells: understanding linker molecules through theory and experiment. We have investigated the role of linker molecules in quantum-dot-sensitized solar cells (QDSSCs) using density-functional theory (DFT) and experiments. Linkers not only govern the number of attached QDs but also influence charge separation, recombination, and transport. Understanding their behavior is therefore not straightforward. DFT calculations show that mercaptopropionic acid (MPA) and cysteine (Cys) exhibit characteristic binding configurations on TiO(2) surfaces. This information is used to optimize the cell assembly process, yielding Cys-based cells that significantly outperform MPA cells, and reach power conversion efficiencies (PCE) as high as 2.7% under AM 1.5 illumination. Importantly, the structural information from theory also helps understand the cause for this improved performance.
{"Chemical": ["cysteine", "TiO(2)", "mercaptopropionic acid", "Cys", "MPA"]}