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:

A design of experiments to optimize a new manufacturing process for high activity protein-containing submicron particles. A novel method for the manufacture of protein/peptide-containing submicron particles was developed in an attempt to provide particles with increased activity while using high energy input technologies. The method consists of antisolvent co-precipitation from an aqueous solution containing both an amino acid core material (e.g. D,L-valine), and either bovine serum albumin (BSA) or lysozyme (Lys) as model proteins. The aqueous solution was added to the organic phase by means of a nebulizer to increase the total surface area of interaction for the precipitation process. Sonication proved to be an effective method to produce small particle sizes while maintaining high activity of Lys. The use of a polysorbate or sorbitan ester derivatives as stabilizers proved to be necessary to yield submicron particles. Particles with very high yields (approximately 100%) and very high activity after manufacture (approximately 100%) could be obtained. A particle size of 439.0 nm, with a yield of 48.8% and with final remaining activity of98.7% was obtained. By studying various factors using a design of experiments strategy (DoE) we were able to establish the critical controlling factors for this new method of manufacture.
{"Chemical": ["sorbitan ester", "amino acid", "D,L-valine", "polysorbate"]}