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:

Electrical method to quantify nanoparticle interaction with lipid bilayers. Understanding as well as rapidly screening the interaction of nanoparticles with cell membranes is of central importance for biological applications such as drug and gene delivery. Recently, we have shown that "striped" mixed-monolayer-coated gold nanoparticles spontaneously penetrate a variety of cell membranes through a passive pathway. Here, we report an electrical approach to screen and readily quantify the interaction between nanoparticles and bilayer lipid membranes. Membrane adsorption is monitored through the capacitive increase of suspended planar lipid membranes upon fusion with nanoparticles. We adopt a Langmuir isotherm model to characterize the adsorption of nanoparticles by bilayer lipid membranes and extract the partition coefficient, K, and the standard free energy gain by this spontaneous process, for a variety of sizes of cell-membrane-penetrating nanoparticles. We believe that the method presented here will be a useful qualitative and quantitative tool to determine nanoparticle interaction with lipid bilayers and consequently with cell membranes.
{"Chemical": []}