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:

The influence of rolling friction on the shear behaviour of non-cohesive pharmaceutical granules - An experimental and numerical investigation. Granule shear behaviour was investigated experimentally and numerically to evaluate the reliability of the numerical model. Additionally, parameters affecting the ensuing flow regimes - elastic quasi-static and inertial non-collisional - were highlighted. Furthermore, the influence of using the Lees-Edwards periodic boundary conditions or the standard boundary conditions was studied. Experiments were performed with microcrystalline cellulose granules of three size distributions using the FT4 powder rheometer. The numerical parameters, particle size, effective density, and particle stiffness were selected to match the experimental conditions. Experimentally, an unexpected particle size effect was evident where the resistance to shear increased with particle size. Numerically, combining rolling friction and increased shear rate enabled a transition from the inertial non-collisional to the elastic quasi-static regime at a reduced sliding friction coefficient. Presumably, this is an effect of increased particle overlap creating stronger contacts and facilitating force chain formation. Both boundary conditions provided comparable results provided a correction of system size was made, where larger systems were required for the standard boundary conditions. A satisfactory qualitative agreement between the experimentally and numerically determined yield loci emphasised the predictive capacity of the DEM. Rolling friction was in addition concluded to be an essential model parameter for obtaining an improved quantitative agreement.
{"Chemical": []}