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Research on the calibration method of discrete element physical property parameters in the pressing process of binary mixed particles
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An-qi LUO1, Meng-tao ZHAO1, Chi MA1, Qin XIAO1, Zheng LU1, Tian-bing GUAN1, Shuang-kou CHEN1, Hui-min SUN2, *, Hai-jun HUANG3, Ai-ping WANG3, Chuan-yun DAI3, *
Acta Pharmaceutica Sinica | 2025, 60(4) : 1137 - 1146
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Acta Pharmaceutica Sinica | 2025, 60(4): 1137-1146
Original Articles
Research on the calibration method of discrete element physical property parameters in the pressing process of binary mixed particles
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An-qi LUO1, Meng-tao ZHAO1, Chi MA1, Qin XIAO1, Zheng LU1, Tian-bing GUAN1, Shuang-kou CHEN1, Hui-min SUN2, *, Hai-jun HUANG3, Ai-ping WANG3, Chuan-yun DAI3, *
Affiliations
  • 1College of Chemistry and Chemical Engineering, Chongqing University of Science and Technology, Chongqing 401331, China
  • 2China National Institute for Food and Drug Control, Beijing 100050, China
  • 3Chongqing Key Laboratory of Digitalization of Pharmaceutical Processes, College of Traditional Chinese Medicine, Chongqing University of Chinese Medicine, Chongqing 402760, China
Published: 2025-04-12 doi: 10.16438/j.0513-4870.2024-0977
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The study of micromechanical behavior during tablet pressing is often limited to phenomenological studies, accurate calibration of the discrete element model parameters of binary particles is a prerequisite for conducting modeling research on tablet compression. In this study, we take pregelatinized starch and microcrystalline cellulose as the research objects, and apply the Edinburgh elasto-plastic adhesion (EEPA) contact model to establish a discrete elemental simulation model for binary material pressing. Taking tablet force-hardness and force-volume reduction as response values, the optimal values of the discrete meta-parameters that significantly affect tablet pressing are obtained by applying Plackett-Burman design, Latin hypercubic sampling, Kriging model, and Non-dominated Sorting Genetic Algorithm (NSGA-Ⅱ) calibration. The results obtained the optimum combination of discrete element method (DEM) parameters for pregelatinized starch, Poisson's ratio 0.257, shear modulus 1×109 Pa, granule-particle static friction coefficient 0.165, unit normal stiffness 2.419 2×109 N·m-3, unit tangential stiffness 7.954 6×109 N·m-3, and strength of adhesive force -0.009 155 8 N. For microcrystalline cellulose, Poisson's ratio 0.381, shear modulus 1.04×109 Pa, particle-particle static friction coefficient 0.719, unit normal stiffness 3.171 5×109 N·m-3, unit tangential stiffness 6.746 2×109 N·m-3, and strength of adhesion -0.038 7 N. For optimum combinations of the DEM parameters for the binary blend of excipients, particle-particle collision recovery coefficient 0.1, unit normal stiffness 9.947 1×109 N·m-3, unit tangential stiffness 1.994 5×109 N·m-3, and adhesion force strength -0.060 35. The simulation results under the optimal parameter combination are similar to the experimental results, indicating that the calibrated parameters can be used for discrete element simulation research and provide theoretical basis and data support for the subsequent intelligent and continuous production of tablets.

bimodal mixed particle  /  discrete element method  /  parameter calibration  /  compression
An-qi LUO, Meng-tao ZHAO, Chi MA, Qin XIAO, Zheng LU, Tian-bing GUAN, Shuang-kou CHEN, Hui-min SUN, Hai-jun HUANG, Ai-ping WANG, Chuan-yun DAI. Research on the calibration method of discrete element physical property parameters in the pressing process of binary mixed particles[J]. Acta Pharmaceutica Sinica, 2025 , 60 (4) : 1137 -1146 . DOI: 10.16438/j.0513-4870.2024-0977
Year 2025 volume 60 Issue 4
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Article Info
doi: 10.16438/j.0513-4870.2024-0977
  • Receive Date:2024-09-10
  • Online Date:2025-10-29
  • Published:2025-04-12
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  • Received:2024-09-10
  • Revised:2024-12-14
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Affiliations
    1College of Chemistry and Chemical Engineering, Chongqing University of Science and Technology, Chongqing 401331, China
    2China National Institute for Food and Drug Control, Beijing 100050, China
    3Chongqing Key Laboratory of Digitalization of Pharmaceutical Processes, College of Traditional Chinese Medicine, Chongqing University of Chinese Medicine, Chongqing 402760, China
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表12种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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