Dingeman L.H. van der Haven , Maria Mikoroni , Andrew Megarry , Ioannis S. Fragkopoulos , James A. Elliott
{"title":"用于药粉压实有限元预测建模的多组分混合和脱混模型","authors":"Dingeman L.H. van der Haven , Maria Mikoroni , Andrew Megarry , Ioannis S. Fragkopoulos , James A. Elliott","doi":"10.1016/j.apt.2024.104513","DOIUrl":null,"url":null,"abstract":"<div><p>A set of numerical methods is described that allows predictive finite element method (FEM) simulations of the compaction of multi-component pharmaceutical powder formulations across the entire range of compositions. An automated parametrisation procedure was used to extract density-dependent Drucker-Prager Cap (dDPC) model parameters from experimental data. Subsequently, these parameters were interpolated (mixed) or extrapolated (demixed) to predict dDPC model parameters of unseen powder formulations. Pure, binary, and ternary formulations of micro-crystalline cellulose (MCC, plastic), dibasic calcium phosphate dihydrate (DCPD, brittle), and pre-gelatinised starch (STA, elastic) powders were used to validate the parametrisation and mixing/demixing methodologies. FEM simulations were capable of reproducing compaction curves with errors only marginally greater than the experimental variability. Using only pure component data, FEM simulations with mixing rules were capable of predicting the compaction curves of mixtures as well as their shear stress distributions. Moreover, with data of only two or three powder formulations, a new demixing methodology was able to predict the behaviour of the constituent powders. The combination of these methodologies provides a powerful tool to rapidly explore powder formulations anywhere within the composition phase diagram, providing compaction curves but also stress profiles that are essential to early-stage formulation process development and tooling design.</p></div>","PeriodicalId":7232,"journal":{"name":"Advanced Powder Technology","volume":null,"pages":null},"PeriodicalIF":4.2000,"publicationDate":"2024-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0921883124001894/pdfft?md5=345f2c8e3bcf89595a6d777990744a74&pid=1-s2.0-S0921883124001894-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Multi-component mixing and demixing model for predictive finite element modelling of pharmaceutical powder compaction\",\"authors\":\"Dingeman L.H. van der Haven , Maria Mikoroni , Andrew Megarry , Ioannis S. Fragkopoulos , James A. Elliott\",\"doi\":\"10.1016/j.apt.2024.104513\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>A set of numerical methods is described that allows predictive finite element method (FEM) simulations of the compaction of multi-component pharmaceutical powder formulations across the entire range of compositions. An automated parametrisation procedure was used to extract density-dependent Drucker-Prager Cap (dDPC) model parameters from experimental data. Subsequently, these parameters were interpolated (mixed) or extrapolated (demixed) to predict dDPC model parameters of unseen powder formulations. Pure, binary, and ternary formulations of micro-crystalline cellulose (MCC, plastic), dibasic calcium phosphate dihydrate (DCPD, brittle), and pre-gelatinised starch (STA, elastic) powders were used to validate the parametrisation and mixing/demixing methodologies. FEM simulations were capable of reproducing compaction curves with errors only marginally greater than the experimental variability. Using only pure component data, FEM simulations with mixing rules were capable of predicting the compaction curves of mixtures as well as their shear stress distributions. Moreover, with data of only two or three powder formulations, a new demixing methodology was able to predict the behaviour of the constituent powders. The combination of these methodologies provides a powerful tool to rapidly explore powder formulations anywhere within the composition phase diagram, providing compaction curves but also stress profiles that are essential to early-stage formulation process development and tooling design.</p></div>\",\"PeriodicalId\":7232,\"journal\":{\"name\":\"Advanced Powder Technology\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":4.2000,\"publicationDate\":\"2024-06-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S0921883124001894/pdfft?md5=345f2c8e3bcf89595a6d777990744a74&pid=1-s2.0-S0921883124001894-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Advanced Powder Technology\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0921883124001894\",\"RegionNum\":2,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENGINEERING, CHEMICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advanced Powder Technology","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0921883124001894","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, CHEMICAL","Score":null,"Total":0}
Multi-component mixing and demixing model for predictive finite element modelling of pharmaceutical powder compaction
A set of numerical methods is described that allows predictive finite element method (FEM) simulations of the compaction of multi-component pharmaceutical powder formulations across the entire range of compositions. An automated parametrisation procedure was used to extract density-dependent Drucker-Prager Cap (dDPC) model parameters from experimental data. Subsequently, these parameters were interpolated (mixed) or extrapolated (demixed) to predict dDPC model parameters of unseen powder formulations. Pure, binary, and ternary formulations of micro-crystalline cellulose (MCC, plastic), dibasic calcium phosphate dihydrate (DCPD, brittle), and pre-gelatinised starch (STA, elastic) powders were used to validate the parametrisation and mixing/demixing methodologies. FEM simulations were capable of reproducing compaction curves with errors only marginally greater than the experimental variability. Using only pure component data, FEM simulations with mixing rules were capable of predicting the compaction curves of mixtures as well as their shear stress distributions. Moreover, with data of only two or three powder formulations, a new demixing methodology was able to predict the behaviour of the constituent powders. The combination of these methodologies provides a powerful tool to rapidly explore powder formulations anywhere within the composition phase diagram, providing compaction curves but also stress profiles that are essential to early-stage formulation process development and tooling design.
期刊介绍:
The aim of Advanced Powder Technology is to meet the demand for an international journal that integrates all aspects of science and technology research on powder and particulate materials. The journal fulfills this purpose by publishing original research papers, rapid communications, reviews, and translated articles by prominent researchers worldwide.
The editorial work of Advanced Powder Technology, which was founded as the International Journal of the Society of Powder Technology, Japan, is now shared by distinguished board members, who operate in a unique framework designed to respond to the increasing global demand for articles on not only powder and particles, but also on various materials produced from them.
Advanced Powder Technology covers various areas, but a discussion of powder and particles is required in articles. Topics include: Production of powder and particulate materials in gases and liquids(nanoparticles, fine ceramics, pharmaceuticals, novel functional materials, etc.); Aerosol and colloidal processing; Powder and particle characterization; Dynamics and phenomena; Calculation and simulation (CFD, DEM, Monte Carlo method, population balance, etc.); Measurement and control of powder processes; Particle modification; Comminution; Powder handling and operations (storage, transport, granulation, separation, fluidization, etc.)