Discrete computational modelling of twin screw granulation

双螺杆造粒的离散计算模型

• 批准号: EP/M02959X/1
• 负责人: Michael Adams
• 金额: $ 92.37万
• 依托单位: University of Birmingham
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2015
• 资助国家: 英国
• 起止时间: 2015 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FM02959X%2F1
• 关键词: Discrete; computational; modelling; twin; screw

Many industrial processing operations depend on feed materials that are fine powders with poor handling characteristics, which have to be rectified by granulation to form coarser granules. Generally wet granulation is employed, in which a binder is added to the powder in a mixer usually in batch processes. Continuous Twin Screw Granulation (TSG) has considerable potential, eg in the pharmaceutical sector, because of the flexibility in throughput and equipment design, reproducibility, short residence times, smaller liquid/solid ratios and also the ability to granulate difficult to process formulations. However, there remain significant technical issues that limit its widespread use and a greater understanding of the process is required to meet regulatory requirements. Moreover, encapsulated APIs (Active Pharmaceutical Ingredients) are of increasing interest and the development of a TSG process that did not damage such encapsulates would significantly extend applications. Experimental optimisation of TSG is expensive and often sub-optimal because of the high costs of APIs and does not lead to a more generic understanding of the process. Computational modelling of the behaviour of individual feed particles during the process will overcome these limitations. The Distinct Element Method (DEM) is the most widely used method but has rarely been applied to the number of particles in a TSG extruder (~ 55 million) and such examples involve simplified interparticle interactions e.g. by assuming that the particles are smooth and spherical and any liquid is present as discrete bridges rather than the greater saturation states associated with granulation. The project will be based on a multiscale strategy to develop advanced interaction laws that are more representative of real systems. The bulk and interfacial properties of a swelling particulate binder such as microcrystalline cellulose will be modelled using Coarse-grained Molecular Dynamics to derive inputs into a meso-scale Finite Discrete Element Method model of formulations that include hard particles and a viscous polymeric binder (hydroxypropylcellulose). Elastic particles (e.g. lactose and encapsulates) with viscous binder formulations will be modelled using the Fast Multi-pole Boundary Element Method. These micro- and meso-scale models will be used to provide closure for a DEM model of TSG. It will involve collaboration with the Chinese Academy of Science, which has pioneered the application of massively parallel high performance computing with GPU clusters to discrete modelling such as DEM, albeit with existing simpler interaction laws. An extensive experimental programme will be deployed to measure physical inputs and validate the models. The screw design and operating conditions of TSG for the formulations considered will be optimised using DEM and the results validated empirically. Optimisation criteria will include the granule size distribution, the quality of tablets for granules produced from the lactose formulation and the minimisation of damage to encapsulates. The primary benefit will be to provide a modelling toolbox for TSG for enabling more rapid and cost-effective optimisation, and allow encapsulated APIs to be processed. Detailed data post-processing will elucidate mechanistic information that will be used to develop regime performance maps. The multiscale modelling will have applications to a wide range of multiphase systems as exemplified by a large fraction of consumer products, catalyst pastes for extrusion processes, and agriculture products such as pesticides. The micro- and mesoscopic methods have generic applications for studying the bulk and interfacial behaviour of hard and soft particles and also droplets in emulsions. The combination of advanced modelling and implementation on massively parallel high performance GPU clusters will allow unprecedented applications to multiphase systems of enormous complexity.

许多工业加工操作依赖于具有差的处理特性的细粉末的进料材料，其必须通过造粒来整流以形成较粗的颗粒。通常采用湿法制粒，其中粘合剂通常以分批方法在混合器中加入粉末中。连续双螺杆造粒（TSG）具有相当大的潜力，例如在制药行业，因为在吞吐量和设备设计，再现性，停留时间短，更小的液体/固体比的灵活性，也有能力克服难以处理的配方。然而，仍然存在限制其广泛使用的重大技术问题，并且需要对该过程有更好的理解以满足监管要求。此外，封装的API（活性药物成分）越来越受到关注，并且不破坏这种封装物的TSG工艺的开发将显著扩展应用。 TSG的实验优化是昂贵的，并且由于API的高成本而常常是次优的，并且不会导致对该过程的更一般的理解。对过程中单个进料颗粒的行为进行计算建模将克服这些限制。离散单元法（DEM）是最广泛使用的方法，但很少应用于TSG挤出机中的颗粒数量（约5500万），并且这样的示例涉及简化的颗粒间相互作用，例如通过假设颗粒是光滑的和球形的，并且任何液体作为离散桥而不是与造粒相关的更大的饱和状态存在。该项目将以多尺度战略为基础，开发更能代表真实的系统的先进相互作用定律。将使用粗粒分子动力学对溶胀颗粒粘合剂（如微晶纤维素）的体积和界面性质进行建模，以获得包含硬颗粒和粘性聚合物粘合剂（羟丙基纤维素）的配方的中尺度有限元离散元方法模型的输入。将使用快速多极边界元法对具有粘性粘合剂配方的弹性颗粒（例如乳糖和胶囊）进行建模。这些微尺度和中尺度模型将用于为TSG的DEM模型提供闭合。它将涉及与中国科学院的合作，中国科学院率先将GPU集群的大规模并行高性能计算应用于离散建模，如DEM，尽管现有的相互作用定律更简单。将部署一个广泛的实验方案，以测量实际投入并验证模型。将使用DEM优化所考虑配方的TSG的螺杆设计和操作条件，并根据经验验证结果。优化标准将包括粒度分布、乳糖制剂生产的颗粒的片剂质量以及胶囊损坏的最小化。主要的好处是为TSG提供一个建模工具箱，以实现更快速和更具成本效益的优化，并允许处理封装的API。详细的数据后处理将阐明机制信息，将用于制定制度的性能地图。多尺度建模将应用于广泛的多相系统，例如大部分消费品，用于挤出工艺的催化剂糊，以及农药等农产品。微观和介观的方法具有通用的应用程序，用于研究硬颗粒和软颗粒以及乳液中的液滴的本体和界面行为。先进的建模和大规模并行高性能GPU集群的实现相结合，将允许前所未有的应用程序的多相系统的巨大复杂性。

项目成果

Effects of Moisture on the Mechanical Properties of Microcrystalline Cellulose and the Mobility of the Water Molecules as Studied by the Hybrid Molecular Mechanics-Molecular Dynamics Simulation Method

• DOI: 10.1002/polb.24801
• 发表时间: 2019-02
• 期刊: Journal of Polymer Science Part B: Polymer Physics
• 作者: I. H. Sahputra;A. Alexiadis;M. Adams

A fast multipole boundary element method implemented for wet single particle and wall interactions

一种用于湿单颗粒和壁相互作用的快速多极边界元方法

• DOI: 10.1016/j.powtec.2018.03.029
• 发表时间: 2019
• 期刊: Powder Technology
• 影响因子: 5.2
• 作者: Andrews J

Temperature and configurational effects on the Young's modulus of poly (methyl methacrylate): a molecular dynamics study comparing the DREIDING, AMBER and OPLS force fields

温度和构型对聚甲基丙烯酸甲酯杨氏模量的影响：比较 DREIDING、AMBER 和 OPLS 力场的分子动力学研究

• DOI: 10.1080/08927022.2018.1450983
• 发表时间: 2018
• 期刊: Molecular Simulation
• 影响因子: 2.1
• 作者: Sahputra I

A Coarse Grained Model for Viscoelastic Solids in Discrete Multiphysics Simulations

离散多物理场仿真中粘弹性固体的粗粒模型

• DOI: 10.3390/chemengineering4020030
• 发表时间: 2020
• 期刊: ChemEngineering
• 影响因子: 2.5
• 作者: Sahputra I