CAREER: Multi-scale modeling and analysis of reactive granulation processes

职业:反应造粒过程的多尺度建模和分析

基本信息

  • 批准号:
    1350152
  • 负责人:
  • 金额:
    $ 40万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2014
  • 资助国家:
    美国
  • 起止时间:
    2014-01-01 至 2021-06-30
  • 项目状态:
    已结题

项目摘要

1350152 - RamachandranThe overall goal of this proposal is to develop an integrated research and educational program centered around the interface of Particle Technology and Process Systems Engineering (PSE). The fields of particle technology and PSE are often asynchronous with limited interactions and inter- facing between them. From a research perspective, this is evidenced by the application of PSE to primarily only chemical, biological and energy systems. From an educational perspective, students are typically trained in either PSE or particle technology with limited overlap in training between the two fields. These factors motivate the need for a new research and educational paradigm termed Particulate Process Systems Engineering (PPSE). PPSE represents a systems engineering approach to the understanding and design of multi-scale particulate processes for their overall practical application in particulate-based industries. Within this theme, the overall research objective of this proposal is to quantitatively understand, design and optimize the interactions between material properties, process parameters, chemical reaction and transport phenomena to predict product performance of particulate materials for a class of reactive-particulate processes known as reactive granulation. The educational aims are designed to integrate the research findings of this project to instill a methodology combined with assessment and evaluation to equip graduating students at the interface of particulate technology and PSE focusing on 1) incorporating aspects of PPSE in the senior design course and 2) raising awareness of PPSE via outreach activities.Intellectual merits: The proposal is aimed at studying the challenging multi-scale aspects of reactive granulation processes and is synergistically integrated with high-performance computing and optimization strategies to enable the multi-scale model to be practically utilized by industrial companies for granulation process design and optimization at scale-up. The project should result in better scientific understanding of the coupling between chemical reaction and particle-wetting, and the systematic integration of different models and model forms across multiple lengths and time scales. The work should also lead to a quantitative methodology to optimally operate industrial granulation processes at scale-up. The PI expects this project to yield key advances that bridge the gap between PSE and particle technology, resulting in new knowledge and methodologies applicable to other particulate-based multi-scale systems (e.g. crystallization, polymerization), enabling the advancement of scientific understanding in other particulate-based industrial manufacturing operations.Broader impacts: These research findings could be used to enhance the efficiency, profitability and sustainability of many industries (e.g. food, pharmaceutical, consumer goods) that deal with granulation processes to manufacture their products, thus directly impacting the U.S. economy. Codes and a library of solutions to problems developed during the project will be made available for other researchers in the field to use (and improve upon) via the ERC-SOPs pharmaHUB Engineering Virtual Organization for Pharmaceutical Engineering and Science, which has an easy-to-use interface for resource sharing. Research findings will also be integrated into the senior design course creating a PPSE track to better train graduating students in process design and optimization of particulate processes. This is in addition to pre-college (DSI/GSET RU programs) and freshman (RU Byrne?s seminar series) outreach by the PI using his research findings to create a pipeline in place to motivate students to do an honors thesis (RU Slades scholars program) in their sophomore to senior year, thus benefiting the numerous particulate-based industries in the NJ vicinity, as the students graduate with enhanced skills in this field. This will be combined with assessment and evaluation via the RU Center for Teaching Advancement and Assessment to monitor student, program and employer outcomes, for continued improvement of proposed educational initiatives. Proposed international collaboration with The University of Sheffield, UK, (which is internationally renowned in particle technology) will also benefit graduate students involved in this project as they interact with academics and industrial experts and have direct access to state-of-the-art large-scale equipment. Longer term societal benefits relate to enhanced manufacturing operations that lower costs of particulate-based medicinal drugs and consumer goods.
1350152 -Ramachandran该提案的总体目标是围绕粒子技术和过程系统工程(PSE)的接口开发一个综合的研究和教育计划。粒子技术和PSE领域通常是异步的,它们之间的交互和接口有限。从研究的角度来看,PSE主要仅应用于化学,生物和能源系统。从教育的角度来看,学生通常接受PSE或粒子技术的培训,这两个领域之间的培训重叠有限。这些因素促使需要一个新的研究和教育范式称为颗粒过程系统工程(PPSE)。PPSE代表了一种系统工程方法,用于理解和设计多尺度颗粒过程,以实现其在颗粒工业中的整体实际应用。在此主题内,本提案的总体研究目标是定量了解、设计和优化材料性能、工艺参数、化学反应和传输现象之间的相互作用,以预测一类反应性颗粒工艺的颗粒材料的产品性能,称为反应性造粒。教育目标旨在整合本项目的研究成果,以灌输一种与评估和评价相结合的方法,使毕业生掌握颗粒技术和PSE的界面,重点是1)将PPSE的各个方面纳入高级设计课程,2)通过推广活动提高PPSE的意识。该提案旨在研究具有挑战性的多尺度方面的反应性造粒过程,并与高性能计算和优化策略协同集成,以实现多尺度的反应性造粒过程。规模模型实际上是由工业公司用于造粒工艺设计和优化的规模。该项目应导致更好地科学理解化学反应和颗粒润湿之间的耦合,以及跨多个长度和时间尺度的不同模型和模型形式的系统集成。这项工作还应导致一个定量的方法,以优化操作工业造粒过程中的规模。PI希望该项目能够产生关键的进步,弥合PSE和粒子技术之间的差距,从而产生适用于其他基于颗粒的多尺度系统的新知识和方法(例如结晶、聚合),从而推动对其他基于颗粒的工业制造操作的科学理解。这些研究结果可用于提高许多行业(如食品,制药,消费品)的效率,盈利能力和可持续性,这些行业处理造粒过程以制造其产品,从而直接影响美国经济。在项目期间开发的问题解决方案的代码和库将通过ERC-SOP pharmaHUB制药工程和科学工程虚拟组织提供给该领域的其他研究人员使用(和改进),该组织具有易于使用的资源共享界面。研究结果也将被整合到高级设计课程,创建一个PPSE轨道,以更好地培养毕业生在工艺设计和颗粒工艺优化。这是除了大学预科(DSI/GSET RU计划)和新生(RU伯恩?的研讨会系列)推广PI使用他的研究成果,以创造一个管道到位,激励学生做一个荣誉论文(RU Slades学者计划)在他们的大二到大四,从而有利于在新泽西州附近的众多颗粒为基础的行业,作为学生毕业与增强技能在这一领域。这将与评估和评价通过RU中心教学进步和评估相结合,以监测学生,计划和雇主的成果,为拟议的教育举措的持续改进。与英国谢菲尔德大学(在颗粒技术方面享有国际声誉)的拟议国际合作也将使参与该项目的研究生受益,因为他们与学者和工业专家互动,并直接获得最先进的大型设备。长期的社会效益与提高生产能力有关,这些生产能力降低了微粒类药物和消费品的成本。

项目成果

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Rohit Ramachandran其他文献

Characterization of NIR interfaces for the feeding and in-line monitoring of a continuous granulation process
  • DOI:
    10.1016/j.ijpharm.2019.118848
  • 发表时间:
    2020-01-25
  • 期刊:
  • 影响因子:
  • 作者:
    Andrés D. Román-Ospino;Ashutosh Tamrakar;Benoît Igne;Elyse Towns Dimaso;Christian Airiau;Donald J. Clancy;Glinka Pereira;Fernando J. Muzzio;Ravendra Singh;Rohit Ramachandran
  • 通讯作者:
    Rohit Ramachandran
Quantitative validation and analysis of the regime map approach for the wet granulation of industrially relevant zirconium hydroxide powders
  • DOI:
    10.1016/j.powtec.2016.02.026
  • 发表时间:
    2016-06-01
  • 期刊:
  • 影响因子:
  • 作者:
    Manogna Adepu;Siddhi Hate;Angelique Bétard;Sarang Oka;Marek Schongut;Maitraye Sen;Yadvaindera Sood;Dorit Wolf;Stefan Wieland;Frantisek Stepanek;Fernando Muzzio;Benjamin Glasser;Rohit Ramachandran
  • 通讯作者:
    Rohit Ramachandran
Population Balance Model Validation and Predictionof CQAs for Continuous Milling Processes: toward QbDin Pharmaceutical Drug Product Manufacturing
  • DOI:
    10.1007/s12247-013-9155-0
  • 发表时间:
    2013-07-05
  • 期刊:
  • 影响因子:
    2.700
  • 作者:
    Dana Barrasso;Sarang Oka;Ariel Muliadi;James D. Litster;Carl Wassgren;Rohit Ramachandran
  • 通讯作者:
    Rohit Ramachandran
CPU and GPU based acceleration of high-dimensional population balance models via the vectorization and parallelization of multivariate aggregation and breakage integral terms
通过多元聚集和破碎积分项的矢量化和并行化对高维群体平衡模型进行基于CPU和GPU的加速
  • DOI:
    10.1016/j.compchemeng.2025.109037
  • 发表时间:
    2025-05-01
  • 期刊:
  • 影响因子:
    3.900
  • 作者:
    Ashley Dan;Urjit Patil;Abhinav De;Bhavani Nandhini Mummidi Manuraj;Rohit Ramachandran
  • 通讯作者:
    Rohit Ramachandran
Switching from batch to continuous granulation: A case study of metoprolol succinate ER tablets
  • DOI:
    10.1016/j.ijpharm.2022.121598
  • 发表时间:
    2022-04-05
  • 期刊:
  • 影响因子:
  • 作者:
    Lalith Kotamarthy;Xin Feng;Alaadin Alayoubi;Pradeep Kumar Bolla;Rohit Ramachandran;Muhammad Ashraf;Thomas O'Connor;Ahmed Zidan
  • 通讯作者:
    Ahmed Zidan

Rohit Ramachandran的其他文献

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{{ truncateString('Rohit Ramachandran', 18)}}的其他基金

EAGER:REAL-D: Smart Decision Making using Data and Advanced Modeling Approaches
EAGER:REAL-D:使用数据和高级建模方法进行智能决策
  • 批准号:
    1839007
  • 财政年份:
    2018
  • 资助金额:
    $ 40万
  • 项目类别:
    Standard Grant

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