Population balance modeling and digital design of degree of agglomeration in industrial crystallization

Abstract This study presents a coupled population balance model (PBM) for describing the degree‐of‐agglomeration (DoA) in crystallization by independently tracking total particle and agglomerate number densities. Applied to an industrial active pharmaceutical ingredient, the model outperformed bridge‐counting methods and accurately captured DoA trends using only inline concentration and crystal size distributions (CSDs). An optimization strategy minimizing agglomeration through temperature and cooling adjustments showed that thermal cycling reduced agglomeration and enhanced crystallinity. A multi‐objective optimization revealed improvements in dispersity and crystallinity, albeit with reduced particle size. Model‐based quality‐by‐control profiles surpassed the original quality‐by‐design recipe in agglomeration control and robustness, validated by image analysis and scanning electron microscopy. The optimized strategy also shortened batch times without compromising quality, demonstrating the benefits of digital design in crystallization optimization.

Authors

Institutions

Publication Details

Journal
AIChE Journal
Published
2026-06-13
DOI
https://doi.org/10.1002/aic.70502
Primary Topic
Crystallization and Solubility Studies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Population balance modeling and digital design of degree of agglomeration in industrial crystallization

Yi Yang, Zoltán K. Nagy, Neda Nazemifard, Hemalatha Kilari et al.
AIChE Journal
Crystallization and Solubility Studies
article

Population balance modeling and digital design of degree of agglomeration in industrial crystallization

Yi Yang, Zoltán K. Nagy, Neda Nazemifard, Hemalatha Kilari, Yun-Sun Kang, C. Benjamin Renner, Charles Papageorgiou
article en

Abstract

Abstract This study presents a coupled population balance model (PBM) for describing the degree‐of‐agglomeration (DoA) in crystallization by independently tracking total particle and agglomerate number densities. Applied to an industrial active pharmaceutical ingredient, the model outperformed bridge‐counting methods and accurately captured DoA trends using only inline concentration and crystal size distributions (CSDs). An optimization strategy minimizing agglomeration through temperature and cooling adjustments showed that thermal cycling reduced agglomeration and enhanced crystallinity. A multi‐objective optimization revealed improvements in dispersity and crystallinity, albeit with reduced particle size. Model‐based quality‐by‐control profiles surpassed the original quality‐by‐design recipe in agglomeration control and robustness, validated by image analysis and scanning electron microscopy. The optimized strategy also shortened batch times without compromising quality, demonstrating the benefits of digital design in crystallization optimization.

AIChE Journal
Purdue University West Lafayette (US), Takeda (United States) (US)
Openalex Percentile: Top 13%
Crystallization and Solubility Studies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.