TY - JOUR
T1 - The SABYDOMA Safety by Process Control framework for the production of functional, safe and sustainable nanomaterials
AU - Kardamaki, Argyri
AU - Nikolakopoulos, Athanassios
AU - Kavousanakis, Mihalis
AU - Doganis, Philip
AU - Jellicoe, Matt
AU - Stokes, William
AU - Hongisto, Vesa
AU - Simmons, Matthew
AU - Chamberlain, Thomas W.
AU - Kapur, Nikil
AU - Grafström, Roland
AU - Nelson, Andrew
AU - Sarimveis, Haralambos
PY - 2025/8
Y1 - 2025/8
N2 - The production of nanomaterials (NMs) has gained significant attention due to their unique properties and versatile applications in fields such as medicine, energy, and electronics. However, ensuring the large-scale synthesis of safe and sustainable NMs while maintaining their functionality remains a critical challenge. This study introduces the Safety by Process Control (SbPC) framework, a novel methodology integrating dynamic first-principles modeling, Model Predictive Control (MPC), and real-time safety monitoring. The framework employs a physics-based population balance model with a Method Of Moments (MOM) approximation to predict the evolution of key NM properties. A toxicity inferential sensor, built on experimental data, is integrated to facilitate real-time hazard assessment. The efficiency of the proposed framework is demonstrated using a continuous silver nanoparticle (Ag NP) production system as a case study. The proposed approach ensures the production of high-quality, safe, and sustainable NMs, aligning with Safe and Sustainable by Design (SSbD) principles and addressing gaps in current NM manufacturing processes. The framework's adaptability to other NM types highlights its potential as a transformative tool for sustainable nanotechnology.
AB - The production of nanomaterials (NMs) has gained significant attention due to their unique properties and versatile applications in fields such as medicine, energy, and electronics. However, ensuring the large-scale synthesis of safe and sustainable NMs while maintaining their functionality remains a critical challenge. This study introduces the Safety by Process Control (SbPC) framework, a novel methodology integrating dynamic first-principles modeling, Model Predictive Control (MPC), and real-time safety monitoring. The framework employs a physics-based population balance model with a Method Of Moments (MOM) approximation to predict the evolution of key NM properties. A toxicity inferential sensor, built on experimental data, is integrated to facilitate real-time hazard assessment. The efficiency of the proposed framework is demonstrated using a continuous silver nanoparticle (Ag NP) production system as a case study. The proposed approach ensures the production of high-quality, safe, and sustainable NMs, aligning with Safe and Sustainable by Design (SSbD) principles and addressing gaps in current NM manufacturing processes. The framework's adaptability to other NM types highlights its potential as a transformative tool for sustainable nanotechnology.
KW - Model Predictive Control
KW - Nanomaterial synthesis
KW - Safe and sustainable by design
KW - Safety-by-process-control
UR - http://www.scopus.com/inward/record.url?scp=105002561079&partnerID=8YFLogxK
U2 - 10.1016/j.compchemeng.2025.109113
DO - 10.1016/j.compchemeng.2025.109113
M3 - Article
AN - SCOPUS:105002561079
SN - 0098-1354
VL - 199
JO - Computers and Chemical Engineering
JF - Computers and Chemical Engineering
M1 - 109113
ER -