The SABYDOMA Safety by Process Control framework for the production of functional, safe and sustainable nanomaterials

Argyri Kardamaki, Athanassios Nikolakopoulos, Mihalis Kavousanakis, Philip Doganis, Matt Jellicoe, William Stokes, Vesa Hongisto, Matthew Simmons, Thomas W. Chamberlain, Nikil Kapur, Roland Grafström, Andrew Nelson, Haralambos Sarimveis

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)
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Abstract

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.

Original languageEnglish
Article number109113
Number of pages16
JournalComputers and Chemical Engineering
Volume199
DOIs
Publication statusPublished - Aug 2025
Externally publishedYes

Keywords

  • Model Predictive Control
  • Nanomaterial synthesis
  • Safe and sustainable by design
  • Safety-by-process-control

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