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Volume 13
Issue 2
10.3390/pr13020388
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This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
Article

Digitised Optimisation of Nanoparticle Synthesis via Laser Ablation: An Industry 4.0 Multivariate Approach for Enhanced Production

by
Brian Freeland
1,2,*,
Ronan McCann
3,
Burcu Akkoyunlu
2,
Manuel Tiefenthaler
1,4,
Michal Dabros
4,
Mandy Juillerat
4,
Keith D. Rochfort
2,
Greg Foley
2 and
Dermot Brabazon
1
1
I-Form Advanced Manufacturing Research Centre, Dublin City University, Glasnevin, D09 V209 Dublin, Ireland
2
School of Biotechnology, Dublin City University, Glasnevin, D09 V209 Dublin, Ireland
3
School of Science and Computing, South East Technological University, X91 Waterford, Ireland
4
School of Engineering and Architecture HES-SO, University of Applied Sciences and Arts Western Switzerland, Bd de Pérolles 80, CH-1700 Fribourg, Switzerland
*
Author to whom correspondence should be addressed.
Processes 2025, 13(2), 388; https://doi.org/10.3390/pr13020388
Submission received: 1 October 2024 / Revised: 3 December 2024 / Accepted: 10 December 2024 / Published: 31 January 2025
(This article belongs to the Section Materials Processes)
Versions Notes

Abstract

The synthesis of nanoparticles (NPs) via laser ablation synthesis in solution (LASiS) is a promising method for sustainable and efficient nanoparticle fabrication. This work investigates the transition from one-factor-at-a-time experimentation to a more efficient, multivariate approach for optimising NP production efficiency. By applying the Industry 4.0 principles, the objective is to digitise and automate laboratory processes to increase productivity and robustness. Design of Experiments (DoE) strategies, Taguchi orthogonal arrays and full-factorial design (FFD), have been employed to enhance laser ablation processes. Both models confirmed that increasing laser power led to higher colloid absorbance, with the Taguchi DoE offering rapid initial process mapping and FFD providing a higher-resolution analysis. The optimal laser repetition rate of 30 kHz was identified as a balance between pulse energy and thermal effects on the target, maximising ablation efficiency. The Taguchi model had a prediction of NP size with an R2 value of 0.49, while the FFD struggled with accurate size prediction. Additionally, this study introduced a recirculation flow regime as a rapid test platform for predicting optimal conditions for continuous flow production. Using a semi-autonomous DoE platform decreased the operator involvement and increased the process selectivity. This proof-of-concept for on-the-bench NP rapid manufacturing demonstrated how efficient NP synthesis processes can be developed by clarifying the effects of varying parameters on colloid productivity, paving the way for broader industrial applications in the future.
Keywords: nanoparticles; laser ablation synthesis in solution; silicon nanoparticles; additive manufacturing; design of experiments; automation; Industry 4.0; material processing nanoparticles; laser ablation synthesis in solution; silicon nanoparticles; additive manufacturing; design of experiments; automation; Industry 4.0; material processing

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MDPI and ACS Style

Freeland, B.; McCann, R.; Akkoyunlu, B.; Tiefenthaler, M.; Dabros, M.; Juillerat, M.; Rochfort, K.D.; Foley, G.; Brabazon, D. Digitised Optimisation of Nanoparticle Synthesis via Laser Ablation: An Industry 4.0 Multivariate Approach for Enhanced Production. Processes 2025, 13, 388. https://doi.org/10.3390/pr13020388

AMA Style

Freeland B, McCann R, Akkoyunlu B, Tiefenthaler M, Dabros M, Juillerat M, Rochfort KD, Foley G, Brabazon D. Digitised Optimisation of Nanoparticle Synthesis via Laser Ablation: An Industry 4.0 Multivariate Approach for Enhanced Production. Processes. 2025; 13(2):388. https://doi.org/10.3390/pr13020388

Chicago/Turabian Style

Freeland, Brian, Ronan McCann, Burcu Akkoyunlu, Manuel Tiefenthaler, Michal Dabros, Mandy Juillerat, Keith D. Rochfort, Greg Foley, and Dermot Brabazon. 2025. "Digitised Optimisation of Nanoparticle Synthesis via Laser Ablation: An Industry 4.0 Multivariate Approach for Enhanced Production" Processes 13, no. 2: 388. https://doi.org/10.3390/pr13020388

APA Style

Freeland, B., McCann, R., Akkoyunlu, B., Tiefenthaler, M., Dabros, M., Juillerat, M., Rochfort, K. D., Foley, G., & Brabazon, D. (2025). Digitised Optimisation of Nanoparticle Synthesis via Laser Ablation: An Industry 4.0 Multivariate Approach for Enhanced Production. Processes, 13(2), 388. https://doi.org/10.3390/pr13020388

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