PREdictive Modelling with QuantIfication of UncERtainty for MultiphasE Systems

Grover, Liam (Co-Investigator)
Simmons, Mark (Principal Investigator)
Vigolo, Daniele (Co-Investigator)

Short title	PREdictive Modelling with QuantIfication of UncERtainty for MultiphasE Systems
Status	Active
Effective start/end date	1/10/19 → 30/03/25

Funding

Engineering & Physical Science Research Council

8 Article

Explainable AI models for predicting drop coalescence in microfluidics device
Hu, J., Zhu, K., Cheng, S., Kovalchuk, N., Soulsby, A., Simmons, M., Matar, O. K. & Arcucci, R., 1 Feb 2024, In: Chemical Engineering Journal. 481, 16 p., 148465.
Research output: Contribution to journal › Article › peer-review

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Spreading of aqueous surfactant solutions on oil substrates: Superspreaders vs non-superspreaders
Kovalchuk, N. M., Sagisaka, M., Komiyama, H. & Simmons, M. J. H., May 2024, In: Journal of Colloid and Interface Science. 661, p. 1046-1059 14 p.
Research output: Contribution to journal › Article › peer-review

Open Access
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Accurate identification and measurement of the precipitate area by two-stage deep neural networks in novel chromium-based alloys
Xia, Z., Ma, K., Cheng, S., Blackburn, T., Peng, Z., Zhu, K., Zhang, W., Xiao, D., Knowles, A. & Arcucci, R., 26 May 2023, (E-pub ahead of print) In: Physical Chemistry Chemical Physics.
Research output: Contribution to journal › Article › peer-review

Open Access
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