Stefano Pagliara
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Associate Professor
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About
Stefano Pagliara is an Associate Professor at the University of Exeter, United Kingdom. His research areas include the study of bacterial responses to antibiotics, the development of antimicrobial agents, and the analysis of bacterial membrane permeability. Recent publications have explored topics such as the kinetics of single-cell killing, the synthesis of fluorescent probes for bacterial identification, and innovative microfluidic methods for investigating microbial behavior.
Recent Grants
Grant: Close
Understanding molecular accumulation in single cells via microfluidics and omics
Open Date: 2021-11-01
Close Date: 2024-10-31
Grant: Close
Formation of synthetic blastocysts by self-organization of human naïve pluripotent stem cells
Open Date: 2021-08-31
Close Date: 2024-08-30
Grant: Close
A Label-free, Ultra-High-Throughput Bacteriolysis Droplet Screening Platform (KillerDrop)
Open Date: 2020-06-30
Close Date: 2022-01-31
Grant: Close
Mechanisms and evolutionary consequences of host immunosuppression by anti-CRISPR phages
Open Date: 2020-01-06
Close Date: 2023-07-04
Grant: Close
Developing a Novel Physical and Mathematical Framework for Studying Antibiotic Efficacy
Open Date: 2019-09-30
Close Date: 2023-06-21
Articles (15)
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2023
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2023
Herringbone micromixers are a powerful tool for introducing advection into microfluidic systems. While these mixers are typically used for mixing fluids faster than the rate of diffusion, there has been recent interest in using the device to enhance interactions between suspended particles and channel walls. We show how the common approximations applied to herringbone micromixer theory can have a significant impact on results. We show that the inclusion of gravity can greatly alter the interaction probability between suspended particles and channel walls. We also investigate the proposed impedance matching condition and the inclusion of imperfect binding using numerical methods, and investigate transient behaviors using an experimental system. These results indicate that while traditional methods, such as simple streamline analysis, remain powerful tools, it should not be considered predictive in the general case.
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2023
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2023
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2023
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2022
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2022
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2022
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2021
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2021
Collaborators (14)
Krasimira Tsaneva-Atanasova
Professor of Mathematics for Healthcare
University of Exeter
Tatiana Dimitriu
University of St Andrews
Matthew Cooper
Professor
University of Queensland
Mark Szczelkun
University of Bristol
Mathew McLaren
University of Exeter
Richard Chahwan
University of Zurich
Feodor Y. Ogrin
-
David Milner
University of Oxford
Jasna Rakonjac
Professor
Massey University
Alyson E. Santoro
-
Nela Nikolic
Lecturer in Microbiology
University of Southampton
Vicki Gold
Senior Lecturer
University of Exeter
Matthew Kellom
DOE Joint Genome Institute
Bertram Daum
University of Exeter
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