Stefano Pagliara

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Associate Professor

University of Exeter
Country flagUnited Kingdom

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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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2022

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2022

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2021

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2021

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2021

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2021

Collaborators (14)

Krasimira Tsaneva-Atanasova

Professor of Mathematics for Healthcare

University of Exeter

UNITED KINGDOM
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Tatiana Dimitriu

University of St Andrews

UNITED KINGDOM
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Matthew Cooper

Professor

University of Queensland

AUSTRALIA
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Mark Szczelkun

University of Bristol

UNITED KINGDOM
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Mathew McLaren

University of Exeter

UNITED KINGDOM
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Richard Chahwan

University of Zurich

SWITZERLAND
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Feodor Y. Ogrin

-

UNITED KINGDOM
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David Milner

University of Oxford

UNITED KINGDOM
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Jasna Rakonjac

Professor

Massey University

NEW ZEALAND
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Alyson E. Santoro

-

UNITED STATES
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Nela Nikolic

Lecturer in Microbiology

University of Southampton

UNITED KINGDOM
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Vicki Gold

Senior Lecturer

University of Exeter

UNITED KINGDOM
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Matthew Kellom

DOE Joint Genome Institute

UNITED STATES
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Bertram Daum

University of Exeter

UNITED KINGDOM
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