activity
20102024
most citedA transferable ab-initio based force field for aqueous ions

67 citations · 324 across the 24 of their papers we have counts for

collaborators
Showing 2022Show all

6 papers · 1 filter

physics.flu-dyn2022★ 8 cited

Learning to swim efficiently in a nonuniform flow field

Krongtum Sankaewtong, John J. Molina, Matthew S. Turner +1

Microswimmers can acquire information on the surrounding fluid by sensing mechanical queues. They can then navigate in response to these signals. We analyse this navigation by comb…

cond-mat.soft2022★ 11 cited

Dynamics of microswimmers near a liquid-liquid interface with viscosity difference

Chao Feng, John J. Molina, Matthew S. Turner +1

Transport of material across liquid interfaces is ubiquitous for living cells and is also a crucial step in drug delivery and in many industrial processes. The fluids that are pres…

cond-mat.soft2022★ 1 cited

Dynamics of microswimmers near a soft penetrable interface

Chao Feng, John J. Molina, Matthew S. Turner +1

Few simulations exist for microswimmers near deformable interfaces. Here, we present numerical simulations of the hydrodynamic flows associated with a single microswimmer embedded…

cond-mat.soft2022★ 9 cited

Collective Motion of Quincke Rollers with Fully Resolved Hydrodynamics

Shun Imamura, Kohei Sawaki, John J. Molina +2

A Quincke roller is a unique active particle that can run and tumble freely on a flat plate due to the torque generated by a uniform DC electric field applied perpendicular to the…

econ.TH2022★ 9 cited

Rational social distancing policy during epidemics with limited healthcare capacity

Simon K. Schnyder, John J. Molina, Ryoichi Yamamoto +1

Epidemics of infectious diseases posing a serious risk to human health have occurred throughout history. During recent epidemics there has been much debate about policy, including…

cs.LG2022★ 1 cited

Nash Neural Networks : Inferring Utilities from Optimal Behaviour

John J. Molina, Simon K. Schnyder, Matthew S. Turner +1

We propose Nash Neural Networks () as a new type of Physics Informed Neural Network that is able to infer the underlying utility from observations of how rational individuals…