Ionic Conductivity in Confinement

About This Grant

NON-TECHNICAL SUMMARY This award supports research aimed at improving our understanding of ion transport in spatially-confined, electrically-charged environments. Living organisms employ ions to transmit sensory signals, store information in memory, and convert chemical energy into work. These functionalities often involve ions in confined aqueous environments. In biological systems, ion transport occurs through channels, proteins, and membranes, where the confined geometries enable enhanced responsiveness to stimuli. Within cellular environments, these stimuli are self-generated by changes in local ionic and molecular compositions. The team hypothesizes that the response of ions to external stimuli in artificial channels and synthetic confined morphologies can be used to emulate neuronal functions, such as information signaling and processing. To explore this, they aim to investigate the mechanisms by which information and energy are transferred via ionic structural changes and motion in confined environments. Ionic motion in solutions is typically driven externally by electric fields (electro-osmosis) or ionic concentration gradients (ionic diffusion-osmosis) and is strongly influenced by geometry and surface properties. Surface-induced electro-osmosis and ionic diffusion-osmosis occur when electric fields or gradients are self-generated due to non-uniform surface properties. These properties include spatially varying chemical activity, ion fluxes, and structural asymmetries, such as irregular charge distributions or asymmetric geometries. The supported research will focus on developing theoretical, numerical, and computational approaches to design and analyze both externally driven and surface-induced ionic flows in confined systems, with an emphasis on understanding the roles of surface and geometric effects. The goal will be to uncover the mechanisms underlying ionic signaling to enable the design of ionic systems capable of storing and transferring information, mimicking brain-like functionalities. This research has the potential to lay the foundation for the development of ionic machines—soft, adaptive materials that encode and process information using ionic currents. Additionally, the team is committed to educating students and postdocs in this emerging interdisciplinary field, which has immense technological relevance and promises to drive innovations in futuristic applications. TECHNICAL SUMMARY This award supports research aimed at improving our understanding of ion transport in spatially-confined, electrically-charged environments. The team will attempt to design biomimetic materials that perform information and energy transference in nanochannels using ions as charge carriers. They will develop molecular simulations and continuum theory to determine the relationship between memory effects and ionic microstructures in the transport of ions. They will employ classification schemes to assess the system's ionic clustering conditions, topology, and time evolution required to produce non-linear and time-dependent ionic conductivities. These features are essential to create memory effects. The team will also explore the mechanisms to modify ionic conductivity in nanochannels by considering polarizable surfaces of various geometries and the impact of direct and time-dependent biasing electric fields. There are currently no efficient computational methods to address surface polarization effects on strong confinement by topologies other than flat. To develop ionic signals' information transference and processing paradigms, the team will develop computational methods to investigate ionic currents at pore boundaries and non-symmetric structures. They will also develop analytical models and numerical methods to analyze the combined effect of ionic fluxes with charge patterns in surface-induced electro-osmosis and ionic diffusion-osmosis. The supported research will answer fundamental questions about information transference, signaling, and key biophysical processes. It will provide a physical understanding of molecular interactions in nano- and micro-sized confinement of charge-containing systems. In doing so, it will aid the design of new materials for various applications, including water desalination, ion separation, and blue energy harvesting. This award will impact diverse fields, including biology, neuroscience, and materials science, by employing the results of the supported research to interpret experimental measurements and design new functionalities. The results of all studies will be published in peer-reviewed journals, and the ream will develop open-source computational codes to assist researchers working on related theoretical and computational problems. The award will also enable training of students and postdocs in a highly interdisciplinary area of research. The participating students and postdoctoral researchers will acquire knowledge in several disciplines, including statistical mechanics, electrostatics, fluid mechanics, and thermodynamics. In addition, the students will learn and develop numerical techniques, molecular simulation methods, and different computational skills, including high-performance computing techniques and programming languages. Overall, students and postdocs will receive training to pursue a career in diverse fields, including environmental science, biotechnology, informatics, computer science, and materials science. The team will support undergraduate students via post-baccalaureate positions as summer internships or during the academic year in the local colleges to help them gain knowledge of research in iontronics, an emerging field that employs ionic flows to design ionic machines that perform advanced functionalities. STATEMENT OF MERIT REVIEW This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.