Ion transport in multilayer solid-state nanopores for memory and biosensing applications

Solid-state nanopores have emerged as powerful platforms for investigating nanoscale transport phenomena and single-molecule sensing, owing to their structural robustness, chemical stability, and ability to simultaneously probe ionic and in-plane currents during biomolecule translocation. This dissertation presents a comprehensive computational framework to analyze and engineer ion and biomolecule dynamics in atomically thin 2D solid-state membranes and their multilayer architectures for applications in nanofluidics, biosensing, and molecular data storage. Through molecular dynamics simulations coupled with electron transport modeling, this work focuses on the mechanisms governing asymmetric ion transport in “Janus” MoSSe nanopore membranes with pore charges and demonstrates tunable control of ion dwell times through multilayer MoSSe architectures. In addition, a multilayer MoS₂–hBN heterostructure is shown to effectively reduce noise in in-plane current signals, thereby improving sensing precision. Furthermore, an algorithmic framework is developed to detect and differentiate RNA tail lengths attached to double-stranded DNA, advancing the feasibility of DNA-based data storage. Together, these findings highlight how intrinsic charge asymmetry, structural engineering, and hybrid computational modeling can be employed to optimize solid-state nanopore performance for next-generation nanofluidic, sensing, and memory device applications.

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Electrical & Computer Engr

Grantor

University of Illinois Urbana-Champaign

Year dc:date

2025

Author dc:creator

• Chakraborty, Rajat

Contributors dc:contributor

• Leburton, Jean-Pierre
• Kim, Kyekyoon
• Milenkovic, Olgica
• Di Ventra, Massimiliano

• Solid-state nanopore
• Ion transport
• Molecular dynamics simulation
• Multilayer nanopore
• Nanofluidics

Statement dc:rights

• Copyright 2025 Rajat Chakraborty

Language dc:language

en

Handle dc:identifier

https://hdl.handle.net/2142/132770

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/132770