Ion transport in multilayer solid-state nanopores for memory and biosensing applications
Chakraborty, Rajat
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https://hdl.handle.net/2142/132770
Description
Title
Ion transport in multilayer solid-state nanopores for memory and biosensing applications
Author(s)
Chakraborty, Rajat
Issue Date
2025-12-04
Director of Research (if dissertation) or Advisor (if thesis)
Leburton, Jean-Pierre
Doctoral Committee Chair(s)
Leburton, Jean-Pierre
Committee Member(s)
Kim, Kyekyoon
Milenkovic, Olgica
Di Ventra, Massimiliano
Department of Study
Electrical & Computer Eng
Discipline
Electrical & Computer Engr
Degree Granting Institution
University of Illinois Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Keyword(s)
Solid-state nanopore
Ion transport
Molecular dynamics simulation
Multilayer nanopore
Nanofluidics
Language
eng
Abstract
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 MoS$_2$–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.
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