Research

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Electrical, Electromechanical, and Optoelectronic Response of Nanodevices

We are primarily a Theory & Modeling group who work on a variety of problems using quantum mechanical methods to understand devices and materials. The focus of our work centers around  bio nanostructures, 2D materials, nanowires and oxides.

We use a variety of tools to model these structures. To find the atomic coordinates we use both Monte Carlo and classical & quantum molecular dynamics methods. To study the electronic properties, we use both density functional theory and tight binding methods. To study the electrical transport properties of nanostructures, we develop both algorithms and code based on non equilibrium quantum approaches.

We work on both fundamental and applied problems. Our current directions of focus are:

1. DNA and Protein Nanostructures: We are interested in understanding how to enhance the conductance of biomolecules (proteins and DNA) and build interesting heterostructures out of them. Current projects are centered on:

    • Topological effects in peptides and DNA
    • Force field development for hybrid DNA structures
    • Electrical contacts to biomolecules
    • Device ideas
    • Use of machine learning to understand experimental conductance traces through molecular structures (see our code released in github)

Figure 1

Figure: Transport in a peptide with iron centers. See A Spin-Dependent Model for Multi-Heme Bacterial Nanowires | ACS Nano

2. Theory and Algorithms: We work on the theory and algorithms involved in modeling the equations that govern quantum transport, with decoherence included. Our interest lies in both systems that are crystalline/periodic and those without an obvious underlying periodicity. We model decoherence both withing the context of a phonon both that interacts with the electrons and with a hierarchy of models using decoherence probes.

Figure 1  Figure: Efficient methods for quantum transport. See Charge transport through DNA with energy-dependent decoherence, Phys. Rev. E 108, 044403 (2023)

3. Memory Devices: We explore new concepts for memory devices such a DNA memory, and also explore emerging device ideas based on resistive memory and phase change memory. Our modeling methods to explore these topics range from ab initio molecular dynamics to kinetic monte carlo simulation to Green’s function methods to simple resistive networks.

Figure 1Figure: Concept of DNA Memory by self assembly. See Performance analysis of DNA crossbar arrays for high-density memory storage applications | Scientific Reports (nature.com)

4. Neuromorphic devices and materials:

We are trying to understand ion intercalation in two-dimensional materials. One of the goals of this effort is to investigate if we can build neuromorphic devices and control switching characteristics. We have just started two projects on this recently, working with a highly interdisciplinary team consisting of collaborators from material science, chemistry, device fabrication and circuits.