MRS Meetings and Events

 

EL20.09.03 2023 MRS Fall Meeting

Low-Temperature Liquid Metal Printing for Sustainable Fabrication of 2D Oxide Electronics

When and Where

Nov 30, 2023
10:30am - 10:45am

Hynes, Level 3, Room 301

Presenter

Co-Author(s)

William Scheideler1,Andrew Hamlin1,Simon Agnew1

Dartmouth College1

Abstract

William Scheideler1,Andrew Hamlin1,Simon Agnew1

Dartmouth College1
Low-thermal budget fabrication of metal oxide semiconductors could unlock these materials’ potential for emerging applications in sensing, computing, and memory devices via 3D heterogeneous integration with CMOS electronics. Towards that goal, we present a low-temperature, energy-efficient approach to deposit high performance two-dimensional (2D) metal oxides and heterostructures. Our approach consists of continuous liquid metal printing (CLMP) driven by Cabrera-Mott oxidation of liquid metal alloys, for depositing of 2D oxide layers as thin as 1 nm and multilayers 10’s of nm. The simplicity of this vacuum-free CLMP process mitigates the need for high capital expenditure equipment and eliminates use of toxic gases. Metal oxidation is thermodynamically favorable, allowing rapid growth kinetics at the millisecond time-scale for wafer scale deposition in less than 2 seconds at temperatures from 200 °C down to 120 °C for back-end-of line (BEOL) applications as well as flexible electronics.<br/>We present a study of the physics of liquid metal printing of 2D binary and ternary oxides based on alloys of In, Ga, Zn, and Sn by utilizing rapid film thickness measurements based on spectroscopic reflectometry. We investigate the limits of printing speed and model the influence of speed and print temperature on 2D oxide growth kinetics and crystallinity as determined from XRD. Finally, we apply CLMP to assemble heterostructures with 1 nm-level precision for enhancing modulation doping at 2D oxide interfaces, resulting in exceptionally conductive (&gt; 500 S/cm) printed conductive oxide layers.

Keywords

2D materials | electrical properties

Symposium Organizers

Gina Adam, George Washington University
Sayani Majumdar, Tampere University
Radu Sporea, University of Surrey
Yiyang Li, University of Michigan

Symposium Support

Bronze
APL Machine Learning | AIP Publishing

Publishing Alliance

MRS publishes with Springer Nature