MRS Meetings and Events

 

MD02.07.36 2023 MRS Spring Meeting

Database of Computed Properties for Color Center Defects in Silicon

When and Where

Apr 13, 2023
5:00pm - 7:00pm

Moscone West, Level 1, Exhibit Hall

Presenter

Co-Author(s)

Vsevolod Ivanov1,Alexander Ivanov2,Jacopo Simoni1,Prabin Parajuli1,Thomas Schenkel1,Liang Tan1

Lawrence Berkeley National Laboratory1,Brown University2

Abstract

Vsevolod Ivanov1,Alexander Ivanov2,Jacopo Simoni1,Prabin Parajuli1,Thomas Schenkel1,Liang Tan1

Lawrence Berkeley National Laboratory1,Brown University2
Color center defects in silicon are emerging as a promising platform for realizing a number of applications in quantum information science (QIS), including quantum sensing, single-photon sources, and integrated quantum communication between quantum computer nodes. Several well-studied defects such as the G-center, W-center, and T-center, possess some of the necessary attributes for these applications, including narrow linewidths, emission in the telecommunications band, long electron spin coherence times, and coupling between spin and optical degrees of freedom. Despite this, no known defect is perfectly suitable for QIS applications, and in fact different devices can require defects with expressly distinct sets of properties. We report the publication of a searchable online quantum defect database containing the computed properties of over 5000 distinct silicon defect structures. Formation energies, defect energy levels, ground and excited spin states, zero phonon lines, and electric dipole matrix elements are provided for each defect, which are then used to screen for candidate defects with emission within the telecommunications band, non-trivial spin state, and strong optical coupling. Additionally, a machine learning approach is applied to predict defect properties directly from structural data.<br/><br/>This work was supported by the Office of Fusion Energy Sciences and the Molecular Foundry, a DOE Office of Science User Facility, supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231.

Keywords

defects

Symposium Organizers

Soumendu Bagchi, Los Alamos National Laboratory
Huck Beng Chew, The University of Illinois at Urbana-Champaign
Haoran Wang, Utah State University
Jiaxin Zhang, Oak Ridge National Laboratory

Symposium Support

Bronze
Patterns and Matter, Cell Press

Session Chairs

Soumendu Bagchi
Haoran Wang

In this Session

MD02.07.01
Automated Defect Analysis of CdSe Nanoparticles through Supervised Learning with Large Simulated Databases

MD02.07.02
STEM Image Analysis Based on Deep Learning—Identification of Vacancy of Defects and Polymorphs of MoS2

MD02.07.03
Beyond Single Molecules: Intermolecular Interference Effects

MD02.07.04
Insight into the Reactivity of Electrocatalytic Glycerol Oxidation—The Strength of the Hydroxyl Group Bonding on Surface

MD02.07.05
Ripplocation Boundaries and Kink Boundaries in Layered Solids

MD02.07.06
Data-Driven Electrode Optimization for Vanadium Redox Flow Battery by Reduced Order Model

MD02.07.07
Application of Baysian Super Resolution to Spectroscopic Data Analysis

MD02.07.08
A Workflow to Track Time-Resolved Dislocation Behavior in High Temperature Aluminum

MD02.07.09
Investigation of Solidification in Supercooled Water Drops using Large Data Sets of Synchronized Optical Images and X-ray Diffraction Patterns

MD02.07.10
Characterizing Dislocations by formulating the Invisibility Criterion for DFXM

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Publishing Alliance

MRS publishes with Springer Nature