Title: Exploration of Electrochemical Reactions at Organic–Inorganic Halide Perovskite Interfaces via Machine Learning in In Situ Time-of-Flight Secondary Ion Mass Spectrometry

Abstract

The instability of hybrid organic–inorganic perovskite (HOIP) devices is one of the significant challenges preventing commercialization. Exploring these phenomena is severely limited by the complexity of the intrinsic electrochemistry of HOIPs, the presence of multiple volatile and mobile ionic species, and the possible role of environmentally induced reactions at surfaces and triple-phase junctions. Here, in situ studies of the electrochemistry of methylammonium lead bromide perovskite with the Au electrode interface are reported via light- and voltage-dependent time-of-flight secondary ion mass spectrometry (ToF-SIMS) imaging of lateral perovskite heterostructures. While ToF-SIMS allows for the visualization of the chemical composition along the surface and its evolution with light and electrical bias, the interpretation of the multidimensional data obtained is often limited due to strong correlations between chemical signatures and the need to track multiple peaks at once. Here, a machine learning workflow combining the Hough transform and non-negative matrix factorization and no-negative tensor decomposition is developed to avoid this limitation and extract salient features of associated chemical changes and to separate the light- and voltage-dependent dynamics. Finally, combining these in situ characterizations and the machine learning workflow provides comprehensive information on the chemical nature of moving species, ion accumulation, and interfacial electrochemical reactionsmore » in HOIP devices.« less

Authors:

Higgins, Kate ^[1]; Lorenz, Matthias  ^[2];

• Search DOE PAGES for author "Lorenz, Matthias"
• Search DOE PAGES for ORCID "0000-0003-0867-8548"

Ziatdinov, Maxim  ^[2];

• Search DOE PAGES for author "Ziatdinov, Maxim"
• Search DOE PAGES for ORCID "0000-0003-2570-4592"

Vasudevan, Rama K.  ^[2];

• Search DOE PAGES for author "Vasudevan, Rama K."
• Search DOE PAGES for ORCID "0000-0003-4692-8579"

Ievlev, Anton  ^[2];

• Search DOE PAGES for author "Ievlev, Anton"
• Search DOE PAGES for ORCID "0000-0003-3645-0508"

Lukosi, Eric D. ^[1]; Ovchinnikova, Olga S.  ^[2];

• Search DOE PAGES for author "Ovchinnikova, Olga S."
• Search DOE PAGES for ORCID "0000-0001-8935-2309"

Kalinin, Sergei V.  ^[2];

• Search DOE PAGES for author "Kalinin, Sergei V."
• Search DOE PAGES for ORCID "0000-0001-5354-6152"

Ahmadi, Mahshid  ^[1]

• Search DOE PAGES for author "Ahmadi, Mahshid"
• Search DOE PAGES for ORCID "0000-0002-3268-7957"

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+ Show Author Affiliations

1. Univ. of Tennessee, Knoxville, TN (United States)
2. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

Publication Date:

Tue Jul 07 00:00:00 EDT 2020

Research Org.:

Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

Sponsoring Org.:

USDOE Office of Science (SC), Basic Energy Sciences (BES)

OSTI Identifier:

1659601

Grant/Contract Number:  

AC05-00OR22725

Resource Type:

Accepted Manuscript

Journal Name:

Advanced Functional Materials

Additional Journal Information:

Journal Volume: 30; Journal Issue: 36; Journal ID: ISSN 1616-301X

Publisher:

Wiley

Country of Publication:

United States

Language:

English

Subject:

36 MATERIALS SCIENCE; electrochemical reaction; ion migration; machine learning; MAPbBr3; perovskite; ToF-SIMS