Connection between the physicochemical characteristics of amorphous carbon thin films and their electrochemical properties
Abstract
Connecting a material's surface chemistry with its electrocatalytic performance is one of the major questions in analytical electrochemistry. This is especially important in many sensor applications where analytes from complex media need to be measured. Unfortunately, today this connection is still largely missing except perhaps for the most simple ideal model systems. Here we present an approach that can be used to obtain insights about this missing connection and apply it to the case of carbon nanomaterials. In this paper we show that by combining advanced computational techniques augmented by machine learning methods with x-ray absorption spectroscopy (XAS) and electrochemical measurements, it is possible to obtain a deeper understanding of the correlation between local surface chemistry and electrochemical performance. As a test case we show how by computationally assessing the growth of amorphous carbon (a-C) thin films at the atomic level, we can create computational structural motifs that may in turn be used to deconvolute the XAS data from the real samples resulting in local chemical information. Then, by carrying out electrochemical measurements on the same samples from which x-ray spectra were measured and that were further characterized computationally, it is possible to gain insight into the interplay between themore »
- Authors:
-
[1]
- Aalto Univ., Espoo (Finland)
- SLAC National Accelerator Lab., Menlo Park, CA (United States). Stanford Synchrotron Radiation Lightsource (SSRL); Univ. of Oulu (Finland)
- Publication Date:
- Research Org.:
- SLAC National Accelerator Laboratory (SLAC), Menlo Park, CA (United States)
- Sponsoring Org.:
- USDOE Office of Science (SC), Basic Energy Sciences (BES); Marie Skłodowska-Curie Grant
- OSTI Identifier:
- 1868905
- Grant/Contract Number:
- AC02-76SF00515; 841621
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Journal of Physics. Condensed Matter
- Additional Journal Information:
- Journal Volume: 33; Journal Issue: 43; Journal ID: ISSN 0953-8984
- Publisher:
- IOP Publishing
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND SUPERFLUIDITY; electrocatalysis; amorphous carbon; x-ray spectroscopy; density functional theory; machine learning
Citation Formats
Leppänen, Elli, Aarva, Anja, Sainio, Sami, Caro, Miguel A., and Laurila, Tomi. Connection between the physicochemical characteristics of amorphous carbon thin films and their electrochemical properties. United States: N. p., 2021.
Web. doi:10.1088/1361-648x/ac1a2e.
Leppänen, Elli, Aarva, Anja, Sainio, Sami, Caro, Miguel A., & Laurila, Tomi. Connection between the physicochemical characteristics of amorphous carbon thin films and their electrochemical properties. United States. https://doi.org/10.1088/1361-648x/ac1a2e
Leppänen, Elli, Aarva, Anja, Sainio, Sami, Caro, Miguel A., and Laurila, Tomi. Wed .
"Connection between the physicochemical characteristics of amorphous carbon thin films and their electrochemical properties". United States. https://doi.org/10.1088/1361-648x/ac1a2e. https://www.osti.gov/servlets/purl/1868905.
@article{osti_1868905,
title = {Connection between the physicochemical characteristics of amorphous carbon thin films and their electrochemical properties},
author = {Leppänen, Elli and Aarva, Anja and Sainio, Sami and Caro, Miguel A. and Laurila, Tomi},
abstractNote = {Connecting a material's surface chemistry with its electrocatalytic performance is one of the major questions in analytical electrochemistry. This is especially important in many sensor applications where analytes from complex media need to be measured. Unfortunately, today this connection is still largely missing except perhaps for the most simple ideal model systems. Here we present an approach that can be used to obtain insights about this missing connection and apply it to the case of carbon nanomaterials. In this paper we show that by combining advanced computational techniques augmented by machine learning methods with x-ray absorption spectroscopy (XAS) and electrochemical measurements, it is possible to obtain a deeper understanding of the correlation between local surface chemistry and electrochemical performance. As a test case we show how by computationally assessing the growth of amorphous carbon (a-C) thin films at the atomic level, we can create computational structural motifs that may in turn be used to deconvolute the XAS data from the real samples resulting in local chemical information. Then, by carrying out electrochemical measurements on the same samples from which x-ray spectra were measured and that were further characterized computationally, it is possible to gain insight into the interplay between the local surface chemistry and electrochemical performance. To demonstrate this methodology, we proceed as follows: after assessing the basic electrochemical properties of a-C films, we investigate the effect of short HNO3 treatment on the sensitivity of these electrodes towards an inner sphere redox probe dopamine to gain knowledge about the influence of altered surface chemistry to observed electrochemical performance. Overall, these results pave the way towards a more general assessment of electrocatalysis in different systems and provide the first steps towards data driven tailoring of electrode surfaces to gain optimal performance in a given application.},
doi = {10.1088/1361-648x/ac1a2e},
journal = {Journal of Physics. Condensed Matter},
number = 43,
volume = 33,
place = {United States},
year = {Wed Aug 18 00:00:00 EDT 2021},
month = {Wed Aug 18 00:00:00 EDT 2021}
}
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