Towards the application of fast Fourier transform - scanning electrochemical impedance microscopy (FFT-SEIM)

Valiūnienė, Aušra; Sabirovas, Tomas; Petroniene, Jurate; Ramanavičius, Arūnas

doi:10.1016/j.jelechem.2020.114067

Cited by 16 publications

(3 citation statements)

References 51 publications

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“…To reduce the duration of the measurements, the SEIM technique was hybridized with Fast-Fourier Transform based EIS (FFT-EIS) which makes it possible to simultaneously measure up to 50 single sine-signals. The resulting non-faradaic FFT-SEIM application is used in the field of bio-electrochemistry for in-situ and operando evaluation of electrochemical processes (Morkvenaite-Vilkonciene et al, 2017;Vali unienė et al, 2020).…”

Section: Scanning Probe Microscopymentioning

confidence: 99%

Scanning Probe Microscopy Facility for Operando Study of Redox Processes on Lithium ion Battery Electrodes

Legerstee¹,

Boekel

Boonstra

et al. 2021

Front. Chem.

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An Atomic Force Microscope (AFM) is combined with a special designed glovebox system and coupled to a Galvanostat/Potentiostat to allow measurements on electrochemical properties for battery research. An open cell design with electrical contacts makes it possible to reach the electrode surface with the cantilever so as to perform measurements during battery operation. A combined AFM-Scanning Electro-Chemical Microscopy (AFM-SECM) approach makes it possible to simultaneously obtain topological information and electrochemical activity. Several methods have been explored to provide the probe tip with an amount of lithium so that it can be used as an active element in a measurement. The “wet methods” that use liquid electrolyte appear to have significant drawbacks compared to dry methods, in which no electrolyte is used. Two dry methods were found to be best applicable, with one method applying metallic lithium to the tip and the second method forming an alloy with the silicon of the tip. The amount of lithium applied to the tip was measured by determining the shift of the resonance frequency which makes it possible to follow the lithiation process. A FEM-based probe model has been used to simulate this shift due to mass change. The AFM-Galvanostat/Potentiostat set-up is used to perform electrochemical measurements. Initial measurements with lithiated probes show that we are able to follow ion currents between tip and sample and perform an electrochemical impedance analysis in absence of an interfering Redox-probe. The active probe method developed in this way can be extended to techniques in which AFM measurements can be combined with mapping electrochemical processes with a spatial resolution.

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Section: Scanning Probe Microscopymentioning

confidence: 99%

Scanning Probe Microscopy Facility for Operando Study of Redox Processes on Lithium ion Battery Electrodes

Legerstee¹,

Boekel

Boonstra

et al. 2021

Front. Chem.

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“…We first conduct a pre-training task for feature representation, adopting the feature of rotation and frequency domain, which can enlarge the data capacity to 2-5 times of the original data. The frequency spectrum describes the frequency structure of the signals and the relationship between the frequency and the amplitude of frequency signals, so we use the Fourier transform [26] to calculate the frequency characteristics of the signal. The features in the frequency domain and rotation are fed into a four-layer CNN for supervised training by using new added labels.…”

Section: The Self-supervised Sleep Recognition Modelmentioning

confidence: 99%

Self-Supervised Learning From Multi-Sensor Data for Sleep Recognition

2020

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Sleep recognition refers to detection or identification of sleep posture, state or stage, which can provide critical information for the diagnosis of sleep diseases. Most of sleep recognition methods are limited to single-task recognition, which only involves single-modal sleep data, and there is no generalized model for multi-task recognition on multi-sensor sleep data. Moreover, the shortage and imbalance of sleep samples also limits the expansion of the existing machine learning methods like support vector machine, decision tree and convolutional neural network, which lead to the decline of the learning ability and overfitting. Self-supervised learning technologies have shown their capabilities to learn significant feature representations. In this paper, a novel self-supervised learning model is proposed for sleep recognition, which is composed of an upstream self-supervised pre-training task and a downstream recognition task. The upstream task is conducted to increase the data capacity, and the information of frequency domain and the rotation view are used to learn the multi-dimensional sleep feature representations. The downstream task is undertaken to fuse bidirectional long-short term memory and conditional random field as the sequential data recognizer to produce the sleep labels. Our experiments shows that our proposed algorithm provide promising results in sleep identification and can further be applied in clinical and smart home environments as a diagnostic tool. The source code is provided at: ''https://github.com/zhaoaite/SSRM ''.

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“…Existing studies clearly suggest that SECCM has the ability to perform full-scale DC electrochemical polarization to extract localized kinetic properties to pinpoint the origin of corrosion in heterogeneous surfaces. , In fact, the application of SECCM to study corrosion has been explored by Unwin et al However, AC electrochemical polarization such as EIS is less explored using SECCM probes but has an immense potential to enable understanding of the interfacial changes between the metal and electrolyte. , Previously, a combination of SECM and EIS was used to study the surface-dependent electrochemical properties and elucidate the redox and reactive kinetics at the interfaces. − Ramanavicius et al developed a new approach combining SECM with fast Fourier transform EIS (FFT-EIS) to evaluate the interface with slower diffusion kinetics or lower surface area, which has an important application in the biomedical field. − Therefore, it is clear that EIS can be a valuable tool to characterize the changes in charge-transfer resistance due to surface oxidation, for example during the corrosion of two conjoined metals. Herein, we combined conventional SECCM with EIS to develop scanning electrochemical cell impedance microscopy (SECCIM) to deconvolute charge transfer, adsorption, and emergence of resistive oxide films during surface corrosion.…”

Section: Introductionmentioning

confidence: 99%

Understanding Localized Corrosion on Metal Surfaces Using Scanning Electrochemical Cell Impedance Microscopy (SECCIM)

et al. 2022

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Understanding the electrochemical properties at a localized scale is critically important to comprehend the origin of corrosion and develop multifunctional materials with robust corrosion resistance, particularly at conjoined metal interfaces typically encountered in automobile manufacturing. Scanning electrochemical cell microscopy (SECCM) is an emerging technique which enables to study the corrosion of metal surfaces to be visualized at the microscopic level. In this work, we developed scanning electrochemical cell impedance microscopy (SECCIM) by combining SECCM with electrochemical impedance spectroscopy (EIS) and explored the unique advantages of using SECCIM to measure the corrosion kinetics on single-crystal Mg (0001) as the model surface using direct current and alternating current polarization techniques. Specifically, a theta capillary with a tip diameter of 10 μm filled with a 0.01 M NaCl electrolyte was used as a probe to perform spatially resolved potentiodynamic Tafel polarization and EIS. The combination of traditional SECCM with EIS led to the development of SECCIM and enabled us to study small interfacial events such as charge transfer, adsorption, and emergence of resistive oxide films on the surface using the distribution of relaxation time analysis. Furthermore, by comparing localized SECCIM measurements with bulk electrochemical measurements, we establish the reliability of SECCIM for the mapping of corrosion potential and associated charge-transfer resistance on the Mg (0001) surface. Our results indicate that SECCIM measurement with Tafel and EIS analysis will provide an unparalleled ability to characterize the pitting corrosion mechanism on the heterogeneous surface of mixed-metal alloys and metal joints.

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Towards the application of fast Fourier transform - scanning electrochemical impedance microscopy (FFT-SEIM)

Cited by 16 publications

References 51 publications

Scanning Probe Microscopy Facility for Operando Study of Redox Processes on Lithium ion Battery Electrodes

Scanning Probe Microscopy Facility for Operando Study of Redox Processes on Lithium ion Battery Electrodes

Self-Supervised Learning From Multi-Sensor Data for Sleep Recognition

Understanding Localized Corrosion on Metal Surfaces Using Scanning Electrochemical Cell Impedance Microscopy (SECCIM)

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