Super-resolution Scanning Electrochemical Microscopy.
Lisa Irene StephensNicholas A PayneJanine MauzerollPublished in: Analytical chemistry (2020)
To achieve super-resolution scanning electrochemical microscopy (SECM), we must overcome the theoretical limitation associated with noncontact electrochemical imaging of surface-generated species. This is the requirement for mass transfer to the electrode, which gives rise to the diffusional broadening of surface features. In this work, a procedure is developed for overcoming this limitation and thus generating "super-resolved" images using point spread function (PSF)-based deconvolution, where the point conductor plays the same role as the point emitter in optical imaging. In contrast to previous efforts in SECM towards this goal, our method uses a finite element model to generate a pair of corresponding blurred and sharp images for PSF estimation, avoiding the need to perform parameter optimization for effective deconvolution. It can therefore be used for retroactive data treatment and an enhanced understanding of the structure-property relationships that SECM provides.
Keyphrases
- high resolution
- label free
- gold nanoparticles
- optical coherence tomography
- finite element
- molecularly imprinted
- ionic liquid
- high speed
- deep learning
- convolutional neural network
- mass spectrometry
- electronic health record
- tandem mass spectrometry
- magnetic resonance
- single molecule
- high throughput
- big data
- magnetic resonance imaging
- minimally invasive
- electron transfer
- machine learning
- single cell
- photodynamic therapy
- contrast enhanced
- solid phase extraction
- artificial intelligence