2024
DOI: 10.1021/acsami.4c01159
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Ultradense Electrochemical Chips with Arrays of Nanostructured Microelectrodes to Enable Sensitive Diffusion-Limited Bioassays

Gabriel J. C. Pimentel,
Lucas B. Ayres,
Juliana N. Y. Costa
et al.

Abstract: Nanostructured microelectrodes (NMEs) are an attractive alternative to yield sensitive bioassays in unprocessed samples. However, although valuable for different applications, nanoporous NMEs usually cannot boost the sensitivity of diffusion-limited analyses because of the enlarged Debye length within the nanopores, which reduces their accessibility. To circumvent this limitation, nanopore-free gold NMEs were electrodeposited from 45 μm SU-8 apertures, featuring nanoridged microspikes on a recessed surface of … Show more

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Cited by 3 publications
(9 citation statements)
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“…As noted in two-electrode cells, a voltage was applied between the WE and QRE fingers while the electrical current between these electrodes was monitored. The currents produced on WE from either [Fe(CN) 6 ] 4– oxidation (CA assays) or [Fe(CN) 6 ] 3–/4– redox quasi-reversible reactions (SWV assays) were followed. , …”
Section: Resultsmentioning
confidence: 99%
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“…As noted in two-electrode cells, a voltage was applied between the WE and QRE fingers while the electrical current between these electrodes was monitored. The currents produced on WE from either [Fe(CN) 6 ] 4– oxidation (CA assays) or [Fe(CN) 6 ] 3–/4– redox quasi-reversible reactions (SWV assays) were followed. , …”
Section: Resultsmentioning
confidence: 99%
“…An additional strategy to obtain microfabricated high-density arrays was recently described by our group. , This method relies on the vertical integration of grid-patterned, two-electrode arrays of Au thin-film fingers onto glass, notably decreasing the number of contact pads and enhancing the integration density. For example, our chip would only require 22 pads to operate 96 cells.…”
mentioning
confidence: 99%
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“…For example, Malkiel et al report a Deep Learning model capable of predicting plasmonic nanostructure geometries that produce optimal responses upon interaction with various biomarkers [ 155 ]. Similarly, machine learning models have been employed in the design of electrodeposited electrochemical sensors [ 156 ].…”
Section: Artificial Intelligence In Biosensingmentioning
confidence: 99%