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The multi-channel potentiostat: Development and evaluation of a scalable mini-potentiostat array for investigating electrochemical reaction mechanisms.

ABSTRACT: A potentiostat is an essential piece of analytical equipment for studying electrochemical devices and reactions. As the design of electrochemical devices evolve, applications for systems with multiple working electrodes have become more common. These applications drive a need for low-cost multi-channel potentiostat systems. We have developed a portable, low-cost and scalable system with a modular design that can support 8 to 64 channels at a cost as low as $8 per channel. This design can replace the functionality of commercial potentiostats which cost upwards of $10k for certain applications. Each channel in the multi-channel potentiostat has an independent adjustable voltage source with a built-in ammeter and switch, making the device flexible for various configurations. The multi-channel potentiostat is designed for low current applications (nA range), but its purpose can change by varying its shunt resistor value. The system can either function as a standalone device or remotely controlled. We demonstrate the functionality of this system for the control of a 24-channel bioelectronic ion pump for open- and closed- loop control of pH.

SUBMITTER: Pansodtee P

PROVIDER: S-EPMC8445456 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

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The multi-channel potentiostat: Development and evaluation of a scalable mini-potentiostat array for investigating electrochemical reaction mechanisms.

Pansodtee Pattawong P Selberg John J Jia Manping M Jafari Mohammad M Dechiraju Harika H Thomsen Thomas T Gomez Marcella M Rolandi Marco M Teodorescu Mircea M

PloS one 20210916 9

A potentiostat is an essential piece of analytical equipment for studying electrochemical devices and reactions. As the design of electrochemical devices evolve, applications for systems with multiple working electrodes have become more common. These applications drive a need for low-cost multi-channel potentiostat systems. We have developed a portable, low-cost and scalable system with a modular design that can support 8 to 64 channels at a cost as low as $8 per channel. This design can replace ...[more]

PMID: 34529717

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Project description:Analysis of compound-protein interactions (CPIs) has become a crucial prerequisite for drug discovery and drug repositioning. In vitro experiments are commonly used in identifying CPIs, but it is not feasible to discover the molecular and proteomic space only through experimental approaches. Machine learning's advances in predicting CPIs have made significant contributions to drug discovery. Deep neural networks (DNNs), which have recently been applied to predict CPIs, performed better than other shallow classifiers. However, such techniques commonly require a considerable volume of dense data for each training target. Although the number of publicly available CPI data has grown rapidly, public data is still sparse and has a large number of measurement errors. In this paper, we propose a novel method, Multi-channel PINN, to fully utilize sparse data in terms of representation learning. With representation learning, Multi-channel PINN can utilize three approaches of DNNs which are a classifier, a feature extractor, and an end-to-end learner. Multi-channel PINN can be fed with both low and high levels of representations and incorporates each of them by utilizing all approaches within a single model. To fully utilize sparse public data, we additionally explore the potential of transferring representations from training tasks to test tasks. As a proof of concept, Multi-channel PINN was evaluated on fifteen combinations of feature pairs to investigate how they affect the performance in terms of highest performance, initial performance, and convergence speed. The experimental results obtained indicate that the multi-channel models using protein features performed better than single-channel models or multi-channel models using compound features. Therefore, Multi-channel PINN can be advantageous when used with appropriate representations. Additionally, we pretrained models on a training task then finetuned them on a test task to figure out whether Multi-channel PINN can capture general representations for compounds and proteins. We found that there were significant differences in performance between pretrained models and non-pretrained models.

Project description:A novel multi-channel poly(methyl methacrylate) (PMMA) microfluidic biosensor with interdigitated ultramicroelectrode arrays (IDUAs) for electrochemical detection was developed. The focus of the development was a simple fabrication procedure and the realization of a reliable large IDUA that can provide detection simultaneously to several microchannels. As proof of concept, five microchannels are positioned over a large single IDUA where the channels are parallel with the length of the electrode finger. The IDUAs were fabricated on the PMMA cover piece and bonded to a PMMA substrate containing the microfluidic channels using UV/ozone-assisted thermal bonding. Conditions of device fabrication were optimized realizing a rugged large IDUA within a bonded PMMA device. Gold adhesion to the PMMA, protective coatings, and pressure during bonding were optimized. Its electrochemical performance was studied using amperometric detection of potassium ferri and ferro hexacyanide. Cumulative signals within the same chip showed very good linearity over a range of 0-38 μM (R(2) = 0.98) and a limit of detection of 3.48 μM. The bonding of the device was optimized so that no cross talk between the channels was observed which otherwise would have resulted in unreliable electrochemical responses. The highly reproducible signals achieved were comparable to those obtained with separate single-channel devices. Subsequently, the multi-channel microfluidic chip was applied to a model bioanalytical detection strategy, i.e., the quantification of specific nucleic acid sequences using a sandwich approach. Here, probe-coated paramagnetic beads and probe-tagged liposomes entrapping ferri/ferro hexacyanide as the redox marker were used to bind to a single-stranded DNA sequence. Flow rates of the non-ionic detergent n-octyl-β-D-glucopyranoside for liposome lysis were optimized, and the detection of the target sequences was carried out coulometrically within 250 s and with a limit of detection of 12.5 μM. The robustness of the design and the reliability of the results obtained in comparison to previously published single-channel designs suggest that the multi-channel device offers an excellent opportunity for bioanalytical applications that require multianalyte detection and high-throughput assays.

Dataset Information

The multi-channel potentiostat: Development and evaluation of a scalable mini-potentiostat array for investigating electrochemical reaction mechanisms.

Publications

The multi-channel potentiostat: Development and evaluation of a scalable mini-potentiostat array for investigating electrochemical reaction mechanisms.

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