Programmable Soft-Matter Electronics

Ivanov, Artemii S.; Nikolaev, Konstantin G.; Novikov, Alexander S.; Yurchenko, Stanislav O.; Novoselov, Kostya S.; Andreeva, Daria V.; Skorb, Ekaterina V.

doi:10.1021/acs.jpclett.1c00007

Cited by 19 publications

(19 citation statements)

References 35 publications

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“…In addition, the function of the system could be expanded to have the ability of powder particle size invariance and powder color invariance. In the future, other approaches may also be applied to the identification of foreign matter, such as machine learning [31] and Hirshfeld surface analysis [32].…”

Section: Discussionmentioning

confidence: 99%

An Automatic Foreign Matter Detection and Sorting System for PVC Powder

et al. 2022

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In the present study, an automatic defect detection system has been assembled and introduced for Polyvinyl chloride (PVC) powder. The average diameter for PVC powder is approximately 100 μm. The system hardware includes a powder delivery device, a sieving device, a circular platform, an image capture device, and a recycling device. A defect detection algorithm based on YOLOv4 was developed using CSPDarkNet53 as the backbone for feature extraction, spatial pyramid pooling (SPP) and path aggregation network (PAN) as the neck, and Yoloblock as the head. An auto-annotation algorithm was developed based on a digital image processing algorithm to save time in feature engineering. Several hyper-parameters have been employed to improve the efficiency of detection in the process of training YOLOv4. The Taguchi method was utilized to optimize the performance of detection, in which the mean average precision (mAP) is the response. Results show that our optimized YOLOv4 has a test mAP of 0.9385, compared to 0.8653 and 0.7999 for naïve YOLOv4 and Faster RCNN, respectively. Additionally, with the optimized YOLOv4, there is no false alarm for images without any foreign matter.

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Section: Discussionmentioning

confidence: 99%

An Automatic Foreign Matter Detection and Sorting System for PVC Powder

et al. 2022

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Section: Hydrogelsmentioning

confidence: 99%

Recent Progress of Layer‐by‐layer Assembly, Free‐Standing Film and Hydrogel Based on Polyelectrolytes

Ivanov

Pershina

Nikolaev

et al. 2021

Macromolecular Bioscience

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Nowadays, polyelectrolytes play an essential role in the development of new materials. Their use allows creating new properties of materials and surfaces and vary them in a wide range. Basically, modern methods are divided into three areas—the process of layer‐by‐layer deposition, free‐standing films, and hydrogels based on polyelectrolytes. Layer‐by‐layer assembly of polyelectrolytes on various surfaces is a powerful technique. It allows giving surfaces new properties, for example, protect them from corrosion. Free‐standing films are essential tools for the design of membranes and sensors. Hydrogels based on polyelectrolytes have recently shown their applicability in electrical and materials science. The creation of new materials and components with controlled properties can be achieved using polyelectrolytes. This review focuses on new technologies that have been developed with polyelectrolytes over the last five years.

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“…Hydrogels are increasingly used in various fields: flexible electronics, , sensing, − wound dressing, , and energy saving. , Soft biomimetic interfaces involving hydrogels and liquid metals and alloys play an important role in gaining more and more information about various complex biosystems. Among all complex biosystems, the potential of the “good” microbiome is of greatest interest .…”

Section: Introductionmentioning

confidence: 99%

“…However, its detection rates are still low compared to traditional methods . There are hydrogel-based systems that are used to detect various biological molecules . This technique has already proven itself well as a selective analysis for the tick-borne encephalitis virus .…”

Section: Introductionmentioning

confidence: 99%

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Soft Hydrogel Actuator for Fast Machine-Learning-Assisted Bacteria Detection

Lavrentev

Rumyantsev

Ivanov

et al. 2022

ACS Appl. Mater. Interfaces

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We demonstrate that our bio-electrochemical platform facilitates the reduction of detection time from the 3-day period of the existing tests to 15 min. Machine learning and robotized bioanalytical platforms require the principles such as hydrogel-based actuators for fast and easy analysis of bioactive analytes. Bacteria are fragile and environmentally sensitive microorganisms that require a special environment to support their lifecycles during analytical tests. Here, we develop a bio-electrochemical platform based on the soft hydrogel/eutectic gallium–indium alloy interface for the detection of Streptococcus thermophilus and Bacillus coagulans bacteria in various mediums. The soft hydrogel-based device is capable to support bacteria’ viability during detection time. Current–voltage data are used for multilayer perceptron algorithm training. The multilayer perceptron model is capable of detecting bacterial concentrations in the 104 to 108 cfu/mL range of the culture medium or in the dairy products with high accuracy (94%). Such a fast and easy biodetection is extremely important for food and agriculture industries and biomedical and environmental science.

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Programmable Soft-Matter Electronics

Cited by 19 publications

References 35 publications

An Automatic Foreign Matter Detection and Sorting System for PVC Powder

An Automatic Foreign Matter Detection and Sorting System for PVC Powder

Recent Progress of Layer‐by‐layer Assembly, Free‐Standing Film and Hydrogel Based on Polyelectrolytes

Soft Hydrogel Actuator for Fast Machine-Learning-Assisted Bacteria Detection

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