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Detailed Characterization of a Fully Additive Covalent Bonded PCB Manufacturing Process (SBU-CBM Method). Processes (Basel) 2022. [DOI: 10.3390/pr10040636] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
To bridge the technology gap between IC-level and board-level fabrications, a fully additive selective metallization has already been demonstrated in the literature. In this article, the surface characterization of each step involved in the fabrication process is outlined with bulk metallization of the surface. This production technique has used polyurethane as epoxy resin and proprietary grafting chemistry to functionalize the surface with covalent bonds on an FR-4 base substrate. The surface was then metalized using an electroless copper (Cu) bath. This sequential growth of layers on top of each other using an actinic laser beam and palladium (Pd) ions to deposit Cu is analyzed. State-of-the-art material characterization techniques were employed to investigate process mechanism at the interfaces. Density functional theory calculations were performed to validate the experimental evidence of covalent bonding of the layers. This manufacturing approach is capable of adding metallic layers in a selective manner to the printed circuit boards at considerably lower temperatures. A complete analysis of the process using bulk deposition of the materials is illustrated in this work.
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Tripathy S, Supraja P, Mohanty S, Sai VM, Agrawal T, Chowdary CG, Taranikanti M, Bandaru R, Mudunuru AK, Tadi LJ, Suravaram S, Siddiqui IA, Maddur S, Guntuka RK, Singh R, Singh V, Singh SG. Artificial Intelligence-Based Portable Bioelectronics Platform for SARS-CoV-2 Diagnosis with Multi-nucleotide Probe Assay for Clinical Decisions. Anal Chem 2021; 93:14955-14965. [PMID: 34694783 DOI: 10.1021/acs.analchem.1c01650] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
In the context of the recent pandemic, the necessity of inexpensive and easily accessible rapid-test kits is well understood and need not be stressed further. In light of this, we report a multi-nucleotide probe-based diagnosis of SARS-CoV-2 using a bioelectronics platform, comprising low-cost chemiresistive biochips, a portable electronic readout, and an Android application for data acquisition with machine-learning-based decision making. The platform performs the desired diagnosis from standard nasopharyngeal and/or oral swabs (both on extracted and non-extracted RNA samples) without amplifying the viral load. Being a reverse transcription polymerase chain reaction-free hybridization assay, the proposed approach offers inexpensive, fast (time-to-result: ≤ 30 min), and early diagnosis, as opposed to most of the existing SARS-CoV-2 diagnosis protocols recommended by the WHO. For the extracted RNA samples, the assay accounts for 87 and 95.2% test accuracies, using a heuristic approach and a machine-learning-based classification method, respectively. In case of the non-extracted RNA samples, 95.6% decision accuracy is achieved using the heuristic approach, with the machine-learning-based best-fit model producing 100% accuracy. Furthermore, the availability of the handheld readout and the Android application-based simple user interface facilitates easy accessibility and portable applications. Besides, by eliminating viral RNA extraction from samples as a pre-requisite for specific detection, the proposed approach presents itself as an ideal candidate for point-of-care SARS-CoV-2 diagnosis.
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Affiliation(s)
- Suryasnata Tripathy
- Indian Institute of Technology Hyderabad, Kandi, Sangareddy, Telangana 502285, India
| | - Patta Supraja
- Indian Institute of Technology Hyderabad, Kandi, Sangareddy, Telangana 502285, India
| | - Swati Mohanty
- Indian Institute of Technology Hyderabad, Kandi, Sangareddy, Telangana 502285, India
| | - Vallepu Mohan Sai
- Indian Institute of Technology Hyderabad, Kandi, Sangareddy, Telangana 502285, India
| | - Tushant Agrawal
- Indian Institute of Technology Hyderabad, Kandi, Sangareddy, Telangana 502285, India
| | | | - Madhuri Taranikanti
- All India Institute of Medical Sciences, Bibinagar, Hyderabad, Telangana 508126, India
| | - Rajiv Bandaru
- ESIC Medical College, S R Nagar, Hyderabad, Telangana 500038, India
| | | | - Lakshmi Jyothi Tadi
- All India Institute of Medical Sciences, Bibinagar, Hyderabad, Telangana 508126, India.,ESIC Medical College, S R Nagar, Hyderabad, Telangana 500038, India
| | - Swathi Suravaram
- ESIC Medical College, S R Nagar, Hyderabad, Telangana 500038, India
| | | | - Srinivas Maddur
- ESIC Medical College, S R Nagar, Hyderabad, Telangana 500038, India
| | | | - Ranjana Singh
- Indian Institute of Technology Hyderabad, Kandi, Sangareddy, Telangana 502285, India
| | - Vikrant Singh
- School of Medicine, University of California, 1 Shields Avenue, Davis, California 95616, United States
| | - Shiv Govind Singh
- Indian Institute of Technology Hyderabad, Kandi, Sangareddy, Telangana 502285, India
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