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Hassan A, de Sousa DS, Bertaglia T, Crespilho FN. Enhanced label-free detection of proteins on Au nanoparticle micropatterns for surface-enhanced infrared absorption spectroscopy. Chem Commun (Camb) 2024; 60:7212-7215. [PMID: 38910552 DOI: 10.1039/d4cc01320d] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/25/2024]
Abstract
A label-free one-step lithographically masked deposition technique was implemented for the fabrication of gold nanoparticle (Au NP) micropatterns. These micropatterns serve as active substrates for surface-enhanced infrared absorption spectroscopy (SEIRAS) and exhibit a substantial increase in the IR signal upon adsorption of multiple proteins compared to untreated surfaces. Micro-FTIR chemical imaging was conducted to evaluate the efficacy of Au NP micropatterns as singular enhancers for SEIRAS across diverse IR-active substrates demonstrating a promising application for the detection of proteins at low concentrations within biological fluids.
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Affiliation(s)
- Ayaz Hassan
- Interdisciplinary Research Center in Biomedical Materials (IRCBM), COMSATS University Islamabad, Lahore Campus, 1.5 KM defense Road Off Raiwand Road Lahore, Pakistan.
| | - Daniel S de Sousa
- São Carlos Institute of Chemistry, University of São Paulo, São Carlos, SP 13560-970, Brazil.
| | - Thiago Bertaglia
- São Carlos Institute of Chemistry, University of São Paulo, São Carlos, SP 13560-970, Brazil.
| | - Frank N Crespilho
- São Carlos Institute of Chemistry, University of São Paulo, São Carlos, SP 13560-970, Brazil.
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Liu X, Zhang Z, Zhou J, Liu W, Zhou G, Lee C. Artificial Intelligence-Enhanced Waveguide "Photonic Nose"- Augmented Sensing Platform for VOC Gases in Mid-Infrared. SMALL (WEINHEIM AN DER BERGSTRASSE, GERMANY) 2024:e2400035. [PMID: 38576121 DOI: 10.1002/smll.202400035] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/03/2024] [Revised: 03/17/2024] [Indexed: 04/06/2024]
Abstract
On-chip nanophotonic waveguide sensor is a promising solution for miniaturization and label-free detection of gas mixtures utilizing the absorption fingerprints in the mid-infrared (MIR) region. However, the quantitative detection and analysis of organic gas mixtures is still challenging and less reported due to the overlapping of the absorption spectrum. Here,an Artificial-Intelligence (AI) assisted waveguide "Photonic nose" is presented as an augmented sensing platform for gas mixture analysis in MIR. With the subwavelength grating cladding supported waveguide design and the help of machine learning algorithms, the MIR absorption spectrum of the binary organic gas mixture is distinguished from arbitrary mixing ratio and decomposed to the single-component spectra for concentration prediction. As a result, the classification of 93.57% for 19 mixing ratios is realized. In addition, the gas mixture spectrum decomposition and concentration prediction show an average root-mean-square error of 2.44 vol%. The work proves the potential for broader sensing and analytical capabilities of the MIR waveguide platform for multiple organic gas components toward MIR on-chip spectroscopy.
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Affiliation(s)
- Xinmiao Liu
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore, 117583, Singapore
- Center for Intelligent Sensors and MEMS (CISM), National University of Singapore, Singapore, 117608, Singapore
- Department of Mechanical Engineering, National University of Singapore, Singapore, 117575, Singapore
| | - Zixuan Zhang
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore, 117583, Singapore
- Center for Intelligent Sensors and MEMS (CISM), National University of Singapore, Singapore, 117608, Singapore
| | - Jingkai Zhou
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore, 117583, Singapore
- Center for Intelligent Sensors and MEMS (CISM), National University of Singapore, Singapore, 117608, Singapore
| | - Weixin Liu
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore, 117583, Singapore
- Center for Intelligent Sensors and MEMS (CISM), National University of Singapore, Singapore, 117608, Singapore
| | - Guangya Zhou
- Center for Intelligent Sensors and MEMS (CISM), National University of Singapore, Singapore, 117608, Singapore
- Department of Mechanical Engineering, National University of Singapore, Singapore, 117575, Singapore
| | - Chengkuo Lee
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore, 117583, Singapore
- Center for Intelligent Sensors and MEMS (CISM), National University of Singapore, Singapore, 117608, Singapore
- NUS Suzhou Research Institute (NUSRI), Suzhou, Jiangsu, 215123, China
- NUS Graduate School's Integrative Sciences and Engineering Programme (ISEP), National University of Singapore, Singapore, 117583, Singapore
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Song HZ. Editorial of the Special Issue 'Nano-Optics and Nano-Optoelectronics: Challenges and Future Trends'. NANOMATERIALS (BASEL, SWITZERLAND) 2024; 14:169. [PMID: 38251134 PMCID: PMC10819956 DOI: 10.3390/nano14020169] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/18/2023] [Accepted: 12/21/2023] [Indexed: 01/23/2024]
Abstract
Through nano-optics and nano-optoelectronics, we can investigate the characteristics of light at the nanometer scale and the interaction of nanometer-scale objects with light [...].
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Affiliation(s)
- Hai-Zhi Song
- Quantum Research Center, Southwest Institute of Technical Physics, Chengdu 610041, China; ; Tel.: +86-158-2823-9155
- Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu 610054, China
- State Key Laboratory of High Power Semiconductor Lasers, Changchun University of Science and Technology, Changchun 130013, China
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