Literature DB >> 27976865

Self-Referenced Smartphone-Based Nanoplasmonic Imaging Platform for Colorimetric Biochemical Sensing.

Xinhao Wang1, Te-Wei Chang1, Guohong Lin1, Manas Ranjan Gartia2, Gang Logan Liu1,3.   

Abstract

Colorimetric sensors usually suffer due to errors from variation in light source intensity, the type of light source, the Bayer filter algorithm, and the sensitivity of the camera to incoming light. Here, we demonstrate a self-referenced portable smartphone-based plasmonic sensing platform integrated with an internal reference sample along with an image processing method to perform colorimetric sensing. Two sensing principles based on unique nanoplasmonics enabled phenomena from a nanostructured plasmonic sensor, named as nanoLCA (nano Lycurgus cup array), were demonstrated here for colorimetric biochemical sensing: liquid refractive index sensing and optical absorbance enhancement sensing. Refractive indices of colorless liquids were measured by simple smartphone imaging and color analysis. Optical absorbance enhancement in the colorimetric biochemical assay was achieved by matching the plasmon resonance wavelength with the chromophore's absorbance peak wavelength. Such a sensing mechanism improved the limit of detection (LoD) by 100 times in a microplate reader format. Compared with a traditional colorimetric assay such as urine testing strips, a smartphone plasmon enhanced colorimetric sensing system provided 30 times improvement in the LoD. The platform was applied for simulated urine testing to precisely identify the samples with higher protein concentration, which showed potential point-of-care and early detection of kidney disease with the smartphone plasmonic resonance sensing system.

Entities:  

Mesh:

Year:  2016        PMID: 27976865     DOI: 10.1021/acs.analchem.6b02484

Source DB:  PubMed          Journal:  Anal Chem        ISSN: 0003-2700            Impact factor:   6.986


  12 in total

1.  Smartphone supported backlight illumination and image acquisition for microfluidic-based point-of-care testing.

Authors:  Gang Chen; Hui Hui Chai; Ling Yu; Can Fang
Journal:  Biomed Opt Express       Date:  2018-09-04       Impact factor: 3.732

2.  Scalable Fabrication of Quasi-One-Dimensional Gold Nanoribbons for Plasmonic Sensing.

Authors:  Chuanzhen Zhao; Xiaobin Xu; Abdul Rahim Ferhan; Naihao Chiang; Joshua A Jackman; Qing Yang; Wenfei Liu; Anne M Andrews; Nam-Joon Cho; Paul S Weiss
Journal:  Nano Lett       Date:  2020-02-13       Impact factor: 11.189

Review 3.  Smartphone-based Surface Plasmon Resonance Sensors: a Review.

Authors:  Gaurav Pal Singh; Neha Sardana
Journal:  Plasmonics       Date:  2022-06-10       Impact factor: 2.726

Review 4.  Recent Progress in Optical Biosensors Based on Smartphone Platforms.

Authors:  Zhaoxin Geng; Xiong Zhang; Zhiyuan Fan; Xiaoqing Lv; Yue Su; Hongda Chen
Journal:  Sensors (Basel)       Date:  2017-10-25       Impact factor: 3.576

5.  An Optical Biosensing Strategy Based on Selective Light Absorption and Wavelength Filtering from Chromogenic Reaction.

Authors:  Hyeong Jin Chun; Yong Duk Han; Yoo Min Park; Ka Ram Kim; Seok Jae Lee; Hyun C Yoon
Journal:  Materials (Basel)       Date:  2018-03-06       Impact factor: 3.623

6.  Recent Patient Health Monitoring Platforms Incorporating Internet of Things-Enabled Smart Devices.

Authors:  Minhee Kang; Eunkyoung Park; Baek Hwan Cho; Kyu-Sung Lee
Journal:  Int Neurourol J       Date:  2018-07-31       Impact factor: 2.835

Review 7.  Surface Plasmon Resonance Optical Sensor: A Review on Light Source Technology.

Authors:  Briliant Adhi Prabowo; Agnes Purwidyantri; Kou-Chen Liu
Journal:  Biosensors (Basel)       Date:  2018-08-26

8.  Robust Smartphone Assisted Biosensing Based on Asymmetric Nanofluidic Grating Interferometry.

Authors:  Foelke Purr; Max-Frederik Eckardt; Jonas Kieserling; Paul-Luis Gronwald; Thomas P Burg; Andreas Dietzel
Journal:  Sensors (Basel)       Date:  2019-05-03       Impact factor: 3.576

9.  Smartphone Biosensor System with Multi-Testing Unit Based on Localized Surface Plasmon Resonance Integrated with Microfluidics Chip.

Authors:  Zhiyuan Fan; Zhaoxin Geng; Weihao Fang; Xiaoqing Lv; Yue Su; Shicai Wang; Hongda Chen
Journal:  Sensors (Basel)       Date:  2020-01-13       Impact factor: 3.576

10.  Applying Machine Learning with Localized Surface Plasmon Resonance Sensors to Detect SARS-CoV-2 Particles.

Authors:  Jiawei Liang; Wei Zhang; Yu Qin; Ying Li; Gang Logan Liu; Wenjun Hu
Journal:  Biosensors (Basel)       Date:  2022-03-13
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