Photonics Research, Volume. 13, Issue 2, 541(2025)

Low-cost prototype for real-time analysis using liquid crystal optical sensors in water quality assessment

M. Simone Soares1,2、†, Francisco Gameiro1、†, Jan Nedoma3, Nuno Santos2, Pedro L. Almeida4,5, and Carlos Marques1,6、*
Author Affiliations
  • 1CICECO - Aveiro Institute of Materials & Physics Department, University of Aveiro, Aveiro, Portugal
  • 2I3N & Physics Department, University of Aveiro, Aveiro, Portugal
  • 3Department of Telecommunications, VSB - Technical University of Ostrava, Ostrava, Czech Republic
  • 4I3N - CENIMAT, School of Sciences and Technology, NOVA University of Lisbon, Lisbon, Portugal
  • 5UnIRE, ISEL, Polytechnic University of Lisbon, Lisbon, Portugal
  • 6Department of Physics, VSB - Technical University of Ostrava, Ostrava, Czech Republic
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    Figures & Tables(15)
    Diagram representing the working principle of the LC-based sensors.
    The process of functionalizing the glass slides is represented in this diagram, where every step before glueing is represented [15].
    Diagram of the polarized optical microscope configuration.
    Finalized prototype, with the components fitted in an encasing.
    3D model of the final version encasing for the setup: (a) complete box with lid; (b) light source section, with LED slot; (c) lens section of the box; and (d) sensor support.
    (left) Representation of the frame alignment relative to the support. (right) Image captured by positioning the lens at an optimal distance, for an E. coli sensor with a concentration of 2.69×103 CFU/mL.
    Region of detection for an E. coli biosensor with a concentration of 3.84 CFU/mL and a width of 6.4 mm: (a) without and (b) with the width adjustment.
    Fit for the selected batch of E. coli biosensors, for the concentration with the percentage of colored pixels. The X axis is on a logarithmic scale.
    Detection of the sensors for (a) E. coli ATTC35218 (E8); (b) Bacillus (O26); and (c) Acinetobacter (D6).
    Bar graph for the average percentage for Bacillus (O26), Acinetobacter (D6), and E. coli (E8).
    (a) Portion of the 3D-printed box design to let sunlight reach the sample. (b) Equipment used to conduct the testing outdoors.
    Graph displaying the percentage of colored pixels detected at 8:30 and 13:30 concerning the box’s angle of inclination.
    Example of the analysis with the GUI. (a) Lower concentration E. coli sensor (2.12×10−1 CFU/mL, corresponding to 36.55%). (b) Control sensor. (c) Higher concentration E. coli sensor (4.20×108 CFU/mL).
    • Table 1. Percentage of Colored Pixels for Each Possible Orientation

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      Table 1. Percentage of Colored Pixels for Each Possible Orientation

      Orientation1234
      E. coli percentage (%)47.55±0.0747.19±0.0546.69±0.0846.78±0.44
    • Table 2. Change in the Measured Percentage of Colored Pixels for a Time Window of 1 Montha

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      Table 2. Change in the Measured Percentage of Colored Pixels for a Time Window of 1 Montha

      SensorConcentration (CFU/mL)Change in Detection (%)
      E13.8413.40±11.72
      E33.84×1037.20±5.77
      E63.84×1062.02±0.77
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    M. Simone Soares, Francisco Gameiro, Jan Nedoma, Nuno Santos, Pedro L. Almeida, Carlos Marques, "Low-cost prototype for real-time analysis using liquid crystal optical sensors in water quality assessment," Photonics Res. 13, 541 (2025)

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    Paper Information

    Category: Surface Optics and Plasmonics

    Received: Oct. 3, 2024

    Accepted: Dec. 4, 2024

    Published Online: Feb. 10, 2025

    The Author Email: Carlos Marques (carlos.marques@ua.pt)

    DOI:10.1364/PRJ.543957

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