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Nanoparticle-Based (Bio)Sensors for Biomedical and Environmental Monitoring

This special issue belongs to the section “D:Materials and Processing“.

Special Issue Information

Dear Colleagues,

Nanoparticles have emerged as powerful tools in sensor technology, offering enhanced sensitivity, selectivity, and rapid response times. Their unique physicochemical properties, including high surface area-to-volume ratios and tunable optical, electrical, and chemical characteristics, make them ideal candidates for applications in both biomedical and environmental monitoring.

Nanoparticle-based (Bio)sensors operate by exploiting the unique interactions between nanoparticles and target analytes. These interactions can lead to measurable changes in optical (e.g., fluorescence, surface plasmon resonance), electrical (e.g., conductivity, impedance), or chemical properties.

Nanoparticle-based (bio)sensors include, metallic nanoparticle sensors, quantum dot (QD) sensors, carbon-based nanoparticle sensors, and magnetic nanoparticle sensors.

Their applications in Biomedical Monitoring include the following:

  • Disease Diagnosis: Early detection of diseases such as cancer, diabetes, and neurodegenerative disorders through biomarker sensing;
  • Point-of-Care Testing: Portable diagnostic tools/kits for rapid disease detection in remote locations;
  • Drug Monitoring: Real-time tracking of therapeutic drug levels in patients.

Their applications in Environmental Monitoring include the following:

  • Heavy Metal Detection: Monitoring lead, mercury, and arsenic levels in water bodies;
  • Air Quality Sensing: Detection of volatile organic compounds (VOCs) and greenhouse gases;
  • Pathogen Detection: Identification of bacterial and viral contaminants in water and food sources.

Despite their advantages, nanoparticle-based (bio)sensors face challenges such as stability, reproducibility, and potential toxicity. Future advancements will likely focus on improving biocompatibility, miniaturization for portable devices, and integration not only with mobile phones but also with artificial intelligence for real-time data analysis.

Nanoparticle-based (bio)sensors hold great promise for advancing biomedical diagnostics and environmental safety. Their continued development will enhance the precision, efficiency, and accessibility of monitoring systems, contributing to improved health and sustainability outcomes.

Prof. Dr. Stella Girousi
Guest Editor

Prof. Dr. Dilsat Ozkan-Ariksoysal
Guest Editor Assistant

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Micromachines is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2100 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • nanoparticles
  • electrode modification
  • sensors
  • biomedical monitoring
  • environmental monitoring

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Micromachines - ISSN 2072-666X