Startseite A review on the synthesis, properties, and applications of Janus nanoparticles
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A review on the synthesis, properties, and applications of Janus nanoparticles

  • Rallabandi Pattabhi Ramaraju , Vissamsetti Jairam , Mohammed Saleem Farhaan , BVS Praveen EMAIL logo , Pachimatla Rajesh und Mechiri Sandeep Kumar
Veröffentlicht/Copyright: 15. August 2025
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Abstract

Janus nanoparticles (JNPs) are distinguished by their dual-faced structure, where each side exhibits distinct physical, chemical, or functional properties. This asymmetry enables JNPs to perform multiple roles simultaneously, making them highly versatile for drug delivery, biosensing, bioimaging, and environmental remediation applications. Synthesis methods such as masking, self-assembly, phase separation, and selective surface modification allow precise control over JNP morphology and functionality, enabling tailored properties like amphiphilic surfaces, magnetic or fluorescent domains, and hybrid compositions. Characterization tools such as SEM, TEM, and XRD mapping are crucial for understanding their structural and compositional attributes, facilitating optimization for specific applications. In biomedicine, JNPs show promise in targeted drug delivery, bioimaging, and theranostics, combining diagnostic and therapeutic capabilities. In environmental engineering, they are effective in water decontamination and removing heavy metals from contaminated water. This review provides a comprehensive overview of synthesis strategies, characterization techniques, applications, and critical analysis of JNPs, highlighting recent advancements and future directions to overcome the challenges.


Corresponding author: BVS Praveen, Department of Chemical Engineering, Chaitanya Bharathi Institute of Technology (CBIT), Hyderabad, 500075, India, E-mail:

  1. Research ethics: Not applicable.

  2. Informed consent: Not applicable.

  3. Author contributions: The author has accepted responsibility for the entire content of this manuscript and approved its submission.

  4. Use of Large Language Models, AI and Machine Learning Tools: None declared.

  5. Conflict of interest: The author states no conflict of interest.

  6. Research funding: None declared.

  7. Data availability: Not applicable.

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Received: 2025-02-27
Accepted: 2025-08-04
Published Online: 2025-08-15

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