Posted in | News | Nanomaterials

Nanotechnology and AI Partner to Create Smart Anticounterfeiting Tags

In a study published in the journal ACS Applied Materials & Interfaces, a mix of chemistry, nanomaterials, and artificial intelligence (AI) was used to produce a straightforward yet cryptographic anticounterfeiting measure.

Nanotechnology and AI Partner to Create Smart Anticounterfeiting Tags​​​​​​​

​​​​​​​Study: Nanocatalyst-Enabled Physically Unclonable Functions as Smart Anticounterfeiting Tags with AI-Aided Smartphone Authentication. Image Credit: Cavan-Images/Shutterstock.com

The Need for Effective Anticounterfeiting Techniques

The requirement for robust anti-counterfeit solutions is driving scholarly and corporate research to enhance the authenticity and safety of products. The spread of counterfeit commodities is a huge nuisance all over the globe, particularly in the retail and pharmaceutical industries. Fake pharma goods endanger patients and compromise public health, resulting in high economic and social costs for developed as well as developing nations.

To put the magnitude of the issue into perspective, counterfeit medications for treatments of pneumonia and malaria kill roughly 250,000 children annually. Such a significant problem necessitates a serious technical effort to develop powerful anti-counterfeit technologies that are also consistent with market constraints.

Numerous substances and chemical procedures have been suggested as biometric markers. These vary from intricate ink compositions utilized in currency notes to luminous upconverting nano-phosphorous tags, inkjet printable conjugate polymeric platforms, or molecular identifiers like peptides, DNA, and polymers that promise large encoding potentials and secrecy.

These technologies, however, may be cloneable. Moreover, they often need costly hardware and highly skilled workers, restricting their practical uses.

Nanotechnology can Improve PUFs

A highly sophisticated anti-counterfeit technique was provided in this system using physically unclonable functions (PUFs) that are predicated on distinct markers created by chemical procedures in a stochastic mechanism. The unpredictability created by the non-deterministic technique assures that replicating the PUF key is just about impossible whenever the PUF sequence is digitized and saved.

If there are not enough distinct markers to secure a significant number of objects, PUFs' encoding capability may be restricted. Owing to the unpredictability and huge parametric space provided by nanostructures paired with physiochemical procedures, this problem may be solved if PUFs are created using methods based on nanotechnology that provide a significant encoding potential which translates to a large quantity of distinct markers.

Critical Aspects of PUFs

The distinguishing physical trait is often a randomized two-dimensional or three-dimensional pattern, leading to various visual readings. Certain nanotechnology-based PUFs, like glass microbead randomized speckle patterning, inkjet-printed unclonable quantum dot (QD) fluorescent tags, and Au nanoparticle (NP) or Ag nanowire (NW) randomized patterns have lately been described.

Tag reading is crucial because several approaches depend on intricate hardware for verification, like dark-field, fluorescent, or electron microscopy, limiting their applicability for the overall supply chain needs, like mobility, quickness, repeatability, and reduced price of the procedure.

Salient Features of the Study

The technique suggested in this study aimed to achieve all of the aforementioned desirable characteristics, delivering an adequate anti-counterfeit approach via a rapid (1 minute), reversible, and equipment-free colorimetry reading facilitated by nanoscale Pt catalysts, which would be usable at any juncture of the supply network, even the end user.

Owing to the creation of a dependable AI method for quick and reliable visual marker authentication on the basis of Deep Learning and Computer Vision approaches, this nanotechnology-facilitated system may be readily encoded and then authorized via a cellphone.

Key Takeaways

In this study, the team demonstrated the possibility of merging chemistry, nanotechnology, and artificial intelligence to build novel cross-discipline techniques aimed at addressing critical sustainability and security challenges.

A sophisticated reversible PUF marker was presented that combined the achievement of distinct patterning with substantial encryption capabilities with a visual colorimetry reading perceptible by the human eye and analyzable using a cellphone.

The approach adopted by the team provided great ease in authenticating (i.e., equipment-free visual reading) as well as cutting-edge encryption capabilities by using the catalytic characteristics of nanoparticles. The suggested technique may be improved by creating various stochastic patterns and platforms, resulting in even greater security levels.

The ability to achieve repeated verification cycles in ambient settings, owing to the rapid (ON/OFF) color emergence/fading system evoked by the nanoscale platinum catalysts, opens up fresh avenues for in-situ analyses of potential counterfeits of high-quality goods throughout the entire supply network, from quality control after production to individual evaluation by the end-user.

Reference

Moglianetti, M., Pedone, D. et al. (2022). Nanocatalyst-Enabled Physically Unclonable Functions as Smart Anticounterfeiting Tags with AI-Aided Smartphone Authentication. ACS Applied Materials & Interfaces. https://pubs.acs.org/doi/10.1021/acsami.2c02995

Disclaimer: The views expressed here are those of the author expressed in their private capacity and do not necessarily represent the views of AZoM.com Limited T/A AZoNetwork the owner and operator of this website. This disclaimer forms part of the Terms and conditions of use of this website.

Shaheer Rehan

Written by

Shaheer Rehan

Shaheer is a graduate of Aerospace Engineering from the Institute of Space Technology, Islamabad. He has carried out research on a wide range of subjects including Aerospace Instruments and Sensors, Computational Dynamics, Aerospace Structures and Materials, Optimization Techniques, Robotics, and Clean Energy. He has been working as a freelance consultant in Aerospace Engineering for the past year. Technical Writing has always been a strong suit of Shaheer's. He has excelled at whatever he has attempted, from winning accolades on the international stage in match competitions to winning local writing competitions. Shaheer loves cars. From following Formula 1 and reading up on automotive journalism to racing in go-karts himself, his life revolves around cars. He is passionate about his sports and makes sure to always spare time for them. Squash, football, cricket, tennis, and racing are the hobbies he loves to spend his time in.

Citations

Please use one of the following formats to cite this article in your essay, paper or report:

  • APA

    Rehan, Shaheer. (2022, May 27). Nanotechnology and AI Partner to Create Smart Anticounterfeiting Tags. AZoNano. Retrieved on November 22, 2024 from https://www.azonano.com/news.aspx?newsID=39195.

  • MLA

    Rehan, Shaheer. "Nanotechnology and AI Partner to Create Smart Anticounterfeiting Tags". AZoNano. 22 November 2024. <https://www.azonano.com/news.aspx?newsID=39195>.

  • Chicago

    Rehan, Shaheer. "Nanotechnology and AI Partner to Create Smart Anticounterfeiting Tags". AZoNano. https://www.azonano.com/news.aspx?newsID=39195. (accessed November 22, 2024).

  • Harvard

    Rehan, Shaheer. 2022. Nanotechnology and AI Partner to Create Smart Anticounterfeiting Tags. AZoNano, viewed 22 November 2024, https://www.azonano.com/news.aspx?newsID=39195.

Tell Us What You Think

Do you have a review, update or anything you would like to add to this news story?

Leave your feedback
Your comment type
Submit

While we only use edited and approved content for Azthena answers, it may on occasions provide incorrect responses. Please confirm any data provided with the related suppliers or authors. We do not provide medical advice, if you search for medical information you must always consult a medical professional before acting on any information provided.

Your questions, but not your email details will be shared with OpenAI and retained for 30 days in accordance with their privacy principles.

Please do not ask questions that use sensitive or confidential information.

Read the full Terms & Conditions.