ReviewMaterials (Basel, Switzerland)2025
Recent Advances in Carbon-Based Sensors for Food and Medical Packaging Under Transit: A Focus on Humidity, Temperature, Mechanical, and Multifunctional Sensing Technologies-A Systematic Review.
Review in Materials (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed.
- Smart Chemical Sensors for Monitoring and Detection of Spoilage in Fermented and Non-Fermented Food Products.Sensors (Basel, Switzerland) · 2026Review
- Smart Adsorption-Based Nanocatalysts for Active Food Packaging: A Critical Look at the Gap Between Concept and Application.Nanomaterials (Basel, Switzerland) · 2026Review
- Carbon-Based Nanoplatforms in Diabetes: A New Paradigm in Diagnosis and Treatment.Annals of biomedical engineering · 2026Review
- Article
- Perspectives on Eco-Friendly Food Packaging: Challenges, Solutions, and Trends.Foods (Basel, Switzerland) · 2025Review
- Influence of Surface Texture in Additively Manufactured Biocompatible Materials and Triboelectric Behavior.Materials (Basel, Switzerland) · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
All carbon-based sensors play a critical role in ensuring the sustainability of smart packaging while enabling real-time monitoring of parameters such as humidity, temperature, pressure, and strain during transit. This systematic review covers the literature between 2013 and 16 November 2024 in the Scopus, Web of Science, IEEE Xplore, and Wiley databases, focusing on carbon-based sensor materials, structural design, and fabrication technologies that contribute to maximizing the sensor performance and scalability with particular emphasis on food and pharmaceutical product packaging applications. After being subjected to the inclusion and exclusion criteria, 164 studies were included in this review. The results show that most humidity sensors are made using graphene oxide (GO), though there is some progress toward cellulose and cellulose-based materials. Graphene and carbon nanotubes (CNTs) are predominant in temperature and mechanical sensors. The application of composites with structural design (e.g., porous and 3D structures) significantly improves sensitivity, long-term stability, and multifunctionality, whereas manufacturing methods such as spray coating and 3D printing further drive production scalability. The transition from metal to carbon-based electrodes could also reduce the cost. However, the scalability, long-term stability, and real-world validation remain challenges to be addressed. Future research should further enhance the performance and scalability of carbon-based sensors through low-energy fabrication techniques and the development of sustainable advanced materials to provide solutions for practical applications in dynamic transportation environments.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.