- CBI - CERN
- UPC - IED - ESADE
- info@visiofibre.com
Having observed and understood that the problem was evidently in need of a focused approach, our project was shaped from two distinct perspectives.
On one hand, there was a process that required a strategic approach to achieve the final objective: reducing the amount of microplastics and raising public awareness. This necessitated considering the general lack of interest and awareness among the population, as well as the dearth of information among companies and governmental organizations, which contributed to the problem remaining unacknowledged and, consequently, a lack of interest in finding solutions. Indeed, the process needed to be guided by a roadmap where each technological advancement was justified by its social impact, gradually increasing interest and improving technology.
Additionally, it was essential to seek out a technology that was easy, fast, and efficient. This technology would need to collect microplastic samples and then analyze them. It was crucial that this technology be integrated into the various stages of the roadmap and, ideally, be improved and refined over the years. The impact of this technology was so significant that it would be beneficial far beyond the short-term scope of our project, especially considering the challenges in raising awareness among governments and businesses and the lack of information.
Our investigation into the technologies led us to the conclusion that detecting microplastics is an extremely challenging task, with no single technology available that can easily and efficiently identify microplastics due to their highly varied sizes and shapes. To detect them, we must leverage certain properties such as gasification and the radiation spectrum. Moreover, even though our goal is merely to determine the concentration of microplastics in the air, regardless of the type, the vast diversity of microplastics and their propensity to be easily mistaken for calcium or other particles make it impossible to find a technology that looks solely at the overall concentration of microplastics. The process requires distinctive detection of each type of microplastic and then, if necessary, the aggregation of the total concentration from the samples.
Ultimately, we aim for our technology to closely mirror real-world conditions, ensuring that the microplastic samples we collect are as reliable and representative as possible of human inhalation. This approach will enable us to draw more accurate correlations and conclusions in post-analysis more easily.
In order to reach a conclusion about the most useful technology for our project, we weighed the different properties of each technology, taking into account the pros and cons they presented. This collaborative process led us to the following results:
The Iall technology
With its high-focused lens, it is particularly useful for large area scanning like beaches, and it can detect particles in the 5-10 um range. Its effectiveness, though, is contingent on having a stable surface for accurate operation.
Infrared Spectroscopy (IR)
It provides a more affordable option for microplastic detection, capable of identifying particles between 50-100 micrometers. However, the requirement for pre-sampling and a longer analysis time of 4-5 hours (extending to 8 hours when fibers are involved) can be seen as drawbacks. The results are also measured in parts per unit mass or volume.
Pyrolysis
It is another technique used for microplastic detection. Its affordability and accuracy in determining the concentration of microplastics make it an attractive option. However, it is limited to small samples and requires high temperatures (600 ºC) for analysis, which may not be suitable for all types of samples. Results are given in milligrams per liter (mg/L), a different metric that might be more suitable for certain analyses.
Sniffdrone
This drone-based technology is adept at detecting gases and can collect air samples in a chamber for analysis. Its mobility and transportability are key advantages, allowing for flexible deployment. However, a limitation lies in its machine learning algorithm, which is not modifiable, potentially restricting its adaptability.
H3D VisionAir
It combines computer vision with machine learning to identify shapes, colors, and infrared signatures. Equipped with a camera and advanced optics, it’s a powerful tool for visual analysis. However, it falls short in detecting smaller microplastics and requires an electronic microscope for more detailed analysis.
Raman Spectroscopy
It is a sophisticated and costly method that stands out for its precision in detecting microplastics within a range of 5-10 micrometers. It’s a time-intensive process, taking about 130 minutes for analysis, and demands a small pre-sample that needs to be extrapolated to understand the broader sample. Results are measured in parts per unit mass or volume.
Optical Microscopes
Effective in detecting the shape and location of microplastics. Combinable with other technologies, cannot classify types of microplastics and may confuse them with other materials.
Another issue that needed to be addressed in order to tackle the technology was how the samples were collected: whether to collect them in solid state using filters or in gaseous state using air chambers. Here we are going to present our reasoning proces:
Filter
Advantages:
Disadvantages:
Air Chamber
Advantages:
Disadvantages:
Some of the proposals we have considered include using a drone, like the Crazyflie, to collect samples, or the use of masks with integrated filters that would utilize human breathing during inhalation to gather samples.
Raman Spectroscopy was chosen for our project as the ideal solution, not for being one of the most used technologies to detect mircoplastics(Identification of microplastics using Raman spectroscopy: Latest developments and future prospects – Silvia Lacorte), but also due to its superior specificity and precision in detecting a wide range of microplastic particles, particularly those within the challenging 5-10 micrometer size range. This level of detail is essential for our project, which aims not just to detect the presence of microplastics but to understand their concentration with high accuracy.
While Raman Spectroscopy does have its drawbacks, such as higher costs and longer analysis times compared to some other technologies, these were not deemed sufficient to outweigh its benefits. Moreover, Attract Technologies provides us with a Raman Spectroscopy system. Their equipment presumably offers the optimal balance between performance and usability, making it well-suited to our fieldwork and research objectives. Modifying and adapting their device will make the system perfect for our purposes.
The extended duration required for analysis is a reasonable compromise considering the high quality and reliability of the data obtained. Moreover, there have been advancements in the form of projects and real prototypes that have led to the creation of compact, useful devices capable of detecting these small particles. While these devices might not exhibit top-tier performance, they are sufficiently effective for the needs of our project.
Other technologies were considered but ultimately not selected for various reasons. For instance, while Infrared Spectroscopy is more affordable, it lacks the precision of Raman and requires a lengthy analysis process. Pyrolysis, despite its affordability, is constrained by its small sample size and the high temperatures needed for analysis, which limits its field applicability.
The Sniffdrone’s inflexibility due to its fixed machine learning algorithm, and the H3D VisionAir’s need for additional equipment to detect smaller particles, made them less suitable for our diverse and broad-scaled field applications. Similarly, while Optical Microscopes and Crazyflie Drones have their merits, they fall short in the classification of microplastics and adaptability to various environmental conditions, which are critical for our project’s goals.
However, Ramman spectroscopy needs a presampling and, in the first steps, we will probably require the help of microscopes to focus the high concentration places of microplastics
Finally, we have also decided to use filters, mainly because of their affordable cost, ease of use, and compatibility with Raman spectroscopy technology.
The use of drones did not provide stability and did not adapt well to practical scenarios. Although masks seemed like a good alternative, they contradicted one of the basic principles we discussed earlier. While collecting samples, we would also be preventing exposure before even demonstrating the certainty and correlation of our concerns relating microplastics to health issues.
By attaching an air vacuum pump to the filter, we can simulate human inhalation, making the device more realistic. To make the system more efficient and cost-effective, we could place the filter in different regions and areas. This approach would cover multiple users per filter, similar to what Silvia did in her paper «Airborne microplastic particle concentrations and characterization in indoor urban microenvironments.»
Reflecting on our past experiences, we have utilized a range of workshops and events that have significantly contributed to the development and success of our project. Here’s how each activity played a crucial role:
CBI4AI Project Presentation: Mattia presented their AI-based image recognition to detect tumors. This innovative approach involved utilizing a camera system integrated with advanced artificial intelligence algorithms capable of identifying and analyzing tumor characteristics in medical images. This also helped us to know how a presentation should be.
How to Communicate Ideas Workshop: This workshop enhanced our ability to articulate our ideas more effectively. We learned techniques to present our concepts in a more engaging and understandable manner, which was essential for our project’s success.
Goals Setting Workshop: We established clear, achievable goals for our project. This workshop helped us in defining our project’s direction and milestones, ensuring we remained focused and on track.
Consolidation & Validation Workshop with Rafael Pérez: Rafael’s insights were invaluable in helping us consolidate our research findings and validate our project’s assumptions and direction. We integrated these learnings into our project, strengthening its foundation.
PuzzleX Event with Last Technologies: Attending this event exposed us to the latest advancements in Quantum, AI, and other exponential technologies. This exposure broadened our perspective and inspired us to think innovatively about our project’s approach, especially in terms of technological applications.
Researchers Q&A Sessions: These sessions provided us with direct access to experts in various fields. We utilized these opportunities to ask specific questions related to our project, gaining insights that were directly applicable to our work. They were super helpful because in a previous stage we were overdoing the technology and we made some changes on our project.
Ideation Workshop: Here, we brainstormed and developed creative solutions for our project. The workshop was instrumental in pushing our thinking beyond conventional boundaries.
Communication Workshop: We further honed our communication skills, focusing on how to effectively convey our project’s message and engage our audience. Alissa was our instructor and he is soo good doing her work and knows a lot how to understand people and teach them to communicate.
Barcelona Supercomputing Center visit: Although optional, this visit was an eye-opener to the capabilities of supercomputing servers center in Barcelona, next to UPC.
CERN Final Trip: This approach allowed us to focus intensely on our project without distractions, fostering a more productive and creative environment.
Input from CBI Faculty, IdeaSquare staff, and Experts: The feedback and insights from various professionals provided us with diverse perspectives and expert advice, which we incorporated into our project. Feedbacks from Ramon Bragós, Eduard Alarcón, Jordi Pla, Ole Anton Werner, Mireia Sierra, and other coaches which here too helpful to also rewrite our solution.
Utilizing IdeaSquare Resources: Access to IdeaSquare’s resources at CERN enabled us to develop high-quality prototypes and refine our solutions with state-of-the-art technology. The lab was incredible to develop our scientific prototypes.
Final Gala at CERN: This was not just a celebration but also an opportunity to showcase our project, network with visitors, and receive feedback. We enjoyed a lot this experience.
We arrived to the step in which we had to create a prototype in order to show the world what we were explaining and prove that it was possible to create a device which helps detecting microplastics in order to make changes in a future to reduce their concentration (even though that this is a future step).
Then, as Raman Spectroscopy is a very expensive system and it was not viable using it for a prototype, we managed to use a colorspectroscopy system made with an Arduino Sensor and a MATLAB App. For the device of the filters, we used materials from UPC and CERN to make a prototype with an Erlenmeyer, an air pump, and creating a hole in which we can introduce the filter to take the samples.
“Empowering Vietnam textile factories workers by reducing their overexposure to microplastics to avoid lung disseasses.”
Making the invisible impossible to ignore
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