Laura Natali and David Bronte Ciriza during the presentation on the fundamentals of effective communication.(Photo by Alireza Khoshzaban.)During the ActiveMatter meeting in Lisbon, Laura Natali and David Bronte Ciriza proposed a two hours activity on the fundamentals of effective communication. The activity was structured in an interactive way, and it began with a open discussion about the importance of communication, especially in science.
Then, the ESRs briefly described their research in a popular science style, so addressed to a broader public. The first hour concluded with a presentation about rules to keep in mind while communicating both in oral and written form.
Afterwards, a few examples among the written texts were selected and discussed with all the participants. The aim was to exchange feedback and suggestions on how to make the communication more effective. The feedback was the inspiration for everyone to review their communication example, and the final versions are being uploaded on the official twitter account @ActiveMatterITN.
Snapshot of the motion of an ellipsoid in a double beam optical trap. (Image by D. Bronte Ciriza) Optical systems are ubiquitous in modern society, with an ever-increasing number of applications covering medical sciences, spatial exploration, information processing and industry, to name but a few examples. In this context, David presented his work on machine learning enhanced optical forces calculations at PHOTOPTICS 2022 between the 10th and the 11th of February. The conference took place online and it was the perfect opportunity to learn from other scientists and discuss the relevance of optics for the study of active matter systems.
David (right) discussing the results with Phil Jones (left). (Photos provided by D. Bronte Ciriza) Between the 11th of the January and the 14th of April David visited UCL to work together with Giorgio Volpe and Phil Jones. During this time in London he studied elongated active particles in complex optical fields, finding some interesting properties that still need to be further understood. Getting to know other people working with soft and active matter gave rise to new ideas and inspiration. More to come!
Carolina (left) and David (right) in the micro 3D printing room. (Image by D. Bronte Ciriza.)From the 11th to the 19th of December 2021, David Bronte Ciriza visited the Soft Materials and Interfaces lab at ETH Zurich. During this visit, David learnt different techniques to fabricate elongated microparticles, and together with Carolina van Baalen produced the ones that will be tested under different optical landscapes in David’s secondment in UCL London. This visit has also served as an opportunity to meet other early stage researchers at ETH Zurich working in related topics, allowing to discuss different ideas in the fields of microfabrication, optical tweezers, and active matter.
Raman Tweezers are used to detect tires and road wear particles in water. We analyze samples collected from a brake test platform, highlighting the presence of car tires and brake particles debris with sub-micrometric dimensions. (Featuring work from Dr Pietro G. Gucciardi, Prof Giovanni Volpe, and Dr Fabienne Lagarde).Raman tweezers for tire and road wear micro- and nanoparticles analysis
R. Gillibert, A. Magazzù, A. Callegari, D. Bronte-Ciriza, A. Foti, M. G. Donato, O. M. Maragò, G. Volpe, M. L. de La Chapelle, F. Lagarde and P. G. Gucciardi.
Tire and road wear particles (TRWP) are non-exhaust particulate matter generated by road transport means during the mechanical abrasion of tires, brakes and roads. TRWP accumulate on the roadsides and are transported into the aquatic ecosystem during stormwater runoffs. Due to their size (sub-millimetric) and rubber content (elastomers), TRWP are considered microplastics (MPs). While the amount of the MPs polluting the water ecosystem with sizes from ∼5 μm to more than 100 μm is known, the fraction of smaller particles is unknown due to the technological gap in the detection and analysis of <5 μm MPs. Here we show that Raman tweezers, a combination of optical tweezers and Raman spectroscopy, can be used to trap and chemically analyze individual TRWPs in a liquid environment, down to the sub-micrometric scale. Using tire particles mechanically grinded from aged car tires in water solutions, we show that it is possible to optically trap individual sub-micron particles, in a so-called 2D trapping configuration, and acquire their Raman spectrum in few tens of seconds. The analysis is then extended to samples collected from a brake test platform, where we highlight the presence of sub-micrometric agglomerates of rubber and brake debris, thanks to the presence of additional spectral features other than carbon. Our results show the potential of Raman tweezers in environmental pollution analysis and highlight the formation of nanosized TRWP during wear.
Optical beam focused into the liquid: the tire particles are pushed away from the laser focus.
Raman Tweezers for Tire and Road Wear Micro- and Nanoparticles Analysis
Pietro Giuseppe Gucciardi, Gillibert Raymond, Alessandro Magazzù, Agnese Callegari, David Bronte Ciriza, Foti Antonino, Maria Grazia Donato, Onofrio M. Maragò, Giovanni Volpe, Marc Lamy de La Chapelle & Fabienne Lagarde
Environmental Science: Nano 9, 145 – 161 (2022)
ChemRxiv: https://doi.org/10.33774/chemrxiv-2021-h59n1
doi: https://doi.org/10.1039/D1EN00553G
Tire and Road Wear Particles (TRWP) are non-exhaust particulate matter generated by road transport means during the mechanical abrasion of tires, brakes and roads. TRWP accumulate on the roadsides and are transported into the aquatic ecosystem during stormwater runoffs. Due to their size (sub-millimetric) and rubber content (elastomers), TRWP are considered microplastics (MPs). While the amount of the MPs polluting the water ecosystem with sizes from ~ 5 μm to more than 100 μm is known, the fraction of smaller particles is unknown due to the technological gap in the detection and analysis of < 5 μm MPs. Here we show that Raman Tweezers, a combination of optical tweezers and Raman spectroscopy, can be used to trap and chemically analyze individual TWRPs in a liquid environment, down to the sub-micrometric scale. Using tire particles mechanically grinded from aged car tires in water solutions, we show that it is possible to optically trap individual sub-micron particles, in a so-called 2D trapping configuration, and acquire their Raman spectrum in few tens of seconds. The analysis is then extended to samples collected from a brake test platform, where we highlight the presence of sub-micrometric agglomerates of rubber and brake debris, thanks to the presence of additional spectral features other than carbon. Our results show the potential of Raman Tweezers in environmental pollution analysis and highlight the formation of nanosized TRWP during wear.
A screenshot taken during the round table discussion of 20 September 2021.
On the 20th of September, the last round table of the Initial Training on Theoretical Methods took place. The discussion was let by the ESRs David, Sandrine, Liam, Carolina, Danne, and Laura. We were excited by the presence of an inspiring panel composed of Felix Ritort, Roberto Cerbino, Kirsty Wan, Fabio Giavazzi, Bernhard Mehlig, and François Nédélec.
The quote “If a system is in equilibrium, it’s probably death” ignited a lively and dynamic discussion around the topic of this final round table: “The universality of active matter: From biology to man-made models.”
Several topics were discussed ranging from active matter length scales and entropy production, to the equipartition theorem and universality. The session left us pondering about the definition of active matter: From single cells to the galaxy, where does the definition of active matter end? Our panelists conclude that it all depend on the question we ask ourselves. The round table was closed with a highlight of the most interesting avenues and opportunities in active matter, including the merge information and activity, realization of in vivo systems, as well as the manipulation of soft matter systems. Some inspiring words from one of the panelists let us realize: “We are the future of active matter.”
A screenshot taken during the round table discussion of 9 September 2021.
Today the second round table of the Initial Training on Theoretical Methods took place, entitled “Theoretical aspects of collective behavior”. The round table was hosted by ESRs David, Jesus, Ojus, Carolina, Alireza, Dana, and Umar. The inspiring group of speakers included Margarida Telo da Gama, Fernando Peruani, Nicoletta Gnan, and Claudio Maggi.
Many matters were discussed, ranging from the limits of collective behavior and the role of communication in emergence, to the compatibility between experiments and theory of collective behavior. Examples can be found in both natural and artificial environments, even combinations with varying degrees of active motion. This adds to the challenge of defining valuable, even if not accurate, models. At the core, collective behavior highlights how the system can be much more than just the sum of individual entities.
Comparison between the Geometrical Optics (GO) method and the Neural Network (NN) for the optical forces and torques calculation. The NN improvement in speed and accuracy could help to study the motion of active particles in optical landscapes. Image by D. Bronte Ciriza.Machine learning to enhance the calculation of optical forces in the geometrical optics approximation David Bronte Ciriza, Alessandro Magazzù, Agnese Callegari, Maria A. Iatì, Giovanni Volpe, Onofrio M. Maragò Submitted to:ELS-XIX (2021) Date: 14 July Time: 12:50 CEST
Short Abstract: We show how machine learning can improve the speed and accuracy of the optical force calculations in the geometrical optics approximation
Extended Abstract: Since the pioneering work by Ashkin in the 1970’s, optical forces have played a fundamental role in fields like biology, nanotechnology, or atomic physics. In all these fields, numerical simulations are of great help for validating theories, for the planning of experiments, and in the interpretation of the results. However, the calculation of the forces is computationally expensive and prohibitively slow for numerical simulations when the forces need to be calculated many times in a sequential way.
Recently, machine learning has been demonstrated to be a promising approach to improve the speed of these calculations and therefore, to expand the applicability of numerical simulations for experimental design and analysis. In this work we show that machine learning can be used to improve not only the speed but also the accuracy of the force calculation in the geometrical optics regime, valid when the particles are significantly bigger than the wavelength of the incident light. This is first demonstrated for the case of a spherical particle with 3 degrees of freedom and later expanded to 9 degrees of freedom by including all the relevant parameters involved in the optical forces calculation. Machine learning is proved as a compact, accurate, and fast approach for optical forces calculation and presents a tool that can be used to study systems that, due to computation limitations, were out of the scope of the traditional ray optics approach.
New ActiveMatter logos: color and BW version. (Image by ActiveMatter ESRs)With a joint effort of the ESR students, a new logo for the ActiveMatter website was designed. The idea started as a handdrawing on a piece of paper and was quickly adapted to a better version with drawing softwares. More than 15 logos were suggested and submitted to a vote. The competition was fierce but we all came to agree on one of them and we are happy to present you the new official logo of the ITN ActiveMatter !
