Cond-Mat Nano-Tech Summit
The Scientific Area of Condensed Matter Physics and Nanotechnology (AFMCNT) has the pleasure to invite you to the Cond-Mat Nano-Tec Summit 2024
És estudante de doutoramento em Matéria Condensada e Nanotecnologia no Departamento de Física do IST ? Então a Área Científica de Física da Matéria Condensada e Nanotecnologia está super interessada an atua investigação. Junta-te ao evento Cond-Mat Nano-Tech, a realizar no dia 10 de Julho das 14h00 às 16h00 no Campus Tecnológico e Nuclear - ULisboa, Bobadela. Leva o teu pitch, nós levamos o lanche. Até lá !
Registos e Template para o Pitch em https://forms.gle/NN7ahvX55EF7cHFc9
Prazo para registos: 08 de Julho, 2024
Prazo para submissão dos slides do pitch: 08 de Julho, 2024
Sabe mais sobre o que a Area faz em https://sites.google.com/tecnico.ulisboa.pt/afmcnt
Are you a PhD student in Condensed Matter and Nanotechnology at the Department of Physics at IST? If so, the Scientific Area of Condensed Matter Physics and Nanotechnology is super interested in your investigation. Join the Cond-Mat Nano-Tech event, to be held on the 10th of July from 14h00 to 16h00 at IST - Technological and Nuclear Campus, Bobadela. Take your pitch, we will take the snacks. See you there !
Registration and Pitch Template at: https://forms.gle/NN7ahvX55EF7cHFc9
Registration deadline: 08 July, 2024
Deadline for the submission of the pitch slides: 08 July, 2024
Know more about AFMCNT at https://sites.google.com/tecnico.ulisboa.pt/afmcnt
Katharina Lorenz (INESC MN, LATR) - Welcome and Introduction to CTN
We will show opportunities for materials characterization and modification using ion beams at Campus Tecnológico e Nuclear (CTN)
Vania Silverio (INESC MN) - Stay Cool, Think Fast: Mastering Thermal Management for AI, Machine Learning, and Big Data Success
As AI, Machine Learning, and Big Data continue to transform industries, data centers are facing unprecedented demands for processing power and storage. This increased workload generates significant heat, posing a critical challenge for data center operators. Effective thermal management is essential to ensure optimal system performance, reduce downtime, and increase efficiency. From heat sink design to advanced fluid dynamics, I will show what is being done at the Microfluidics Lab at INESC MN to meet thermal management needs in datacenters.
Carlo Alfisi (INESC MN, DF/IST) - Plasmonic Metamaterial
Plasmonic metamaterials exploit engineered structures to manipulate light at the micro-nanoscale, enhancing electromagnetic fields. These materials can significantly amplify signals from particles, making them highly effective for high elusive particle detection applications.
Mario G. de Blas (INESC MN) - Power meter with TMR sensor technology: from physics to electronic applications
In my presentation, I will give a brief introduction on how to transition from physical concepts to creating an electronic circuit with a specific application. In this case, I will talk about TMR magnetic sensors and how they can be used to create power meters. I will start with a brief introduction to what a sensor based on the Tunneling effect is, how to measure its output signal, and then explain the main components of an electronic circuit until a final product is created.
Beatriz Sequeira-Antunes (INESC MN, IBEB, Ablute)- Development of a urinalysis biochip system for continuous monitoring of health parameters integrated into a sanitary device
Urine, rich in biomarkers and easily collected, is ideal for early diagnostics. Continuous urine metabolite monitoring enables early disease detection, improving treatment outcomes. My PhD aims to develop a Lab-on-a-Chip system to measure urine pH and detect various metabolites, addressing the current gap in continuous monitoring solutions.
Duarte Magalhães Esteves (INESC MN, LATR) - Defect-engineered β-Ga2O3:Cr3+
Ga2O3 is an emerging wide bandgap semiconductor whose mechanically-exfoliated flakes have promising applications. A patented novel process for the defect-induced exfoliation of nanomembranes by ion implantation is currently under investigation in the context of this work, aiming at the development of ionising radiation dosimeters based on the Cr3+ red/infrared luminescence.
Miguel C. Pedro (INESC MN, LATR) - Ga2O3 membrane p-n heterojunction devices
In my work, n-type β-Ga2O3 membranes obtained from ion-beam-assisted exfoliation will be used to create p-n heterojunctions with p-type materials such as Si and GaN. The resulting structures are devices that will be tested as photodetectors and LEDs. This work will involve microfabrication, simulations and different characterisation techniques.
Diogo Gonçalves (INESC MN) - n-ary spintronics-based edge computing co-processor for artificial intelligence
I will present how I am developing multi-level magnetic tunnel junctions (M2TJs) to achieve n-ary state cells, which improves energy efficiency and processing speed for neuromorphic computing and AI applications.
Daniela Rodrigues Pereira (INESC MN, LATR) - MoO3 functionalization by defect engineering
By defect creation, it is possible to tune the electrical and optical properties of MoO3 nanostructures. This functionalized 2D-MoO3 was studied for field effect transistors and bio-optical sensors.
Francisco Matos (INESC MN) - Free layer optimization and noise measurements in magnetic tunnel junctions
Free layer optimization in magnetoresistive sensors is crucial for compact and efficient magnetic field detection. CoFeSiB magnetic films surpass traditional NiFe layers, offering improved signal and noise performance. This presentation covers the reasoning for this material choice, noise measurement methods, and a brief overview of the resulting noise performance improvement.
Muhammad Muntazir Mehdi (DF/IST) - Data processing software for FC NMR relaxometry and characterization of advanced materials
I will show how I am characterizing novel magnetic ionic liquids by relaxometry profiles, NMR diffusometry, X-ray diffraction and MD simulations. The presentation will also cover how I am developing a modular software tool for analyzing FFC-NMR data, accommodating multi-exponential behavior with new models, while offering statistical tools, pipeline integration, and standard data export.
See last year's presentations here