Predicting Complete IV Curves for Perovskite Solar Cells with AI. Perovskite solar cells are a groundbreaking technology, offering high efficiency and low manufacturing costs, making them a promising candidate for the future of renewable energy. Their tunable properties and rapid development have captured significant interest in both academic and industrial sectors. This project focuses on […]

Perovskite solar cells stand out due to their rapid advancements and high efficiency, combined with the promise of cost-effective production. These attributes have placed them at the forefront of next-generation renewable energy solutions. This project integrates physics-based principles into AI models to reconstruct IV curves, reducing reliance on extensive input parameters. By incorporating optoelectronic governing […]

Laser-driven plume formation is a surprising and so far theoretically unpredicted phenomenon of Newtonian fluids. The group at the Max Planck Institue for the Structure and Dynamics of Matter (MPSD) have observed this behaviour in glycerol, a Newtonian fluid, whereby elastic, rubber-like responses in the material have been produced on timescales many orders of magnitude […]

In Brazil, malaria accounts for the highest morbidity registered in the Americas. In this country, 99.5% of the cases of malaria are registered in the Brazilian Amazon. The main goal of this research is to investigate how riberinhos experience and act upon malaria in endemic areas of Manaus and Careiro, State of Amazonas, Brazil. This […]

This research explores the creation and study of a prototype controller with integrated thermal feedback (hot/cold tactile output). This type of device has not previously been explored or understood deeply in academic Human-Computer Interaction or Games User Research Literature. The controller with integrated thermal feedback will be evaluated in a simple 3D game and compared […]

The purpose of the project is to design a paper-based device for the co-detection of nitric oxide (NO) and glucose in a tumor angiogenesis model. By combining paper technologies to electrochemical sensing, we envision that an easy-to-use, smart tumor model can be built. The devices will be tested on co-cultured endothelial and tumor cells, to […]

The proposed project aims to develop a new, eco-friendly construction material by combining fly ash and Sidoarjo mud to create a self-compacting geopolymer mix. This innovative material will replace traditional aggregates, making it more sustainable and reducing environmental impact. The project leverages the international collaboration to address waste management issues and promote sustainable construction practices. […]

Parkinson’s disease (PD) is a devastating brain disorder accompained by the death of dopamine-producing neurons. Aging is the main risk factor for PD, but early-onset forms also exist and are often linked to mutations in PRKN gene, which encodes for a cellular protein called Parkin. Evidence suggests that these mutations may perturb dopamine neuron function […]

Measurement of magnetic field vector by a compact diamond quantum sensor Measuring magnetic field is important for material and device characterization. Although various methods have been developed, challenges persist in accurately measuring local magnetic field vectors. Our lab has been developing a compact diamond quantum sensor to overcome the challenge. The diamond sensor uses nitrogen […]

The proposed MITACS GRA project is part of the Human Surgeome Project at the German Cancer Center, which uses advanced machine learning and deep learning technologies to improve surgical practices. By analyzing large amounts of surgical video data, the project aims to enhance surgical training, skill assessment, and workflow. It will develop systems that provide […]

This project aims to create a training system for laparoscopic procedures focused on gynecological surgeries using a 3D-printed torso phantom. The mannequin features apertures for inserting laparoscopic tools (trocars) and a camera, with visible 3D-printed organs inside. The goal is to develop a training module that integrates virtual anatomical models with real-world views using HoloLens […]

Bond dissociation enthalpy (BDE) is a fundamental chemical property for predicting molecular stability and reactivity. BDEs are crucial for understanding antioxidant efficiency, enzyme catalysis, surface functionalization chemistry, and drug discovery. This project will focus on predicting BDEs for C-O and C-C bond types in lignin-derived molecules, essential for efficient lignin decomposition processes in biofuel production […]