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Sensing with 2D Materials

After the successful separation of a monolayer of carbon atoms with honeycomb lattice known as graphene in 2004, a large group of 2D materials known as TMDCs and MXenes were discovered and studied. The realm of 2D materials and their heterostructures has created new opportunities for the development of various types of advanced rigid, flexible and stretchable biosensors, and chemical, optoelectronic and electrical sensors due to their unique and versatile electrical, chemical, mechanical and optical properties. The high surface to volume ratio and quantum confinement in 2D materials make them strong candidates for the development of sensors with improved sensitivity and performance. This group of atomically thin material also offer mechanical flexibility and limited stretchability harvested towards making flexible and stretchable sensors that can be used at the interface with soft tissues and in soft robotics. However, challenges remain in fully realizing their potential in practical applications.

The aim of this collection is to highlight the current progress in the research of 2D materials, focusing on their integration into sensing technologies. We seek to provide a comprehensive overview of the advancements made in this area while addressing the challenges faced in developing practical applications.

PAPO: Perception-Aware Policy Optimization for Multimodal Reasoning

Suppose you’re trying to solve a puzzle that includes both words and pictures — like reading a comic strip and figuring out what happens next. That’s the kind of challenge today’s AI faces in “multimodal reasoning,” where it must understand both text and images to think and respond accurately.

New advanced imaging technology enables detailed disease mapping in tissue samples

Researchers from Aarhus University—in a major international collaboration—have developed a groundbreaking method that can provide more information from the tissue samples doctors take from patients every day.

The new technique, called Pathology-oriented multiPlexing or PathoPlex, can look under a microscope at over 100 different proteins in the same small piece of tissue—instead of just 1–2 at a time, as is done now.

The technology, which has just been published in the journal Nature, combines advanced image processing with machine learning to map complex disease processes in detail.

“We Gave AI $20 Million to Rethink Science”: Nexus Super-System Set to Turbocharge US Innovation Like Never Before

IN A NUTSHELL 🚀 Nexus, a $20 million supercomputer, is set to transform U.S. scientific research with its AI power. 🔬 Designed for accessibility, Nexus democratizes high-performance computing, allowing researchers nationwide to apply for access. 🌐 Georgia Tech, in collaboration with the NCSA, is creating a shared national research infrastructure through Nexus. 📈 With unprecedented

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