New Material to Improve Quantum Computing Data Storage
Scientists design metamaterials that manipulate light to store quantum information while protecting fragile qubits.
Machine Learning and Low-Cost Devices to Democratise Air Pollution Monitoring
Researchers built a small affordable air pollution detection device to involve more people in contributing to air quality monitoring programmes with the help of machine learning.
Machine Learning for More Efficient Hash Functions
Researchers created better hash functionality to reduce data collisions with the help of machine learning and optimised computation time.
Machine Learning to Advance Additive Manufacturing in the U.S.
Engineers utilised Machine Learning to develop new technology for flaws early detection and prediction in 3D printed materials.
Researchers Develop Nanosensors to Improve Food Production
The nanosensors offered a rapid, real-time, and in vivo method to mitigate plant stress-level changes in food crops and potentially improve growth and yield.
Researchers Create Thin, Flexible Materials for Future Devices
Researchers designed single-layer 2D materials which may bend when in a ferroelectric condition to a specific direction, making them helpful in future products.
Balancing AI and Humans for Effective Design in the U.S.
Researchers in the United States have discovered that merging AI and human labour produces the best results in simplifying a complex project by balancing fast AI and detail-oriented human work that would be difficult or impossible to create with traditional methods.
Evaluating Drone Efficiency for E-commerce Distribution in the U.S.
Researchers found that drone deliveries need to be calculated better and balanced with other delivery options since, in certain conditions, it costs more than a diesel truck.
Accelerating Low-Cost Catalyst Development for Clean Fuels
Scientists at the US Department of Energy’s Argonne National Laboratory have developed a machine learning model that can assess catalysts for decarbonisation technology in milliseconds rather than months.
U.S.: Atomic-Level Virus Model for Better Flu Treatment
Researchers built a computer model for the influenza virus at an atomic level to design better vaccines and antivirals against influenza in the future – a discovery that offers huge potential for an issue that has been eluding healthcare experts for years.
