Lincoln Laboratory technologies win seven R&D 100 Awards for 2025
Inventions that protect US service members, advance computing, and enhance communications are recognized among the year's most significant new products.
Inventions that protect US service members, advance computing, and enhance communications are recognized among the year's most significant new products.
Balancing automation and agency, Associate Professor Arvind Satyanarayan develops interactive data visualizations that amplify human creativity and cognition.
MIT CSAIL researchers developed SustainaPrint, a system that reinforces only the weakest zones of eco-friendly 3D prints, achieving strong results with less plastic.
System developed at MIT could provide realistic predictions for a wide variety of reactions, while maintaining real-world physical constraints.
Artificially created data offer benefits from cost savings to privacy preservation, but their limitations require careful planning and evaluation, Kalyan Veeramachaneni says.
VaxSeer uses machine learning to predict virus evolution and antigenicity, aiming to make vaccine selection more accurate and less reliant on guesswork.
A new computational model makes sense of the cognitive processes humans use to evaluate punishment.
Solubility predictions could make it easier to design and synthesize new drugs, while minimizing the use of more hazardous solvents.
You can adjust the frequency range of this durable, inexpensive antenna by squeezing or stretching its structure.
New research shows automatically controlling vehicle speeds to mitigate traffic at intersections can cut carbon emissions between 11 and 22 percent.
Storage systems from Cloudian, co-founded by an MIT alumnus, are helping businesses feed data-hungry AI models and agents at scale.
Researchers created polymers that are more resistant to tearing by incorporating stress-responsive molecules identified by a machine-learning model.
By visualizing Escher-like optical illusions in 2.5 dimensions, the “Meschers” tool could help scientists understand physics-defying shapes and spark new designs.
This new approach could lead to enhanced AI models for drug and materials discovery.
The platform identifies, mixes, and tests up to 700 new polymer blends a day for applications like protein stabilization, battery electrolytes, or drug-delivery materials.