Anything-goes “anyons” may be at the root of surprising quantum experiments
MIT physicists say these quasiparticles may explain how superconductivity and magnetism can coexist in certain materials.
MIT physicists say these quasiparticles may explain how superconductivity and magnetism can coexist in certain materials.
Research illustrates how areas within the brain’s executive control center tailor messages in specific circuits with other brain regions to influence them with information about behavior and feelings.
CSAIL researchers find even “untrainable” neural nets can learn effectively when guided by another network’s built-in biases using their guidance method.
MIT-IBM Watson AI Lab researchers developed an expressive architecture that provides better state tracking and sequential reasoning in LLMs over long texts.
A new book providing a roadmap for blending innovation with tradition among shrinking towns blossomed from a practicum in the MIT Department of Urban Studies and Planning.
Global Change Outlook report for 2025 shows how accelerated action can reduce climate risks and improve sustainability outcomes, while highlighting potential geopolitical hurdles.
The AI-powered tool could inform the design of better sensors and cameras for robots or autonomous vehicles.
Stimulating the liver to produce some of the signals of the thymus can reverse age-related declines in T-cell populations and enhance response to vaccination.
New analysis provides the first national, bottom-up estimate of cement’s natural carbon dioxide uptake across buildings and infrastructure.
The consortium convenes industry, academia, and policy leaders to navigate competing demands and reimagine materials supply.
Using new molecules that block an immune checkpoint, researchers showed they could stimulate a strong anti-tumor immune response.
An AI-driven system lets users design and build simple, multicomponent objects by describing them with words.
Tracking how fruit fly motor neurons edit their RNA, neurobiologists cataloged hundreds of target sites and varying editing rates, finding many edits altered communication- and function-related proteins.
MIT researchers found a way to predict how efficiently materials can transport protons in clean energy devices and other advanced technologies.
The approach could apply to more complex tissues and organs, helping researchers to identify early signs of disease.