- Why some quantum materials stall while others scaleIn a new study, MIT researchers evaluated quantum materials’ potential for scalable commercial success — and identified promising candidates.
- Earthquake damage at deeper depths occurs long after initial activityWhile the Earth’s upper crust recovers quickly from seismic activity, new research finds the mid-crust recovers much more slowly, if at all.
- Engineering next-generation fertilizersMIT postdoc Giorgio Rizzo harnesses plant chemistry to design sustainable fertilizers that could reshape modern farming.
- Optimizing food subsidies: Applying digital platforms to maximize nutritionAn algorithm can change the face of food assistance policy in the Global South, says MIT assistant professor and J-WAFS researcher Ali Aouad.
- Checking the quality of materials just got easier with a new AI toolActing as a “virtual spectrometer,” SpectroGen generates spectroscopic data in any modality, such as X-ray or infrared, to quickly assess a material’s quality.
- New MIT initiative seeks to transform rare brain disorders researchThe Rare Brain Disorders Nexus aims to accelerate the development of novel therapies for a spectrum of uncommon brain diseases.
- Geologists discover the first evidence of 4.5-billion-year-old “proto Earth”Materials from ancient rocks could reveal conditions in the early solar system that shaped the early Earth and other planets.
- A new system can dial expression of synthetic genes up or downThe promoter editing system could be used to fine-tune gene therapy or to more efficiently reprogram cells for therapeutic use.
- Immune-informed brain aging research offers new treatment possibilities, speakers saySpeakers at MIT’s Aging Brain Initiative symposium described how immune system factors during aging contribute to Alzheimer’s, Parkinson’s and other conditions. The field is leveraging that knowledge to develop new therapies.
- MIT Schwarzman College of Computing and MBZUAI launch international collaboration to shape the future of AIThe MIT–MBZUAI Collaborative Research Program will unite faculty and students from both institutions to advance AI and accelerate its use in pressing scientific and societal challenges.
- How to reduce greenhouse gas emissions from ammonia productionProposed system would combine two kinds of plants, creating greater efficiency and lowering costs while curbing climate-changing emissions.
- Using generative AI to diversify virtual training grounds for robotsNew tool from MIT CSAIL creates realistic virtual kitchens and living rooms where simulated robots can interact with models of real-world objects, scaling up training data for robot foundation models.
- MIT physicists improve the precision of atomic clocksA new method turns down quantum noise that obscures the “ticking” of atoms, and could enable stable, transportable atomic clocks.
- Uncovering new physics in metals manufacturingMIT researchers discovered a hidden atomic order that persists in metals even after extreme processing.
- Engineered “natural killer” cells could help fight cancerA new study identifies genetic modifications that make these immune cells, known as CAR-NK cells, more effective at destroying cancer cells.
- New prediction model could improve the reliability of fusion power plantsThe approach combines physics and machine learning to avoid damaging disruptions when powering down tokamak fusion machines.
- Printable aluminum alloy sets strength records, may enable lighter aircraft partsIncorporating machine learning, MIT engineers developed a way to 3D print alloys that are much stronger than conventionally manufactured versions.
- Study sheds light on musicians’ enhanced attentionBrain imaging suggests people with musical training may be better than others at filtering out distracting sounds.
- Chemists create red fluorescent dyes that may enable clearer biomedical imagingThe new dyes are based on boron-containing molecules that were previously too unstable for practical use.
- AI maps how a new antibiotic targets gut bacteriaMIT CSAIL and McMaster researchers used a generative AI model to reveal how a narrow-spectrum antibiotic attacks disease-causing bacteria, speeding up a process that normally takes years.
- A simple formula could guide the design of faster-charging, longer-lasting batteriesMIT researchers developed a model that explains lithium intercalation rates in lithium-ion batteries.
- Accounting for uncertainty to help engineers design complex systemsThe approach could enable autonomous vehicles, commercial aircraft, or transportation networks that are more reliable in the face of real-world unpredictability.
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