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Georgia Institute of Technology


The physics of brain development: How cells pull together to form the neural tube

Georgia Tech researchers used computer models to reveal how cells physically pull the neural tube closed during early development. The study found that forces generated by cells create a 'purse string' mechanism made of actin, which tightens and draws the tube closed through a synchronized pattern of cell movement.

SourceGeorgia Institute of Technology·JournalCurrent Biology·TypeComputational simulation/modeling·DateApr 20, 2026

Safe artificial intelligence isn’t enough, according to new Georgia Tech research

AI research at Georgia Tech suggests that simple safety measures are not enough to address the technology's moral implications. The study proposes a middle ground between safe and autonomous AI by advocating for 'end-constrained ethical AI.' This approach prioritizes fairness, honesty, and transparency in AI decision-making.

SourceGeorgia Institute of Technology·JournalScience and Engineering Ethics·DateFeb 26, 2026

Seashells inspire a better way to recycle plastic

The Georgia Tech researchers created a material inspired by seashells to improve the recycling of plastics, reducing variability in mechanical properties and maintaining performance. The new approach has potential savings of hundreds of millions of dollars and could keep more plastic out of landfills.

SourceGeorgia Institute of Technology·JournalProceedings of the National Academy of Sciences·TypeExperimental study·DateAug 13, 2025

Study demonstrates low-cost method to remove CO₂ from air using cold temperatures, common materials

Researchers at Georgia Tech have developed a low-cost method to remove CO2 from the air using extremely cold air and widely available porous sorbent materials. The approach could reduce the cost of capturing one metric ton of CO2 to as low as $70, approximately three times lower than current methods.

SourceGeorgia Institute of Technology·JournalEnergy & Environmental Science·TypeExperimental study·DateJul 7, 2025

Scientists uncover key mechanism in evolution: Whole-genome duplication drives long-term adaptation

Researchers discovered that whole-genome duplication persists for thousands of generations due to its advantage in growing larger cells and forming bigger clusters, leading to the development of multicellularity. The study provides new insights into how genome duplication contributes to biological complexity.

SourceGeorgia Institute of Technology·JournalNature·TypeExperimental study·DateMar 26, 2025

Renewable energy policies provide benefits across state lines

Researchers examined how clean energy policies affect neighboring states and found that stronger policies lead to more renewable electricity generation. The study suggests that individual state policies are more effective than previously thought, and that geographical proximity plays a significant role in spillover effects.

SourceGeorgia Institute of Technology·JournalProceedings of the National Academy of Sciences·TypeData/statistical analysis·DateAug 20, 2024

Unraveling the physics of knitting

Researchers have developed a mathematical theory of knitted materials, enabling the creation of programmable textiles with adjustable elasticity. The study, led by Georgia Tech physicists, explores the relationships between yarn manipulation, stitch patterns, and fabric behavior to expand knitting's applications beyond clothing.

SourceGeorgia Institute of Technology·JournalNature Communications·TypeExperimental study·DateJun 4, 2024

Weaker ocean currents lead to decline in nutrients for North Atlantic ocean life during prehistoric climate change, research shows

Researchers found that weaker ocean currents during the Younger Dryas period led to a decline in nutrient availability, resulting in decreased biological productivity in the North Atlantic. This study supports predictions about the impact of climate change on ocean circulation and life.

SourceGeorgia Institute of Technology·JournalScience·TypeSurvey·DateMay 9, 2024

Georgia Tech and Meta create massive open dataset to advance AI solutions for carbon capture

A massive open dataset, OpenDAC, has been created to accelerate direct air capture technology development while reducing costs. The database enables the training of an AI model that predicts material interactions with high accuracy, significantly faster than traditional chemistry simulations.

SourceGeorgia Institute of Technology·JournalACS Central Science·TypeComputational simulation/modeling·DateMay 2, 2024

Universal controller could push robotic prostheses, exoskeletons into real-world use

Researchers at Georgia Tech have developed a universal approach to controlling robotic exoskeletons that requires no training, calibration, or adjustments. The system uses deep learning to autonomously adjust assistance levels for walking, standing, and climbing stairs, reducing user effort and metabolic expenditure.

SourceGeorgia Institute of Technology·JournalScience Robotics·TypeExperimental study·DateMar 20, 2024

Researchers reveal roadmap for AI innovation in brain and language learning

A new study highlights the importance of differentiating between formal and functional competence in language learning models. Researchers argue that leveraging human neuroscience insights can help develop more powerful AIs that mimic the brain's modularity, leading to improved performance and natural user interaction.

SourceGeorgia Institute of Technology·JournalTrends in Cognitive Sciences·TypeSystematic review·DateMar 19, 2024

Cicadas’ unique urination unlocks new understanding of fluid dynamics

Researchers studied cicadas' jet-like urination to challenge insect pee paradigms. They found that larger animals like cicadas can emit jets due to gravity and inertial forces, unlike smaller ones that typically produce droplets. This discovery has far-reaching implications for bio-inspired engineering and monitoring applications.

SourceGeorgia Institute of Technology·JournalProceedings of the National Academy of Sciences·TypeObservational study·DateMar 11, 2024

Researchers leverage AI to develop early diagnostic test for ovarian cancer

Researchers have developed an AI-driven test that accurately diagnoses ovarian cancer in women clinically classified as normal, improving detection of early-stage disease. The test uses machine learning and blood metabolite information to assign a probability of disease presence or absence, offering a more clinically informative approach.

SourceGeorgia Institute of Technology·JournalGynecologic Oncology·TypeComputational simulation/modeling·DateJan 29, 2024

Research shows disadvantaged people wait significantly longer for power restoration after major storms

Researchers analyzed data from 15 million customers in nine states and found that people in lower socioeconomic tiers experience significantly longer power outage durations. The study suggests that poorer communities are more distant from critical infrastructure or require more significant repairs to power lines.

SourceGeorgia Institute of Technology·JournalPNAS Nexus·TypeComputational simulation/modeling·DateDec 14, 2023

New polymer membranes, AI predictions could dramatically reduce energy, water use in oil refining

Researchers at Georgia Tech have developed new polymer membranes that can improve distillation processes, reducing the global energy and water use. The DUCKY polymers use a novel combination of characteristics to selectively bind desirable molecules, making them a promising solution for industries.

SourceGeorgia Institute of Technology·JournalNature Materials·TypeExperimental study·DateOct 16, 2023

Novel bacterial proteins from seafloor shine light on climate and astrobiology

Scientists have identified a previously unknown class of bacterial proteins that suppress the growth of methane clathrates as effectively as commercial chemicals, but are non-toxic and scalable. This discovery has significant implications for reducing greenhouse gas emissions and increasing the safety of transporting natural gas.

SourceGeorgia Institute of Technology·JournalPNAS Nexus·TypeExperimental study·DateSep 27, 2023