It’s a fairly niche product now, but a new study from Georgia Tech engineers suggests insulation made from hemp fibers could be a viable industry in the U.S., creating jobs, a manufacturing base, and greener homes and buildings at the same time.

Making the switch could slash the impact of one of the biggest sources of greenhouse gas emissions: Buildings account for roughly 1/5 of emissions globally. By some estimates, using hemp-based products would reduce the environmental impact of insulation by 90% or more. 

The Georgia Tech researchers’ work, reported this month in the Journal of Cleaner Production, is one of the first studies to evaluate the potential for scaling up U.S. production and availability of hemp-based insulation products.

Read about their findings on the College of Engineering website.

A new study explores how complex chemical mixtures change under shifting environmental conditions, shedding light on the prebiotic processes that may have led to life on Earth.

Led by Loren Williams (Georgia Institute of Technology) and Moran Frenkel-Pinter (The Hebrew University of Jerusalem) and published in Nature Chemistry, the team’s paper  investigates how chemical mixtures evolve over time, offering new insights into the origins of biological complexity.

“Our research applies concepts from evolutionary biology to chemistry,” explains Williams, a professor in the School of Chemistry and Biochemistry. “We know that everything in biology can be reduced to chemistry, but the idea of this paper is that in the right conditions, chemistry can evolve, too. We call this chemical evolution.”

While much research has focused on individual chemical reactions that could lead to biological molecules, this study establishes an experimental model to explore how entire chemical systems evolve when exposed to environmental changes. 

“Chemical evolution is chemistry that keeps changing and doing new things,” Williams explains. “It’s unending chemical change, but with exploration of new chemical spaces. We wondered if we could set up a system that does that without introducing new molecules ourselves — instead we had the system oscillate between wet and dry conditions.” 

In nature, these systems might look like a landscape where water condenses, and then dries out, over and over again — conditions that arise naturally from the day-night cycles of our planet.

From simple molecules to complex systems

The study identified three key findings — chemical systems can continuously evolve without reaching equilibrium, avoid uncontrolled complexity through selective chemical pathways, and exhibit synchronized population dynamics among different molecular species. This suggests that environmental factors played a key role in shaping the molecular complexity needed for life to emerge.

“This research offers a new perspective on how molecular evolution might have unfolded on early Earth,” says Frenkel-Pinter, assistant professor in the Institute of Chemistry at The Hebrew University of Jerusalem. “By demonstrating that chemical systems can self-organize and evolve in structured ways, we provide experimental evidence that may help bridge the gap between prebiotic chemistry and the emergence of biological molecules.” 

Beyond its relevance to origins-of-life research, the study’s findings may have broader applications in synthetic biology and nanotechnology. Controlled chemical evolution could be harnessed to design new molecular systems with specific properties, potentially leading to innovations in materials science, drug development, and biotechnology.

This research is shared jointly with The Hebrew University of Jerusalem newsroom.

Four million Americans suffer from glaucoma, an incurable eye disease that slowly degrades peripheral vision and eventually leads to blindness. Researchers at Georgia Tech have discovered a potential way to stop this degradation and possibly save people’s vision before it’s too late.

Raquel Lieberman, a professor in the School of Chemistry and Biochemistry and the Parker H. Petit Institute for Bioengineering and Bioscience, and her lab team have discovered two new antibodies with promise to treat glaucoma. The antibodies can break down the protein myocilin, which, when it malfunctions, can cause glaucoma.

Lieberman’s group recently published this research in the Proceedings of the National Academy of Sciences: Nexus.

Protein Problems

Myocilin is just one of hundreds of thousands of proteins that make up the human body. In the eye, an especially delicate balance of proteins and fluid enables sight. The aqueous humor, a clear fluid, bathes the lens that helps focus light into the retina. In a healthy eye, the fluid drains regularly, but if something prevents the fluid from circulating, it increases pressure.

“Your eyeball is kind of like a basketball,” explained Lieberman. “If you want it to work optimally, it has to be pressurized.” 

Lieberman’s team has learned that if myocilin mutates, it clumps up and prevents aqueous humor from draining, increasing eye pressure. If left unmanaged, glaucoma and — eventually — blindness will occur. 

Antibody Answer

Lieberman’s lab characterized two new antibodies that each, in their unique way, can destroy myocilin gone rogue. One binds in a way that does not prevent myocilin from clumping; the other prevents the protein from aggregating. Both effectively break down myocilin so it no longer blocks the aqueous humor from flowing. 

“These exciting results provide proof of concept that targeted antibodies for mutant myocilin aggregation could be therapeutic,” said Alice Ma, a Ph.D. graduate who worked on the research. “This represents a new paradigm for treating other diseases associated with protein clumping, like Alzheimer’s. These studies hold the potential to save the eyesight of millions of glaucoma patients.”

The findings have been the culmination of nearly two decades of research with Lieberman’s close collaborator, University of Texas at Austin chemical engineering Professor Jennifer Maynard, whose group helped discover the two antibodies that responded to the mutation. Lieberman’s group then worked to understand how the antibodies functioned, determining the two that most successfully broke down the protein. 

“This study builds on 10 years of work that explains how myocilin folds to how to break it down,” Lieberman said. “I am at a very fortunate place in my career where this fundamental research coalesces into what we could use clinically.”

Treatment Transformation

Lieberman hopes the antibodies can help treat glaucoma patients, particularly those with early onset glaucoma, often children. She now has a research collaboration with Rebecca Neustein, a physician at Emory University who treats these young patients. 

“She doesn't have much hope to give her patients for curing glaucoma,” Lieberman said. “So she was very excited that we could do some genotyping and figure out who these antibodies can help.”

Lieberman’s research offers a clearer future for millions suffering from glaucoma and those at risk of developing the disease. By leveraging antibodies to target and break down malfunctioning myocilin, this discovery not only paves the way for new treatments for glaucoma but also opens doors for addressing other protein-aggregation diseases like Alzheimer’s, Parkinson’s, and even Type 2 diabetes. 

Funding: National Institutes of Health

Animation by Raul Perez

Dust and rocks residing on the surface of the moon take a beating in space. Without a protective magnetosphere and atmosphere like Earth’s, the lunar surface faces continual particle bombardment from solar wind, cosmic rays, and micrometeoroids. This constant assault leads to space weathering. 

New NASA-funded research by Georgia Tech offers fresh insights into the phenomenon of space weathering. Examining Apollo lunar samples at the nanoscale, Tech researchers have revealed risks to human space missions and the possible role of space weathering in forming some of the water on the moon. 

Most previous studies of the moon involved instruments mapping it from orbit. In contrast, this study allowed researchers to spatially map a nanoscale sample while simultaneously analyzing optical signatures of Apollo lunar samples from different regions of the lunar surface — and to extract information about the chemical composition of the lunar surface and radiation history. 

The researchers recently published their findings in Scientific Reports. 

“The presence of water on the moon is critical for the Artemis program. It’s necessary for sustaining any human presence and it’s a particularly important source for oxygen and hydrogen, the molecules derived from splitting water,” said Thomas Orlando, Regents’ Professor in the School of Chemistry and Biochemistry, co-founder and former director of the Georgia Tech Center for Space Technology and Research, and principal investigator of Georgia Tech’s Center for Lunar Environment and Volatile Exploration Research (CLEVER).

Building on a Decade of Lunar Science Research 

As a NASA SSERVI (Solar System Exploration Research Virtual Institute), CLEVER is an approved NASA laboratory for analysis of lunar samples and includes investigators from multiple institutes and universities across the U.S. and Europe. Research areas include how solar wind and micrometeorites produce volatiles, such as water, molecular oxygen, methane, and hydrogen, which are all crucial to supporting human activity on the moon. 

Georgia Tech has built a large portfolio in human exploration and lunar science over the last decade with two NASA Solar System Exploration Research Virtual Institutes: CLEVER and its predecessor, REVEALS (Radiation Effects on Volatiles and Exploration of Asteroids and Lunar Surfaces). 

Studying Moon Samples at the Nanoscale Level 

Georgia Tech’s labs are world-renowned, particularly for analyzing surfaces and semiconductor materials. For this work, the Georgia Tech team also tapped the University of Georgia (UGA) Nano-Optics Laboratory run by Professor Yohannes Abate in the Department of Physics and Astronomy. While UGA is a member of CLEVER, its nano-FTIR spectroscopy and nanoscale imaging equipment was historically used for semiconductor physics, not space science. 

“This is the first time these tools have been applied to space-weathered lunar samples, and it’s the first we’ve been able to see good signatures of space weathering at the nanoscale,” says Orlando. 

Normal spectrometers are at a much larger scale, with the ability to see more bulk properties of the soil, explains Phillip Stancil, professor and head of the UGA physics department. 

The UGA equipment enabled the study of samples “in tens of nanometers.” To illustrate how small nanoscale is, Stancil says a hydrogen atom is .05 nanometers, so 1 nm is the size of 20 atoms if placed side by side. The spectrometers provide high-resolution details of the lunar grains down to hundreds of atoms. 

“We can look at an almost atomistic level to understand how this rock was formed, its history, and how it was processed in space,” Stancil says. 

“You can learn a lot about how the atom positions change and how they are disrupted due to radiation by looking at the tiny sample at an atomistic level,” says Orlando, noting that a lot of damage is done at the nanoscale level. They can determine if the culprit is space weathering or from a process left over during the rock’s formation and crystallization. 

Finding Radioactive Damage, Evidence of Water 

The researchers found damage on the rock samples, including changes in the optical signatures. That insight helped them understand how the lunar surface formed and evolved but also provided “a really good idea of the rocks’ chemical composition and how they changed when irradiated,” says Orlando. 

Some of the optical signatures also showed trapped electron states, which are typically missing atoms and vacancies in the atomic lattice. When the grains are irradiated, some atoms are removed, and the electrons get trapped. The types of traps and how deep they are, in terms of energy, can help determine the radiation history of the moon. The trapped electrons can also lead to charging, which can generate an electrostatic spark. On the moon, this could be a problem for astronauts, exploration vehicles, and equipment. 

“There is also a difference in the chemical signatures. Certain areas had more neodymium (a chemical element also found in the Earth’s crust) or chromium (an essential trace mineral), which are made by radioactive decay,” Orlando says. The relative amounts and locations of these atoms imply an external source like micrometeorites. 

Translating Research to Human Risks on the Moon 

Radiation and its effects on the dust and lunar surface pose dangers to people, and the main protection is the spacesuit. 

Orlando sees three key risks. First, the dust could interfere with spacesuits’ seals. Second, micrometeorites could puncture a spacesuit. These high-velocity particles form after breaking off from larger chunks of debris. Like solar storms, they are hard to predict, and they’re dangerous because they come in at high-impact velocities of 5 kilometers per second or higher. “Those are bullets, so they will penetrate the spacesuits,” Orlando says. Third, astronauts could breathe in dust left on the suits, causing respiratory issues. NASA is studying many approaches for dust removal and mitigation. 

Mapping the Moon: Going from Nanoscale to Macroscale 

The next research phase will involve combining the UGA analysis tools with a new tool from Georgia Tech that will be used to analyze Apollo lunar samples that have been in storage for over 50 years. 

“We will combine two very sophisticated analysis tools to look at these samples in a level of detail that I don’t think has been done before,” Orlando says. 

The goal is to build models that can feed into orbital maps of the moon. To get there, the Georgia Tech and UGA team will need to go from nanoscale to the full macro scale to show what’s happening on the lunar surface and the location of water and other key resources, including methane, needed to support humanity’s moon and deep-space exploration goals.

A new data creation paradigm and algorithmic breakthrough from Georgia Tech has laid the groundwork for humanoid assistive robots to help with laundry, dishwashing, and other household chores. The framework enables these robots to learn new skills by mimicking actions from first-person videos of everyday activities.

Current training methods limit robots from being produced at the necessary scale to put a robot in every home, said Simar Kareer, a Ph.D. student in the School of Interactive Computing.

“Traditionally, collecting data for robotics means creating demonstration data,” Kareer said. “You operate the robot’s joints with a controller to move it and achieve the task you want, and you do this hundreds of times while recording sensor data, then train your models. This is slow and difficult. The only way to break that cycle is to detach the data collection from the robot itself.”

Other fields, such as computer vision and natural language processing (NLP), already leverage training data passively culled from the internet to create powerful generative AI and large-language models (LLMs).

Many roboticists, however, have shifted toward interventions that allow individual users to teach their robots how to perform tasks. Kareer believes a similar source of passive data can be established to enable practical generalized training that scales the production of humanoid robots.

This is why Kareer collaborated with School of IC Assistant Professor Danfei Xu and his Robot Learning and Reasoning Lab to develop EgoMimic, an algorithmic framework that leverages data from egocentric videos.

Meta’s Ego4D dataset inspired Kareer’s project. The benchmark dataset, released in 2023, consists of first-person videos of humans performing daily activities. This open-source data set trains AI models from a first-person human perspective.

“When I looked at Ego4D, I saw a dataset that’s the same as all the large robot datasets we’re trying to collect, except it’s with humans,” Kareer said. “You just wear a pair of glasses, and you go do things. It doesn’t need to come from the robot. It should come from something more scalable and passively generated, which is us.”

Kareer acquired a pair of Meta’s Project Aria research glasses, which contain a rich sensor suite and can record video from a first-person perspective through external RGB and SLAM cameras.

Kareer recorded himself folding a shirt while wearing the glasses and repeated the process. He did the same with other tasks such as placing a toy in a bowl and groceries into a bag. Then, he constructed a humanoid robot with pincers for hands and attached the glasses to the top to mimic a first-person viewpoint.

The robot performed each task repeatedly for two hours. Kareer said building a traditional training algorithm would take days of teleoperating and recording robot sensory data. For his project, he only needed to gather a baseline of sensory data to ensure performance improvement. 

Kareer bridged the gap between the two training sets with the EgoMimic algorithm. The robot’s task performance rating increased by as much as 400% among various tasks with just 90 minutes of recorded footage. It also showed the ability to perform these tasks in unseen environments.

If enough people wear Aria glasses or other smart glasses while performing daily tasks, it can create the passive data bank needed to train robots on a massive scale.

This type of data collection can enable nearly endless possibilities for roboticists to help humans achieve more in their everyday lives. Humanoid robots can be produced and trained at an industrial level and be able to perform tasks the same way humans do.

“This work is most applicable to jobs that you can get a humanoid robot to do,” Kareer said. “In whatever industry we are allowed to collect egocentric data, we can develop humanoid robots.”

Kareer will present his paper on EgoMimic at the 2025 IEEE Engineers’ International Conference on Robotics and Automation (ICRA), which will take place from May 19 to 23 in Atlanta. The paper was co-authored by Xu and School of IC Assistant Professor Judy Hoffman, fellow Tech students Dhruv Patel, Ryan Punamiya, Pranay Mathur, and Shuo Cheng, and Chen Wang, a Ph.D. student at Stanford.