New UIUC center to develop autonomous construction systems, ecosystem

Grant and Award Announcement

UNIVERSITY OF ILLINOIS GRAINGER COLLEGE OF ENGINEERING

 

IMAGE: PHOTO COURTESY OF THE GRAINGER COLLEGE OF ENGINEERING AT THE UNIVERSITY OF ILLINOIS view more 

CREDIT: THE GRAINGER COLLEGE OF ENGINEERING AT THE UNIVERSITY OF ILLINOIS

The University of Illinois’ Grainger College of Engineering will be the site of a new research and development center dedicated to autonomous construction technologies, with funding from the US Army Corps of Engineers.

With a fleet of self-driving vehicles, the center will focus on some of the most pressing questions related to autonomous construction technologies, including ones related to control systems, expert systems, artificial intelligence, gap crossing and demolition; system architecture; and manufacturing technologies such as additive manufacturing. Numerous vehicle types will be tested and developed, including traditional wheeled vehicles, skid-steers and tracked vehicles.

The mission of the new Center for Autonomous Construction in Manufacturing at Scale (CACMS) will focus on translational research — turning emerging technologies and basic research efforts into real-world solutions that will be of value to the US Army and the State of Illinois. CACMS will serve as a partnership resource for the US Army Corps of Engineers’ Engineer Research and Development Center (USACE ERDC), enabling targeted interdisciplinary research using congressionally directed funding through Senator Dick Durbin’s office.

“This new center will provide leadership in translational research related to autonomous construction systems; support the growth of entrepreneurial ecosystems, programs and expertise; provide a community hub for emerging technologies; and help strengthen Illinois’ reputation as a technologically advanced and high-tech hub within the US,” says Professor William R. Norris, the center’s founding director.

Efforts to establish CACMS were supported at UIUC by the Department of Industrial and Enterprise Systems Engineering (ISE), Grainger Engineering, a Strategic Research Initiative grant and the Discovery Partners Institute. The center will align its work with new research directions; provide training, conferences and workshops; and promote partnerships among academia, industry and government.

Norris is a distinguished UIUC alumnus (B.S. ’96, M.S. ’97 and Ph.D. ’01) and has many years of relevant engineering experience with John Deere and other companies, as well as an MBA from Duke University. The new center is a spin-off of his well-known UIUC Autonomous and Unmanned Vehicle Systems Lab (AUVSL), which has received over $5.5M in external funding since 2018. Key projects completed by AUVSL have included ones on expert systems in construction, autonomous construction systems, a robot-augmented mobility wheelchair device and an architecture for autonomous additive manufacturing with concrete.

CACMS is designed to be self-funded after its third year. Initially, it will be funded with $2.45M from ERDC, with the potential for an additional $1.8M later in 2023 and $3.75M in 2024. The first round of research projects will be supervised by a team of subject matter experts from the Grainger College of Engineering and Texas A&M University.

The center will be a pipeline for real-world solutions to challenging technical problems within the academic, business and government domains, and will contribute to maintaining US technical expertise in robotics and autonomous systems. CACMS is expected to establish UIUC and the State of Illinois as a go-to hub of innovation and translation in the autonomous construction area. The center comes on the heels of UIUC and ERDC’s signing of a new Educational Partnership Agreement (EPA) and a Cooperative Research and Development Agreement (CRADA). The EPA between UIUC and ERDC will encourage and enhance study in science, technology, engineering and mathematics (STEM)fields, such as materials science and engineering, computer and data science, digital twinning, physics, robotics, supply chain logistics, and sustainability and resilience. The CRADA will enable closer collaboration in research efforts of interest to the military.

Click here to watch video.

 

Researchers develop low-cost sensor to enhance robots' sense of touch

Researchers from Queen Mary University of London, along with collaborators from China and USA have developed an L3 F-TOUCH sensor to enhance tactile capabilities in robots, allowing it to "feel" objects and adjust its grip accordingly

Peer-Reviewed Publication

QUEEN MARY UNIVERSITY OF LONDON

 

IMAGE: THE SENSOR FEELING THE OBJECTS. view more 

CREDIT: F-TOUCH TEAM

Achieving human-level dexterity during manipulation and grasping has been a long-standing goal in robotics. To accomplish this, having a reliable sense of tactile information and force is essential for robots. A recent study, published in IEEE Robotics and Automation Letters, describes the L3 F-TOUCH sensor that enhances the force sensing capabilities of classic tactile sensors. The sensor is lightweight, low-cost, and wireless, making it an affordable option for retrofitting existing robot hands and graspers. 

The human hand can sense pressure, temperature, texture, and pain. Additionally, the human hand can distinguish between objects based on their shape, size, weight, and other physical properties. Many current robot hands or graspers are not even close to human hands as they do not have integrated haptic capabilities, complicating handling objects. Without knowledge about the interaction forces and the shape of the handled object, the robot fingers would not have any "feel of touch," and objects could easily slip out of the robot hand's fingers or even be crushed if they are fragile.  

The study, led by Professor Kaspar Althoefer of Queen Mary University of London, presents the new L3 F-TOUCH - high-resolution fingertip sensor, where L3 stands for Lightweight, Low-cost, wireLess communication. The sensor can measure an object's geometry and determine the forces to interact with it. Unlike other sensors that estimate interaction forces via tactile information acquired by camera images, the L3 F-TOUCH measures interaction forces directly, achieving higher measurement accuracy.  

"In contrast to its competitors that estimate experienced interaction forces through reconstruction from camera images of the deformation of their soft elastomer, the L-3 F-TOUCH measures interaction forces directly through an integrated mechanical suspension structure with a mirror system achieving higher measurement accuracy and wider measurement range. The sensor is physically designed to decouple force measurements from geometry information. Therefore, the sensed three-axis force is immuned from contact geometry compared to its competitors. Through embedded wireless communications, the sensor also outperforms competitors with regards to integrability with robot hands." says Professor Kaspar Althoefer. 

When the sensor touches the surface, a compact suspension structure enables the elastomer – a rubber-like material that deforms to measure high-resolution contact geometry exposed to an external force – to displace upon contact. To make sense of this data, the elastomer’s displacement is tracked by detecting the movement of a special marker, a so-called ARTag, allowing us to measure contact forces along the three major axes (x, y, and z) via a calibration process. 

“We will focus our future work on extending the sensor's capabilities to measure not only force along the three major axes but also rotational forces such as twist, which could be experienced during screw fastening while remaining accurate and compact. These advancements can enable the sense of touch for more dynamic and agile robots in manipulation tasks, even in human-robot interaction settings, like for patient rehabilitation or physical support of the elderly.” adds Professor Althoefer. 

This breakthrough could pave the way for more advanced and reliable robotics in the future, as with the L3 F-TOUCH sensor, robots can have a sense of touch, making them more capable of handling objects and performing complex manipulation tasks. 

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JOURNAL

IEEE Robotics and Automation Letters

DOI

10.1109/LRA.2023.3292575 

ARTICLE TITLE

L3 F-TOUCH: A Wireless GelSight With Decoupled Tactile and Three-Axis Force Sensing

 

A simpler method for learning to control a robot

Researchers develop a machine-learning technique that can efficiently learn to control a robot, leading to better performance with fewer data.

Reports and Proceedings

MASSACHUSETTS INSTITUTE OF TECHNOLOGY

Researchers from MIT and Stanford University have devised a new machine-learning approach that could be used to control a robot, such as a drone or autonomous vehicle, more effectively and efficiently in dynamic environments where conditions can change rapidly. 

This technique could help an autonomous vehicle learn to compensate for slippery road conditions to avoid going into a skid, allow a robotic free-flyer to tow different objects in space, or enable a drone to closely follow a downhill skier despite being buffeted by strong winds.

The researchers’ approach incorporates certain structure from control theory into the process for learning a model in such a way that leads to an effective method of controlling complex dynamics, such as those caused by impacts of wind on the trajectory of a flying vehicle. One way to think about this structure is as a hint that can help guide how to control a system.

“The focus of our work is to learn intrinsic structure in the dynamics of the system that can be leveraged to design more effective, stabilizing controllers,” says Navid Azizan, the Esther and Harold E. Edgerton Assistant Professor in the MIT Department of Mechanical Engineering and the Institute for Data, Systems, and Society (IDSS), and a member of the Laboratory for Information and Decision Systems (LIDS). “By jointly learning the system’s dynamics and these unique control-oriented structures from data, we’re able to naturally create controllers that function much more effectively in the real world.”

Using this structure in a learned model, the researchers’ technique immediately extracts an effective controller from the model, as opposed to other machine-learning methods that require a controller to be derived or learned separately with additional steps. With this structure, their approach is also able to learn an effective controller using fewer data than other approaches. This could help their learning-based control system achieve better performance faster in rapidly changing environments. 

“This work tries to strike a balance between identifying structure in your system and just learning a model from data,” says lead author Spencer M. Richards, a graduate student at Stanford University. “Our approach is inspired by how roboticists use physics to derive simpler models for robots. Physical analysis of these models often yields a useful structure for the purposes of control — one that you might miss if you just tried to naively fit a model to data. Instead, we try to identify similarly useful structure from data that indicates how to implement your control logic.”

Additional authors of the paper are Jean-Jacques Slotine, professor of mechanical engineering and of brain and cognitive sciences at MIT, and Marco Pavone, associate professor of aeronautics and astronautics at Stanford. The research will be presented at the International Conference on Machine Learning (ICML).

Learning a controller

Determining the best way to control a robot to accomplish a given task can be a difficult problem, even when researchers know how to model everything about the system. 

A controller is the logic that enables a drone to follow a desired trajectory, for example. This controller would tell the drone how to adjust its rotor forces to compensate for the effect of winds that can knock it off a stable path to reach its goal.

This drone is a dynamical system — a physical system that evolves over time. In this case, its position and velocity change as it flies through the environment. If such a system is simple enough, engineers can derive a controller by hand.  

Modeling a system by hand intrinsically captures a certain structure based on the physics of the system. For instance, if a robot were modeled manually using differential equations, these would capture the relationship between velocity, acceleration, and force. Acceleration is the rate of change in velocity over time, which is determined by the mass of and forces applied to the robot. 

But often the system is too complex to be exactly modeled by hand. Aerodynamic effects, like the way swirling wind pushes a flying vehicle, are notoriously difficult to derive manually, Richards explains. Researchers would instead take measurements of the drone’s position, velocity, and rotor speeds over time, and use machine learning to fit a model of this dynamical system to the data. But these approaches typically don’t learn a control-based structure. This structure is useful in determining how to best set the rotor speeds to direct the motion of the drone over time.

Once they have modeled the dynamical system, many existing approaches also use data to learn a separate controller for the system.

“Other approaches that try to learn dynamics and a controller from data as separate entities are a bit detached philosophically from the way we normally do it for simpler systems. Our approach is more reminiscent of deriving models by hand from physics and linking that to control,” Richards says.

Identifying structure

The team from MIT and Stanford developed a technique that uses machine learning to learn the dynamics model, but in such a way that the model has some prescribed structure that is useful for controlling the system. 

With this structure, they can extract a controller directly from the dynamics model, rather than using data to learn an entirely separate model for the controller.

“We found that beyond learning the dynamics, it’s also essential to learn the control-oriented structure that supports effective controller design. Our approach of learning state-dependent coefficient factorizations of the dynamics has outperformed the baselines in terms of data efficiency and tracking capability, proving to be successful in efficiently and effectively controlling the system’s trajectory,” Azizan says. 

When they tested this approach, their controller closely followed desired trajectories, outpacing all the baseline methods. The controller extracted from their learned model nearly matched the performance of a ground-truth controller, which is built using the exact dynamics of the system. 

“By making simpler assumptions, we got something that actually worked better than other complicated baseline approaches,” Richards adds.

The researchers also found that their method was data-efficient, which means it achieved high performance even with few data. For instance, it could effectively model a highly dynamic rotor-driven vehicle using only 100 data points. Methods that used multiple learned components saw their performance drop much faster with smaller datasets.

This efficiency could make their technique especially useful in situations where a drone or robot needs to learn quickly in rapidly changing conditions.

Plus, their approach is general and could be applied to many types of dynamical systems, from robotic arms to free-flying spacecraft operating in low-gravity environments.

In the future, the researchers are interested in developing models that are more physically interpretable, and that would be able to identify very specific information about a dynamical system, Richards says. This could lead to better-performing controllers.

This research is supported, in part, by the NASA University Leadership Initiative and the Natural Sciences and Engineering Research Council of Canada.

###

Written by Adam Zewe

Paper: “Learning Control-Oriented Dynamical Structure from Data”

https://arxiv.org/pdf/2302.02529.pdf

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ARTICLE TITLE

“Learning Control-Oriented Dynamical Structure from Data”

 

KAIST presents a microbial cell factory as a source of eco-friendly food and cosmetic coloring​

Peer-Reviewed Publication

THE KOREA ADVANCED INSTITUTE OF SCIENCE AND TECHNOLOGY (KAIST)

 

IMAGE: [FIGURE 1] EXAMPLES OF PRODUCTION OF FOOD AND COSMETIC COMPOUNDS USING MICROBIAL CELL FACTORIES view more 

CREDIT: KAIST METABOLIC AND BIOMOLECULAR ENGINEERING NATIONAL RESEARCH LABORATORY

Despite decades of global population growth, global food crisis seems to be at hand yet again because the food productivity is cut severely due to prolonged presence of abnormal weather from intensifying climate change and global food supply chain is deteriorated due to international conflicts such as wars exacerbating food shortages and nutritional inequality around the globe. At the same time, however, as awareness of the environment and sustainability rises, an increase in demand for more eco-friendly and high-quality food and beauty products is being observed not without a sense of irony. At a time like this, microorganisms are attracting attention as a key that can handle this couple of seemingly distant problems.

KAIST (President Kwang-Hyung Lee) announced on the 26th that Kyeong Rok Choi, a research professor of the Bioprocess Research Center and Sang Yup Lee, a Distinguished Professor of the Department of Chemical and Biomolecular Engineering, published a paper titled “Metabolic Engineering of Microorganisms for Food and Cosmetics Production” upon invitation by Nature Reviews Bioengineering to be published online published by Nature after peer review.

  ※ Paper title: Systems metabolic engineering of microorganisms for food and cosmetics production

  ※ Author information: Kyeong Rok Choi (first author) and Sang Yup Lee (corresponding author)

Systems metabolic engineering is a research field founded by Distinguished Professor Sang Yup Lee of KAIST to more effectively develop microbial cell factories, the core factor of the next-generation bio industry to replace the existing chemical industry that relies heavily on petroleum. By applying a systemic metabolic engineering strategy, the researchers have developed a number of high-performance microbial cell factories that produce a variety of food and cosmetic compounds including natural substances like heme and zinc protoporphyrin IX compounds which can improve the flavor and color of synthetic meat, lycopene and β-carotene which are functional natural pigments that can be widely used in food and cosmetics, and methyl anthranilate, a grape-derived compound widely used to impart grape flavor in food and beverage manufacturing.

In this paper written upon invitation by Nature, the research team covered remarkable cases of microbial cell factory that can produce amino acids, proteins, fats and fatty acids, vitamins, flavors, pigments, alcohols, functional compounds and other food additives used in various foods and cosmetics and the companies that have successfully commercialized these microbial-derived materials Furthermore, the paper organized and presents systems metabolic engineering strategies that can spur the development of industrial microbial cell factories that can produce more diverse food and cosmetic compounds in an eco-friendly way with economic feasibility.

  

Image of Coloring

CREDIT

KAIST Metabolic and Biomolecular Engineering National Research Laboratory

< Figure 1. Examples of production of food and cosmetic compounds using microbial cell factories >

For example, by producing proteins or amino acids with high nutritional value through non-edible biomass used as animal feed or fertilizer through the microbial fermentation process, it will contribute to the increase in production and stable supply of food around the world. Furthermore, by contributing to developing more viable alternative meat, further reducing dependence on animal protein, it can also contribute to reducing greenhouse gases and environmental pollution generated through livestock breeding or fish farming. 

In addition, vanillin or methyl anthranilate, which give off vanilla or grape flavor, are widely added to various foods, but natural products isolated and refined from plants are low in production and high in production cost, so in most cases, petrochemicals substances derived from vanillin and methylanthranilic acid are added to food. These materials can also be produced through an eco-friendly and human-friendly method by borrowing the power of microorganisms. 

Ethical and resource problems that arise in producing compounds like Calmin (cochineal pigment), a coloring added to various cosmetics and foods such as red lipstick and strawberry-flavored milk, which must be extracted from cochineal insects that live only in certain cacti. and Hyaluronic acid, which is widely consumed as a health supplement, but is only present in omega-3 fatty acids extracted from shark or fish livers, can also be resolved when they can be produced in an eco-friendly way using microorganisms.

 

KAIST Research Professor Kyeong Rok Choi, the first author of this paper, said, “In addition to traditional fermented foods such as kimchi and yogurt, foods produced with the help of microorganisms like cocoa butter, a base ingredient for chocolate that can only be obtained from fermented cacao beans, and monosodium glutamate, a seasoning produced through microbial fermentation are already familiar to us”. “In the future, we will be able to acquire a wider variety of foods and cosmetics even more easily produced in an eco-friendly and sustainable way in our daily lives through microbial cell factories.” he added.

CAPTION

[Figure 2] Systems metabolic engineering strategy to improve metabolic flow in microbial cell factories

CREDIT

KAIST Metabolic and Biomolecular Engineering National Research Laboratory

Distinguished Professor Sang Yup Lee said, “It is engineers’ mission to make the world a better place utilizing science and technology.” and added, “Continuous advancement and active use of systems metabolic engineering will contribute greatly to easing and resolving the problems arising from both the food crisis and the climate change."

This research was carried out as a part of the “Development of Protein Production Technology from Inorganic Substances through Control of Microbial Metabolism System Project” (Project Leader: Kyeong Rok Choi, KAIST Research Professor) of the the Center for Agricultural Microorganism and Enzyme (Director Pahn-Shick Chang) supported by the Rural Development Administration and the “Development of Platform Technologies of Microbial Cell Factories for the Next-generation Biorefineries Project” (Project Leader: Sang Yup Lee, KAIST Distinguished Professor) of the Petroleum-Substitute Eco-friendly Chemical Technology Development Program supported by the Ministry of Science and ICT. 

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JOURNAL

Nature Reviews Bioengineering

DOI

10.1038/s44222-023-00076-y 

METHOD OF RESEARCH

Meta-analysis

SUBJECT OF RESEARCH

Not applicable

ARTICLE TITLE

Systems metabolic engineering of microorganisms for food and cosmetics production

 

Bacteria as Blacksmiths

ISTA scientists use a bath of swimming bacteria to assemble unconventional materials

Peer-Reviewed Publication

INSTITUTE OF SCIENCE AND TECHNOLOGY AUSTRIA

 

IMAGE: SCIENTISTS AT THE INSTITUTE OF SCIENCE AND TECHNOLOGY AUSTRIA (ISTA) FORGE SOFT MATERIALS FROM “LEGO”-LIKE BUILDING BLOCKS WITH THE ENERGY PRODUCED BY SWIMMING BACTERIA. ILLUSTRATION. view more 

CREDIT: © ISTA

A hot bath is a place to relax. For scientists, it is also where molecules or tiny building blocks meet to form materials. Researchers at the Institute of Science and Technology Austria (ISTA) take it to the next level and use the energy of swimming bacteria to forge materials. A recent study in Nature Physics shows us how this works and the potential sustainability benefits that may arise from this innovative approach.

You never know when dazzling ideas will strike you. Sometimes they emerge from the most unexpected places, like a boulder gym in Vienna. Such was the case for ISTA’s Daniel Grober, a graduate student in the research group of physicist Jérémie Palacci, who had been working on how to assemble materials leveraging the energy of swimming bacteria, and Mehmet Can Uçar, a postdoc in Edouard Hannezo's group. Fueled by their shared passion for science and climbing, discussions at the gym turned into a paper-pen model of Grober’s experiment. Their concept captivated Ivan Palaia, a postdoc in Anđela Šarić’s group, who decided to join the task force.

Together, this dynamic all-ISTA trio embarked on a collaborative effort that now reaches its pinnacle with a paper published today in Nature Physics. The study shows a novel experimental strategy to fabricate materials from small building blocks. It translates ideas from metallurgy—the fine art of blacksmithing, where cycles of high temperature and slow cooling set a material’s structure—into soft materials, using the activity from a bath of swimming bacteria.

What are active baths?
In Jérémie Palacci’s research group at the Institute of Science and Technology Austria, it is all about microscopic particles. “Our work revolves around tiny ‘Lego’-like building blocks that are a hundred times smaller than a hair. We try to understand how these components come together and form larger structures,” he explains. Typically, when these building blocks are suspended in water, they jiggle due to temperature, which provides the energy for the particles to hop back and forth randomly. A phenomenon first rationalized by Einstein in 1905 and known as Brownian motion.

To introduce order amidst the chaos, adding an “active agent” to the water is beneficial. This results in what is known as an “active bath”, where the agent acts like a small fire. In principle, with this extra energy, you can hope to control the assembly and properties of materials—the way the blacksmith forges. However, until now, an approach where for instance bacteria is used to forge, had never been explored.

Bacteria — the fire
Palacci’s student, Daniel Grober, took on this challenge and started to construct such an active bath with characteristics inspired by metallurgy. Grober says, “We used E. coli bacteria as an active agent, as their swimming movement provided energy and some kind of agitation—‘temperature’ for a physicist, equivalent to 2000 °C, similar to the one needed to craft metals. But because it is made by bacteria, and it is not a real oven, it remains gentle enough to be used with gels and soft materials without burning them.” The building blocks were microscopic particles in the form of sticky colloids—round beads that stick together when in contact.

This idea proved to be successful. The swimming bacteria effectively amplified the motion of the beads, resulting in the formation of aggregations and gel-like structures.

Dance to the beat of bacteria
Moreover, the observation of these newly formed clusters showed an intriguing singularity. At all times, the aggregates were spinning clockwise, but very slowly. To shed light on this observation, Grober conducted a statistical analysis of the system’s motion. He confirmed a slow and persistent rotation of the aggregates that originates in the clockwise spin (chirality) of the E. coli flagella—the minuscule appendages that propel the bacteria in their movement. The scientist suspected that the rotational motion played a pivotal role in forming the unconventional structures he observed.

Presenting his work in a weekly lab meeting intrigued his colleague Ivan Palaia, which led to the understanding of the phenomenon. Palaia proposed a minimal computational model, to capture the chirality of the bacterial bath without simulating the swimming bacteria. The computer simulations were first validated by quantitatively reproducing the experimental results before providing a deeper understanding of the mechanism.  The model confirmed the salient role of the rotation in shaping gels, by forming remarkable structures with exotic mechanical properties that cannot be achieved conventionally.

More to come in the future
This utilization of bacterial baths to assemble unconventional materials holds great promise. For instance, although the study was limited to 2D structures at the micron scale, the approach was designed for its potential in upscaling. “With this innovative approach, it could theoretically be possible to construct 3D samples, large enough to be held in the palm of my hand!” Palacci adds. This advancement could also enhance the sustainability of material production by harnessing energy from bacteria rather than relying on external energy sources.

Finally, the study serves as a proof of concept, laying the foundation for Palacci’s ERC-funded project called “VULCAN: matter powered from within” and underlines once again the significance of interdisciplinary collaboration in science that drives innovation. “The project would have never reached this conceptual and quantitative depth without the collaborative work fostered by ISTA”, Palacci concludes.

Dancing aggregates (Video) [VIDEO] | 

An active bath of swimming bacteria. (A) Aggregation of sticky beads in a thermal (normal) bath or in a bath of swimming bacteria. (B) Experimental aggregation in the thermal or the bacterial bath, showing the formation of visually distinct gel structures.

CREDIT

© Palacci Group/Nature Physics

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JOURNAL

Nature Physics

DOI

10.1038/s41567-023-02136-x 

METHOD OF RESEARCH

Experimental study

SUBJECT OF RESEARCH

Not applicable

ARTICLE TITLE

Unconventional colloidal aggregation in chiral bacterial baths

ARTICLE PUBLICATION DATE

27-Jul-2023

Making renewable, infinitely recyclable plastics using bacteria

Scientists engineered microbes to make the ingredients for recyclable plastics – replacing finite, polluting petrochemicals with sustainable alternatives.

Peer-Reviewed Publication

DOE/LAWRENCE BERKELEY NATIONAL LABORATORY

 

IMAGE: RESEARCHERS AT BERKELEY LAB HAVE USED BACTERIA TO BRING BIORENEWABILITY TO RECYCLABLE PLASTICS. view more 

CREDIT: JENNY NUSS/BERKELEY LAB

Plastic waste is a problem. Most plastics can’t be recycled, and many use finite, polluting petrochemicals as the basic ingredients. But that’s changing. In a study published today in Nature Sustainability, researchers successfully engineered microbes to make biological alternatives for the starting ingredients in an infinitely recyclable plastic known as poly(diketoenamine), or PDK.

The finding comes from collaboration among experts at three facilities at the Department of Energy’s Lawrence Berkeley National Laboratory (Berkeley Lab): the Molecular Foundry, the Joint BioEnergy Institute (JBEI), and the Advanced Light Source. 

“This is the first time that bioproducts have been integrated to make a PDK that is predominantly bio-based,” said Brett Helms, staff scientist at the Molecular Foundry who led the project. “And it’s the first time that you see a bio-advantage over using petrochemicals, both with respect to the material’s properties and the cost of producing it at scale.”

Unlike traditional plastics, PDK can be repeatedly deconstructed into pristine building blocks and formed into new products with no loss in quality. PDKs initially used building blocks derived from petrochemicals, but those ingredients can be redesigned and produced with microbes instead. Now, after four years of effort, collaborators have manipulated E. coli to turn sugars from plants into some of the starting materials – a molecule known as triacetic acid lactone, or bioTAL – and produced a PDK with roughly 80% bio-content.

“We’ve demonstrated that the pathway to 100% bio-content in recyclable plastics is feasible,” said Jeremy Demarteau, a project scientist on the team contributing to biopolymer development. “You’ll see that from us in the future.”

PDKs can be used for a variety of products, including adhesives, flexible items like computer cables or watch bands, building materials, and “tough thermosets,” rigid plastics made through a curing process. Researchers were surprised to find that incorporating the bioTAL into the material expanded its working temperature range by up to 60 degrees Celsius compared to the petrochemical version. This opens the door to using PDKs in items that need specific working temperatures, including sports gear and automotive parts such as bumpers or dashboards.

Solving the plastic waste problem

The United Nations Environment Program estimates that we globally produce about 400 million tons of plastic waste every year, and that number is predicted to climb to more than 1 billion tons by 2050. Of the 7 billion tons of plastic waste already created, only about 10 percent has been recycled, while most is discarded into landfills or burned. 

“We can’t keep using our dwindling supply of fossil fuels to feed this insatiable desire for plastics,” said Jay Keasling, a professor at UC Berkeley, senior faculty scientist in Berkeley Lab’s Biosciences Area, and the CEO of JBEI. “We want to help solve the plastic waste problem by creating materials that are both biorenewable and circular – and providing an incentive for companies to use them. Then people could have the products they need for the time they need them, before those items are transformed into something new.”

The study released today also builds on a 2021 environmental and technological analysis, which showed that PDK plastic could be commercially competitive with conventional plastics if produced at a large scale.

“Our new results are extremely encouraging,” said Corinne Scown, a staff scientist in Berkeley Lab’s Energy Technologies Area and a vice president at JBEI. “We found that with even modest improvements to the production process, we could soon be making bio-based PDK plastics that are both cheaper and emit less CO2 than those made with fossil fuels.” 

Those improvements would include speeding up the rate at which microbes convert sugars to bioTAL, using bacteria that can transform a wider variety of plant-derived sugars and other compounds, and powering the facility with renewable energy. 

This work was supported by the Department of Energy’s Bioenergy Technologies Office. The Molecular Foundry is a DOE Office of Science, Office of Basic Energy Sciences user facility that specializes in nanoscale science. JBEI is a Bioenergy Research Center funded by DOE’s Office of Science. The Advanced Light Source is a DOE Office of Science user facility.

PDK technology is available for licensing and collaboration. If interested, please contact Berkeley Lab’s Intellectual Property Office, ipo@lbl.gov. 

Raw bioTAL (left) can be combined with other chemicals and processed into a biorenewable, recyclable PDK plastic (right).

CREDIT

Jeremy Demarteau/Berkeley Lab

A GIF showing how PDK plastic readily breaks down when put in an acidic solution. The acid helps to break the bonds between the monomers (the plastic’s building blocks) and separate them from the chemical additives that give plastic its look and feel.

CREDIT

Peter Christensen/Berkeley Lab

Founded in 1931 on the belief that the biggest scientific challenges are best addressed by teams, Lawrence Berkeley National Laboratory and its scientists have been recognized with 16 Nobel Prizes. Today, Berkeley Lab researchers develop sustainable energy and environmental solutions, create useful new materials, advance the frontiers of computing, and probe the mysteries of life, matter, and the universe. Scientists from around the world rely on the Lab’s facilities for their own discovery science. Berkeley Lab is a multiprogram national laboratory, managed by the University of California for the U.S. Department of Energy’s Office of Science.

DOE’s Office of Science is the single largest supporter of basic research in the physical sciences in the United States, and is working to address some of the most pressing challenges of our time. For more information, please visit energy.gov/science.

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JOURNAL

Nature Sustainability

DOI

10.1038/s41893-023-01160-2 

ARTICLE TITLE

Biorenewable circularity in polydiketoenamine plastics

ARTICLE PUBLICATION DATE

27-Jul-2023