Category: Chemistry

How to harness the potential of highly reactive radical molecules to work in pairs and spur transformative chemistry?

Bulk them up.

That is the approach of a new Cornell-led collaboration that attached large fragments to the infamously temperamental molecules, increasing their girth to insulate them from their hyperreactive partners.

The technique could prove to be a boon for creating new and improved derivatives of pharmaceutical compounds.

The group’s paper, “Regioselective Aliphatic C–H Functionalization Using Frustrated Radical Pairs,” published July 5 in Nature. The lead author is doctoral student Zhipeng Lu.

The project, led by Song Lin, professor of chemistry and chemical biology in the College of Arts and Sciences, emerged from the Lin Group’s previous experiments with synthetic electrochemistry. In that process, electrodes pass an electrical current through a chemical reaction to activate inert molecules that will form chemical bonds that otherwise might not be achievable.

Electrochemistry also happens to be one of the most efficient ways to generate high reactive radicals from simple chemical feedstocks.

“That’s where we thought, hey, when we have these radicals, how can we control them as well? If you can harness them and use them to react with a pharmaceutical, they can do really cool chemistry,” Lin said. “It’s really our interest in electrochemistry and radical chemistry that allowed us to think about these fundamental problems.”

Radicals are highly reactive, but they have the potential to bond in pairs by sharing a pair of single electrons. The challenge is getting them close enough to cooperate without annihilating each other.

The researchers’ solution was to bulk up the radicals by attaching groups of carbon and hydrogen atoms to their surface, effectively giving each molecule a set of antlers that allowed them to preserve their native reactivity while keeping their partner at a safe distance—also known as “frustrating” them.

“We use frustrated radicals to activate carbon-hydrogen bonds and convert them into other chemical bonds, which can affect the property of the original molecule,” Lin said. “This strategy can thus be used to improve efficacy of drug molecules, for example.”

Carbon-hydrogen bonds are ideal candidates for the task because they are commonly found in organic molecules—a carbon molecule, for example, can have upwards of 20 or 30 bonds. They are also quite strong, which is why they are often conscripted into service for pharmaceutical development.

At the same time, due to their strength, carbon-hydrogen bonds can be difficult to separate out. And because they are so plentiful, selectively functionalizing individual sites is not easy.

Lin’s group collaborated with researchers from the San Francisco-based company Genentech to identify substrate targets that would enable the desired chemical reactions. The team installed large functional groups, such as trimethylsilyl, on the frustrated radicals.

“You have this barrel of substituents to make it more hindered,” Lin said. “It is actually a very simple idea. How do you use size to control the reactivity and use them to do something useful?”

Once the products were made, the team teased them apart and analyzed the reactivity and selectivity through high-level nuclear magnetic resonance and gas and liquid chromatography.

The group’s technique can help medicinal chemists initiate dozens of different chemical transformations for a range of applications, from derivatizing more efficient pharmaceutical products and enhancing their biological activity to tracking how drugs degrade in the human body.

Co-authors include postdoctoral researchers Minsoo Ju and Yi Wang; recent Cornell graduate Jonathan Meinhardt; former postdoctoral researcher Jesus Martinez Alvarado; and researchers Elisia Villemure and Jack Terrett from Genentech.

More information: Zhipeng Lu et al, Regioselective aliphatic C–H functionalization using frustrated radical pairs, Nature (2023). DOI: 10.1038/s41586-023-06131-3

Journal information: Nature 

Provided by Cornell University 

Indiscriminate use of packaging materials derived from petroleum has led to a huge buildup of plastic in landfills and the ocean, as these materials have low degradability and are not significantly recycled. To mitigate this problem and meet growing demand for products that are safe for human health and the environment, the food industry is investing in the development of more sustainable packaging alternatives that preserve nutritional quality as well as organoleptic traits such as color, taste, smell and texture.

An example is a film made of a compound derived from limonene, the main component of citrus fruit peel, and chitosan, a biopolymer derived from the chitin present in exoskeletons of crustaceans.

The film was developed by a research group in São Paulo state, Brazil, comprising scientists in the Department of Materials Engineering and Bioprocesses at the State University of Campinas’s School of Chemical Engineering (FEQ-UNICAMP) and the Packaging Technology Center at the Institute of Food Technology (ITAL) of the São Paulo State Department of Agriculture and Supply, also in Campinas.

The results of the research are reported in an article published in Food Packaging and Shelf Life.

“We focused on limonene because Brazil is one of the world’s largest producers of oranges [if not the largest] and São Paulo is the leading orange-producing state,” said Roniérik Pioli Vieira, last author of the article and a professor at FEQ-UNICAMP.

Limonene has been used before in film for food packaging to enhance conservation thanks to its antioxidant and anti-microbial action, but its performance is impaired by volatility and instability during the packaging manufacturing process, even on a laboratory scale.

This is one of the obstacles to the use of bioactive compounds in commercial packaging. It is often produced in processes that involve high temperatures and high shear rates due to cutting or shaping. Bioactive additives easily degrade in these processes.

“To solve this problem, we came up with the idea of using a derivative of limonene called poly(limonene), which isn’t volatile or particularly unstable,” Vieira said.

The researchers chose chitosan for the film matrix because it is a polymer of natural origin and has well-known antioxidant and anti-microbial properties. Their hypothesis was that combining the two materials would produce a film with enhanced bioactive properties.

In the laboratory, the scientists compared films with limonene and poly(limonene) in varying proportions to address the challenge of finding a way to combine them with chitosan, since theoretically they do not mix. The researchers opted for polymerization, a process in which polymers is made from smaller organic molecules.

In this case, they used a compound with polar chemical functions to start the reaction and to increase interaction between the additive and the polymer matrix. They then analyzed the resulting film to evaluate properties such as antioxidant capacity, light and water vapor protection, and resistance to high temperatures.

The results were highly satisfactory. “The films with the poly(limonene) additive outperformed those with limonene, especially in terms of antioxidant activity, which was about twice as potent,” Vieira said. The substance also performed satisfactorily as an ultraviolet radiation blocker and was found to be non-volatile, making it suitable for large-scale production of packaging, where processing conditions are more severe.

The films are not yet available for use by manufacturers, mainly because chitosan-based plastic is not yet produced on a sufficiently large scale to be competitive, but also because the poly(limonene) production process needs to be optimized to improve yield and to be tested during the manufacturing of commercial packaging.

“Our group is working on this. We’ve investigated other applications of poly(limonene) in the biomedical field, for example. We’re trying to demonstrate the multifunctionality of this additive, whose origins are renewable,” Vieira said.

More information: Sayeny de Ávila Gonçalves et al, Poly(limonene): A novel renewable oligomeric antioxidant and UV-light blocking additive for chitosan-based films, Food Packaging and Shelf Life (2023). DOI: 10.1016/j.fpsl.2023.101085

Provided by FAPESP 

Millions of roads across the United States are constructed with asphalt pavement that’s deteriorating over time. Now, researchers at the University of Missouri are using recyclables, including plastic waste, as a sustainable solution to fix America’s fracturing road system.

In partnership with the Missouri Department of Transportation (MoDOT), researchers from the Mizzou Asphalt Pavement and Innovation Lab (MAPIL) recently created a real-world test road using recycled materials like scrap tires and plastic waste along a portion of Interstate 155 in the Missouri Bootheel.

By increasing the sustainability of asphalt mixes, this innovative method can help reduce the number of items going into landfills or leaking into the environment, said Bill Buttlar, director of MAPIL.

“Missouri is the Show-Me State, so we take a very pragmatic view,” Buttlar said. “The science can be thorny and difficult, but we are up to the task. We’re excited that while our approach is complicated in the lab, its simple to execute in the field, so it makes it easily adaptable, scalable and cost-effective to incorporate into many types of road environments.”

The I-155 project takes the group’s previous test road, installed along a stretch of Stadium Boulevard in Columbia, Missouri, one step further. Instead of just testing four different types of recycled materials, the I-155 project will evaluate the real-world effectiveness of nine different types of recycled materials in the creation of asphalt pavement. This includes three different types of polyethylene (PE)—a material commonly found in plastic grocery bags—and ground tire rubber, which is a newer way of disposing scrap tires.

“These projects afford us an opportunity to intentionally build the next generation of roads with these materials not as a type of linear landfill, but to also help the environment while making the value of dollars spent on transportation infrastructure like this stretch farther into the future,” said Buttlar, who is also the Glen Barton Chair in Flexible Pavements.

MU is on the leading-edge of this type of work in the U.S. because its team has addressed most of the translational research questions like durability and safety that could prevent a general contractor or department of transportation from adopting this ground-breaking strategy.

“We don’t just live in the laboratory,” Buttlar said. “In the field of transportation material research, we need to see how all the various materials used to construct a road—the rock, the asphalt and the recycled materials—behave in the real world and gel together to build a road.”

“Asphalt is liquefied with heat, and when you put an additive in like a plastic or rubber material, you must get everything to bond together with good adhesion. But we’re only going to know if that happens successfully when we produce it on a full-scale level and then expose it to elements, such as different weather conditions and heavy traffic.”

MAPIL specializes in a dry process, which allows the researchers to easily add the recyclables directly into the mixture before it’s applied to a road surface.

“The form, shape and size of the plastics bring different challenges in how the material flows, how it behaves and how it mixes,” said Punya Rath, an assistant research professor in the Department of Civil and Environmental Engineering who works at MAPIL. “So, we did extensive small-scale testing for almost an entire year before we moved to a larger scale out in the field with contractors.”

One advantage of this process is that the researchers can test the mixtures in the field using a mobile research lab, which they developed and used for both the Stadium Boulevard and I-155 projects.

“It helps the Missouri Department of Transportation (MoDOT) immensely to have a mobile research lab on-site in the field that has the ability to rapidly test samples and provide results within 24–48 hours to better inform the process,” Rath said.

Citing environmental concerns, Buttlar said the team makes sure everything they do is within the current limits as established by the Environmental Protection Agency (EPA).

“We are designing the material to be able to hold or capture the environmental by-products at the highest percentage for the longest amount of time. It’s not going to be a 100% containment,” Buttlar said. “Everything built in a natural environment will degrade over time, so that’s why EPA has standards for everything, and we make sure we are safely within those standards.”

In an effort to discover new 2D materials, a team of scientists from Ames National Laboratory determined the structure of boron monoxide. This compound was first discovered in the 1940s and maintained research interest throughout the years. Scientists were, however, unable to determine the structure of the material due to technological limitations of the time. Using new NMR methods and previously unavailable analytical tools, the team from Ames Lab finally solved the structure of this deceptively simple material.

“We initially weren’t really looking into studying this particular material,” said Frédéric Perras, a scientist from Ames Lab and member of the research team. “We were actually trying to make a carbon-free covalent organic framework.” A covalent organic framework is a low-density and porous material with a periodically ordered crystal structure. It is composed of organic molecules that are linked together through covalent bonds.

“However, after many synthesis trials, we could not get a highly crystalline covalent organic framework material,” said Wenyu Huang, another scientist from Ames Lab and member of the team. Perras’ and Huang’s groups are interested in these materials for alternative energy applications.

The team ended up making a boron-based material that Perras said was difficult to characterize. Through their research, they came upon literature dating back to 1940 that contained descriptions of the exact reaction the team was working on, and the synthesis of a material called boron monoxide. Unfortunately, previous scientists were unable to determine the structure of the material. This research is further discussed in the paper published in Journal of the American Chemical Society.

Luckily, technology for materials research has advanced since the 1940s. “Because of our expertise in nuclear magnetic resonance spectroscopy, and the development of new methods to which people in the 40s, 50s, and 60s didn’t have access, we thought that we might be able to lay this nearly century old mystery to rest,” said Perras.

Perras explained that boron monoxide is made using a precursor molecule that acts like building blocks. These molecules stick together through dehydration reactions. The key to understating the structure is to figure out how the blocks are physically arranged. “So we developed some NMR methods that allow us to study the orientation of these building blocks relative to each other. Basically, we found that adjacent precursor molecules were getting organized parallel to each other, which matched one of the previously proposed models,” Perras said.

“We also applied a lot of other techniques, including powder X-ray diffraction, which showed that these nanosheets organized themselves into what’s called a turbostratic arrangement,” said Perras. He explained that these stacked nanosheets are like a stack of paper thrown onto a desk. Once they land, they are not perfectly aligned, but they remain in a stack.

According to Perras, there has been a lot of recent interest in synthesizing new boron-based 2D materials. Understanding the structure of this one could lead to the synthesis of other useful boron-based 2D materials. “What really excites me is just the fact that this is an old problem. It’s such a basic material; when you write down the chemical formula, it’s BO. So, it’s interesting from that point of view that we finally solved its structure,” said Perras

More information: Frédéric A. Perras et al, The Structure of Boron Monoxide, Journal of the American Chemical Society (2023). DOI: 10.1021/jacs.3c02070

Journal information: Journal of the American Chemical Society 

Provided by Ames National Laboratory 

A research team led by Prof. Chen Chilai from the Hefei Institutes of Physical Science of the Chinese Academy of Sciences has developed a deep-sea mass spectrometer. It has completed several sea trials in a specific area of the deep sea.

The extreme environment of the deep sea has shaped unique biological processes and harbors significant mineral resources, the detection of which is a frontier issue in international Earth science research. Deep sea in-situ detection technology allows continuous acquisition of information on the components, concentrations and variations of deep-sea samples in both temporal and spatial dimensions. Therefore, it is increasingly being used in extreme deep-sea environments.

In this study, the deep-sea mass spectrometer worked continuously and reliably for more than eight hours under simulated water depths of -5,800 meters. It achieved long-term (25.8 hours) in-situ detection of dissolved gases in the cold seep region of the deep sea and online detection of dissolved gases from the sea surface to the seabed (-1,388 m to 0 m).

This allowed the researchers to obtain important scientific data, such as the temporal variation curve of the concentration of small molecular dissolved gases and the vertical concentration distribution profile in the deep-sea seabed. The results were published in Chinese Journal of Analytical Chemistry.

This technology is not only applicable to deep-sea exploration but also to the acquisition of dissolved gas information in inland rivers, lakes and near-shore waters. Relevant research in this area is also underway.

“We have been committed to the research of key technologies and applications of mass spectrometry,” said Prof. Chen. “The development of this deep-sea mass spectrometer paves the way for the study of the origin and early evolution of life, as well as the study of global climate change.”

More information: Han Wang et al, Development and application of an underwater mass spectrometer for in situ detection of deep-sea dissolved gases, Chinese Journal of Analytical Chemistry (2023). DOI: 10.1016/j.cjac.2023.100299

Provided by Chinese Academy of Sciences 

Structural materials with useful mechanical properties have applications in a diverse range of fields. A reliable way to enhance the properties of structural materials is to make them lighter without compromising their strength.

Carbon fiber reinforced plastics (CFRPs) are perhaps the most prominent example of this approach. These plastics are made up of tiny, yet extremely strong threads of carbon atoms held together by a plastic matrix. Owing to their low weight, high durability, and exceptional mechanical performance, CFRP laminates are being incorporated into state-of-the-art aerospace applications, transportation, and construction.

However, designing CFRP laminates can be a very time-consuming endeavor. Engineers must run multiple strength tests to benchmark CFRP specimens whenever they adjust a given design. This drives up the cost of the final product and hinders the applications of CFRPs in a wider range of fields.

Against this backdrop, a duo of researchers, Dr. Chenyu Wang, a former Ph.D. student at the Graduate School of Sophia University, and Professor Toshio Nagashima from Sophia University, developed a novel method to conduct numerical simulations of damage propagation in CFRP laminates. Their findings were published online in the journal Composite Structures.

The researchers based their approach on a quasi-3D version of the extend finite element method (XFEM). In FEM, a structure or material is divided into small sub-regions known as elements, followed by the solving of physical equations for each element, to determine the overall response of the system. The “extend” version, which has been used in this study, adds functions that capture local effects around discontinuities, enabling more accurate modeling of damage propagation in form of crack growth.

Notably, since CFRP laminates are made of stacked layers of material, modeling them as flat planes (2-dimensional or 2D) would fail to capture anomalies such as delamination.

In contrast, a 3-dimensional (3D) FEM simulation would be computationally intensive and complex to set up. To overcome these issues, the researchers took a balanced approach. They first modeled the desired CFRP laminate as a 2D structure composed of quadrilateral finite elements and marked the position where cracks might occur. Then, they projected this structure in the thickness direction, while the models used to simulate delamination and matrix crack were automatically generated through their simulation system.

This strategy made the computations manageable and the modeling to simulate CFRP damage more easily and efficiently.

To verify the validity of their approach, the researchers ran simulations of three different strength and damage propagation tests on CFRP laminates and compared their results with the experimental data reported in other studies.

The first was an open-hole tension test, in which a CFRP laminate with a circular hole in the middle was pulled from one end while the other end was anchored.

The second was a quasi-static indentation (QSI) test, where a hard semi-sphere was pressed slowly and steadily against a CFRP laminate.

Lastly, the third test was the compression-after-impact test, in which the damaged specimens from the QSI test were subjected to a compressive force to assess their integrity and damage tolerance.

Overall, the results of the proposed simulation method agreed well with the experimental data, outperforming the existing quasi-3D XFEM-based techniques. Confident about the potential of the novel approach, Dr. Wang says, “The applications of composite materials such as CFRP will become more extensive and efficient if the results of this study are utilized in related fields.”

The widespread adoption of CFRPs is also likely to have important ecological implications. “In the future, if the damage of composite materials can be predicted more efficiently and accurately via numerical simulations, their cost will decrease. If these lightweight and high-strength materials are further applied in transportation, it will have a positive impact on energy savings and environmental protection,” adds Dr. Wang.

If commercial aircraft could lower their fuel consumption and time taken for design by incorporating CFRPs, the cost of flying could significantly reduce.

More information: Chenyu Wang et al, Damage propagation analysis of CFRP laminate by quasi-3D XFEM using hexahedral elements, Composite Structures (2023). DOI: 10.1016/j.compstruct.2023.117024

Provided by Sophia University

Scientists of the NOMAD Laboratory at the Fritz Haber Institute of the Max Planck Society recently proposed a workflow that can dramatically accelerate the search for novel materials with improved properties. They demonstrated the power of the approach by identifying more than 50 strongly thermally insulating materials. These can help alleviate the ongoing energy crisis, by allowing for more efficient thermoelectric elements, i.e., devices able to convert otherwise wasted heat into useful electrical voltage.

Discovering new and reliable thermoelectric materials is paramount for making use of the more than 40% of energy given off as waste heat globally and help mitigate the growing challenges of climate change. One way to increase the thermoelectric efficiency of a material is to reduce its thermal conductivity, κ, and thereby maintaining the temperature gradient needed to generate electricity.

However, the cost associated with studying these properties limited the computational and experimental investigations of κ to only a minute subset of all possible materials. A team of the NOMAD Laboratory recently made efforts to reduce these costs by creating an AI-guided workflow that hierarchically screens out materials to efficiently find new and better thermal insulators.

The work recently published in npj Computational Materials proposes a new way of using Artificial Intelligence (AI) to guide the high-throughput search for new materials. Instead of using physical/chemical intuition to screen out materials based on general, known or suspected trends, the new procedure learns the conditions that lead to the desired outcome with advanced AI methods. This work has the potential to quantify the search for new energy materials and increase the efficiency of these searches.

The first step in designing these workflows is to use advanced statistical and AI methods to approximate the target property of interest, κ in this case. To this end, the sure-independence screening and sparsifying operator (SISSO) approach is used. SISSO is a machine learning method that reveals the fundamental dependencies between different materials properties from a set of billions of possible expressions.

Compared to other “black-box” AI models, this approach is similarly accurate, but additionally yields analytic relationships between different material properties. This allows us to apply modern feature importance metrics to shed light on which material properties are the most important. In the case of κ, these are the molar volume, V_m; the high-temperature limit Debye Temperature, θ_D,∞; and the anharmonicity metric factor, σ^A.

Furthermore, the described statistical analysis allows to distill out rule-of-thumbs for the individual features that enable to a priori estimate the potential of material to be a thermal insulator. Working with the three most important primary features hence allowed to create AI-guided computational workflows for discovering new thermal insulators.

These workflows use state-of-the-art electronic structure programs to calculate each of the selected features. During each step materials were screened out that are unlikely to be good insulators based on their values of V_m, θ_D,∞, and σ^A. With this, it is possible to reduce the number of calculations needed to find thermally insulating materials by over two orders of magnitude.

In this work, this is demonstrated by identifying 96 thermal insulators (κ < 10 Wm^-1K^-1) in an initial set of 732 materials. The reliability of this approach was further verified by calculating κ for 4 of these predictions with highest possible accuracy.

Besides facilitating the active search for new thermoelectric materials, the formalisms proposed by the NOMAD team can be also applied to solve other urgent material science problems.

More information: Thomas A. R. Purcell et al, Accelerating materials-space exploration for thermal insulators by mapping materials properties via artificial intelligence, npj Computational Materials (2023). DOI: 10.1038/s41524-023-01063-y

Provided by Max Planck Society 

Human sweat is a rich source of health information, offering insights into a person’s hydration level, electrolyte balance, and overall physiological state. For instance, lactate level in sweat is a useful biomarker of exercise intensity. Its measurement can help estimate the amount of lactic acid in the blood and, in turn, predict muscle fatigue.

Today, wearable sensors make it possible to continuously monitor biomarkers such as sweat lactate. Using the latest microfluidics technology, scientists have developed devices that convey minuscule amounts of sweat to tiny chemical sensors, which can transmit their measurements in real time wirelessly.

However, one common problem in such devices is that their microfluidic channels tend to trap air bubbles present in the sweat. If these bubbles cover the sensor’s electrodes, the measurements get interrupted, interfering with the continuous monitoring of the target biomarker.

To address this issue, a research team, led by Associate Professor Isao Shitanda from Tokyo University of Science (TUS) in Japan, has come up with a novel microfluidic sweat lactate sensor whose measurements remain unaffected by the air bubbles. Their study, published in ACS Sensors, was co-authored by Dr. Masahiro Motosuke, Dr. Tatsunori Suzuki, Dr. Shinya Yanagita, and Dr. Takahiro Mukaimoto from TUS.

The proposed wearable device consists of a relatively simple layered structure—a conventional lactate oxidase sensor attached via double-sided tape to a microfluidic system made of a silicone polymer. When the person wearing the device begins to perspire, the sweat enters the microfluidic channels via four inlets and flows toward a reservoir near which the electrodes are located. Old sweat exits the system through an outlet as new sweat enters, and a small wireless transmitter reports the measured lactate levels.

The key innovation in the proposed design was the use of a larger-than-usual sweat reservoir. “By increasing the length of the reservoir in the microfluidic channel, a space of approximately four microliters was created for trapping any air bubbles that infiltrate the device, thereby preventing them from contacting the electrodes of the sensor,” explains Dr. Shitanda.

The researchers tested their sensor in a series of laboratory experiments. They verified that the bubble-trapping region worked as intended by injecting bubbles into the device while measuring lactate levels in artificial sweat. In addition, the measurements were not affected by the sweat flow rate, and the response of the sensor remained stable for approximately two hours.

Lastly, the researchers tested the device on a male volunteer who exercised on a stationary bike for almost an hour. The sensor showed a lactate concentration correlation ranging from 1 to 50 mM as well as a correlation between sweat and blood lactate levels.

Overall, the results of this study hint at the potential of wearable microfluidic sensors for monitoring sweat biomarkers during exercise. “Since the microfluidic system of the proposed lactate sensor is fabricated from a soft, flexible, and non-irritating material, it could be used to continuously monitor lactate levels in sweat, especially in sports and medicine,” remarks Dr. Shitanda.

“Wearable lactate sensors may become useful condition management tools in sports such as soccer and basketball, allowing team managers to know when it’s best to replace a player.”

Only time will tell what training management and healthcare monitoring will look like in the future as wearable sensors become more capable and reliable.

More information: Isao Shitanda et al, Air-Bubble-Insensitive Microfluidic Lactate Biosensor for Continuous Monitoring of Lactate in Sweat, ACS Sensors (2023). DOI: 10.1021/acssensors.3c00490

Journal information: ACS Sensors 

Provided by Tokyo University of Science 

Wearable medical devices, such as the soft exoskeletons that provide support for stroke patients or controlled drug delivery patches, have to be made of materials that can adapt intelligently and autonomously to the wearer’s movements and to changing environmental conditions. These are precisely the type of autonomously switchable polymer materials that have recently been developed by materials scientists at the University of Stuttgart and pharmacists at the University of Tübingen, whose research findings have been reported in Advanced Materials Technologies.

The collaborating groups, which are headed up by Prof. Sabine Ludwigs (Institute of Polymer Chemistry) and Prof. Holger Steeb (Institute of Mechanics, MIB) at the University of Stuttgart and Prof. Dominique Lunter (at the University of Tübingen’s Department of Pharmaceutical Technology), have published a paper entitled “Autonomous Adaptation of Intelligent Humidity-Programmed Hydrogel Patches,” in which they demonstrate how intelligent polymer materials can be produced, whereby the word “intelligent” refers to the fact that the properties of the material can adapt autonomously to the environmental conditions in which they are used.

The rigidity of the materials in question can change by more than four orders of magnitude depending on humidity and temperature, and can undergo elastic changes even when subjected to major deformations, which enables the mechanical properties to adjust to the respective application.

Very high degree of adaptability

One of the authors of the paper, Sabine Ludwigs, refers to these materials as “intelligent rubber materials” and explains that “this high level of adaptability makes our polymers ideally suited for robots made of soft organic materials, such as those used in biomedicine or in search and rescue missions—the keyword here being ‘soft robotics.’ These polymers are also very well suited for use in smart skin applications, such as exoskeletons made of soft flexible fabrics.”

For both applications, the material needs to allow for both fast and slow movements, meaning it needs to have adjustable viscoelastic properties. “That is exactly what the material we have developed is able to do,” says Holger Steeb.

In addition, the material’s hydro-adaptability and reversible water absorption capacity make it suitable for use as a patch for the controlled release of drugs via the skin. The researchers specifically conducted experiments with the release of the painkiller diclofenac in a skin model. “The key mechanism is that it is the patch itself that controls the release of the active ingredient in response to the variable moisture levels of the wound, i.e., depending on the fluids that seep out of the wound,” says Dominique Lunter, a pharmaceutical expert based in Tübingen, Germany.

The relevant research was carried out as part of the recently established cross-faculty Functional Soft Materials Laboratory (FSM Lab) at the University of Stuttgart’s Data-integrated Simulation Science Cluster of Excellence (EXC 2075, SimTech). This is the result of a very successful collaboration between two research groups headed up by Sabine Ludwigs who specializes in polymer chemistry, and Holger Steeb, whose work is focused on the mechanics and function of smart polymer materials.

The vision: Materials that respond to active triggers

Going forward, the researchers are planning to investigate multifunctional material systems, which are able to autonomously adapt to their environment as well as react to active triggers, such as electrical stimuli. They are also planning to use simulations as a basis for modeling and predicting complex architectures.

As such, the polymer materials research results also benefit the studies being carried out by the university’s Data-Integrated Simulation Science (SimTech) cluster of excellence.

More information: Stephan Pflumm et al, Autonomous Adaption of Intelligent Humidity‐Programmed Hydrogel Patches for Tunable Stiffness and Drug Release, Advanced Materials Technologies (2023). DOI: 10.1002/admt.202300937

Journal information: Advanced Materials Technologies 

Provided by University of Stuttgart 

Polymers have become an indispensable part of everyday life. However, the current polymers represent only a small fraction of the huge number of polymers that theoretically exist.

Prof. Dr. Christopher Kuenneth at the University of Bayreuth, Germany, together with research partners in Atlanta, U.S., have now developed a digital system that promises extraordinarily high economical, technological and ecological benefits: from around 100 million theoretically possible polymers, their system can precisely select those materials that have an ideal property profile for targeted applications at unprecedented speed.

The new system is presented in Nature Communications.

Kuenneth, Professor of Computational Materials Science at the Faculty of Engineering at the University of Bayreuth, and Prof. Dr. Rampi Ramprasad at the Georgia Institute of Technology in Atlanta have named their new system “polyBERT.” The name comes from the interdisciplinarity from which polyBERT emerged: insights, concepts and techniques of polymer chemistry, linguistics and natural language processing, and the new artificial intelligence paradigm.

polyBERT is a system that treats the chemical structure of polymers like a chemical language: each word that can be formed in this language is a unique name for a theoretically possible polymer. The molecular building blocks and structures of respective polymers are reflected in these names. Building on new insights from linguistics and computer science, polyBERT has been trained and developed to a learning system by the research team in Bayreuth and Atlanta.

From polymer language to digital ‘fingerprints’

In a first step, polyBERT has learned the names of about 100 million theoretically possible polymers. These names are combinations of molecular units contained in approximately 13,000 polymers. The training of polyBERT makes it understand the polymer language, and correctly identify building blocks and structures of about 100 million polymers. The learning digital system can even use the polymer language on its own. This means that polyBERT can generate further names of previously unknown but theoretically possible polymers.

Linked to the chemical language expertise is another capability: polyBERT automatically translates polymer names that it knows into numerical representations, so-called “fingerprints.” Each fingerprint is a unique code word consisting of numbers from which the building blocks and structure of the respective polymer can be inferred. This automatic generation of digital fingerprints is far less error-prone and much faster than human-generated fingerprints for each chemical structure of polymers.

Rapid and precise prediction of polymer properties

polyBERT derives its enormous practical relevance from the teaching process, by the researchers in Bayreuth and Atlanta, about numerous characteristic polymer properties that are particularly relevant for technological applications. The system is therefore able to unambiguously correlate fingerprints and properties of polymers.

Novel techniques from the field of artificial intelligence enable polyBERT to precisely select, with high accuracy and at unprecedented speed, those polymers required for specific applications from the 100 million theoretically possible polymers.

“polyBERT is an exceptionally high-performance system for rapid and accurate prediction of polymer properties. Therefore, our research has the potential to significantly accelerate the design, synthesis and technological application of polymers,” says Kuenneth.

Past study identifies bioplastics

The importance of machine learning approaches to polymer research is already demonstrated by a past study that Kuenneth published in the journal Communications Materials in December 2022. Here, he and research partners at Atlanta and the Los Alamos National Laboratories in the United States present a similar artificial neural network-based system for predicting polymer properties.

This system is capable of countering global plastic waste pollution. About 75 percent of industrially produced plastics are based on fossil raw materials. The new system can significantly accelerate the search for biopolymers which can replace these plastics: The authors of the study identified 14 biologically producible and degradable polymers from 1.4 million possible candidates that can replace the current industrial plastics as soon as fast and cost-effective synthesis processes become available.

More information: Christopher Kuenneth et al, polyBERT: a chemical language model to enable fully machine-driven ultrafast polymer informatics, Nature Communications (2023). DOI: 10.1038/s41467-023-39868-6

Journal information: Nature Communications 

Provided by Bayreuth University