Category: Chemistry

by Chinese Academy of Sciences

Researchers led by Prof. Gao Xiang from the Shenzhen Institute of Advanced Technology (SIAT) of the Chinese Academy of Sciences and Prof. Lu Lu from the Harbin Institute of Technology have proposed a novel method to transform wastewater contaminants into valuable chemicals using sunlight, thus paving the way for sustainable and eco-friendly chemical manufacturing.

The study was published in Nature Sustainability.

Conventional chemical manufacturing relies on energy-intensive processes. Semiconductor biohybrids, integrating efficient light-harvesting materials with superior living cells, have emerged as an exciting advancement in utilizing solar energy for chemical production. However, the challenge lies in finding an economically viable and environmentally friendly approach to scale up this technology.

In this study, the researchers set out to convert pollutants from wastewater into semiconductor biohybrids directly in the wastewater environment. The concept involves utilizing the organic carbon, heavy metals, and sulfate compounds present in wastewater as the raw materials for constructing these biohybrids, and subsequently converting them into valuable chemicals.

Nevertheless, real industrial wastewater usually varies in its composition of major organic pollutants, heavy metals, and complex pollutants, all of which are often toxic to bacterial cells and difficult for them to metabolize efficiently. It also contains high levels of salt and dissolved oxygen that require bacteria with an aerobic sulfate reduction capacity. Thus, it’s challenging to use wastewater as bacteria feedstock.

To overcome this, the researchers selected a fast-growing marine bacterium, Vibrio natriegens, which has exceptional tolerance for high salt concentration and a capacity for utilizing various carbon sources. They introduced an aerobic sulfate reduction pathway into V. natriegens and trained the engineered strain to utilize different metal and carbon sources in order to produce semiconductor biohybrids directly from such wastewater.

Their primary target chemical for production was 2,3-butanediol (BDO), a valuable commodity chemical.

By engineering a strain of V. natriegens, they generated hydrogen sulfide, which played a pivotal role in facilitating the production of CdS nanoparticles that efficiently absorb light. These nanoparticles, renowned for their biocompatibility, enabled the in-situ creation of semiconductor biohybrids and enabled the non-photosynthetic bacteria to utilize light.

The results showed that these sunlight-activated biohybrids exhibited significantly enhanced BDO production, surpassing yields achievable through bacterial cells alone. Furthermore, the process displayed scalability, achieving solar-driven BDO production on a substantial 5-liter scale using actual wastewater.

“The biohybrid platform not only boasts a lower carbon footprint but also reduces product costs, leading to an overall smaller environmental impact when compared to both traditional bacterial fermentation and fossil fuel-based BDO production methods,” said Prof. Gao. “Remarkably, these biohybrids could be produced using a variety of wastewater sources.”

More information: Pi, S. et al, Solar-driven waste-to-chemical conversion by wastewater-derived semiconductor biohybrids, Nature Sustainability (2023). DOI: 10.1038/s41893-023-01233-2. www.nature.com/articles/s41893-023-01233-2

Journal information: Nature Sustainability 

Provided by Chinese Academy of Sciences 

by FAPESP

Polyalthic acid from copaiba oil is an effective antibacterial and should be used to develop alternative medications that can contribute to the effort to overcome antimicrobial resistance (“superbugs”), according to an article by researchers based in Brazil and the United States published in the journal Antibiotics.

More than 2.8 million antibiotic-resistant infections occur in the US and more than 35,000 people die as a result each year, says a report issued in 2019 by the Centers for Disease Control and Prevention (CDC).

Antimicrobial or antibiotic resistance is when germs (bacteria, fungi) develop the ability to defeat the antibiotics designed to kill them (it does not mean our bodies are resistant to antibiotics). It is expected to become the main global cause of death by 2050.

The crisis is due to improper prescribing of antibiotics, intense use of these drugs in agriculture, and overuse of a small number since the leading pharmaceutical companies decided to abandon the development of antibiotics owing to high cost and low return on investment.

In this context, resorting to plants as a source of novel drugs has proved a promising alternative.

To stimulate knowledge production in this field, researchers in Brazil at the University of São Paulo’s Ribeirão Preto School of Pharmaceutical Sciences (FCFRP-USP) and São Carlos Institute of Physics (IFSC-USP), in collaboration with colleagues at the University of Franca (UNIFRAN), also in Brazil, and the College of Pharmacy and Health Sciences at Western New England University (WNE) in the US, investigated copaiba oil, derived from Copaifera trees and traditionally used in the Amazon region as a natural remedy for its wound-healing, anti-inflammatory and antimicrobial properties. Its main constituents are diterpenes (20%), including polyalthic acid, and sesquiterpenes (80%). Both groups of compounds are anti-inflammatory and antimicrobial.

The researchers synthesized four polyalthic acid analogs with structural modifications to make them more active against pathogens, and investigated their efficacy against biofilms of Staphylococcus epidermidis, a bacterium that causes skin and digestive tract infections, and against several Gram-positive bacteria (Enterococcus faecalis, Enterococcus faecium, S. epidermidis and Staphylococcus aureus). They also determined the minimum dosage required to inhibit planktonic (free-floating) bacteria.

Activity tests and comparisons with the original polyalthic acid and the drug most prescribed by physicians showed that the analogs developed by the researchers eradicated S. epidermidis, and were active against all the Gram-positive bacteria tested. Although they were less active than the prescribed drug, the results reinforced the importance of additional in vitro and in vivo testing of the substance.

“The advantage of studying polyalthic acid is that previous research has shown that some terpenes don’t lose their activity, and their continuous use therefore doesn’t make bacteria develop resistance,” said Cássia Suemi Mizuno, a researcher at WNE and last author of the article.

The analogs were found to be safe in an analysis of hemolytic activity, i.e. their ability to destroy red blood cells.

Next steps

“Our research is an important contribution to efforts to beat antimicrobial resistance and serves as a foundation on which other groups can made further progress,” Mizuno said.

Next steps will include producing more derivatives with other parts of the polyalthic acid molecule, improving their activity and pursuing prospective partners in the pharmaceutical industry for more research, she added.

Investment in copaiba oil extraction in the Amazon will be needed, as will the recruitment of forest dwellers who are familiar with the native vegetation and can identify the species with the highest level of polyalthic acid content (Copaifera reticulata Ducke).

“It should be stressed that we don’t destroy any trees in our research. Extraction of copaiba oil is like rubber tapping. You just make a groove in the bark of the tree trunk,” Mizuno said.

More information: Marcela Argentin et al, Synthesis and Antibacterial Activity of Polyalthic Acid Analogs, Antibiotics (2023). DOI: 10.3390/antibiotics12071202

Provided by FAPESP 

by Li Yuan, Chinese Academy of Sciences

Alkaline CO₂ electrolysis can produce multicarbon (C₂₊) products such as ethylene and acetate, yet suffers from low CO₂ utilization efficiency.

Tandem electrolysis, which connects solid oxide or acidic CO₂ electrolysis to CO and alkaline CO electrolysis to C₂₊ products in sequential electrolyzers, is a carbon-efficient route. However, to date, CO electrolysis generally shows high current density and selectivity for C₂₊ products, but selective generation of a specific C₂₊ product is still challenging.

Recently, a research team led by Profs. Wang Guoxiong and Gao Dunfeng from the Dalian Institute of Chemical Physics (DICP) of the Chinese Academy of Sciences (CAS) has proposed a new strategy by constructing metal-organic interfaces for CO electrolysis to acetate with high selectivity.

This study was published in Angewandte Chemie International Edition on Sept. 25.

The researchers tuned the reaction microenvironments surrounding catalytically active sites by constructing Cu-organic interfaces through in-situ electrochemical reconstruction of molecular Cu complexes. Benefiting from the favorable reaction microenvironment, they achieved good catalytic performance for CO electrolysis to acetate, in terms of current density, Faradaic efficiency, and yield.

With a copper phthalocyanine (CuPc) electrode measured in a home-made alkaline membrane electrode assembly (MEA) electrolyzer, they obtained an acetate Faradaic efficiency as high as 84.2% and an acetate carbon selectivity of 92.1% at 500 mA cm^-2. The maximum acetate partial current density and formation rate reached 605 mA cm^-2 and 0.38 mmol min^-1, respectively, translating into an acetate yield as high as 63.4%.

The Cu-organic interface created a favorable reaction microenvironment that enhanced *CO adsorption, lowered the energy barrier for C-C coupling, and facilitated the formation of CH₃COOH over other multicarbon products, thus rationalizing the selective acetate production.

“Our study highlights the potential of constructing metal-organic interfaces for tailoring reaction microenvironments for highly selective production of a specific C₂₊ product from CO electrolysis,” said Prof. Gao.

More information: Youwen Rong et al, Directing the Selectivity of CO Electrolysis to Acetate by Constructing Metal‐Organic Interfaces, Angewandte Chemie International Edition (2023). DOI: 10.1002/anie.202309893

Journal information: Angewandte Chemie International Edition 

Provided by Chinese Academy of Sciences 

by Staffordshire University

Forensic fibers can survive underwater for much longer than previously thought—which could help criminal investigators uncover vital evidence.

New research led by Staffordshire University’s Centre for Crime, Justice and Security has found that fiber evidence can survive on fabrics underwater for several weeks.

Claire Gwinnett, Professor of Forensic and Environmental Science, explained, “Evidence, such as weapons and victim’s bodies, are often found in aquatic environments including rivers and lakes.”

“However, if items have been submerged in water for more than seven days then many forensic examiners believe that any valuable trace evidence will be gone and won’t seek it out.”

To date, very few studies have investigated fiber persistence on fabrics submerged underwater. The dynamic nature of aquatic environments mean that the studies are difficult to conduct in situ and variables, such as water flow rate, are not possible to control.

The Forensic Fiber Freshwater (3F) project was conducted in partnership with Lunz Mesocosm Infrastructure (LMI), WasserCluster Lunz, the University of Vienna and Italy’s University of Milano-Bicocca.

This study used artificial streams, known as mesocosms, to investigate the persistence rate of polyester fibers on different fabric types over a four-week exposure time.

Usually used for ecological research, this is the first time that mesocosms have been employed to look at forensic evidence.

Two flow velocities, high and low, were used on three textiles: woolen/nylon mix carpet, 100% polyester fleece, and 95% polyester/5% elastane sports vest.

Initial loss rates were highest for the first hour of submergence for the carpet, fleece and sports vest. However, persistence rates remained mostly constant after 24 hours for all textiles and the two flow rates used did not significantly affect fiber persistence.

Ph.D. researcher Afsané Kruszelnicki said, “It would be expected that a higher flow rate would have a lower number of retained fibers compared to a lower flow rate, yet no significant difference was seen in all but one condition.”

“Even after four weeks, the lowest percentage of remaining fibers was 33.4%. This clearly indicates that it is extremely valuable to search for fiber evidence even after a long exposure time.”

Professor Gwinnett said, “Our findings could change how police direct investigations and help to uncover forensic evidence that was previously thought to be lost. We hope this will help investigators to identify more suspects and ultimately lead to more convictions.”

“The study also highlights the benefits of using mesocosms which mimic realistic aquatic environments in a controlled setting. This is the first time that mesocosms have been used to look at forensic evidence and we hope it will pave the way for further studies to investigate different types of trace evidence such as gunshot residue, pollen, fingerprints or DNA.”

Dr. Katrin Attermeyer, coordinator of the stream mesocosms in Lunz am See and aquatic microbial ecologist at WasserCluster Lunz and the University of Vienna, added, “This interdisciplinary collaboration between forensic scientists and aquatic ecologists has not only provided insights into other sciences, but has also shown that mesocosms, traditionally used to answer ecological questions, are a valuable asset to other research areas such as forensic sciences.”

The findings are published in the journal Forensic Science International.

More information: Afsané Kruszelnicki et al, An investigation into the use of riverine mesocosms to analyse the effect of flow velocity and recipient textiles on forensic fibre persistence studies, Forensic Science International (2023). DOI: 10.1016/j.forsciint.2023.111818

Journal information: Forensic Science International 

Provided by Staffordshire University 

by National Institute for Materials Science

GPT-4, the latest version of the artificial intelligence system from OpenAI, the developers of Chat-GPT, demonstrates considerable usefulness in tackling chemistry challenges, but still has significant weaknesses. “It has a notable understanding of chemistry, suggesting it can predict and propose experimental results in ways akin to human thought processes,” says chemist Kan Hatakeyama-Sato, at the Tokyo Institute of Technology.

Hatakeyama-Sato and his colleagues discuss their exploration of the potential of GPT-4 in chemical research in the journal Science and Technology of Advanced Materials: Methods.

GPT-4, which stands for Generative Pre-trained Transformer 4, belongs to a category of artificial intelligence systems known as large language models. These can gather and analyze vast quantities of information in search of solutions to challenges set by users. One advance for GPT-4 is that it can use information in the form of images in addition to text.

Although the specific datasets used for training GPT-4 have not been disclosed by its developers, it has clearly learned a significant amount of detailed chemistry knowledge. To analyze its capabilities, the researchers set the system a series of chemical tasks focused on organic chemistry—the chemistry of carbon-based compounds. These covered basic chemical theory, the handling of molecular data, predicting the properties of chemicals, the outcome of chemical processes and proposing new chemical procedures.

The results of the investigation were varied, revealing both strengths and significant limitations. GPT-4 displayed a good understanding of general textbook-level knowledge in organic chemistry. It was weak, however, when set tasks dealing with specialized content or unique methods for making specific organic compounds. It displayed only partial efficiency in interpreting chemical structures and converting them into a standard notation. One interesting feat was its ability to make accurate predictions for the properties of compounds that it had not specifically been trained on. Overall, it was able to outperform some existing computational algorithms, but fell short against others.

“The results indicate that GPT-4 can tackle a wide range of tasks in chemical research, spanning from textbook-level knowledge to addressing untrained problems and optimizing multiple variables,” says Hatakeyama-Sato. “Inevitably, its performance relies heavily on the quality and quantity of its training data, and there is much room for improvement in its inference capabilities.”

The researchers emphasize that their work was only a preliminary investigation, and that future research should broaden the scope of the trials and dig deeper into the performance of GPT-4 in more diverse research scenarios.

They also hope to develop their own large language models specializing in chemistry and explore their integration with existing techniques.

“In the meantime, researchers should certainly consider applying GPT-4 to chemical challenges, possibly using hybrid methods that include existing specialized techniques,” Hatakeyama-Sato concludes.

More information: Kan Hatakeyama-Sato et al, Prompt engineering of GPT-4 for chemical research: what can/cannot be done?, Science and Technology of Advanced Materials: Methods (2023). DOI: 10.1080/27660400.2023.2260300

Provided by National Institute for Materials Science

by American Chemical Society

As Halloween approaches, so too does the anticipation of a trick-or-treating stash filled with fun-sized chocolate candy bars. But to satisfy our collective craving for this indulgence, millions of cocoa pods are harvested annually. While the beans and pulp go to make chocolate, their husks are thrown away. Now, researchers reporting in ACS Sustainable Chemistry & Engineering show that cocoa pod husks could be a useful starting material for flame retardants.

It’s estimated that about 24 million tons of leftover cocoa pod husks are produced yearly. Waste husks have been explored as a source of carbohydrates and sugars, but they also contain lignin, a tough lipid polymer found in many woody plants. And lignin could be a renewable replacement for some substances typically derived from petroleum, such as flame retardants.

While most methods to produce lignin have centered on hardwood trees, some scientists have processed other plant materials that would otherwise go to waste, such as rice husks and pomegranate peels. So, Nicholas J. Westwood and coworkers wanted to see if high-quality lignin could be extracted from cocoa pod husks and determine whether it has the potential to make valuable, practical materials.

The researchers obtained cocoa husks and milled them into a powder. After rinsing to remove fatty residues, they boiled the powdered husks in a mixture of butanol and acid, a standard lignin extraction method called the butanosolv process. They next confirmed the isolated lignin’s quality and high purity, finding no evidence of carbohydrates or other contaminants.

Then, over the course of three chemical steps, the team modified the pure lignin biopolymer to have flame-retardant properties. They attached 9,10-dihydro-9-oxa-10-phosphaphenanthrene-10-oxide, which is a fire suppressant molecule called DOPO, into the backbone of the lignin polymer.

In experiments, when the modified lignin was heated, it charred—but did not burn up—a sign that it could act as a flame retardant. The researchers recognize that human safety tests are important and plan to conduct them after the next phase of testing. In the future, the researchers say they will optimize the properties of their cocoa pod husk-based flame-retardant materials.

More information: Daniel J. Davidson et al, Organosolv Pretreatment of Cocoa Pod Husks: Isolation, Analysis, and Use of Lignin from an Abundant Waste Product, ACS Sustainable Chemistry & Engineering (2023). DOI: 10.1021/acssuschemeng.2c03670

Journal information: ACS Sustainable Chemistry & Engineering 

Provided by American Chemical Society 

by University of Vienna

The DNA double helix is composed of two DNA molecules whose sequences are complementary to each other. The stability of the duplex can be fine-tuned in the lab by controlling the amount and location of imperfect complementary sequences.

Fluorescent markers bound to one of the matching DNA strands make the duplex visible, and fluorescence intensity increases with increasing duplex stability. Now, researchers at the University of Vienna succeeded in creating fluorescent duplexes that can generate any of 16 million colors—a work that surpasses the previous 256 colors limitation.

This very large palette can be used to “paint” with DNA and to accurately reproduce any digital image on a miniature 2D surface with 24-bit color depth. This research was published in the Journal of the American Chemical Society.

The unique ability of complementary DNA sequences to recognize and assemble as duplexes is the biochemical mechanism for how genes are read and copied. The rules of duplex formation (also called hybridization) are simple and invariable, making them predictable and programmable too.

Programming DNA hybridization allows for synthetic genes to be assembled and large-scale nanostructures to be built. This process always relies on perfect sequence complementarity. Programming instability vastly expands our ability to manipulate molecular structure and has applications in the field of DNA and RNA therapeutics.

In this novel study, researchers at the Institute of Inorganic Chemistry at the University of Vienna showed that controlled hybridization can result in the creation of 16 million colors and can accurately reproduce any digital image in DNA format.

A canvas the size of a fingernail

To create color, different small DNA strands linked to fluorescent molecules (markers) that can emit either red, green or blue color are hybridized to a long complementary DNA strand on the surface. To vary the intensity of each color, the stability of the duplex is lowered by carefully removing bases of the DNA strand at pre-defined positions along the sequence.

With lower stability comes a darker shade of color, and fine-tuning this stability results in the creation of 256 shades for all color channels. All shades can be mixed and matched within a single DNA duplex, thus generating 16 million combinations and matching the color complexity of modern digital images. To achieve this level of precision in DNA-to-color conversion, > 45,000 unique DNA sequences had to be synthesized.

To do so, the research team used a method for parallel DNA synthesis called maskless array synthesis (MAS). With MAS, hundreds of thousands of unique DNA sequences can be synthesized at the same time and on the same surface, a miniature rectangle the size of a fingernail.

Since the approach allows the experimenter to control the location of any DNA sequence on that surface, the corresponding color can also be selectively assigned to a chosen location. By automating the process using dedicated computer scripts, the authors were able to transform any digital image into a DNA photocopy with accurate color rendition. “Essentially, our synthesis surface becomes a canvas for painting with DNA molecules at the micrometer scale,” says Jory Lietard, PI in the Institute of Inorganic Chemistry.

Resolution is currently limited to XGA, but the reproduction process is applicable to 1080p, as well as potentially 4K image resolution. “Beyond imaging, a DNA color code could have very useful applications in data storage on DNA,” says Tadija Kekić, Ph.D. candidate in the group of Jory Lietard. As evidenced by the 2023 Nobel Prize attributed to the development of quantum dots, the chemistry of color has a bright future ahead.

More information: Tadija Kekić et al, A Canvas of Spatially Arranged DNA Strands that Can Produce 24-bit Color Depth, Journal of the American Chemical Society (2023). DOI: 10.1021/jacs.3c06500

Journal information: Journal of the American Chemical Society 

Provided by University of Vienna 

by Virginia Tech

As the COVID-19 pandemic scattered and isolated people, researchers across Virginia Tech connected for a data-driven collaboration seeking improved drugs to fight the disease and potentially many other illnesses.

A multidisciplinary collaboration spanning several colleges at Virginia Tech resulted in a newly published study, “Data Driven Computational Design and Experimental Validation of Drugs for Accelerated Mitigation of Pandemic-like Scenarios,” in the Journal of Physical Chemistry Letters.

The study focuses on using computer algorithms to generate adaptations to molecules in compounds for existing and potential medications that can improve those molecules’ ability to bind to the main protease, a protein-based enzyme that breaks down complex proteins, in SARS-CoV-2, the virus that causes COVID-19.

This process allows exponentially more molecular adaptations to be considered than traditional trial-and-error methods of testing drugs one by one could allow. Candidate molecule adaptations can be identified among myriad possibilities, then narrowed to a few or one that can be created in a laboratory and tested for effectiveness.

“We present a novel transferable data-driven framework that can be used to accelerate the design of new small molecules and materials, with desired properties, by changing the combination of building blocks as well as decorating them with functional groups,” said Sanket A. Deshmukh, associate professor of chemical engineering in the College of Engineering. A “functional group” is a cluster of atoms that generally retains its characteristic properties, regardless of the other atoms in the molecule.

“Interestingly, the newly designed functionalized drug not only had a better half maximal effective concentration value than its parent drug, but also several of the proposed and used antivirals, including remdesivir,” Deshmukh said, referring to a measure of compound potency.

Moving through all the phases of the study would not have been possible without extensive cross-departmental collaboration.

Four Virginia Tech faculty members—Deshmukh; Anne M. Brown, associate professor with University Libraries and the Department of Biochemistry in the College of Agriculture and Life Sciences; Andrew Lowell, assistant professor in the Department of Chemistry in the College of Science; and James Weger-Lucarelli, assistant professor in the Department of Biomedical Sciences and Pathobiology at the Virginia-Maryland College of Veterinary Medicine—are among 13 co-authors of the published study.

The Deshmukh group’s expertise in developing transferable computational models and frameworks for accelerated design of drug-like small molecules and materials, and Brown’s extensive computational expertise in protein structure-function relationships, meshed seamlessly as a baseline for the study.

“Sanket’s group had a molecular repurposing framework, and I have experience with exploiting protein targets,” said Brown. “Combined with Andrew, who does the synthesis, which is to make the compound, and then James doing the testing and the viral assays, we formed a fantastic collaboration.”

But the faculty members stress that it was the graduate students and postdoctoral students in the laboratories who made the study possible. Nine of them are co-authors: Samrendra K. Singh, chemical engineering; Kelsie King, genetics, bioinformatics, and computational biology; Cole Gannett, chemistry; Christina Chuong, biomedical and veterinary sciences; Soumil Y. Joshi, chemical engineering; Charles Plate, chemical engineering; Parisa Farzeen, chemical engineering; Emily M. Webb, entomology; and Lakshmi Kumar Kunche, chemical engineering.

The professors said the students communicated well with one another without any prompting from their mentors. “I think one of the great things to see is the students really talking with one another and collaborating with one another as well without us having to say ‘Do this,'” Deshmukh said.

Finally, the functionalized molecules were tested against live SARS-CoV-2 in a veterinary college laboratory by Weger-Lucarelli and his team.

“Initial virtual screening of the existing database identified a parent compound that was expected to inhibit the protease of SARS-CoV-2,” Weger-Lucarelli said. “Then the data-driven framework altered the structure of that molecule to enhance that activity. We compared those side by side to show that this new compound that was expected to be more potent against SARS-CoV-2 than the parent compound was, in fact, more potent against SARS-CoV-2.”

The process to develop and test a functionalized molecule against COVID-19 has many potential applications even beyond mitigation of COVID-19. Studies are ongoing among the team to employ the same type of research to find functionalized molecules that may be able to treat hepatitis E, dengue fever and chikungunya, the latter two being mosquito-borne illnesses.

“Another direction we’re going in is that we’re targeting proteases and enzymes from other viruses and trying to design other new molecules,” Lowell said.

The algorithm process also has potential in non-biological uses, Sankit said. The “approach is very versatile and is being applied to functionalize and design other materials such as metal organic frameworks (MOFs), glycomaterials, polymers, etc.,” the paper states.

The assembled interdisciplinary team is planning to continue its collaborations.

“None of us could do this work without the other people in this collaboration,” Weger-Lucarelli said.

“This is a great example of the synergy between going from computational prediction to chemical synthesis to testing in viruses,” Brown said, “and how we at Virginia Tech are really emphasizing that interplay between these three areas and taking that to the next level to develop strong collaborative teams.”

More information: Data Driven Computational Design and Experimental Validation of Drugs for Accelerated Mitigation of Pandemic-like Scenarios, The Journal of Physical Chemistry Letters (2023).

Journal information: Journal of Physical Chemistry Letters 

Provided by Virginia Tech 

by Tohoku University

A group of researchers have unraveled the mysteries behind a recently identified material—zirconium nitride (ZrN)—that helps power clean energy reactions. Their proposed framework will help future designs for transition metal nitrides, paving a path for generating cleaner energy.

The study was published in the journal Chemical Science on July 26, 2023, where it featured as the front cover article.

Anion exchange membrane fuel cells (AEMFC) are devices that use hydrogen and oxygen to make clean electricity through chemical reactions, specifically the hydrogen oxidation reaction and the oxygen reduction reaction (ORR). AEMFCs, with their ability to operate in alkaline conditions, provide a suitable environment for earth-based catalysts, offering a cheaper alternative to other efficient catalyst materials, such as platinum.

Recent studies have shown that ZrN exhibits efficient performances—even outperforming platinum—when used for the ORR in alkaline media. ZrN, while not an Earth-abundant material, is still more cost-effective than alternatives. But what lay behind its impressive performance has remained a mystery to scientists.

“To implement our new theoretical framework for ZrN, we decided to employ surface state analysis, electric field effect simulations, and pH-dependent microkinetic modeling,” explains Hao Li, associate professor at Tohoku University’s Advanced Institute for Materials Research (WPI-AIMR) and corresponding author of the paper.

Surface analysis revealed that ZrN has a very thin layer of HO when it is undergoing ORR. This thin layer helps molecules stick to it in a way that is beneficial for the ORR. Moreover, the electric field effect simulations demonstrate that atomic oxygen sticking to this thin-covered surface undergo minimal changes, thereby sticking moderately.

After performing computer simulations, the researchers found that ZrN reaches the sweet spot of ORR in alkaline conditions.

“Our tested theory works well not just for ZrN but also for other materials like Fe₃N, TiN, and HfN, which are similar to ZrN, meaning our idea explains how these materials can be utilized for clean energy too,” adds Hao. “Our framework will help rationalize and design transition metal nitrides for alkaline ORR.”

In the future, Hao and his team plan to extend this framework to study other industrially significant reactions, such as the oxygen evolution reaction.

More information: Heng Liu et al, Origin of the superior oxygen reduction activity of zirconium nitride in alkaline media, Chemical Science (2023). DOI: 10.1039/D3SC01827J

Journal information: Chemical Science 

Provided by Tohoku University