Category: Chemistry

by University of Wisconsin-Madison

The world needs greener ways to make chemicals. In a new study, University of Wisconsin–Madison researchers demonstrate one potential path toward this goal by adapting hydrogen fuel cell technologies. These technologies are already used to power some electric vehicles, laptops and cell phones.

“The chemical industry is a massive energy consumer, and there is a big push to decarbonize the industry,” says Shannon Stahl, a professor in the UW–Madison Department of Chemistry who guided much of the research. “Renewable electricity can provide energy to produce chemicals with a much lower carbon footprint than burning fossil fuels.”

The conventional process uses large quantities of zinc metal as the source of electrons, but handling zinc is complicated and generates large amounts of environmentally unfriendly waste. Working with scientists at the pharmaceutical maker Merck & Co. Inc., UW–Madison chemists and engineers sought to develop a more sustainable method to manufacture ingredients needed to make many types of drugs.

In their search for an alternative process, the researchers took inspiration from hydrogen fuel cells, which use hydrogen gas as the source of electrons to generate electricity.

“The process we are working with needs a green source of electrons,” says Stahl. “We realized that fuel cell technology could be modified to make chemicals rather than electricity,”

Hydrogen gas is an ideal choice in many ways, according to Stahl. It can be generated from renewable electricity, and it creates very little waste. Developing a hydrogen-based way to make pharmaceuticals aligns with renewed interest in a “hydrogen economy.”

“This work is connected to a broader effort to create a hydrogen infrastructure that goes beyond fuel cells and energy production,” says Mathew Johnson, a postdoctoral researcher in the chemistry department who led the study. “This work shows that hydrogen can be combined with electricity to make new drugs.”

The researchers developed a system that uses a type of organic compound called a quinone to pull electrons away from hydrogen. An important feature of this process is that it works well in the absence of water. Fuel cells typically need water to operate effectively, but water can interfere with steps used to make the drug ingredients.

The system then uses electricity to supercharge the electrons, giving the electrons more energy than hydrogen could normally provide.

The team, which included postdoctoral researcher Jack Twilton, chemistry professor Daniel Weix and chemical and biological engineering professor Thatcher Root, described their new system in a paper published Aug. 21 in the journal Nature. They show how it can be used to make dozens of important organic molecules, including a large batch of a pharmaceutical ingredient.

The team is now working to improve the process so it can be used for industrial-scale production. And Stahl and his collaborators see even bigger opportunities for this technology.

“This is a broadly applicable technology for chemical production,” says Johnson. “Many chemical processes need electrons. This is not limited to pharmaceuticals. It should be a very versatile technology.”

More information: Jack Twilton et al, Quinone-mediated hydrogen anode for non-aqueous reductive electrosynthesis, Nature (2023). DOI: 10.1038/s41586-023-06534-2

Journal information: Nature 

Provided by University of Wisconsin-Madison

by Osaka University

How is a donut similar to a coffee cup? This question often serves as an illustrative example to explain the concept of topology. Topology is a field of mathematics that examines the properties of objects that remain consistent even when they are stretched or deformed—provided they are not torn or stitched together. For instance, both a donut and a coffee cup have a single hole. This means, theoretically, if either were pliable enough, it could be reshaped into the other.

This branch of mathematics provides a more flexible way to describe shapes in data, such as the connections between individuals in a social network or the atomic coordinates of materials. This understanding has led to the development of a novel technique: topological data analysis.

In a study, titled “Persistent homology-based descriptor for machine-learning potential of amorphous structures,” in The Journal of Chemical Physics, researchers from SANKEN (The Institute of Scientific and Industrial Research) at Osaka University and two other universities have used topological data analysis and machine learning to formulate a new method to predict the properties of amorphous materials.

A standout technique in the realm of topological data analysis is persistent homology. This method offers insights into topological features, specifically the “holes” and “cavities” within data. When applied to material structures, it allows us to identify and quantify their crucial structural characteristics.

Now, these researchers have employed a method that combines persistent homology and machine learning to predict the properties of amorphous materials. Amorphous materials, which include substances like glass, consist of disordered particles that lack repeating patterns.

A crucial aspect of using machine-learning models to predict the physical properties of amorphous substances lies in finding an appropriate method to convert atomic coordinates into a list of vectors. Merely utilizing coordinates as a list of vectors is inadequate because the energies of amorphous systems remain unchanged with rotation, translation, and permutation of the same type of atoms.

Consequently, the representation of atomic configurations should embody these symmetry constraints. Topological methods are inherently well-suited for such challenges. “Using conventional methods to extract information about the connections between numerous atoms characterizing amorphous structures was challenging. However, the task has become more straightforward with the application of persistent homology,” explains Emi Minamitani, the lead author of the study.

The researchers discovered that by integrating persistent homology with basic machine-learning models, they could accurately predict the energies of disordered structures composed of carbon atoms at varying densities. This strategy demands significantly less computational time compared to quantum mechanics-based simulations of these amorphous materials.

The techniques showcased in this study hold potential for facilitating more efficient and rapid calculations of material properties in other disordered systems, such as amorphous glasses or metal alloys.

More information: Emi Minamitani et al, Persistent homology-based descriptor for machine-learning potential of amorphous structures, The Journal of Chemical Physics (2023). DOI: 10.1063/5.0159349

Journal information: Journal of Chemical Physics 

Provided by Osaka University 

by Wenke Dargel, Martin-Luther-Universität Halle-Wittenberg

A special type of starch could soon be used as an excipient in medicine to improve the treatment of patients. A research team from Martin Luther University Halle-Wittenberg (MLU) has discovered that it makes a suitable drug release system and has advantages over already established excipients. The team reports on its research in the Journal of Controlled Release.

Many active pharmaceutical ingredients are difficult to administer at present as they are poorly absorbed by the body and break down too quickly.

These problems can be overcome by drug delivery systems, which release active substances in the body in a controlled manner over a prolonged period of time. An example of one such application are drug-delivery implants. Once injected, the body degrades them over a longer period of time and the desired substance is released. This technology is already being used to treat diseases like cancer and bacterial infections.

Most currently used drug delivery systems are based on polylactide-co-glycolide (PLGA) and polylactide (PLA). However, these materials have several disadvantages.

“When PLGA and PLA degrade in the body, they create an acidic environment which results in an irregular release of the substances. Optimal treatment would, of course, involve a controlled release. The acidic environment can cause local inflammation and also inactivate drugs prior to their release,” explains Professor Karsten Mäder from the Institute of Pharmacy at MLU. His team has been working for many years on improving existing drug systems and developing new alternatives.

In the current study, the researchers investigated starch as a possible excipient. “Starch could provide an alternative for PLGA and PLA because it is already widely used as an excipient in medicinal products and medical devices,” Mäder adds.

The researchers used a special pharmaceutical-grade starch in their experiments. Rod-shaped implants were created using a special extrusion process. Earlier studies by the team had already confirmed that starch is a suitable carrier substance for the controlled release of drugs. For the current study, the researchers tested the rods in mice. They were able to show that the new system works particularly well for poorly water-soluble drugs, as it releases them continuously over several weeks. There were also no side effects and the starch implant degraded completely.

“Our study shows that special starches could be used in drug delivery systems,” concludes Mäder. However, before this invention could be applied to humans, large-scale clinical studies on its efficacy and safety would need to be conducted.

More information: Golbarg Esfahani et al, A starch-based implant as a controlled drug release system: Non-invasive in vivo characterization using multispectral fluorescence imaging, Journal of Controlled Release (2023). DOI: 10.1016/j.jconrel.2023.05.006

Journal information: Journal of Controlled Release 

Provided by Martin-Luther-Universität Halle-Wittenberg

by Liu Jia, Chinese Academy of Sciences

Nanoindentation testing is a high-precision instrumented indentation test technique that has the advantages of non-destructive testing and simplicity. However, researchers found that when testing the same sample with different Berkovich indenters, inconsistency still arises even if the indenters are regularly calibrated. This inconsistency poses challenges in accurately testing material hardness and comparing data from different laboratories.

In a study published in the Journal of Materials Research and Technology, researchers from the Materials Research Center of the Institute of Modern Physics (IMP) of the Chinese Academy of Sciences (CAS) reported that using different Berkovich indenters for nanoindentation testing, excluding fused silica, yields inconsistent results, and they analyzed the reasons behind this inconsistency.

The researchers identified two main factors contributing to the inconsistent experimental results, i.e., defects in the indenter tip and the indentation size effect.

To quantify their impact on experimental results, they developed a finite element model of the indenter using the indenter area function and proposed a method to correct the indentation size effect on the load-displacement curve.

The results indicated that while defects in the indenter tip have a small direct impact on the experimental results, they do affect the results indirectly by influencing the indentation size effect.

The indentation size effect correction method and indenter modeling approach introduced in this study are expected to be utilized in inverse finite element analysis to determine the constitutive relationship of the tested material.

More information: Xianlong Zhang et al, Inconsistent nanoindentation test hardness using different Berkovich indenters, Journal of Materials Research and Technology (2023). DOI: 10.1016/j.jmrt.2023.07.063

Provided by Chinese Academy of Sciences 

by Ecole Polytechnique Federale de Lausanne

Artificial intelligence is growing into a pivotal tool in chemical research, offering novel methods to tackle complex challenges that traditional approaches struggle with. One subtype of artificial intelligence that has seen increasing use in chemistry is machine learning, which uses algorithms and statistical models to make decisions based on data and perform tasks that it has not been explicitly programmed for.

However, to make reliable predictions, machine learning also demands large amounts of data, which isn’t always available in chemical research. Small chemical datasets simply do not provide enough information for these algorithms to train on, which limits their effectiveness.

Scientists, in the team of Berend Smit at EPFL, have found a solution in large language models such as GPT-3. Those models are pre-trained on massive amounts of texts, and are known for their broad capabilities in understanding and generating human-like text. GPT-3 forms the basis of the more popular artificial intelligence ChatGPT.

The study, published in Nature Machine Intelligence, unveils a novel approach that significantly simplifies chemical analysis using artificial intelligence. Contrary to initial skepticism, the method doesn’t directly ask GPT-3 chemical questions.

“GPT-3 has not seen most of the chemical literature, so if we ask ChatGPT a chemical question, the answers are typically limited to what one can find on Wikipedia,” says Kevin Jablonka, the study’s lead researcher.

“Instead, we fine-tune GPT-3 with a small data set converted into questions and answers, creating a new model capable of providing accurate chemical insights.”

This process involves feeding GPT-3 a curated list of Q&As. “For example, for high-entropy alloys, it is important to know whether an alloy occurs in a single phase or has multiple phases,” says Smit. “The curated list of Q&As are of the type: Q= ‘Is the (name of the high entropy alloy) single phase?’ A= ‘Yes/No.'”

He continues, “In the literature, we have found many alloys of which the answer is known, and we used this data to fine-tune GPT-3. What we get back is a refined AI model that is trained to only answer this question with a yes or no.”

In tests, the model, trained with relatively few Q&As, correctly answered over 95% of very diverse chemical problems, often surpassing the accuracy of state-of-the-art machine-learning models. “The point is that this is as easy as doing a literature search, which works for many chemical problems,” says Smit.

One of the most striking aspects of this study is its simplicity and speed. Traditional machine learning models require months to develop and demand extensive knowledge. In contrast, the approach developed by Jablonka takes five minutes and requires zero knowledge.

The implications of the study are profound. It introduces a method as easy as conducting a literature search, applicable to various chemical problems. The ability to formulate questions like “Is the yield of a [chemical] made with this (recipe) high?” and receive accurate answers can revolutionize how chemical research is planned and carried out.

In the paper, the authors say, “Next to a literature search, querying a foundational model (e.g., GPT-3,4) might become a routine way to bootstrap a project by leveraging the collective knowledge encoded in these foundational models.” Or, as Smit succinctly puts it, “This is going to change the way we do chemistry.”

by Autonomous University of Barcelona

Researchers from the UAB and the ICN2 have developed an innovative material to fight against the spread of pathogens, infections and antimicrobial resistance. Inspired by the substances secreted by mussels to adhere to rocks, it can be used as a coating to protect health care fabrics and provides an effective alternative to commonly used materials such as paper, cotton, surgical masks and commercial plasters.

The research is published in the Chemical Engineering Journal.

The overuse of antibiotics has led to the development of antimicrobial resistance (AMR), a growing threat to public health worldwide. AMR occurs when bacteria change over time and no longer respond to drugs, antibiotics and other related antimicrobial medicines, making infections harder to treat and increasing the risk of pathogen spread, severe illness and death.

In fact, the World Health Organization (WHO) and United Nations (UN) have reported that AMR poses a major threat to human health around the world, probably overtaking cancer as the world’s leading cause of death by 2050.

In this scenario, the development of novel and more efficient antibacterial materials has become essential to reduce pathogen spread, thus preventing infections. Of relevance is the control of bacterial populations in health environments such as hospitals and other health care units to avoid the so-called nosocomial infections, mainly due to bacterial colonization on biomedical surfaces.

Today, this type of infection is the sixth leading cause of death in industrialized countries, and much higher in the developing world, specially affecting immunocompromised and intensive care patients (e.g., burns) and those with chronic pathologies such as diabetes.

Among the different materials that may spread bacterial populations, fabrics represent an integral part of patient care: From the clothes of doctors, surgeons and nurses to medical curtains, bed sheets, pillow coverings, masks, gloves, and bandages, which are directly in contact with sutures and wounds. For all these reasons, antibacterial coatings for medical fabrics have become a very active field of research.

Researchers from the UAB Department of Biochemistry and Molecular Biology, the UAB Institute for Neuroscience (INc-UAB), and the Catalan Institute for Nanoscience and Nanotechnology (ICN2) have developed a family of biocompatible and bioinspired coatings produced by the co-polymerization between catechol derivatives and amino-terminal ligands.

Based on this, they have demonstrated that the use of these mussel-inspired coatings as efficient antimicrobial materials, based on their ability to evolve chemically over time in the presence of air and humid atmospheres, favoring the continuous formation of Reactive Oxygen Species (ROS). In fact, in addition to the formation of ROS, the synthetic methodology results in an excess of superficial free amino groups that induce the disruption of pathogen membranes.

“One of the main components found in the coatings (catechol and polyphenol derivatives) is found in the strands secreted by mussels, which are responsible for their adhesion to rocks under extreme conditions, under saline water,” explain UAB professor Victor Yuste and ICN2 researcher Salvio Suárez. “The fact that the coatings we have developed are inspired by this organism allows them to adhere to practically any type of surface and, in addition, are highly resistant to different environmental conditions such as humidity or the presence of fluids.

“In addition, natural compounds help to obtain more biodegradable, biocompatible materials with lower antimicrobial resistance compared to other bactericidal systems that end up generating resistance and, therefore, rapidly lose effectiveness.”

All of the commonly used sanitary equipment such as paper, cotton, surgical masks, and commercial plasters exhibited intrinsic multi-pathway antibacterial activity with rapid responses against a broad spectrum of microbial species. This included microorganisms that have developed resistance to extreme environmental conditions (such as B. subtilis), as well as pathogens considered the primary source responsible for many current infections, particularly those acquired in health care facilities.

These pathogens encompass multi-resistant microorganisms from both Gram-negative (E. coli and P. aeruginosa) and Gram-positive (S. aureus, methicillin-resistant S. aureus—MRSA and E. faecalis). These materials have also exhibited efficacy against fungi such as C. albicans and C. auris.

Moreover, its efficient application was demonstrated in wet atmospheres, as those found in health care environments, where respiratory droplets and/or other biofluids are present, thus reducing the risks of indirect contact transmission. Such antimicrobial activity was attributed to a direct contact killing process, where the pathogen is initially attached to the coating by catechol molecules and other polyphenol derivatives.

Then, a multi-pathway antibacterial effect is activated, mainly focused on a sustained generation of biosafety levels of ROS and electrostatic interactions with protic amino groups exposed to the surface. These antibacterial mechanisms induced a fast (180 minutes for bacteria and 24 hours for fungi) and efficient (more than 99%) response against pathogens, causing irreversible damage to the microorganisms.

These innovative coatings follow a simple one-step and scalable synthesis under mild conditions, using affordable materials and green chemistry-based methodologies. Moreover, the polyphenolic nature of their compositions and the absence of additional external antimicrobial agents enhance the simplicity of the bio-inspired coatings and avoid the induction of AMR and its cytotoxic effects on host cells and the environment.

Worth mentioning is that different parameters such as color, thickness and adhesion were fine-tuned, thus offering an adaptable solution for the different demands of the final material application. In general, the designed bio-inspired coatings have demonstrated a huge potential for further translation into clinics, as they represent a feasible alternative to existing antimicrobial materials.

by McMaster University

Think of it as recycling on the nanoscale: a tantalizing electrochemical process that can harvest carbon before it becomes air pollution and restructure it into the components of everyday products.The drive to capture airborne carbon dioxide from industrial waste and make it into fuel and plastics is gaining momentum after a team of researchers based at McMaster University, working with computational chemistry experts at Copenhagen’s Danish Technical University, have uncovered precisely how the process works and where it bogs down.Their work is published in the journal Nature Communications.The researchers set out to resolve why synthetic materials that have been shown to catalyze and convert carbon dioxide break down too quickly for the process to be practical at an industrial level.Using extremely powerful magnification equipment at the Canadian Centre for Electron Microscopy (CCEM), which is based on McMaster’s campus, the researchers were able to capture the chemical reaction at nanoscale—billionths of a meter—allowing them to study both the conversion process and understand how the catalyst breaks down under operating conditions.Lead author Ahmed Abdellah spent years developing the techniques that made it possible to observe the process, using an electrochemical reactor small enough to work under the electron microscopes at the center.

“It’s exciting for us that this is the first time anyone has been able to look at both the shapes of these structures and their crystal structures, to see how they evolve at the nanoscale,” says Abdellah, a former Ph.D. student in the chemical engineering lab of Drew Higgins and now a postdoctoral fellow at the CCEM.Higgins, a corresponding author of the paper, hopes the new information will facilitate the global effort to reduce carbon pollution by drawing carbon dioxide away from waste streams and instead recycling it to create useful products that would otherwise be produced from fossil fuels.”What we have found is that catalysts that can convert carbon dioxide into fuels and chemicals restructure quite rapidly under operating conditions. Their structures change and their properties change, right before our very eyes” Higgins says. “That dictates how efficient they are at converting carbon dioxide and how long they last. The catalysts eventually degrade and stop working and we want to know why they do that and how they do that so that we can develop strategies to improve their operational lifetimes.”Abdellah, Higgins and their colleagues are hopeful they and other researchers around the world can use the research results described in the new paper to make the reactive materials last longer and catalyze the process more efficiently, to allow the lab-based process to be scaled up for commercial use.Industries such as cement manufacturing, brewing and distilling, as well as chemical refineries, produce high volumes of readily retrievable carbon dioxide, Higgins explains, making them likely first targets for rolling out the technology once it is improved to the point where it is commercially viable.Other less concentrated forms of CO2 in industrial waste would come next.Though it’s a longshot today, Higgins says it’s possible the same technology could become efficient and stable enough to pull carbon dioxide from ambient air as “feedstock” for fuel and useful chemicals.”We’re still a little ways off, but progress has been very rapid in this field of research and development in the last five years or so,” Higgins says. “Ten years ago, people weren’t thinking about this kind of conversion, but now we’re starting to see promise. Efficiency and durability, though, just aren’t high enough yet. Once these bottlenecks are removed, this idea can really take off.”

by National Institute for Materials Science

An international research team has succeeded for the first time in controlling the chirality of individual molecules through structural isomerization. The team, led by NIMS, the Osaka University Graduate School of Science and the Kanazawa University Nano Life Science Institute (WPI-NanoLSI), also succeeded in synthesizing highly reactive diradicals with two unpaired electrons. They accomplished these tasks using a scanning tunneling microscope probe at low temperatures.

The research is published in the journal Nature Communications.

It is usually quite challenging to control the chirality of individual molecular units and synthesize extremely reactive diradicals in organic chemistry; this has prevented detailed investigation of the electronic and magnetic properties of diradicals. These issues inspired the development of chemical reaction techniques to control structures of individual molecules on the surface.

The research team recently developed a technique that allows them to modify the chirality of specific individual molecular units in a three-dimensional nanostructure in a controlled manner. They achieved this by exciting a target molecular unit with tunneling current from a scanning tunneling microscope probe at low temperature under ultrahigh vacuum conditions.

By precisely controlling current injection parameters (e.g., the molecular site, at which the tunneling current is injected at a given applied voltage), the team was able to rearrange molecular units into three different configurations: two different stereoisomers and a diradical. Finally, the team demonstrated the controllability and reproducibility of the structural isomerization by encoding ASCII characters (reading “NanoProbe Grp. NIMS”) using binary and ternary values in a series of one-dimensional molecular arrays with each array representing a single character.

In future research, the team plans to fabricate novel carbon nanostructures composed of designer molecular units, whose configurations are controlled via the structural isomerization technique developed in this project. In addition, the team will explore the possibility of creating quantum materials in which radical molecular units lead magnetic exchange couplings between the units as designed—a quantum mechanical effect.

This project was carried out by a research team consisting of Shigeki Kawai (Leader, Nanoprobe Group (NG), Center for Basic Research on Materials (CBRM), NIMS), Zhangyu Yuan (Junior Researcher, NG, CBRM, NIMS), Kewei Sun (ICYS Research Fellow, NG, CBRM, NIMS), Oscar Custance (Managing Researcher, NG, CBRM, NIMS), Takashi Kubo (Professor, Department of Chemistry, Graduate School of Science, Osaka University) and Adam S. Foster (Professor, Nano Life Science Institute, Kanazawa University; also Professor, Aalto University).

by Zhang Nannan, Chinese Academy of Sciences

Biological hydrogen-methane conversion refers to the production of methane through the action of microorganisms using hydrogen generated by electrolysis of water with residual power and carbon dioxide present in biogas. This approach promises to overcome the limitations of hydrogen storage, lowering the financial burden of biogas upgrading, and enabling carbon-negative utilization of CO₂ in biogas.

Previously, researchers from the Qingdao Institute of Bioenergy and Bioprocess Technology of the Chinese Academy of Sciences have domesticated and obtained microorganisms with high hydrogen-methane conversion efficiencies. They have also developed two production processes for in-situ and ex-situ biological hydrogen-methane conversion. However, the main factor limiting the efficiency of hydrogen-methane conversion remains the low gas-liquid mass transfer rate of hydrogen.

To address the limitations of low hydrogen mass transfer rates in the hydrogen-methane conversion process, the researchers developed a biotrickling filter (BTF), which facilitates microorganisms growth by using packing material with a rough internal surface. It ensures full contact between the gas and liquid phases, thereby increasing the efficiency of hydrogen utilization.

The study ia published in Chemical Engineering Journal.

In this study, the researchers started by exploring the effects of temperatures (25°C, 37°C, and 55°C) on the hydrogen-methane conversion pathway to determine the optimal temperature for the biotrickling filters. During the operation of the biotrickling filter, the effects of the packing materials (ceramite, volcanic stone, activated carbon) and the optimal ratio of the input gas (H₂/CO₂, v/v) on the conversion process were evaluated.

According to the researchers, the selected packing materials were environmentally friendly, and their large specific surface area and porosity facilitated the growth and attachment of microorganisms. This ensures sufficient contact between the microorganisms and the gas phase, which greatly enhances gas-liquid mass transfer.

The results showed that higher temperature is conducive to hydrogen-methane conversion. At 25°C, the hydrogen-methane conversion efficiency was low (2.5 L/Lw·d), and most of the hydrogen and carbon dioxide were used to produce acetate.

At 55°C, although the reaction process was initially unstable, it eventually reached stability and obtained a hydrogen-methane conversion efficiency of 8.3 L/Lw·d. In contrast, the conversion efficiency was still substantial at 37°C, achieving 7.1 L/Lw·d. Notably, there was no significant difference in the overall methanogenesis process between 37°C and 55°C.

In addition, the optimal input gas (H₂/CO₂) ratio was determined in the BTF experiment, achieving the most satisfactory ratio at 2.5:1 (H₂/CO₂, v/v), which was lower than previously reported values, but higher carbon dioxide removal efficiency was achieved.

The biofilms adhering to the three packing materials all achieved effective hydrogen-methane conversion efficiency at the ratio of 2.5:1, with the BTF using activated carbon as the packing material achieved the highest and the most stable conversion efficiency (91.9%).

The relative fluorescence intensity measurement confirmed that activated carbon had superior microbial immobilization. This study provides a promising approach for the application of BTFs in biogas hydrogen-methane conversion.

by Liu Jia, Chinese Academy of Sciences

Ammonia is essential for food and future energy supply. In the industry, it is mainly produced by the Haber-Bosch process, which operates at high temperatures and pressures. Due to the high energy consumption and carbon emissions of ammonia industry, it is important to develop alternative materials and approaches for efficient N₂ reduction to ammonia driven by renewable energy.

A research group led by Prof. Chen Ping from the Dalian Institute of Chemical Physics (DICP) of the Chinese Academy of Sciences (CAS) has realized photo-driven nitrogen fixation and ammonia synthesis mediated by lithium hydride (LiH). The study is published in Nature Chemistry.

LiH is the simplest saline hydride with a band gap of 3.7 eV. It has been investigated for hydrogen storage due to its high hydrogen content (12.5 wt%). However, the dehydrogenation of LiH is thermodynamically unfavorable.

In this study, the researchers found that ultraviolet (UV) illumination of LiH could induce a notable color change from white to light blue, accompanied by the release of a small amount of H₂ under ambient conditions. Such a phenomenon implied that under UV illumination, LiH underwent photolysis resulting in photon-generated electrons trapped in its hydrogen vacancy as long-lived and electron-rich F centers, which showed a fundamentally different mechanism for charge carrier separation.

The researchers indicated that illuminated LiH had an electron-rich surface with hydrogen vacancies, which facilitated the activation of N₂ to form N-H bond. They co-fed a N₂/H₂ mixture with a low H₂ partial pressure into the LiH powders, leading to photo-catalytic ammonia production under ambient conditions.

“This photochemical route is flexible in operation, which may be amenable to the small-scale and distributed ammonia synthesis powered by intermittent solar energy,” said Prof. Chen.