New material for efficient separation of Deuterium at elevated Temperatures

Helmholtz-Zentrum Berlin für Materialien und Energie

Facebook

XLinkedInWeChatBlueskyMessageWhatsAppEmail

 

image: 

The crystal structure of Cu-ZIF-gis that shows cylindrical straight channels along the c-axis. The pores were calculated with Connolly surfaces with a probe of 1.1 Å. (Cu, orange; N, blue; C, gray; O, magenta; H, white).

view more 

Credit: © Minji Jung / Department of Chemistry, UNIST

A novel porous material capable of separating deuterium (D2) from hydrogen (H2) at a temperature of 120 K has been introduced. Notably, this temperature exceeds the liquefaction point of natural gas, thus facilitating large-scale industrial applications. This advancement presents an attractive pathway for the economical production of D2 by leveraging the existing infrastructure of liquefied natural gas (LNG) production pipelines. The research conducted by Ulsan National Institute of Science & Technology (UNIST), Korea, Helmholtz-Zentrum Berlin, Heinz Maier Leibnitz Zentrum (MLZ), and Soongsil University, Korea, has been published in Nature Communications.

Deuterium, a stable isotope of hydrogen, plays a critical role in enhancing the durability and luminous efficiency of semiconductors and display devices, as well as serving as a fusion fuel in energy production. However, the increasing demand for D2 presents challenges in its production, primarily due to the need to separate from hydrogen through a cryogenic distillation process conducted at temperatures as low as 20 K (-253°C). While research has explored the use of metal-organic frameworks (MOFs) for D2 separation, their efficiency diminishes significantly at elevated temperatures.

In this study, the research team presented a copper-based zeolite imidazolate framework (Cu-ZIF-gis), which shows exceptional D2 separation performance, even at 120 K (-153℃). While typical MOFs operate effectively at around 23 K (-250℃), their performance decreases sharply as temperatures approach 77 K (-196℃). However, the newly developed Cu-based MOF demonstrates a significant advantage in maintaining its effectiveness at higher temperatures.

For the first time, the research team identified that the superior performance of this material results from the increased expansion of its lattice as the temperature rises. At cryogenic temperatures, the pores of the developed MOF are smaller than H2 molecules, thereby inhibiting their passage. However, as the temperature increases, the lattice expands, leading to an increase in pore size. This enlargement facilitates the passage of gases through the pores, thereby enabling the separation of H2 and D2 via the quantum sieving effect, wherein heavier molecules traverse the pores more efficiently at lower temperatures.

Confirmatory in-situ X-ray diffraction (XRD) and quasi-elastic neutron scattering (QENS) experiments, conducted at the Institut Laue-Langevin (ILL) in Grenoble, France, by the joint team from UNIST, HZB and MLZ, confirmed the expansion of the lattice framework with increasing temperature, as well as the difference in isotope diffusivity even at elevated temperatures. Additionally, the analysis from the Thermal Desorption Spectroscopy (TDS) experiments indicated stable D2 separation at elevated temperatures.

Professor Oh remarked, “The reported material exhibits markedly lower energy consumption and enhanced separation efficiency compared to most traditional methods, which operate at extremely low temperatures.” Dr. Jitae Park further noted, “These findings can be applied to develop sustainable isotope separation technologies using existing LNG cryogenic infrastructure, underscoring its potential industrial impact.”

Dr. Margarita Russina highlighted the crucial role of QENS in this study, stating: "With QENS, we can directly probe the molecular motion of H2 and D2 in MOFs, gaining key insights into their diffusion behavior and interactions with porous materials. The observed stronger confinement of D2 compared to H₂, a strictly nanoscale phenomenon, leads to remarkable effects on macroscopic properties, forming the basis for the development of a new generation of materials for more efficient isotope separation."

The research team, jointly led by Professor Hyunchul Oh from the Department of Chemistry at UNIST, Professor Jaheon Kim from Soongsil University, Dr. Jitae Park from Heinz Maier Leibnitz Zentrum (MLZ) at Technical University of Munich (TUM), and Dr. Margarita Russina from Helmholtz-Zentrum Berlin für Materialien und Energie (HZB) in Berlin, Germany announced this advancement on March 19, 2025. The study also involved Minji Jung, Jaewoo Park, and Raeesh Muhammad from the Department of Chemistry at UNIST, who served as co-first authors. The findings of this research have been published in Nature Communications on February 27, 2025. This study was supported by the National Research Foundation (NRF) of Korea and the Ministry of Science and ICT (MSIT), and the Institut Laue-Langevin (ILL) in Grenoble, France for the allocation of beam time.

 

UNIST /red.

---

Journal

Nature Communications

DOI

10.1038/s41467-025-56649-5 

Method of Research

Experimental study

Subject of Research

Not applicable

Article Title

Lattice-driven gating in a Cu-based zeolitic imidazolate framework for efficient high-temperature hydrogen isotope separation

 

Belief in AI as a ‘Great Machine’ could weaken national security crisis responses, new VCU research finds

The Wilder School’s Christopher Whyte investigates how emergency management and homeland security professionals react when faced with an AI threat

Virginia Commonwealth University

Facebook

XLinkedInWeChatBlueskyMessageWhatsAppEmail

Artificial intelligence designed to influence our decisions is everywhere — in Google searches, in online shopping suggestions and in movie streaming recommendations. But how does it affect decision-making in moments of crisis?

Virginia Commonwealth University researcher Christopher Whyte, Ph.D., investigated how emergency management and national security professionals responded during simulated AI attacks. The results reveal that the professionals were more hesitant and doubtful of their abilities when faced with completely AI-driven threats than when confronted with threats from human hackers or hackers who were only assisted by AI.

“These results show that AI plays a major role in driving participants to become more hesitant, more cautious,” he said, “except under fairly narrow circumstances.”

Those narrow circumstances are most concerning to Whyte, an associate professor in VCU’s L. Douglas Wilder School of Government and Public Affairs.

National security organizations design their training programs to cut down on hesitancy in moments of uncertainty. While most of the almost 700 American and European professionals in the study thought AI could boost human abilities, a small group believed AI could eventually fully replace their profession, and human expertise in general. That group responded recklessly to the AI-based threat, accepting risks and rashly forging ahead.

“These are people that believe the totality of what they do — their professional mission and the institutional mission that they support — could be overtaken by AI,” Whyte said.

Artificial intelligence: The next “Great Machine”

Whyte has a theory for why that may be the case.

The discredited “Great Man” theory proposes that the course of history has mainly been shaped by strong political figures, while modern historians give more credit to popular movements. Now, Whyte proposes that history has also been shaped by transformative technological inventions, like the telegraph or radio waves, and misplaced faith in their power — what he has coined the “Great Machine” theory.

But unlike the “Great Man” theory, Whyte said, “Great Machines” are a shared, societal force that can be harnessed for society’s benefit – or for its detriment.

“In the mid-1930s, for instance, we knew that radio waves had a great amount of potential for a lot of things,” Whyte said. “But one of the early ideas was for death rays — you could fry your brain, and so on.”

Death rays caught on, inspiring both science fiction stories and real-life attempts to build them during World War I and the interwar period. It wasn’t until a few years before World War II that scientists began to build something practical with radio waves: radar.

Society currently faces the same problem with AI, Whyte said, which is what he calls a “general purpose” technology that could either help or hurt society. The technology has already dramatically changed how some people think about the world and their place in it.

“It does so many different things that you really do have this emergent area of replacement mentalities,” he said. “As in, the world of tomorrow will look completely different, and my place in it simply won’t exist because [AI] will fundamentally change everything.”

That line of thinking could pose problems for national security professionals as the new technology upends how they think about their own abilities and changes how they respond to emergency situations.

“That is the kind of psychological condition where we unfortunately end up having to throw out the rulebook on what we know is going to combat bias or uncertainty,” Whyte said.

Combating “Skynet”-level threats

To study how AI affects professionals’ decision-making abilities, Whyte recruited almost 700 emergency management and homeland security professionals from the United States, Germany, the United Kingdom and Slovenia to participate in a simulation game.

During the experiment, the professionals were faced with a typical national security threat: A foreign government interfering in an election in their country. They were then assigned to one of three scenarios: a control scenario, where the threat only involved human hackers; a scenario with light, “tactical” AI involvement, where hackers were assisted by AI; and a scenario with heavy levels of AI involvement, where participants were told that the threat was orchestrated by a “strategic” AI program.

When confronted with a strategic AI-based threat — what Whyte calls a “Skynet”-level threat, referencing the “Terminator” movie franchise — the professionals tended to doubt their training and were hesitant to act. They were also more likely to ask for additional intelligence information compared with their colleagues in the other two groups, who generally responded to the situation according to their training.

In contrast, the participants who thought about AI as a “Great Machine” that could completely replace them acted without restraint and made decisions that contradicted their training.

And while experience and education helped moderate how the professionals responded to the AI-assisted attacks, they didn’t affect how the professionals reacted to the “Skynet”-level threat. That could pose a threat as AI attacks become more common, Whyte said.

“People have variable views on whether AI is about augmentation, or whether it really is something that’s going to replace them,” Whyte said. “And that meaningfully changes how people will react in a crisis.”

---

Journal

Journal of Homeland Security and Emergency Management

DOI

10.1515/jhsem-2024-0030 

Article Title

Artificial Intelligence and the “Great Machine” Problem: Avoiding Technology Oversimplification in Homeland Security and Emergency Management

 

The changing sky that plants see

Researchers introduce a numerical tool to predict sunlight patterns to help improve agriculture

Kyushu University

FacebookX

LinkedInWeChatBlueskyMessageWhatsAppEmail

 

image: 

Left: on sunny days, the sun shines directly and mainly reach the top leaves. Right: on cloudy days, sunlight is scattered in all directions, which allows lower leaves to receive more light. Recognizing this difference helps farmers enhance their planting schedules.

view more 

Credit: Kyushu University/Kume lab

Fukuoka, Japan—Researchers from Kyushu University have developed a new numerical model to explain the behavior of sunlight under various weather conditions. Unlike previous methods that focused on how plants perceive sunlight as a pure source of energy, this study introduces a metric to quantify sunlight intensity and its influence on plant growth and blooming patterns. Published in Ecological Informatics, the team hopes their research can benefit the agricultural industry and help farmers make better decisions about crop growth. This advancement is crucial for understanding the variations in plant photosynthesis in response to different sunlight and weather patterns, moreover it may also provide new insight into how changes in cloud cover due to climate change affect vegetation carbon dioxide uptake.

We know plants need the sun to live because it provides the energy for photosynthesis. And while conventional wisdom suggests that the more sun a plant gets the better, it is always not the case. In fact, because of how light is scattered, cloudy weather can greatly benefit a plant’s growth. On cloudy days, sunlight is scattered out more evenly, allowing it to reach lower parts of the plant. In contrast, on sunny days, sunlight energy is stronger but comes from a single direction, causing the leaves on the lower parts of the plant remain shaded, and therefore do not absorb as much sunlight.

“Plants also respond to different wavelengths of sunlight. If you have ever seen a rainbow, you know that sunlight is made up of many wavelengths. Plants sense these different wavelengths of light and alter their growth responses,” explains Amila Siriwardana, first author and PhD student at Kyushu University’s Faculty of Agriculture.

Plants can detect the ratio of wavelengths to understand their surroundings. These ratios are affected by many factors, including atmospheric density, cloud cover, or the altitude of the sun. However, such information had not been categorized in the context of plant physiology and ecology. So, to see how daily sunlight changes during different weather conditions, the research team began a project collecting yearlong sunlight data.

“While many projects look at only the ‘energy’ produced by the sun, our methods set out to categorize both the ‘energy’ and ‘quality’ of light. By sorting sunlight into five categories, from clear skies to overcast, we can better understand how plants can adjust and respond to different light conditions," adds Professor Atsushi Kume, who led the team.

To record sunlight across different times of day and weather conditions the researchers used a device called a spectroradiometer that measures the full spectrum of sunlight. The spectroradiometer was placed on top of Kyushu University’s Faculty of Agriculture building on Ito campus, where it collected data from sunrise to sunset every day in 2021.

Using the collected data, the researchers then developed a machine learning model to sort and predict how sunlight changes. The model works by spotting patterns in weather data such as how much sunlight reaches the ground, how much the light is scattered, how polluted or clear the weather is, and humidity. From these patterns, the model categorized sunlight into five groups on a sliding scale. For example, group one was categorized as a clear sunny day, while group five described overcast cloudy days.

The team noticed that on clear days, like those categorized as group one, more sunlight energy reaches the ground. Conversely, as the sky becomes more overcast, the sunlight energy decreased, but at the same time the scattering of light and the proportion of ultraviolet light increased. Additionally, the color of sunlight shifts slightly, moving from red tones on sunny days to blue tones under cloudy conditions.

Once the numerical model was trained, it could make highly accurate predictions of sunlight patterns using simpler weather data.

“Our method achieved 94% accuracy in predicting sunlight category without the need for expensive advanced equipment,” says Siriwardana. “Our model is especially relevant for regions experiencing four distinct seasons similar to Japan's.”

“We hope our model can be used to address the challenges in modern agriculture. Farmers can use this information to improve greenhouse conditions and planting schedules throughout the year,” Kume explains. "For instance, during Japan's cloudy rainy season in June, farmers might adjust their greenhouse operations or crop spacing to maximize available light. Even in the fall and winter, when sunlight patterns change, farmers can adapt their strategies based on our model.”

In the future, the team hopes to expand the model to cover more climate types, such as high-altitude or tropical regions, and further understand how sunlight affects the environment.

###

For more information about this research, see "Introducing the spectral characteristics index: A novel method for clustering solar radiation fluctuations from a plant-ecophysiological perspective," Amila Nuwan Siriwardana, Atsushi Kume, Ecological Informatics, https://doi.org/10.1016/j.ecoinf.2024.102940

About Kyushu University 
Founded in 1911, Kyushu University is one of Japan's leading research-oriented institutes of higher education, consistently ranking as one of the top ten Japanese universities in the Times Higher Education World University Rankings and the QS World Rankings. The university is one of the seven national universities in Japan, located in Fukuoka, on the island of Kyushu—the most southwestern of Japan’s four main islands with a population and land size slightly larger than Belgium. Kyushu U’s multiple campuses—home to around 19,000 students and 8000 faculty and staff—are located around Fukuoka City, a coastal metropolis that is frequently ranked among the world's most livable cities and historically known as Japan's gateway to Asia. Through its VISION 2030, Kyushu U will “drive social change with integrative knowledge.” By fusing the spectrum of knowledge, from the humanities and arts to engineering and medical sciences, Kyushu U will strengthen its research in the key areas of decarbonization, medicine and health, and environment and food, to tackle society’s most pressing issues.

Video of the Spectroradiometer [VIDEO] | 

The Rotating Shadow band Spectroradiometer (RSS) that measures sunlight. It has a rotating band that intermittently blocks the sunlight, helping scientists measure two types of light: direct sunlight when the band is out of the way, and diffused light when the band shades the sensor. By doing this, researchers can better understand how plants receive and use sunlight throughout the day in various weather conditions.

Credit

Kyushu University/Kume lab

---

Journal

Ecological Informatics

DOI

10.1016/j.ecoinf.2024.102940 

Method of Research

Experimental study

Subject of Research

Not applicable

Article Title

Introducing the spectral characteristics index: A novel method for clustering solar radiation fluctuations from a plant-ecophysiological perspective

Article Publication Date

19-Mar-2025

 

Can online games be an effective intervention to help adolescents reduce substance abuse?

Mizzou researcher aims to identify the key elements of digital games that can best help adolescents ditch bad habits

University of Missouri-Columbia

Facebook

XLinkedInWeChatBlueskyMessageWhatsAppEmail

 

image: 

Mansoo Yu

view more 

Credit: University of Missouri

For adolescents struggling with substance abuse, traditional in-person interventions such as counseling are not always effective, and rural areas often lack access to these services.

A researcher at the University of Missouri is thinking outside the box, aiming to help game designers develop fun, digital games that make ditching bad habits easier by meeting adolescents where they already are: online.

Mansoo Yu, a professor in the College of Health Sciences, looked at 26 studies involving digital interventions including online games, virtual reality games, mobile app games and video games, to identify the key elements that make these interventions effective in helping adolescents reduce drinking, smoking and illicit drug use. He found the most effective games were personalized to the individual playing the game, had a social component for users to compete against their friends and family, and included content that encouraged behavior change.

The findings can provide a blueprint to design digital game-based interventions in ways that are most likely to help adolescents reduce substance abuse and encourage positive development.

“When it comes to designing the most effective interventions, you always want to meet people where they are, and the younger generation often prefers to meet up virtually instead of in person,” Yu said. “Online interventions also increase accessibility in rural areas where in-person clinics and counseling services are not always available.”

Yu added that unhealthy behaviors such as smoking often serve as a way of coping with underlying mental health issues, including anxiety and depression. Therefore, a key element of a successful digital game-based intervention is emphasizing positive activities that can serve as an alternative to unhealthy behaviors.

“Whether it’s sports, mentorship programs, music, painting, outdoor activities or recreation centers, providing resources about healthier alternatives can be very helpful,” Yu said. “There can also be a social component, such as a point system for rewarding good behavior, to create friendly competition and allow users to play with their friends, parents and teachers. Peer modeling can be very impactful for adolescents.”

Games that begin by asking for the user’s specific interests could help create more personalized interventions, ultimately increasing user engagement.

“Hopefully this research helps game designers going forward create the most customized, effective interventions possible,” Yu said. “Mizzou’s strong foundation in both public health and social work, along with its mission as a land-grant university, has given me the opportunity to explore these intersections and advance this work.”

“Game-based digital interventions for enhancing positive development and addressing substance use in adolescents: A systematic review” was published in the international journal Children. Yu collaborated on the study with colleagues from Ewha Womans University in South Korea.

---

Journal

Children

DOI

10.3390/children11121554 

Method of Research

Literature review

Subject of Research

People

Article Title

Game-Based Digital Interventions for Enhancing Positive Development and Addressing Substance Use in Adolescents: A Systematic Review

 

Making food from our organic waste: a good idea only at first sight?

INRAE - National Research Institute for Agriculture, Food and Environment

Facebook

XLinkedInWeChatBlueskyMessageWhatsAppEmail

Waste-to-nutrition technologies aim to transform residual organic waste (such as forestry and agricultural residues, manure, green residues and food waste) into ingredients for human or animal consumption. They are often presented as innovative and sustainable solutions for reducing the environmental impact of food systems. They may involve insect farms fed on agrifood residues, biorefineries to extract proteins from plant residues or the production of proteins by microorganisms in bioreactors. The aim of these emerging technologies in France is to make the best possible use of waste to reduce the use of natural resources. However their actual environmental impact is not well known.

The scientists assessed the environmental impact in France of 5 of these technologies: insect farming, solid fermentation (transformation of food co-products by yeasts), extraction of plant proteins, production of mycoproteins (proteins produced by fungi) and microbial proteins. They carried out a life cycle assessment (LCA) for 9 potential usage scenarios. They compared their environmental impact with that of existing waste recovery technologies such as anaerobic digestion, composting or feeding animals directly from agricultural and food co-products. The assessment considered key environmental indicators such as greenhouse gas (GHG) emissions, marine eutrophication and land and water use, and was made parametric in order to identify the conditions shaping the environmental performance of these technologies.

Their results show that the environmental efficiency of these new technologies is variable and largely depends on consumer acceptance. For example, for these technologies to have a real environmental advantage when feed-grade streams are mobilized, proteins derived from insects or microorganisms would have to replace at least 80% of the weight of meat otherwise produced and consumed. Feeding livestock directly with suitable organic waste often remains a much more efficient way of reducing the environmental impact of food systems, as is already being done in France. In fact, the benefits for the climate of producing new ingredients using waste-to-nutrition technologies are outweighed by the emissions generated during the transformation processes, particularly energy consumption. Even in the best-case scenarios, the contribution of waste-to-nutrition technologies to mitigating climate change remains significantly lower compared with strategies such as reducing food waste or cutting meat consumption*.

*For France the analysis and calculations show that in the best-case scenario, waste-to-nutrition technologies can reduce annual GHG emissions by up to 10 MtCO2-eq. This figure remains well below strategies to reduce food waste (which could reduce GHG emissions by up to 15 MtCO₂-eq y-1) or reduce meat consumption (between 20 and 25 MtCO₂-eq y-1 of potential GHG emission reductions).

---

Journal

Nature Sustainability

DOI

10.1038/s41893-025-01521-z 

Article Title

Environmental mitigation potential of waste-to-nutrition pathways

Article Publication Date

17-Mar-2025