Lifeboat Foundation: Safeguarding Humanity
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Blog – Page 6

As the global demand for sustainable energy solutions continues to grow, Lithuanian researchers have taken a step forward by developing a technology that not only transforms waste into valuable hydrogen but also eliminates a long-standing issue in gasification—the presence of tar. This new method offers an efficient and eco-friendly way to produce high-purity hydrogen from various waste materials, representing a significant advancement in clean energy production.

Hydrogen is a key element in the transition to cleaner energy. However, conventional gasification methods are often unable to ensure its high purity—synthesis gases contain very low concentrations of hydrogen.

This inefficiency limits the industrial application of hydrogen as a clean gas fuel, highlighting the need for more advanced production methods.

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Reinforcement learning (RL) has become central to advancing Large Language Models (LLMs), empowering them with improved reasoning capabilities necessary for complex tasks. However, the research community faces considerable challenges in reproducing state-of-the-art RL techniques due to incomplete disclosure of key training details by major industry players. This opacity has limited the progress of broader scientific efforts and collaborative research.

Researchers from ByteDance, Tsinghua University, and the University of Hong Kong recently introduced DAPO (Dynamic Sampling Policy Optimization), an open-source large-scale reinforcement learning system designed for enhancing the reasoning abilities of Large Language Models. The DAPO system seeks to bridge the gap in reproducibility by openly sharing all algorithmic details, training procedures, and datasets. Built upon the verl framework, DAPO includes training codes and a thoroughly prepared dataset called DAPO-Math-17K, specifically designed for mathematical reasoning tasks.

DAPO’s technical foundation includes four core innovations aimed at resolving key challenges in reinforcement learning. The first, “Clip-Higher,” addresses the issue of entropy collapse, a situation where models prematurely settle into limited exploration patterns. By carefully managing the clipping ratio in policy updates, this technique encourages greater diversity in model outputs. “Dynamic Sampling” counters inefficiencies in training by dynamically filtering samples based on their usefulness, thus ensuring a more consistent gradient signal. The “Token-level Policy Gradient Loss” offers a refined loss calculation method, emphasizing token-level rather than sample-level adjustments to better accommodate varying lengths of reasoning sequences. Lastly, “Overlong Reward Shaping” introduces a controlled penalty for excessively long responses, gently guiding models toward concise and efficient reasoning.

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Researchers at the University of Liverpool and the University of Southampton have used computational design methods to develop non-metal organic porous framework materials, with potential applications in areas such as catalysis, water capture or hydrogen storage.

In a study published in the journal Nature, the research team used inexpensive and abundant non-metallic elements, such as , to design non-metal organic porous frameworks (N-MOFs).

The new materials offer an alternative to (MOFs), a class of porous, crystalline materials made up of metals connected by organic linker compounds.

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Hydrogen is often seen as the fuel of the future on account of its zero-emission and high gravimetric energy density, meaning it stores more energy per unit of mass compared to gasoline. Its low volumetric density, however, means it takes up a large amount of space, posing challenges for efficient storage and transport.

In order to address these deficiencies, hydrogen must be compressed in tanks to 700-bar pressure, which is extremely high. This situation not only incurs but also raises safety concerns.

For hydrogen-powered fuel-cell vehicles (FCVs) to become widespread, the US Department of Energy (DOE) has set specific targets for : 6.5% of the storage material’s weight should be hydrogen (gravimetric storage capacity of 6.5 wt%), and one liter of storage material should hold 50 grams of hydrogen (a volumetric storage capacity of 50 g L‒1). These targets ensure that vehicles can travel reasonable distances without excessive fuel.

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A team of scientists has created a chiral assembly by blending inorganic polyoxometalates and organic cyclodextrin molecules.

Polyoxometalates (POMs) are a class of nanomaterials with many useful applications. However, using polyoxometalates as building blocks to construct chiral POM-based frameworks has been a long-standing challenge for researchers. The team produced a 3D framework in this research, constructed by coordination assembly. The resulting framework features an interlaced organic-inorganic hybrid layer.

The team has published their work in the journal Polyoxometalates.

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The Burj Khalifa, the tallest building in the world, employs advanced construction techniques designed to withstand wind, seismic activity, and its own massive weight. Among these techniques is the “Meta Column System,” which plays a pivotal role by strategically positioning large columns to resist lateral forces, thereby facilitating the construction of such a towering structure.

What if these advanced architectural techniques could be applied to material design?

Metal-Organic Frameworks (MOFs) are porous materials formed by the combination of metal ions and organic ligands, resulting in structures similar to rebar in buildings. The design principle underlying MOFs closely resembles architectural planning.

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Iodine is a crucial element in various industries, but it is one of the least abundant nonmetallic elements on Earth. Although seawater holds around 70% of the world’s iodine reserves, its low concentrations—approximately 60 ppb—make extraction challenging. Additionally, radioactive iodine, which is released during nuclear accidents, presents significant long-term risks to marine ecosystems and human health. Therefore, there is an urgent need for effective strategies to both extract iodine from seawater and address radioactive iodine pollution.

Now, a team at Hainan University has developed a supramolecular organic (SOF) for iodine capture from . This framework has demonstrated the ability to remove 79% of iodine pollution in a simulated contaminated environment. In natural seawater, it achieves an ultrahigh iodine adsorption capacity of 46 mg g−1 within a 20-day extraction period. The research is published in the journal Research.

“The sustainable extraction of iodine from seawater is not only vital to meet the increasing global demand but also essential for mitigating the ecological risks posed by pollution,” said senior author Ning Wang. “Innovative materials can contribute to the field by enhancing the selectivity and capacity for iodine extraction from seawater. Our findings showcase an effective strategy for fabricating multi-dimensional 3D SOF materials and also present a promising material for iodine capture from seawater.”

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Unsubstituted π-electronic systems with expanded π-planes are highly desirable for improving charge-carrier transport in organic semiconductors. However, their poor solubility and high crystallinity pose major challenges in processing and assembly, despite their favorable electronic properties. The strategic arrangement of these molecular structures is crucial for achieving high-performance organic semiconductive materials.

In a significant breakthrough, a research team led by Professor Hiromitsu Maeda from Ritsumeikan University, including Associate Professor Yohei Haketa from Ritsumeikan University, Professor Shu Seki from Kyoto University, and Professor Go Watanabe from Kitasato University, has synthesized a novel organic electronic system incorporating gold (AuIII) and benzoporphyrin molecules, enabling enhanced solubility and conductivity.

The findings of the study were published online in Chemical Science.

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Metal-organic frameworks (MOFs) have been gaining attention as promising carbon-neutral porous materials, thanks to their high performance in gas storage, separation, and conversion. The geometric building blocks of MOFs, metal clusters and organic linkers, allow chemists to predict and synthesize new structures like assembling LEGO. However, finding new metal building blocks is still a daunting challenge due to the complex nature of metal ions in synthesis.

A research team, led by Professor Wonyoung Choe at Ulsan National Institute of Science and Technology (UNIST), South Korea, was inspired by the molecular metal clusters previously synthesized before realized in porous materials. This implies one can predict future MOFs by looking closely at their metal building blocks.

The research team compared zirconium metal clusters found in both MOFs and molecules. Zirconium-based MOFs are one of the representative metal-organic porous materials with remarkable stability and a broad range of applications. The researchers identified seven types of zirconium building blocks in MOFs and discovered additional fourteen types of potential metal building blocks.

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From a very young age, we’re socialized to view the world as being made up of “goodies” and “baddies.” When you’re a child fooling around with your friends in the playground, nobody ever wants to be the baddy. And when it comes to dressing up, everybody wants to be Luke Skywalker—not Darth Vader.

This oversimplified way of viewing the world as being made up of right and wrong or good people and bad people doesn’t dissipate as we grow older. If anything, it tends to solidify as we form the that define who we are in adult life.

This is particularly the case when it comes to our political identities and, specifically, the partisan identities and loyalties that individuals attach themselves to.

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