Chemist Omar Yaghi invented materials called MOFs, a few grams of which have the surface area of a football field. In school, we learn about the Stone Age, the Bronze Age - and we are currently in a silicon age characterised by computers and phones. What might define the next age? Omar Yaghi at the University of California, Berkeley, thinks a family of materials he helped pioneer in the 1990s has a good shot. They are metal-organic frameworks (MOFs), and working out how to make them earned him a share of the 2025 Nobel prize in chemistry .

Super tough microbialites are some of the oldest evidence of life on Earth. Breakthroughs, discoveries, and DIY tips sent every weekday. Among the tricky carnivorous plants, great white shark-killing orca whales, and other remarkable flora and fauna that call South Africa home is a remarkable group of "living rocks." Called microbialites, these communities are similar to coral reefs and are built up by microbes. These tiny living organisms absorb and release dissolved minerals into more solid rock-like forms.

Since 2004, the number of American adults who've enjoyed a daily cup of joe has increased 37 percent. Breakthroughs, discoveries, and DIY tips sent every weekday. Whether you're an early bird or a night owl, coffee is probably part of your daily routine. Since 2004, the number of American adults who've enjoyed a daily cup of java has jumped up 37 percent, the highest level in more than 20 years, according to the National Coffee Association . But coffee is hardly a new invention.

The Royal Swedish Academy of Sciences has awarded the 2025 Nobel Prize in chemistry to Susumu Kitagawa, Richard Robson and Omar M Yaghi for their work in the development of metal organic frameworks (MOF). The three scientists, who won the award on Wednesday, come from the universities of Kyoto in Japan, Melbourne in Australia and Berkeley in the United States, respectively. Such constructions can be used to harvest water from desert air, capture carbon dioxide, store toxic gases or break down traces of pharmaceuticals in the environment. "Metal organic frameworks have enormous potential, bringing previously unforeseen opportunities for custom-made materials with new functions," said Heiner Linke, chair of the Nobel Committee for Chemistry. According to Olof Ramstrom, a member of the Nobel Committee for Chemistry, the new form of molecular architecture can be compared with the handbag of the fictional Harry Potter character Hermione Granger: small on the outside but very large on the inside.

Breakthroughs, discoveries, and DIY tips sent every weekday. At the US Army Corps of Engineers' research facility in central Alaska, a unique tunnel descends underground. They were hunting for something much smaller--and smellier. "The first thing you notice when you walk in there is that it smells really bad. It smells like a musty basement that's been left to sit for way too long," geological scientist Tristan Caro recounted in a statement .

How badly does AI harm the environment? We now have some answers to that question, as both Google and Mistral have published their own self-assessments of the environmental impact of an AI query. In July, Mistral, which publishes its own AI models, published a self-evaluation of the environmental impact of training and querying its model in terms of the amount of carbon dioxide (CO2) produced, the amount of water consumed, and the amount of material consumed. Google took a slightly different approach, publishing the amount of power and water a Gemini query consumes, as well as how much CO2 it produces. Of course, there are caveats: Each report was self-generated, and not performed by an outside auditor.

In George Lucas's classic 1980 film'The Empire Strikes Back', hero Han Solo (Harrison Ford) is frozen in carbonite by the evil Darth Vader. The fictional metal hardened around the heroic space smuggler as it cooled – sealing him in a state of'perfect hibernation'. Carbonite is of course a fictional material, consigned to the realms of the Star Wars galaxy far, far away. But according to one scientist, this scene is not completely the stuff of science-fiction. Dr Alex Baker, a chemist at the University of Warwick, thinks humans could potentially be frozen like Solo with a real-life equivalent.

It's one of the most profound questions in science – did life ever exist on Mars? Now, experts have unearthed evidence that the Red Planet was once habitable. Scientists have found carbon residue in Martian rocks, indicating that an ancient carbon cycle existed. And it means the Red Planet was likely once warm enough to sustain life. Researchers have long believed that, billions of years ago, Mars had a thick, carbon dioxide-rich atmosphere with liquid water on its surface.

The alteration of the climate in various areas of the world is of increasing concern since climate stability is a necessary condition for human survival as well as every living organism. The main reason of climate change is the greenhouse effect caused by the accumulation of carbon dioxide in the atmosphere. In this paper, we design a networked system underpinned by compartmental dynamical thermodynamics to circulate the atmospheric carbon dioxide. Specifically, in the carbon dioxide emitter compartment, we develop an initial-condition-dependent finite-time stabilizing controller that guarantees stability within a desired time leveraging the system property of affinity in the control. Then, to compensate for carbon emissions we show that a cultivation of microalgae with a volume 625 times bigger than the one of the carbon emitter is required. To increase the carbon uptake of the microalgae, we implement the nonaffine-in-the-control microalgae dynamical equations as an environment of a state-of-the-art library for reinforcement learning (RL), namely, Stable-Baselines3, and then, through the library, we test the performance of eight RL algorithms for training a controller that maximizes the microalgae absorption of carbon through the light intensity. All the eight controllers increased the carbon absorption of the cultivation during a training of 200,000 time steps with a maximum episode length of 200 time steps and with no termination conditions. This work is a first step towards approaching net zero as a classical and learning-based network control problem. The source code is publicly available.

This study focuses on membrane-based systems for CO$_2$ separation, addressing the urgent need for efficient carbon capture solutions to mitigate climate change. Linear regression models, based on membrane equations, were utilized to estimate key parameters, including porosity ($\epsilon$) of 0.4805, Kozeny constant (K) of 2.9084, specific surface area ($\sigma$) of 105.3272 m$^2$/m$^3$, mean pressure (Pm) of 6.2166 MPa, viscosity ($\mu$) of 0.1997 Ns/m$^2$, and gas flux (Jg) of 3.2559 kg m$^{-2}$ s$^{-1}$. These parameters were derived from the analysis of synthetic datasets using linear regression. The study also provides insights into the performance of the membrane, with a flow rate (Q) of 9.8778 $\times$ 10$^{-4}$ m$^3$/s, an injection pressure (P$_1$) of 2.8219 MPa, and an exit pressure (P$_2$) of 2.5762 MPa. The permeability value of 0.045 for CO$_2$ indicates the potential for efficient separation. Optimizing membrane properties to selectively block CO$_2$ while allowing other gases to pass is crucial for improving carbon capture efficiency. By integrating these technologies into industrial processes, significant reductions in greenhouse gas emissions can be achieved, fostering a circular carbon economy and contributing to global climate goals. This study also explores how artificial intelligence (AI) can aid in designing membranes for carbon capture, addressing the global climate change challenge and supporting the Sustainable Development Goals (SDGs) set by the United Nations.