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Category: chemistry

From Big Bang To AI, Unified Dynamics Enables Understanding Of Complex Systems

Experiments reveal that inflation not only smooths the universe but populates it with a specific distribution of initial perturbations, creating a foundation for structure formation. The team measured how quantum fluctuations during inflation are stretched and amplified, transitioning from quantum to classical behavior through a process of decoherence and coarse-graining. This process yields an emergent classical stochastic process, captured by Langevin or Fokker-Planck equations, demonstrating how classical stochastic dynamics can emerge from underlying quantum dynamics. The research highlights that the “initial conditions” for galaxy formation are not arbitrary, but constrained by the Gaussian field generated during inflation, possessing specific correlations. This framework provides a cross-scale narrative, linking microphysics and cosmology to life, brains, culture, and ultimately, artificial intelligence, demonstrating a continuous evolution of dynamics across the universe.

Universe’s Evolution, From Cosmos to Cognition

This research presents a unified, cross-scale narrative of the universe’s evolution, framing cosmology, astrophysics, biology, and artificial intelligence as successive regimes of dynamical systems. Rather than viewing these fields as separate, the work demonstrates how each builds upon the previous, connected by phase transitions, symmetry-breaking events, and attractors, ultimately tracing a continuous chain from the Big Bang to contemporary learning systems. The team illustrates how gravitational instability shapes the cosmic web, leading to star and planet formation, and how geochemical cycles establish stable, long-lived attractors, providing the foundation for life’s emergence as self-maintaining reaction networks. The study emphasizes that the universe is not simply evolving in state, but also in its capacity for description and learning, with each transition.

How tumors thrive in acidic, low-oxygen environments?

The authors determined the 3.3 Å cryoEM structure of the human NBCn1 outward facing (OF) conformational state with densities corresponding to the transported ions in the ion coordination site. They also generated NBCn1 inward facing (IF) and intermediate (occluded) structures and characterized the transport cycle and the ion dynamics in the IF and OF states.

The results showed that NBCn1 utilizes an elevator-type transport mechanism with a small vertical shift of the ion coordination site between OF and IF conformational states and that the transported ions permeate without significant energy barriers.

The researchers showed that NBCn1 moves two sodium ions and one carbonate ion through an efficient “elevator-like” motion that minimizes energy use. This allows NBCn1 to achieve a high transport rate of approximately 15,000 ions per second, helping tumor cells maintain an internal pH that promotes survival, division and resistance to acidic stress.

By understanding the structure and function of NBCn1, the study provides a blueprint for designing drugs that could potentially block this transporter and disrupt the internal chemical balance that cancer cells depend on. Targeting this protein in cancer cells specifically could offer a precise way to weaken tumors while minimizing harm to normal tissue.

Scientists have characterized the structure and function of a key survival protein in breast cancer cells that helps explain how these tumors resist environmental stress and thrive in acidic, low-oxygen environments that would normally be toxic to healthy cells.

Breast cancer cells rely on a transporter protein called NBCn1 to bring alkali ions into the cell and maintain a favorable internal pH.

Continue reading “How tumors thrive in acidic, low-oxygen environments?” | >

Consciousness breaks from the physical world by keeping the past alive

Conscious experiences of change, from seeing a bird take flight to listening to a melody, cannot be broken down into ever smaller units of experience. They must inhabit what William James called the “specious present,” a sliding window of time where the immediate past and present overlap. Philosopher Lyu Zhou argues that this exposes a deep rift between mind and matter. When the physical world undergoes change, it does so through succession – one physical state replaces another, and the past is gone – whereas consciousness requires the active retention of the past inside the present, revealing its fundamentally non-physical nature.

1. Consciousness, change and time

You are now conscious as you read this article. Is your consciousness physical? Many today think it is. They claim that it either is a physical system made of matter – most likely the neural network of your brain – or is realized by matter through a physical process, most likely by your brain through a neural biochemical process. However, I hope to convince you that this view is wrong. I hope to show you that your immediate present consciousness has certain features that physical systems and processes cannot have.

Westerly jet stream emerges as key driver of mid-latitude hydroclimatic extremes

In recent years, the global climate has become increasingly extreme, with intensifying alternations of droughts and floods—particularly in ecologically vulnerable mid-latitude regions. But what is driving this hydroclimatic variability? Scientists have long debated the underlying mechanisms.

A research team led by Prof. Long Hao from the Nanjing Institute of Geography and Limnology of the Chinese Academy of Sciences, drilled a 300.8-meter-long lacustrine sediment core in the Datong Basin of Shanxi Province, located in mid-latitude East Asia (Northern China). By reconstructing more than 5.7 million years of Earth’s history, the researchers revealed that the “waviness” of the westerly jet stream is the primary driver of mid-latitude climate variability. The study was recently published in Nature Communications.

This sediment core acts as a detailed “climate archive,” documenting precipitation changes over approximately 5.7 million years—spanning the Pliocene and Pleistocene epochs. By analyzing chemical indicators within the core, the researchers obtained a high-resolution record of ancient precipitation patterns.

Ultra-low power, fully biodegradable artificial synapse offers record-breaking memory

In Nature Communications, a research team affiliated with UNIST present a fully biodegradable, robust, and energy-efficient artificial synapse that holds great promise for sustainable neuromorphic technologies. Made entirely from eco-friendly materials sourced from nature—such as shells, beans, and plant fibers—this innovation could help address the growing problems of electronic waste and high energy use.

Traditional artificial synapses often struggle with high power consumption and limited lifespan. Led by Professor Hyunhyub Ko from the School of Energy and Chemical Engineering, the team aimed to address these issues by designing a device that mimics the brain’s synapses while being environmentally friendly.

This Simple Chemistry Fix Could Revolutionize Flow Batteries

A new twist on bromine-based flow batteries could make large-scale energy storage cheaper, safer, and far longer-lasting. Bromine-based flow batteries store and release energy through a chemical reaction involving bromide ions and elemental bromine. This approach offers several advantages, includ

Molecules as switches for sustainable light-driven technologies

Metal nanostructures can concentrate light so strongly that they can trigger chemical reactions. The key players in this process are plasmons—collective oscillations of free electrons in the metal that confine energy to extremely small volumes. A new study published in Science Advances now shows how crucial adsorbed molecules are in determining how quickly these plasmons lose their energy.

The team led by LMU nanophysicists Dr. Andrei Stefancu and Prof. Emiliano Cortés identified two fundamentally different mechanisms of so-called chemical interface damping (CID), the plasmon damping caused by adsorbed molecules. Which mechanism dominates depends on how the electronic states of the molecule align with those of the metal surface, gold in this case—and this alignment is even reflected in the material’s electrical resistance.

Advancing Physical Understanding with Interpretable Machine Learning

A new artificial neural-network architecture opens a window into the workings of a tool previously regarded as a black box.

Thanks to the extremely large datasets and computing power that have become available in recent years, a new paradigm in scientific discovery has emerged. This new approach is purely data driven, using large amounts of data to train machine-learning models―typically neural networks―to predict the behavior of the natural world [1]. The most prominent achievement of this new methodology has arguably been the AlphaFold model for predicting protein folding (see Research News: Chemistry Nobel Awarded for an AI System That Predicts Protein Structures) [2]. But despite such successes, these data-driven approaches suffer a major drawback in that they are generally “black boxes” that offer no human-accessible understanding of how they make their predictions. This shortcoming also extends to the models’ inputs: It is often desirable to build known domain knowledge into these models, but the data-driven approach excludes that option.

Research reinvents MXene synthesis at a fraction of the cost

MXenes (pronounced like the name “Maxine”) are a class of two-dimensional materials, first identified just 14 years ago, with remarkable potential for energy storage, catalysts, ultrastrong lightweight composites, and a variety of other purposes ranging from electromagnetic shielding to ink that can carry a current.

But manufacturing MXenes has been expensive, difficult and crude.

“MXenes have been made by a very elaborate, multi-step process that involved days of high-temperature work, followed by using dangerous chemicals like hydrofluoric acid and creating a lot of waste,” said Prof. Dmitri Talapin of the University of Chicago Pritzker School of Molecular Engineering (UChicago PME) and Department of Chemistry. “That may have been okay for early-stage research and lab exploration, but became a big roadblock for taking the next step to large-scale applications.”

Archimedean screw inspires new way to encode chirality into magnetic materials

In physics and materials science, the term “spin chirality” refers to an asymmetry in the arrangement of spins (i.e., the intrinsic angular momentum of particles) in magnetic materials. This asymmetry can give rise to unique electronic and magnetic behaviors that are desirable for the development of spintronics, devices that leverage the spin of electrons and electric charge to process or store information.

The creation of materials that exhibit desired spin chirality and associated physical effects on a large scale has so far proved challenging. In a recent paper published in Nature Nanotechnology, researchers at École Polytechnique Fédérale de Lausanne (EPFL), the Max Planck Institute for Chemical Physics of Solids and other institutes introduced a new approach to encode chirality directly into materials by engineering their geometry at a nanoscale.

“Dirk and myself were initially inspired by the elegance of the Archimedean screw and began wondering whether we could build a magnonic analog, something that could ‘pump’ magnons (i.e., collective electron spin excitations) in a similarly directional way,” Dr. Mingran Xu, first author of the paper, told Tech Xplore.

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