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Category: chemistry – Page 202

Decoding Nature’s Hidden Messages

Living organisms constantly navigate dynamic and noisy environments, where they must efficiently sense, interpret, and respond to a wide range of signals. The ability to accurately process information is vital for both executing interspecies survival strategies and for maintaining stable cellular functions, which operate across multiple temporal and spatial scales [1] (Fig. 1). However, these systems often have access to only limited information. They interact with their surroundings through a subset of observable variables, such as chemical gradients or spatial positions, all while operating within constrained energy budgets. In this context, Giorgio Nicoletti of the Swiss Federal Institute of Technology in Lausanne (EPFL) and Daniel Maria Busiello of the Max Planck Institute for the Physics of Complex Systems in Germany applied information theory and stochastic thermodynamics to provide a unified framework addressing this topic [2]. Their work has unraveled potential fundamental principles behind transduction mechanisms that extract information from a noisy environment.

Bacteria, cells, swarms, and other organisms have been observed acquiring information about the environment at extraordinarily high precision. Bacteria can read surrounding chemical gradients to reach regions of high nutrients consistently [3], and cells form patterns during development repetitively and stably by receiving information on the distribution and concentration of external substances, called morphogens [4]. In doing so, they must interact with a noisy environment where the information available is scrambled and needs to be retrieved without corrupting the relevant signal [5]. All this comes at a cost.

The idea that precision is not free is an old one in the field of stochastic thermodynamics, and the cost usually comes in the form of energy dissipation [6]. This trade-off is even more relevant for biological systems that have limited access to energy sources. Living systems are pushed to find optimal strategies to achieve maximum precision while minimizing energy consumption. Consequently, a complete quantitative description of how these strategies are implemented requires the simultaneous application of information theory and stochastic—that is, noisy—thermodynamics.

A scalable convolutional neural network approach to fluid flow prediction in complex environments

While machine learning methods can be used for accurate flow prediction in complex environments, such as for urban structures30 or turbulent fields31, generalizing these approaches to domains of arbitrary size and complexity remains a challenging problem. One reason is that flows near and around obstacles depend on factors associated with the fluid (i.e., Reynolds number) or domain (i.e., boundary conditions), and fixing either of these conditions puts bounds on the validity of the estimated fields. Thus, if we seek broad applicability, then we should seek the fewest set of model restrictions that together provide the most accurate flow predictions. To this end, our approach has been to deconstruct certain types of domains into individual obstacles that each maintain some level of geometrical similarity, so that a single neural network model can be used to predict flows near all structural boundaries of the domain. Flows between these structural surfaces, at a scale on the order of the obstacle diameter, are predicted using a second neural network model in series with the first. Together, this serial-modeling approach allows for rapid prediction of flows in domains that can be represented by a disjoint set of structural elements. This type of domain is common, for example, in urban and periurban areas, wherein buildings conform to a common structural motif that affects ground-level velocity fields.

Another relevant length scale is the grid size used to digitize individual domains for read-in by the model. Thus, we investigated how flow patterns can be affected when this input resolution is varied. Although our choice of grid size is somewhat arbitrary, it is dense enough to capture variation in the relevant velocity fields near individual obstacles, but not so dense that producing a large enough cohort of CFD-generated training datasets becomes computationally intractable.

Our approach can also be trained to predict flows with a variable inlet velocity, which, in the case of urban wind flow prediction, permits model parameterization in terms of current meteorological conditions. In the specific case of aerial dispersion of chemicals throughout an urban environment, our predicted flows are considered as the advective field of a drift-diffusion model of molecular dispersion. This advection field plays a central role because concentration fluctuations decorrelate in relationship with the velocity fluctuations of the advection field, and spatial heterogeneity in the flow patterns is determined by the sequence of obstacles in the flow path.

Newly developed material can suppress thermal runaway in batteries

A team of engineers and materials scientists at LG Chem, Korea’s largest chemical company, has developed a material that they claim could greatly reduce the risk of thermal runaway and resulting fires in batteries. In their paper published in the journal Nature Communications, the group describes how they developed the material and how well it has worked during testing.

Over the past several years, consumers have witnessed or have heard about batteries in smartphones or cars catching on fire. These fires, it has been found, result from thermal runaway, which is where the anode and cathode inside a battery come too close together, or worse, actually touch.

The result is a short, which generates heat, and results soon thereafter in a fire. In this new effort, the team at LG has developed a thin material that, when placed between the cathode and collector, prevents thermal runaway.

Carbon Fiber Structural Battery Paves way for Light, Energy-Efficient Vehicles

When cars, planes, ships or computers are built from a material that functions as both a battery and a load-bearing structure, the weight and energy consumption are radically reduced. A research group at Chalmers University of Technology in Sweden is now presenting a world-leading advance in so-called massless energy storage — a structural battery that could halve the weight of a laptop, make the mobile phone as thin as a credit card or increase the driving range of an electric car by up to 70% on a single charge.

“We have succeeded in creating a battery made of carbon fiber composite that is as stiff as aluminum and energy-dense enough to be used commercially. Just like a human skeleton, the battery has several functions at the same time,” says Chalmers researcher Richa Chaudhary, who is the first author of an article recently published in Advanced Materials.

Research on structural batteries has been going on for many years at Chalmers, and in some stages also together with researchers at the KTH Royal Institute of Technology in Stockholm, Sweden. When Professor Leif Asp and colleagues published their first results in 2018 on how stiff, strong carbon fibers could store electrical energy chemically, the advance attracted massive attention.

Linus Pauling Was Right: Scientists Confirm Century-Old Electron Bonding Theory

A breakthrough study has validated the existence of a stable single-electron covalent bond between two carbon atoms, supporting Linus Pauling’s early 20th-century theory and opening avenues for chemical research.

Covalent bonds, in which two atoms share a pair of electrons, form the foundation of most organic compounds. In 1931, the Nobel Laureate Linus Pauling suggested that covalent bonds made from just a single, unpaired electron could exist, but these single-electron bonds would likely be much weaker than a standard covalent bond involving a pair of electrons.

Since then, single-electron bonds have been observed, but never in carbon or hydrogen. The search for one-electron bonds shared between carbon atoms has stymied scientists.

A breakthrough by UChicago scientists enables greener microfabrication

Imagine being able to create incredibly tiny structures with the same ease and sustainability as printing on paper.

This is the frontier of microfabrication—the process of making microscopic structures that are crucial for the operation of everything from computer chips to medical devices.

…

New, more sustainable process uses water instead of harmful chemicals.

Webb Telescope Unveils New Chemical Insights on Pluto’s Moon Charon

What secrets can Pluto’s moon, Charon, reveal about the formation and evolution of planetary bodies throughout the solar system? This is what a recent study published in Nature Communications hopes to address as an international team of researchers led by the Southwest Research Institute (SwRI) used NASA’s James Webb Space Telescope (JWST) to conduct the first-time detection of hydrogen peroxide and carbon dioxide on Charon’s surface, which adds further intrigue to this mysterious moon, along with complementing previous discoveries of water ice, ammonia-bearing species, and organic materials, the last of which scientists hypothesize could explain Charon’s gray and red surface colors.

“The advanced observational capabilities of Webb enabled our team to explore the light scattered from Charon’s surface at longer wavelengths than what was previously possible, expanding our understanding of the complexity of this fascinating object,” said Dr. Ian Wong, who is a staff scientist at the Space Telescope Science Institute and a co-author on the study.

Detecting hydrogen peroxide is significant since it forms from the broken-up oxygen and hydrogen atoms after water ice is exposed to cosmic rays, solar wind, or solar ultraviolet light. This indicates that the Sun’s activity influences surface processes so far away, with Charon being approximately 3.7 billion miles from the Sun. The researchers determined that Charon’s carbon dioxide serves as a light coating on Charon’s water-ice heavy surface. While the surface of Charon was studied in-depth from NASA’s New Horizons mission in 2015, these new findings provide greater understanding of the physics-based processes responsible for Charon’s unique surface features.

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