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Category: nanotechnology – Page 171

Aluminum is a highly reactive metal that can strip oxygen from water molecules to generate hydrogen gas. Now, researchers at UC Santa Cruz have developed a new cost-effective and effective way to use aluminum’s reactivity to generate clean hydrogen fuel.

In a new study, a team of researchers shows that an easily produced composite of gallium and aluminum creates aluminum nanoparticles that react rapidly with water at room temperature to yield large amounts of hydrogen. According to researchers, the gallium was easily recovered for reuse after the reaction, which yields 90% of the hydrogen that could theoretically be produced from the reaction of all the aluminum in the composite.

Easy aluminum nanoparticles split water and generate hydrogen gas rapidly under ambient conditions.

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Fully organic rechargeable household batteries are an ideal alternative to traditional metal-based batteries, in particular for reducing pollution to landfill and the environment.

Now researchers at Flinders University, with Australian and Chinese collaborators, are developing an all-organic polymer battery that can deliver a cell voltage of 2.8V—a big leap in improving the energy storage capability of organic batteries.

“While starting with small household batteries, we already know organic redox-active materials are typical electroactive alternatives due to their inherently safe, lightweight and structure-tunable features and, most importantly, their sustainable and environmentally friendly,” says senior lecturer in chemistry Dr. Zhongfan Jia, a research leader at Flinders University’s Institute for Nanoscale Science and Technology.

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Building a better supercomputer is something many tech companies, research outfits, and government agencies have been trying to do over the decades. There’s one physical constraint they’ve been unable to avoid, though: conducting electricity for supercomputing is expensive.

Not in an economic sense—although, yes, in an economic sense, too—but in terms of energy. The more electricity you conduct, the more resistance you create (electricians and physics majors, forgive me), which means more wasted energy in the form of heat and vibration. And you can’t let things get too hot, so you have to expend more energy to cool down your circuits.

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With the advent of Big Data, current computational architectures are proving to be insufficient. Difficulties in decreasing transistors’ size, large power consumption and limited operating speeds make neuromorphic computing a promising alternative.

Neuromorphic computing, a new brain-inspired computation paradigm, reproduces the activity of biological synapses by using artificial neural networks. Such devices work as a system of switches, so that the ON position corresponds to the information retention or “learning,” while the OFF position corresponds to the information deletion or “forgetting.”

In a recent publication, scientists from the Universitat Autònoma de Barcelona (UAB), the CNR-SPIN (Italy), the Catalan Institute of Nanoscience and Nanotechnology (ICN2), the Institute of Micro and Nanotechnology (IMN-CNM-CSIC) and the ALBA Synchrotron have explored the emulation of artificial synapses using new advanced material devices. The project was led by Serra Húnter Fellow Enric Menéndez and ICREA researcher Jordi Sort, both at the Department of Physics of the UAB, and is part of Sofia Martins Ph.D. thesis.

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In a paper published by Science, DeepMind demonstrates how neural networks can improve approximation of the Density Functional (a method used to describe electron interactions in chemical systems). This illustrates deep learning’s promise in accurately simulating matter at the quantum mechanical.

In a paper published in the scientific journal Science, DeepMind demonstrates how neural networks can be used to describe electron interactions in chemical systems more accurately than existing methods.

Density Functional Theory, established in the 1960s, describes the mapping between electron density and interaction energy. For more than 50 years, the exact nature of mapping between electron density and interaction energy — the so-called density functional — has remained unknown. In a significant advancement for the field, DeepMind has shown that neural networks can be used to build a more accurate map of the density and interaction between electrons than was previously attainable.

By expressing the functional as a neural network and incorporating exact properties into the training data, DeepMind was able to train the model to learn functionals free from two important systematic errors — the delocalization error and spin symmetry breaking — resulting in a better description of a broad class of chemical reactions.

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A nanomaterials-engineered penetrating sealer developed by Washington State University researchers is able to better protect concrete from moisture and salt—the two most damaging factors in crumbling concrete infrastructure in northern states.

The novel sealer showed a 75% improvement in repelling water and a 44% improvement in reducing salt damage in laboratory studies compared to a commercial sealer. The work could provide an additional way to address the challenge of aging bridges and pavements in the U.S.

“We focused on one of the main culprits that compromises the integrity and durability of concrete, which is moisture,” said Xianming Shi, professor in the Department of Civil and Environmental Engineering who led the work. “If you can keep concrete dry, the vast majority of durability problems would go away.”

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The strongest part of a tree lies not in its trunk or its sprawling roots, but in the walls of its microscopic cells.

A single wood cell wall is constructed from fibers of cellulose—nature’s most abundant polymer, and the main structural component of all plants and algae. Within each fiber are reinforcing , or CNCs, which are chains of organic polymers arranged in nearly perfect crystal patterns. At the nanoscale, CNCs are stronger and stiffer than Kevlar. If the crystals could be worked into materials in significant fractions, CNCs could be a route to stronger, more sustainable, naturally derived plastics.

Now, an MIT team has engineered a composite made mostly from cellulose nanocrystals mixed with a bit of synthetic polymer. The organic crystals take up about 60 to 90 percent of the material—the highest fraction of CNCs achieved in a composite to date.

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A team of researchers from the University of Surrey’s Advanced Technology Institute (ATI) and the Federal University of Pelotas (UFPel), Brazil, has developed a new type of supercapacitor that can be integrated into footwear or clothing, an advance with applications in wearables and IoT (Internet of Things) devices.

A supercapacitor is an electricity storage device, similar to a battery, but it stores and releases electricity much faster.

The researchers have devised a novel method for the development of flexible supercapacitors based on carbon nanomaterials. The new method, which is cheaper and less time-consuming to fabricate, involves transferring aligned carbon nanotube (CNT) arrays from a silicon wafer to a polydimethylsiloxane (PDMS) matrix. This is then coated in a material called polyaniline (PANI), which stores energy through a mechanism known as pseudocapacitance, offering outstanding energy storage properties with exceptional mechanical integrity.

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Researchers at Leipzig University have succeeded in moving tiny amounts of liquid at will by remotely heating water over a metal film with a laser. The currents generated in this way can be used to manipulate and even capture tiny objects. This will unlock groundbreaking new solutions for nanotechnology, the manipulation of liquids in systems in tiny spaces, or in the field of diagnostics, by making it possible to detect the smallest concentrations of substances with new types of sensor systems.

The findings are described in an article recently published in Nature Communications (“Hydrodynamic manipulation of nano-objects by optically induced thermo-osmotic flows”).

Illustration of a gold nanoparticle trapped near a locally heated gold surface by hydrodynamic and van der Waals forces. (Image: Martin Fränzl, Universität Leipzig)

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Delivering what has been so challenging to produce, researchers present an engineered analog of tooth enamel – an ideal model for designing biomimetic materials – designed to closely mimic the composition and structure of biological teeth’s hard mineralized outer layer. It demonstrates exceptional mechanical properties, they say.

Natural tooth enamel – the thin outer layer of our teeth – is the hardest biological material in the human body. It is renowned for its high stiffness, hardness, viscoelasticity, strength, and toughness and exhibits exceptional damage resistance, despite being only several millimeters thick.

Tooth enamel’s unusual combination of properties is a product of its hierarchical architecture – a complex structure made up of mostly hydroxyapatite nanowires interconnected by an amorphous intergranular phase (AIP) consisting of magnesium-substituted amorphous calcium phosphate. However, accurately replicating this type of hierarchical organization in a scalable abiotic composite has remained a challenge.

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