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Circa 1999 could lead to a sorta room temperature hydrogen fill up.


Masses of single-walled carbon nanotubes (SWNTs) with a large mean diameter of about 1.85 nanometers, synthesized by a semicontinuous hydrogen arc discharge method, were employed for hydrogen adsorption experiments in their as-prepared and pretreated states. A hydrogen storage capacity of 4.2 weight percent, or a hydrogen to carbon atom ratio of 0.52, was achieved reproducibly at room temperature under a modestly high pressure (about 10 megapascal) for a SWNT sample of about 500 milligram weight that was soaked in hydrochloric acid and then heat-treated in vacuum. Moreover, 78.3 percent of the adsorbed hydrogen (3.3 weight percent) could be released under ambient pressure at room temperature, while the release of the residual stored hydrogen (0.9 weight percent) required some heating of the sample.

Circa 2019


Thanks to Stanford researchers, there might be a new recipe for hydrogen fuel: saltwater, electrodes and solar power. The researchers have developed a proof-of-concept for separating hydrogen and oxygen gas from seawater via electricity. It’s far cheaper than the current methods, which rely on creating hydrogen fuel from purified water.

Breaking up a substance like water to create hydrogen and oxygen is called electrolysis and is a scientific technique centuries old. It was first codified by British scientific legend Michael Faraday, whose two laws of electrolysis from 1834 still guide scientists today. With a power source connecting to two water-based electrodes, scientists can get hydrogen bubbles to come out of an end called an cathode, while oxygen comes out of an end called an anode.

That works fine for fresh water, but saltwater is trickier because of its ability to corrode electrodes with chloride, which would limit a system’s lifespan. The trick for Hongjie Dai, a professor of chemistry at Stanford, and his team was a change in materials.

What are Soft Robots?

What are Soft Robots?Soft robots are largely made of readily malleable matter, such as fluids, gels, and elastomers, which may match specific materials in a process known as compliance matching. The idea of compliance matching states that materials that make contact with one other should have similar mechanical stiffness in order to transfer internal load uniformly and reduce interfacial tensile stress. This principle, nevertheless, does not applicable to rigid robots (E=109Pa) engaging with soft materials (E=102-106Pa), causing serious damage or mechanical immobility. These kinds of interactions with soft materials are common, for example, with natural skin, muscular tissue, and sensitive interior organs, but also with creatures, artificial predictor variables of biological functions, and so on. Because of this huge disparity in mechanical compliance, it’s simple to assume that stiff robots are unsuitable, if not hazardous, for close human engagement.

The future is optical. Photonic processors promise blazing fast calculation speeds with much lower power demands, and they could revolutionise machine learning.

Photonic computing is as the name suggests, a computer system that uses optical light pulses to form the basis of logic gates rather than electrical transistors. If it can be made to work in such a way that processors can be mass produced at a practical size it has the potential to revolutionise machine learning and other specific types of computing tasks. The emphasis being on the word if. However there are some intriguing sounding products close to coming to market that could changes things drastically.

The idea behind photonic computers is not a new one, with optical matrix multiplications first being demonstrated in the 1970s, however nobody has managed to solve many of the roadblocks to getting them to work on a practical level that can be integrated as easily as transistor based systems. Using photons is an obvious choice to help speed things up. After all all new homes in the UK are built with fibre to the home for a reason. Fibre optic cables are superior to aluminium or copper wires for the modern world of digital data communication. They can transmit more information faster, and over longer distances without signal degradation than metal wiring. However transmitting data from A to B is a whole different kettle of fish to putting such optical pipelines onto a chip fabrication that allows for matrix processing, even though some data centres already use optical cables for faster internal data transfer over short distances.