Month: June 2015

The recent unveiling by Tesla founder Elon Musk of the low-cost Powerwall storage battery is the latest in a series of exciting advances in battery technologies for electric cars and domestic electricity generation.

We have also seen the development of an aluminium-ion battery that may be safer, lighter and cheaper than the lithium-ion batteries used by Tesla and most other auto and technology companies.
These advances are exciting for two main reasons. First, the cost of energy storage, in the form of batteries, is decreasing significantly. This makes electric vehicle ownership and home energy storage much more attainable.
The second, related reason is that these cheaper green technologies may make the transition to a greener economy easier and faster than we have so far imagined (although, as has been recently pointed out on The Conversation, these technologies are only one piece of the overall energy puzzle).
Beware the industrial option

These technological advances, and much of the excitement around them, lend themselves to the idea that solving environmental problems such as climate change is primarily a case of technological adjustment. But this approach encourages a strategy of “superindustrialisation”, in which technology and industry are brought to bear to resolve climate change, through resource efficiency, waste reduction and pollution control. In this context, the green economy is presented as an inevitable green technological economic wave.
But the prospect of this green economic wave needs to be considered within a wider environmental and social context, which makes solving the problems much more complex. Let’s take electric vehicles as an example.
The ecological damage of cars, electric or otherwise, is partly due to the fact that the car industry generates more than 3 million tonnes of scrap and waste every year. In 2009, 14 million cars were scrapped in the United States alone.
The number of cars operating in the world is expected to climb from the current 896 million to 1.2 billion by 2020. The infrastructure associated with growing vehicle use, particularly roads, also makes a significant contribution to the destruction of ecosystems and arguably has important social costs.

Electric vehicles (EVs) offer a substantial greenhouse gas emission improvement from the internal combustion engine. However, this improvement depends on green electricity production.

An EV powered by average European electricity production is likely to reduce a vehicle’s global warming potential by about 20% over its life cycle. This is not insignificant, but it is nowhere near a zero-emission option.

In large part, the life-cycle emissions of an electric vehicle are due to the energy-intensive nature of battery production and the associated mining processes. Indeed, there are questions around battery production and resource depletion, but perhaps more concerning is the impact that mining lithium and other materials for the growing battery economy, such as graphite, will have on the health of workers and communities involved in this global production network.

Processes associated with lithium batteries may produce adverse respiratory, pulmonary and neurological health impacts. Pollution from graphite mining in China has resulted in reports of “graphite rain”, which is significantly impacting local air and water quality.

The production of green technologies creates many interesting contradictions between environmental benefits at the point of use, versus human and environmental costs at the production end. Baoding, a Chinese city southwest of Beijing, has been labelled the greenest city in the world or the world’s only carbon-positive city. This is because Boading produces enormous quantities of wind turbines and solar cells for the United States and Europe, and has about 170 alternative energy companies based there.

But last year the air in the city of Baoding was declared to be the most polluted in China – a country where air quality reportedly contributes to 1.2 million deaths each year. These impacts need to be placed into any discussion or policy frameworks when exploring the shift to a “greener” future.

Beware new problems from new solutions

We should be excited about the shift to greener cars and affordable home electricity storage units, but in the process of starting to solve the technological challenges of climate change we must ensure that we are not creating environmental problems, particularly for the largely unseen workers and communities further up the production stream.

Our response to climate change needs to be more than just a technological adjustment. We argue that the shift to a green economy requires more transformative social political actions via skills and training, worker participation, and the coming together of environmental organisations, unions, business and government.

Indeed, the world of work is a critical site for emission reductions: 80% of Europe’s carbon emissions are workplace-related.

As we adopt emerging greener technologies, we will have to look beyond our shiny new Powerwall, or the electric car parked on the front drive, to ensure that the environmental and social changes promised by green technologies are not just illusions.

References:http://phys.org/

Optical interconnects made of silicon act as a prism to direct infrared light transferring data between computer chips

While the heavy lifting in computer processing takes place inside the chips, an analysis by Stanford professor of electrical engineering, David Miller, showed that up to 80 percent of a microprocessor’s power is eaten up by the transmitting of data as a stream of electrons over wire interconnects. Basically, shipping requires far more energy than production, and chewing through all that power is the reason laptops heat up.

Inspired by the optical technology of the internet, the researchers sought to move data between chips over fiber optic threads beaming photons of light. Besides using far less energy than traditional wire interconnects, chip-scale optic interconnects can carry more than 20 times more data.

The majority of fiber optics are made from silicon, which is transparent to infrared light the same way glass is to visible light. Thus, using optical interconnects made from silicon was an obvious choice. “Silicon works,” said Tom Abate, Stanford Engineering communications director. “The whole industry knows how to work with silicon.”

But optical interconnects need to be designed one at a time, making the switch to the technology impractical for computers since such a system requires thousands of such links. That’s where the inverse design algorithm comes in.

The software provides the engineers with details on how the silicon structures need to be designed for performing tasks specific to their optical circuitry. The group designed a working optical circuit in the lab, copies were made, and all worked flawlessly despite being constructed on less than ideal equipment. The researchers cite this as proof of the commercial viability of their optical circuitry, since typical commercial fabrication plants use highly precise, state-of-the-art manufacturing equipment.

While details of the algorithm’s functions is a tad complex, it basically works by designing silicon structures that are able to bend infrared light in various and useful ways, much like a prism bends visible light into a rainbow. When light is beamed at the silicon link, two wavelengths, or colors, of light split off at right angles in a T shape. Each silicon thread is miniscule – 20 could sit side-by-side within a human hair.

The optical interconnects can be constructed to direct specific frequencies of infrared light to specific locations. And it’s the algorithm that instructs how to create these silicon prisms with just the right amount and bend of infrared light. Once the calculation is made as to the proper shape for each specific task, a tiny barcode pattern is etched onto a slice of silicon.

Building an actual computer that uses the optical interconnects has yet to be realized, but the algorithm is a first big step. Other potential uses for the algorithm include designing compact microscopy systems, ultra-secure quantum communications, and high bandwidth optical communications.

The team describes their work in the journal Nature Photonics.

References:http://www.gizmag.com/

 

A team of researchers from the University of Twente has found a way to 3D print structures of copper and gold, by stacking microscopically small metal droplets. These droplets are made by melting a thin metal film using a pulsed laser. Their work is published on Advanced Materials.

3D printing is a rapidly advancing field, that is sometimes referred to as the ‘new cornerstone of the manufacturing industry’. However, at present, 3D printing is mostly limited to plastics. If metals could be used for 3D printing as well, this would open a wide new range of possibilities. Metals conduct electricity and heat very well, and they’re very robust. Therefore, 3D printing in metals would allow manufacturing of entirely new devices and components, such as small cooling elements or connections between stacked chips in smartphones.
However, metals melt at a high temperature. This makes controlled deposition of metal droplets highly challenging. Thermally robust nozzles are required to process liquid metals, but these are hardly available. For small structures in particular (from 100 nanometres to 10 micrometres) no good solutions for this problem existed yet.
Researchers from FOM and the University of Twente now made a major step towards high-resolution metal printing. They used laser light to melt copper and gold into micrometre-sized droplets and deposited these in a controlled manner. In this method, a pulsed laser is focused on a thin metal film. that locally melts and deforms into a flying drop. The researchers then carefully position this drop onto a substrate. By repeating the process, a 3D structure is made. For example, the researchers stacked thousands of drops to form micro-pillars with a height of 2 millimetres and a diameter of 5 micrometres. They also printed vertical electrodes in a cavity, as well as lines of copper. In effect, virtually any shape can be printed by smartly choosing the location of the drop impact.
High energy

In this study, the researchers used a surprisingly high laser energy in comparison to earlier work, to increase the impact velocity of the metal droplets. When these fast droplets impact onto the substrate, they deform into a disk shape and solidify in that form. The disk shape is essential for a sturdy 3D print: it allows the researchers to firmly stack the droplets on top of each other. In previous attempts, physicists used low laser energies. This allowed them to print smaller drops, but the drops stayed spherical, which meant that a stack of solidified droplets was less stable.
In their article, the researchers explain which speed is required to achieve the desired drop shape. They had previously predicted this speed for different laser energies and materials. This means that the results can be readily translated to other metals as well.
One remaining problem is that the high laser energy also results in droplets landing on the substrate next to the desired location. At present this cannot be prevented. In future work the team will investigate this effect, to enable clean printing with metals, gels, pastas or extremely thick fluids.

References:http://phys.org/

Until now, studies of human interactions through mobile communication and social media have always been conducted at the country scale—using broad strokes to produce illustrations of society’s social networking tendencies. These explorations have concluded that social networks and contacts are primarily created in relation to geographic proximity.

Now, a new study led by MIT researchers bridges the gap between country and city, employing a novel method to explore the dynamic structure of social networks on the urban scale. The study, published this week in Scientific Reports, shows that urban networks are not determined geographically as traditionally thought, but rather socially.
“I was interested to investigate the relationship of social networks and human distance with the built environment and urban transportation,” says Department of Civil and Environmental Engineering (CEE) Associate Professor Marta González, co-author of the paper. “We found that geography plays only a minor role when forming social networking communities within cities. Unlike the country, cities have more dispersed communities.” Understanding how information spreads between social networking communities within a city will be crucial in the implementation of sustainable urban practices and policies in the future, she added.
The research grew from earlier explorations of expansive geolocated communication datasets. Gonzalez said that while the structure of communities was always analyzed before at the country scale, the urban scale had yet to be explored—this fueled her team’s mission to understand how social networks relate to their physical space.
Through the observation of social networks within urban boundaries, the team presents a new perspective on an established study of searchability in self-organized networks. The study extracted phone data from over 25 million phone users, from three countries, over the course of six months. The information was used to systematically outline the structure of network communities within a city.
“We were able, for the first time, to observe how social networks work on a urban scale and their searchability implications,” said lead author Carlos Herrera-Yagüe, of the Technical University of Madrid. Their study, he continued, built the social network that emerged from billions of mobile phone interactions across three countries, in a much higher spatial resolution provided from mobile phone towers.
The paper was co-authored Gonzalez, principal investigator on the study; Herrera-Yaque, lead author; former CEE postdoc Christian Schneider ’13, Rosa Maria Benito and Pedro Zufira professors from Technical University of Madrid, and Zibigniew Smoreda from Orange Labs.
Mobile interactions
Gonzalez and her team systematically demonstrated that cities change the structure of social networks. Using data from 7 billion mobile phone interactions from 155 cities in Spain, France, and Portugal, they explored the role of both social and geographic distances in social networks.
They concluded that urban networks are not determined by geographic proximity, but rather social distance. That is to say, groups of individuals with comparable interests, hobbies, and careers form communities within their city’s social networks.
According to Gonzalez, these findings are most likely related to causes such as urban growth and the economic function of cities. “Social distance is hard to define and measure with passive data,” she says. “But it’s important to know where the communities are within social networks, and how they expand.” It’s the social structure of urban communities, not geographic, that makes social networks searchable within cities.
This understanding that content is spread through homophily and not geography has implications for adoptions of innovations and epidemics within social networks, she adds.
“We are envisioning social media apps for social good—in this case, sustainable adoptions in the city,” she says.
In urban planning, the examination of social networks is influential in the development of urban policies that address problems such as segregation and political divisions. The results of this team’s study, Herrera says, prove that humans have built communities that connect people to all resources, while ignoring the vast majority of the social network.
“This is a remarkably difficult challenge that mankind has solved in a self-organized way,” Herrera remarks. The research has the potential to inspire the creation of a new generation of communications and transportation infrastructures that are decentralized and more focused on society’s use of them.
Gonzalez adds that the current research project opens the way for more detailed studies of the subject, noting, “It would be interesting to see if the socioeconomic status of people, their age, and/or gender have a role in the results found.”
With this newly developed model, Gonzalez and her team will continue to study social network groups and their mobility in order to better understand how to effectively spread information through networks.

References:http://phys.org/