Dave Brain: What a planet needs to sustain life

September 24, 2016

“Venus is too hot, Mars is too cold, and Earth is just right,” says planetary scientist Dave Brain. But why? In this pleasantly humorous talk, Brain explores the fascinating science behind what it takes for a planet to host life — and why humanity may just be in the right place at the right time when it comes to the timeline of life-sustaining planets.

The ‘impossible’ EM Drive is about to be tested in space

September 24, 2016


An actual EM Drive is about to be launched into space for the first time, so scientists can finally figure out – once and for all – if it really is possible for a rocket engine to generate thrust without any kind of exhaust or propellant.

Built by American inventor and chemical engineer, Guido Fetta, the EM Drive is as controversial as it gets, because while certain experiments have suggested that such an engine could work, it also goes against one of the most fundamental laws of physics we have.

As Newton’s Third Law states, “To each action there’s an equal and opposite reaction,” and many physicists say the EM Drive categorically violates that law.

This is because in order for a thruster to gain momentum in a certain direction, it has to expel some kind of propellent or exhaust in the opposite direction.

But the EM Drive simply goes in one direction with no propellant, and thus violates the law of conservation of momentum, which Newton derived from his Third Law.

And not only that, but it could produce enough thrust to blast humans to Mars in just 70 days.

As Fiona MacDonald put it back in June, space enthusiasts love to get excited about the EM Drive, because if it works, it has the potential to remove major barriers in our need to explore the Solar System and beyond.

But just as many are sick of hearing about it, because, on paper at least, it doesn’t work within the laws of physics.

Invented by British scientist Roger Shawyer back in 1999, the EM Drive – short for electromagnetic propulsion drive – purportedly works like this.

It uses electromagnetic waves as ‘fuel’, creating thrust by bouncing microwave photons back and forth inside a cone-shaped closed metal cavity. This causes the ‘pointy end’ of the EM Drive to accelerate in the opposite direction that the drive is going.

“To put it simply, electricity converts into microwaves within the cavity that push against the inside of the device, causing the thruster to accelerate in the opposite direction,” Mary-Ann Russon explains over at The International Business Times.

Since its invention, the EM drive has shown no signs of quitting, in test after test. Last year, trials by NASA scientists at the Eagleworks lab revealed “anomalous thrust signals”, and an independent researcher in Germany conceded that the propulsion system, somehow, does indeed produce thrust.

Fast-forward to now, and there are rumours that the NASA Eagleworks paper we reported on in June has finally passed the peer-review process, and is expected to be published by the American Institute of Aeronautics and Astronautics’ Journal of Propulsion and Power.

If the rumours by José Rodal from MIT are true – and let’s be clear, they’re still just rumours at this point – it could be huge.

As Brendan Hesse explains for Digital Trends:

“This is an important step for the EM Drive as it adds legitimacy to the technology and the tests done thus far, opening the door for other groups to replicate the tests. This will also allow other groups to devote more resources to uncovering why and how it works, and how to iterate on the drive to make it a viable form of propulsion.

So, while a single peer-reviewed paper isn’t going to suddenly equip the human race with interplanetary travel, it’s the first step toward eventually realising that possible future.”

And on top of all of that, we’re about to see an actual EM Drive be blasted into space.

Guido Fetta is CEO of Cannae Inc, and the inventor of the Cannae Drive – a rocket engine that’s based on Roger Shawyer’s original EM Drive design. Last month, he announced that he would launch this thruster on a 6U CubeSat – a type of miniaturised satellite.

David Hambling reports for Popular Mechanics that roughly one-quarter of this shoebox-sized satellite will be taken up by the Cannae Drive, and they’ll stay in orbit for at least six months: “The longer it stays in orbit, the more the satellite will show that it must be producing thrust without propellant.”

No launch date has been set just yet, but it could happen in as soon as six months’ time.

As Hambling points out, Fetta better hurry, because a team of engineers in China, and Shawyer himself, are both also working on their own launchable EM Drives, so someone’s going to get there first, and we seriously cannot wait to see what will happen.

IBM is one step closer to mimicking the human brain

September 24, 2016


Scientists at IBM have claimed a computational breakthrough after imitating large populations of neurons for the first time.

Neurons are electrically excitable cells that process and transmit information in our brains through electrical and chemical signals. These signals are passed over synapses, specialised connections with other cells.

It’s this set-up that inspired scientists at IBM to try and mirror the way the biological brain functions using phase-change materials for memory applications.

Using computers to try to mimic the human brain is something that’s been theorised for decades due to the challenges of recreating the density and power. Now, for the first time, scientists have created their own “randomly spiking” artificial neurons that can store and process data.

“The breakthrough marks a significant step forward in the development of energy-efficient, ultra-dense integrated neuromorphic technologies for applications in cognitive computing,” the scientists said.

The artificial neurons consist of phase-change materials, including germanium antimony telluride, which exhibit two stable states, an amorphous one (without a clearly defined structure) and a crystalline one (with structure). These materials are also the basis of re-writable Blue-ray but in this system the artificial neurons do not store digital information; they are analogue, just like the synapses and neurons in a biological brain.

The beauty of these powerful phase-change-based artificial neurons, which can perform various computational primitives such as data-correlation detection and unsupervised learning at high speeds, is that they use very little energy – just like human brain.

In a demonstration published in the journal Nature Nanotechnology, the team applied a series of electrical pulses to the artificial neurons, which resulted in the progressive crystallisation of the phase-change material, ultimately causing the neuron to fire.

In neuroscience, this function is known as the integrate-and-fire property of biological neurons. This is the foundation for event-based computation and, in principle, is quite similar to how a biological brain triggers a response when an animal touches something hot, for instance.

Tomas Tuma, co-author of the paper, said the breakthrough could help create a new generation of extremely dense neuromorphic computing systems
Tomas Tuma, co-author of the paper, said the breakthrough could help create a new generation of extremely dense neuromorphic computing systems

As part of the study, the researchers organised hundreds of artificial neurons into populations and used them to represent fast and complex signals. When tested, the artificial neurons were able to sustain billions of switching cycles, which would correspond to multiple years of operation at an update frequency of 100Hz.

The energy required for each neuron update was less than five picojoule and the average power less than 120 microwatts — for comparison, 60 million microwatts power a 60 watt light bulb, IBM’s research paper said.

When exploiting this integrate-and-fire property, even a single neuron can be used to detect patterns and discover correlations in real-time streams of event-based data. “This will significantly reduce the area and power consumption as it will be using tiny nanoscale devices that act as neurons,” IBM scientist and author, Dr. Abu Sebastian told WIRED.

This, IBM believes, could be helpful in the further development of internet of things technologies, especially when developing tiny sensors.

“Populations of stochastic phase-change neurons, combined with other nanoscale computational elements such as artificial synapses, could be a key enabler for the creation of a new generation of extremely dense neuromorphic computing systems,” said Tomas Tuma, co-author of the paper.

This could be useful in sensors collecting and analysing volumes of weather data, for instance, said Sebastian, collected at the edge, in remote locations, for faster and more accurate weather forecasts.

The artificial neurons could also detect patterns in financial transactions to find discrepancies or use data from social media to discover new cultural trends in real time. While large populations of these high-speed, low-energy nano-scale neurons could also be used in neuromorphic co-processors with co-located memory and processing units.

Mark Zuckerberg and Priscilla Chan’s $3 billion effort aims to rid world of major diseases by end of century

September 24, 2016


Facebook co-founder Mark Zuckerberg and his wife, Priscilla Chan, on Wednesday announced a $3 billion effort to accelerate scientific research with the wildly ambitious goal of “curing all disease in our children’s lifetime.”

The many components of the initiative include creating universal technology “tools” based on both traditional science and engineering on which all researchers can build, including a map of all cell types, a way to continuously monitor blood for early signs of illness, and a chip that can diagnose all diseases (or at least many of them). The money will also help fund what they referred to as 10 to 15 “virtual institutes” that will bring together investigators from around the world to focus on individual diseases or other goals — an idea that has the potential to upend biomedical science.

Being a scientist in academia today can often be a solitary endeavor as the system is set up to encourage colleagues to keep data exclusive in the hopes that this strategy helps them be more competitive at getting publications and grants. But as more Silicon Valley entrepreneurs like Zuckerberg are seeking to make their mark in the biological sciences, they are emphasizing the power of collaboration and openness.

A centerpiece of the new effort, called Chan Zuckerberg Science, involves creating a “Biohub” at the University of California at San Francisco (UCSF) Mission Bay campus that will bring together scientists from Stanford, the University of California at Berkeley and UCSF.

Zuckerberg and Chan, among the world’s 10 wealthiest couples, with a net worth of $55.2 billion, emphasized that their timeline is long — by the end of the century.

“We have to be patient. This is hard stuff,” Zuckerberg said.

Chan said, “That doesn’t mean no one will ever get sick, but it means our children and their children should get sick a lot less.”

Many of themes articulated by Zuckerberg and Chan on Wednesday in San Francisco echo ideas furthered by other technology philanthropists who have donated substantial amounts of money to medical science. Sean Parker, a Napster co-founder, earlier this year set up a multi-center, $250 million effort to bring together top researchers from around the country to focus on immunotherapy for cancer. Microsoft’s Paul Allen has already invested $100 million in a cell-biology institute to try to create models of the fundamental building blocks of life.

Self-powered ‘materials that compute’ and recognize simple patterns

September 24, 2016


University of Pittsburgh researchers have modeled the design of a “material that computes” — a hybrid material, powered only by its own chemical reactions, that can recognize simple patterns.

The material could one day be integrated into clothing and used to monitor the human body, or developed as a skin for “squishy” robots, for example, according to the researchers, writing in the open-access AAAS journal Science Advances.

A computer that combines gels and piezeoelectric materials

The computations (needed to design the hypothetical material) were modeled utilizing Belousov-Zhabotinsky (BZ) gels, a substance that oscillates in the absence of external stimuli, combined with an overlaying piezoelectric (PZ) cantilever, forming “BZ-PZ” (as in “easy peasy”). The BZ gels oscillate periodically, triggered by chemical stimulation, without the need for external driving stimuli. Piezoelectric (PZ) materials generate a voltage when deformed and, conversely, undergo deformation in the presence of an applied voltage.

Two BZ-PZ oscillator units connected with electrical wires. Triggered by the chemical oscillations, the BZ gels (green) expand in volume, generating a force (F1 and F2) and thereby cause the deflections ξ1 and ξ2 of the PZ cantilevers (orange and blue layers) , which generate an electric voltage U. That voltage then deflects the cantilevers (the inverse PZ effect), which then compress the underlying BZ gels and thereby modify the chemomechanical oscillations in these gels. The end result is the components’ response to self-generated signals (sensing), volumetric changes in the gel (actuation), and the passage of signals between the units (communication). For computation, the communication also leads to synchronization of the BZ gel oscillators. (credit: Yan Fang et al./Science Advances)

“By combining these attributes into a ‘BZ-PZ’ unit and then connecting the units by electrical wires, we designed a device that senses, actuates, and communicates without an external electrical power source,” the researchers explain in the paper.*

The result is that the device can also be used to perform computation. To use that for pattern recognition, the researchers first stored a pattern of numbers as a set of polarities in the BZ-PZ units, and the input patterns were coded with the initial phase of the oscillations imposed on these units.

Multiple BZ-PS units wired in serial and parallel configurations to form a network (credit: Yan Fang et al./Science Advances)

With multiple BZ-PZ units, the oscillators can be wired into a network  formed, for example, from units that are connected in parallel or in series. The resulting transduction between chemomechanical and electrical energy creates signals that quickly propagate and thus permits remote coupled oscillators to communicate and synchronize. This synchronization behavior in BZ-PZ network can be used for oscillator-based computing.

The computational modeling revealed that the input pattern closest to the stored pattern exhibits the fastest convergence time to the stable synchronization behavior, and is the most effective at recognizing patterns. In this study, the materials were programmed to recognize black-and-white pixels in the shape of numbers that had been distorted.

The researchers’ next goal is to expand from analyzing black-and-white pixels to grayscale and more complicated images and shapes, as well as to enhance the devices storage capability.

Perfect for monitoring human and robot bodies

Compared to a traditional computer, these computations are slow and take minutes. “Individual events are slow because the period of the BZ oscillations is slow,” said Victor V. Yashin, Research Assistant Professor of Chemical and Petroleum Engineering. “However, there are some tasks that need a longer analysis, and are more natural in function. That’s why this type of system is perfect to monitor environments like the human body.”

For example, Dr. Yashin said that patients recovering from a hand injury could wear a glove that monitors movement, and can inform doctors whether the hand is healing properly or if the patient has improved mobility. Another use would be to monitor individuals at risk for early onset Alzheimer’s, by wearing footwear that would analyze gait and compare results against normal movements, or a garment that monitors cardiovascular activity for people at risk of heart disease or stroke.

Since the devices convert chemical reactions to electrical energy, there would be no need for external electrical power. This would also be ideal for a robot or other device that could utilize the material as a sensory skin.

The research is funded by a five-year National Science Foundation Integrated NSF Support Promoting Interdisciplinary Research and Education (INSPIRE) grant, which focuses on complex and pressing scientific problems that lie at the intersection of traditional disciplines.

“This work at the University of Pittsburgh … is an example of this groundbreaking shift away from traditional silicon CMOS-based digital computing to a non-von Neumann machine in a polymer substrate, with remarkable low power consumption,” said Sankar Basu, NSF program director.

* This continues the research of Anna C. Balazs, Distinguished Professor of Chemical and Petroleum Engineering, and Steven P. Levitan, the John A. Jurenko Professor of Electrical and Computer Engineering. 

Abstract of Pattern recognition with “materials that compute”

Driven by advances in materials and computer science, researchers are attempting to design systems where the computer and material are one and the same entity. Using theoretical and computational modeling, we design a hybrid material system that can autonomously transduce chemical, mechanical, and electrical energy to perform a computational task in a self-organized manner, without the need for external electrical power sources. Each unit in this system integrates a self-oscillating gel, which undergoes the Belousov-Zhabotinsky (BZ) reaction, with an overlaying piezoelectric (PZ) cantilever. The chemomechanical oscillations of the BZ gels deflect the PZ layer, which consequently generates a voltage across the material. When these BZ-PZ units are connected in series by electrical wires, the oscillations of these units become synchronized across the network, where the mode of synchronization depends on the polarity of the PZ. We show that the network of coupled, synchronizing BZ-PZ oscillators can perform pattern recognition. The “stored” patterns are set of polarities of the individual BZ-PZ units, and the “input” patterns are coded through the initial phase of the oscillations imposed on these units. The results of the modeling show that the input pattern closest to the stored pattern exhibits the fastest convergence time to stable synchronization behavior. In this way, networks of coupled BZ-PZ oscillators achieve pattern recognition. Further, we show that the convergence time to stable synchronization provides a robust measure of the degree of match between the input and stored patterns. Through these studies, we establish experimentally realizable design rules for creating “materials that compute.”