DOE’s new renewable energy Venture Capital unit ARPA-E has just funded an entirely new kind of liquid battery innovation from MIT professor Donald Sadoway, that works like an aluminum plant running in reverse; producing power instead of consuming it.

Under the ARPA-E program at the DOE, the Obama administration has provided record-setting funding for advanced breakthroughs in renewable energy technology – that could propel America to the front of the post-oil age economy.

Just 37 technologies were selected for their potential transformational impact in the world, out of 3,600 applicants. Of the 37 winners; Sadaway’s has received the most funding; with $7 million.

MIT professor Donald Sadoway has come up with a technology never attempted before that could lead to very large-scale commercialization. Renewable energy storage will be worth trillions to whichever nation that can make economical, so Sadoway’s research holds promise: it was limited to domestically available liquid metals that are both plentiful and cheap.

Sadoway’s idea came from the technology used by aluminum smelting plants able to sustain extremely high levels of electrical current for years at a time.

The basic principle is to place three layers of liquid inside a container: Two different metal alloys, and a layer of a salt. The energy is stored in the liquid metals that want to react with one another but can do so only by transferring ions — electrically charged atoms of one of the metals — across the electrolyte, which results in the flow of electric current out of the battery.

When the battery is being charged, some ions migrate through the insulating salt layer to collect at one of the terminals. Then, when the power is being drained from the battery, those ions migrate back through the salt and collect at the opposite terminal.

The whole device is kept at a high temperature, around 700 degrees Celsius, so that the layers remain molten. In the small devices being tested in the lab, maintaining this temperature requires an outside heater, but Sadoway says that in the full-scale version, the electrical current being pumped into, or out of, the battery will be sufficient to maintain that temperature without any outside heat source.

One day, we’ll remember these ARPA-E 37 innovations for fundamentally changing the way we use and produce energy.  By getting the funding out under The Recovery Act; the administration is able to bypass the usual foot-dragging in the Senate that has prevented action on climate and clean energy legislation that is needed to safeguard our future as a first world country.

ARPA-E’s venture capital funding is intended to attract real VC funding so renewable energy technology breakthroughs in university labs can make it through the “Valley of Death” to commercialization.

Let’s hope our own VCs see the promise soon enough. Certainly Lightspeed Venture Partners’ Andrew Chung in Silicon Valley sees grid-scale storage as an area set to explode in the next decade or so; but our VCs better move quickly.

Within a week of the $7 million announcement from our US DOE a French oil company counter-offered Sadoway $4 million. Storage is to renewable energy as the railroad was to the coal industry in the 19th century.

Scientists say they’ve made a breakthrough in their pursuit of computers that “think” like a living thing’s brain – an effort that tests the limits of technology.

Even the world’s most powerful supercomputers can’t replicate basic aspects of the human mind. The machines can’t imagine a wall painted a different colour, for instance, or picture a person’s face and connect that to an emotion.

If researchers can make computers operate more like a brain thinks – by reasoning and dealing with abstractions, among other things – they could unleash tremendous insights in such diverse fields as medicine and economics.

A computer with the power of a human brain is not yet near.

But this week researchers from IBM are reporting that they’ve simulated a cat’s cerebral cortex, the thinking part of the brain, using a massive supercomputer.

The computer has 147,456 processors (most modern PCs have just one or two processors) and 144 terabytes of main memory – 100,000 times as much as your computer has.

The scientists had previously simulated 40 per cent of a mouse’s brain in 2006, a rat’s full brain in 2007, and 1 per cent of a human’s cerebral cortex this year, using progressively bigger supercomputers.

The latest feat, being presented at a supercomputing conference in Portland, Oregon, doesn’t mean the computer thinks like a cat, or that it is the progenitor of a race of robo-cats.

The simulation, which runs 100 times slower than an actual cat’s brain, is more about watching how thoughts are formed in the brain and how the roughly one billion neurons and 10 trillion synapses in a cat’s brain work together.

The researchers created a program that told the supercomputer, which is in the Lawrence Livermore National Laboratory, to behave how a brain is believed to behave.

The computer was shown images of corporate logos, including IBM’s, and scientists watched as different parts of the simulated brain worked together to figure out what the image was.

Dharmendra Modha, manager of cognitive computing for IBM Research and senior author of the paper, called it a “truly unprecedented scale of simulation.”

Researchers at Stanford University and Lawrence Berkeley National Laboratory were also part of the project.

Modha says the research could lead to computers that rely less on “structured” data, such the input 2 plus 2 equals 4, and can handle ambiguity better, like identifying the corporate logo even if the image is blurry.

Or such computers could incorporate senses like sight, touch and hearing into the decisions they make.

One reason that development would be significant to IBM: The company is selling “smarter planet” services that use digital sensors to monitor things like weather and traffic and feed that data into computers that are asked to do something with the information, like predicting a tsunami or detecting freeway accidents.

Other companies could use “cognitive computing” to make better sense of large volumes of information.

Jim Olds, a neuroscientist and director of the Krasnow Institute for Advanced Study at George Mason University, called the new research a “tremendous step.”

Olds, who was not involved in IBM’s work, said neuroscientists have been amassing data about how the brain works much like “stamp collectors,” without a way to tie it together.

“We’ve made tremendous advances in collecting data, but we don’t have a collective theory yet for how this complex organ called the brain produces things like Shakespeare’s sonnets and Mozart’s symphonies,” he said.

“The holy grail for neuroscientists is to map activity from single nerve cells, which they know about, into how billions of nerve cells act in concert.”

Modha says a simulation of a human cortex could come within the next decade if Moore’s Law holds. That’s the rule of thumb that the number of transistors on a computer chip tends to double every two years.

Yet Olds cautioned that simulating the human brain is “such a complex problem that we may not be able to get to an answer, even with supercomputing.”

“There are no guarantees in this game because the sheer complexity of the problem really dwarfs anything we’ve tried to do,” he said.