̽��ֱ�� of Cambridge - ̽��ֱ�� of Massachusetts

ARPA-type funding gives green technology an ‘innovation advantage’, study finds

fpjl2 — Mon, 14 Sep 2020 12:53:41 +0000

A new analysis of the successes and failures of green energy companies in the US has found that those with ARPA funding filed for far more patents in the years after launching than other “cleantech” startups from the same time.

̽��ֱ��“innovation advantage” bestowed by ARPA-E – an energy version of the legendary DARPA (Defense Advanced Research Projects Agency) – was not shared by startups funded via other US government initiatives.

ARPA-type agencies were developed in the US to fund “high risk, high reward” research with the aim of fostering major breakthroughs, often by providing greater freedom to take on highly ambitious technical challenges.

̽��ֱ��new findings offer encouragement to a UK government considering its own British ARPA (or ‘BARPA’), but any agency adopting this model requires a focus in order to flourish – and BARPA’s should be climate, argues Professor Laura Diaz Anadon from the ̽��ֱ�� of Cambridge.

“Our US-based research points to the value of ARPA agencies. ̽��ֱ��UK may well benefit from such an approach in a post-pandemic world, given the technological capital within its universities and private sector,” said Anadon, co-author of the US innovation study.

“ ̽��ֱ��UK should adapt the ARPA model to create an agency for the climate challenge as part of any COVID-19 recovery package. Focusing research and development on next-generation energy storage and renewables, and solutions for decarbonizing shipping, aviation and construction, could boost productivity and deliver large benefits to society,” said Anadon.

Dr Anna Goldstein, first author of the study from the ̽��ֱ�� of Massachusetts Amherst, said: “ARPA is not a one-size-fits-all solution. ARPA agencies are mission-focused, and there is no evidence to suggest this model would work well as a fund for general science and technology.”

̽��ֱ��research was conducted by the ̽��ֱ�� of Cambridge, UK (Prof. Laura Diaz Anadon), the ̽��ֱ�� of Massachusetts Amherst, US (Dr. Anna Goldstein and Prof. Erin Baker), and the Technical ̽��ֱ�� of Munich in Germany (Prof. Claudia Doblinger). It is published today in the journal Nature Energy.

ARPA-E was established at the US Department of Energy under Obama, using a portion of the economic stimulus package that followed the 2009 financial crisis. To date, it has allocated US$3.38 billion.

̽��ֱ��aim was to accelerate innovation in “clean” technologies such as biofuels, smart grids and solar power at a time when it was out of favour with Venture Capital investors, due in part to long development cycles and low initial returns.

For the latest study, researchers investigated whether ARPA-E – a “posterchild” of mission-orientated innovation now under threat from the Trump administration – had translated its unique approach into real-world success.

By constructing a database of 1,287 US cleantech startups, and using patents as a proxy for innovation, they found that companies funded by a fledgling ARPA-E in 2010 went on to file patents at an average of twice the rate of other green energy companies in the years that followed.

̽��ֱ��researchers also measured “business success” by looking at how many companies were taken public or acquired by larger firms, as well as levels of private VC funding and overall survival rates.

While ARPA-funded companies do better than those turned down by ARPA-E, in general they fare no better or worse than other cleantech startups with the same amount of patents and private funding before 2010.

As such, the researchers argue that ARPA-E support alone does not bridge the “valley of death”: the phase between initial funding injection and revenue generation during which startups often fold.

Goldstein said: “It appears that ARPA-E helps startups working on riskier but potentially more disruptive technologies to reach the same levels of success as other, less risky, cleantech firms.”

“However, there is still a need for public funding to bring innovations in clean technology through the ‘valley of death’ so they can become commercial products that compete with legacy technologies and reduce emissions.”

Writing for Cambridge Zero, the ̽��ֱ��’s new climate change initiative, Laura Diaz Anadon points out that, at just 1.7% of GDP, the UK lags in R&D investment: below the EU28 average, and way behind the US, South Korea and Japan.

“While the UK dramatically increased energy investment over the last 20 years, it is still below the levels this country saw in the 1970s and 1980s,” said Anadon, Professor of Climate Change Policy at the ̽��ֱ�� of Cambridge.

“My co-authors and I would recommend trialing a UK version of ARPA-E that can ramp up energy innovation, and support selected projects through to demonstration phase. R&D investments in energy transition would be an inexpensive but essential component of a Covid-19 recovery package.”

“ ̽��ֱ��UK has solid recent experience in the energy space, but in the past several initiatives have fallen prey to volatile government funding before success can be properly gauged. Future efforts will need consistency as well as a set up that would enable state-of-the-art and independent evaluation.”

Startups funded by US agency ARPA-E file patents at twice the rate of similar cleantech firms. ̽��ֱ��UK should trial its own climate-focused ARPA as part of COVID-19 recovery package, argues a Cambridge professor.

̽��ֱ��UK should adapt the ARPA model to create an agency for the climate challenge as part of any COVID-19 recovery package

Laura Diaz Anadon

Ricardo Gomez Angel

Solar panel installation

̽��ֱ��text in this work is licensed under a Creative Commons Attribution 4.0 International License. Images, including our videos, are Copyright © ̽��ֱ�� of Cambridge and licensors/contributors as identified. All rights reserved. We make our image and video content available in a number of ways – as here, on our main website under its Terms and conditions, and on a range of channels including social media that permit your use and sharing of our content under their respective Terms.

Yes

How to cut your lawn for grasshoppers

sc604 — Wed, 22 Nov 2017 00:45:13 +0000

One could be forgiven for wondering what the point of such a question might be. But the solution, proposed by theoretical physicists in the UK and the US, has some intriguing connections to quantum theory, which describes the behaviour of particles at the atomic and sub-atomic scales. Systems based on the principles of quantum theory could lead to a revolution in computing, financial trading, and many other fields.

̽��ֱ��researchers, from the ̽��ֱ�� of Cambridge and the ̽��ֱ�� of Massachusetts Amherst, used computational methods inspired by the way metals are strengthened by heating and cooling to solve the problem and find the ‘optimal’ lawn shape for different grasshopper jump distances. Their results are reported in the journal Proceedings of the Royal Society A.

For the mathematically-inclined gardeners out there, the optimal lawn shape changes depending on the distance of the jump. Counter-intuitively, a circular lawn is never optimal, and instead, more complex shapes, from cogwheels to fans to stripes, are best at retaining hypothetical grasshoppers. Interestingly, the shapes bear a resemblance to shapes seen in nature, including the contours of flowers, the patterns in seashells and the stripes on some animals.

“ ̽��ֱ��grasshopper problem is a rather nice one, as it helps us try out techniques for the physics problems we really want to get to,” said paper co-author Professor Adrian Kent, of Cambridge’s Department of Applied Mathematics and Theoretical Physics. Kent’s primary area of research is quantum physics, and his co-author Dr Olga Goulko works in computational physics.

To find the best lawn, Goulko and Kent had to convert the grasshopper problem from a mathematical problem to a physics one, by mapping it to a system of atoms on a grid. They used a technique called simulated annealing, which is inspired by a process of heating and slowly cooling metal to make it less brittle. “ ̽��ֱ��process of annealing essentially forces the metal into a low-energy state, and that’s what makes it less brittle,” said Kent. “ ̽��ֱ��analogue in a theoretical model is you start in a random high-energy state and let the atoms move around until they settle into a low-energy state. We designed a model so that the lower its energy, the greater the chance the grasshopper stays on the lawn. If you get the same answer – in our case, the same shape – consistently, then you’ve probably found the lowest-energy state, which is the optimal lawn shape.”

For different jump distances, the simulated annealing process turned up a variety of shapes, from cogwheels for short jump distances, through to fan shapes for medium jumps, and stripes for longer jumps. “If you asked a pure mathematician, their first guess might be that the optimal shape for a short jump is a disc, but we’ve shown that’s never the case,” said Kent. “Instead we got some weird and wonderful shapes – our simulations gave us a complicated and rich array of structures.”

Goulko and Kent began studying the grasshopper problem to try to better understand the difference between quantum theory and classical physics. When measuring the spin – the intrinsic angular momentum – of two particles on two random axes for particular states, quantum theory predicts you will get opposite answers more often than any classical model allows, but we don’t yet know how big the gap between classical and quantum is in general. “To understand precisely what classical models do allow, and see how much stronger quantum theory is, you need to solve another version of the grasshopper problem, for lawns on a sphere,” said Kent. Having developed and tested their techniques for grasshoppers on a two-dimensional lawn, the authors plan to look at grasshoppers on a sphere in order to better understand the so-called Bell inequalities, which describe the classical-quantum gap.

̽��ֱ��lawn shapes which Goulko and Kent found also echo some shapes found in nature. ̽��ֱ��famous mathematician and code-breaker Alan Turing came up with a theory in 1952 on the origin of patterns in nature, such as spots, stripes and spirals, and the researchers say their work may also help explain the origin of some patterns. “Turing’s theory involves the idea that these patterns arise as solutions to reaction-diffusion equations,” said Kent. “Our results suggest that a rich variety of pattern formation can also arise in systems with essentially fixed-range interactions. It may be worth looking for explanations of this type in contexts where highly regular patterns naturally arise and are not otherwise easily explained.”

Reference:
Olga Goulko and Adrian Kent. ‘ ̽��ֱ��grasshopper problem.’ Proceedings of the Royal Society A (2017). DOI: http://dx.doi.org/10.1098/rspa.2017.0494

Picture a grasshopper landing randomly on a lawn of fixed area. If it then jumps a certain distance in a random direction, what shape should the lawn be to maximise the chance that the grasshopper stays on the lawn after jumping?

̽��ֱ��grasshopper problem is a rather nice one, as it helps us try out techniques for the physics problems we really want to get to.

Adrian Kent

Alvesgaspar

Grasshopper of Acrididae family: Anacridium aegyptium

̽��ֱ��text in this work is licensed under a Creative Commons Attribution 4.0 International License. For image use please see separate credits above.

Yes

Licence type:

Attribution-ShareAlike