Scientists report first solar cell producing more electrons in photocurrent than solar photons entering cell

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Researchers from the National Renewable Energy Laboratory (NREL) have reported the first solar cell that produces a photocurrent that has an external quantum efficiency greater than 100 percent when photoexcited with photons from the high energy region of the solar spectrum. 

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  The external quantum efficiency for photocurrent, usually expressed as a percentage, is the number of electrons flowing per second in the external circuit of a solar cell divided by the number of photons per second of a specific energy (or wavelength) that enter the solar cell. None of the solar cells to date exhibit external photocurrent quantum efficiencies above 100 percent at any wavelength in the solar spectrum.
The external quantum efficiency reached a peak value of 114 percent. The newly reported work marks a promising step toward developing Next Generation Solar Cells for both solar electricity and solar fuels that will be competitive with, or perhaps less costly than, energy from fossil or nuclear fuels.
Multiple Exciton Generation is key to making it possible
A paper on the breakthrough appears in the Dec. 16 issue of Science Magazine. Titled “Peak External Photocurrent Quantum Efficiency Exceeding 100 percent via MEG in a Quantum Dot Solar Cell,” it is co-authored by NREL scientists Octavi E. Semonin, Joseph M. Luther, Sukgeun Choi, Hsiang-Yu Chen, Jianbo Gao, Arthur J. Nozikand Matthew C. Beard. The research was supported by the Center for Advanced Solar Photophysics, an Energy Frontier Research Center funded by the DOE Office of Science, Office of Basic Energy Sciences. Semonin and Nozik are also affiliated with the University of Colorado at Boulder.
The mechanism for producing a quantum efficiency above 100 percent with solar photons is based on a process called Multiple Exciton Generation (MEG), whereby a single absorbed photon of appropriately high energy can produce more than one electron-hole pair per absorbed photon.
NREL scientist Arthur J. Nozik first predicted in a 2001 publication that MEG would be more efficient in semiconductor quantum dots than in bulk semiconductors. Quantum dots are tiny crystals of semiconductor, with sizes in the nanometer (nm) range of 1-20 nm, where 1 nm equals one-billionth of a meter. At this small size, semiconductors exhibit dramatic effects because of quantum physics, such as:

 

• rapidly increasing bandgap with decreasing quantum dot size,
• formation of correlated electron-hole pairs (called excitons) at room temperature,
• enhanced coupling of electronic particles (electrons and positive holes) through Coulombic forces,
• and enhancement of the MEG process.
Quantum dots confine the charges and harvest excess energy
Quantum dots, by confining charge carriers within their tiny volumes, can harvest excess energy that otherwise would be lost as heat – and therefore greatly increase the efficiency of converting photons into usable free energy.
The researchers achieved the 114 percent external quantum efficiency with a layered cell consisting of antireflection-coated glass with a thin layer of a transparent conductor, a nanostructured zinc oxide layer, a quantum dot layer of lead selenide treated with ethanedithol and hydrazine, and a thin layer of gold for the top electrode.
In a 2006 publication, NREL scientists Mark Hanna and Arthur J. Nozik showed that ideal MEG in solar cells based on quantum dots could increase the theoretical thermodynamic power conversion efficiency of solar cells by about 35 percent relative to today’s conventional solar cells. Furthermore, the fabrication of Quantum Dot Solar Cells is also amenable to inexpensive, high-throughput roll-to-roll manufacturing.
Such potentially highly efficient cells, coupled with their low cost per unit area, are called Third (or Next) Generation Solar Cells. Present day commercial photovoltaic solar cells are based on bulk semiconductors, such as silicon, cadmium telluride, or copper indium gallium (di)selenide; or on multi-junction tandem cells drawn from the third and fifth (and also in some cases fourth) columns of the Periodic Table of Elements. All of these cells are referred to as First- or Second-Generation Solar Cells.
First experiment to show 100-percent-plus in operating solar cells
MEG, also referred to as Carrier Multiplication (CM), was first demonstrated experimentally in colloidal solutions of quantum dots in 2004 by Richard Schaller and Victor Klimov of the DOE’s Los Alamos National Laboratory. Since then, many researchers around the world, including teams at NREL, have confirmed MEG in many different semiconductor quantum dots. However, nearly all of these positive MEG results, with a few exceptions, were based on ultrafast time-resolved spectroscopic measurements of isolated quantum dots dispersed as particles in liquid colloidal solutions.
The new results published in Science by the NREL research team is the first report of MEG manifested as an external photocurrent quantum yield greater than 100 percent measured in operating quantum dot solar cells at low light intensity; these cells showed significant power conversion efficiencies (defined as the total power generated divided by the input power) as high as 4.5 percent with simulated sunlight. While these solar cells are un-optimized and thus exhibit relatively low power conversion efficiency (which is a product of the photocurrent and photovoltage), the demonstration of MEG in the photocurrent of a solar cell has important implications because it opens new and unexplored approaches to improve solar cell efficiencies.
Another important aspect of the new results is that they agree with the previous time-resolved spectroscopic measurements of MEG and hence validate these earlier MEG results. Excellent agreement follows when the external quantum efficiency is corrected for the number of photons that are actually absorbed in the photoactive regions of the cell. In this case, the determined quantum yield is called the internal quantum efficiency. The internal quantum efficiency is greater than the external quantum efficiency because a significant fraction of the incident photons are lost through reflection and absorption in non-photocurrent producing regions of the cell. A peak internal quantum yield of 130% was found taking these reflection and absorption losses into account.
News source:physorg

String theory researchers simulate big-bang on supercomputer

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A trio of Japanese physicists have applied a reformulation of string theory, called IIB, whereby matrices are used to describe the properties of the physical universe, on a supercomputer, to effectively show that the universe spontaneously ballooned in three directions, leaving the other six dimensions tightly wrapped, as string theory has predicted all along. Their work, as described in a paper pre-published on the arXiv server and soon to appear in Physical Review Letters, in effect, describes the birth of the universe.

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  String theory, as most are aware, is the combining of quantum mechanics with the theory of general relativity, which is supposed to be the “theory of everything”; one single theory that can sum up and describe everything that takes place in the universe. A pretty tall order to be sure, but one that thus far has proven to be useful in describing such disparate phenomena as electromagnetism, gravity and the working’s of black holes. The problem with string theory thus far though has been that because of its very nature, it’s been very difficult to prove its real, i.e. that there are actually nine dimensions, with time as a tenth, and that rather than an infinite number of particle points forming the basis of everything, it’s all instead made of an infinite number of lines that oscillate, called strings. Complicating matters is the fact that we can only see three of those dimensions, because, theoretically, the other six are scrunched down into tiny structures called Calabi-Yau manifolds.
To get around these problems, the researchers turned to the IIB matrix model, which is where string theory is represented using an infinitely large matrix; though in this case, it was scaled down to just 32x32 for practical purposes. The team modeled such a matrix on a supercomputer then replicated it to create hundreds of thousands of matrices each simulating the very first moments of the universe. They then ran the simulation for two months averaging the results as they went. The simulation allowed the team to in essence watch as the universe reached the expansion point during the big bang. But more importantly, they were able to see all nine dimensions appear, as if on cue, in three directions, with six of them remaining wrapped tightly, just as string theory has suggested happened during the birth of the universe.
The team next plans to see if they can model how quantum space-time evolves into the one we now perceive around us, by building bigger models using larger matrices.
News source:physorg

Closest Type Ia supernova in decades solves a cosmic mystery

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The Palomar Transient Factory caught SN 2011fe in the Pinwheel Galaxy in the vicinity of the Big Dipper on Aug. 24, 2011. Found just hours after it exploded and only 21 million light years away, the discovery triggered the closest-ever look at a young Type Ia supernova. Credit: Image by B. J. Fulton, Las Cumbres Observatory Global Telescope Network

Type Ia supernovae (SN Ia's) are the extraordinarily bright and remarkably similar "standard candles" astronomers use to measure cosmic growth, a technique that in 1998 led to the discovery of dark energy – and 13 years later to a Nobel Prize, "for the discovery of the accelerating expansion of the universe." The light from thousands of SN Ia's has been studied, but until now their physics – how they detonate and what the star systems that produce them actually look like before they explode – has been educated guesswork.

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  Peter Nugent of the U.S. Department of Energy's Lawrence Berkeley National Laboratory (Berkeley Lab) heads the Computational Cosmology Center in the Lab's Computational Research Division and also leads the Lab's collaboration in the multi-institutional Palomar Transient Factory (PTF). On August 24 of this year, searching data as it poured into DOE's National Energy Research Scientific Computing Center (NERSC) from an automated telescope on Mount Palomar in California, Nugent spotted a remarkable object. It was shortly confirmed as a Type Ia supernova in the Pinwheel Galaxy, some 21 million light-years distant. That's unusually close by cosmic standards, and the nearest SN Ia since 1986; it was subsequently given the official name SN 2011fe.
Nugent says, "We caught the supernova just 11 hours after it exploded, so soon that we were later able to calculate the actual moment of the explosion to within 20 minutes. Our early observations confirmed some assumptions about the physics of Type Ia supernovae, and we ruled out a number of possible models. But with this close-up look, we also found things nobody had dreamed of."
"When we saw SN2011fe, I fell off my chair," says PTF team member Mansi Kasliwal of the Carnegie Institution for Science and the California Institute of Technology. "Its brightness was too faint to be a supernova and too bright to be nova. Only follow-up observations in the next few hours revealed that this was actually an exceptionally young Type Ia supernova."
Because they could closely study the supernova during its first few days, the team was able to gather the first direct evidence for what at least one SN Ia looked like before it exploded, and what happened next. Their results are reported in the 15 December, 2011, issue of the journal Nature.
Confirming a carbon-oxygen white dwarf
Scientists long ago developed models of Type Ia supernovae based on their evolving brightness and spectra. The models assume the progenitor is a binary system – about half of all stars are in binary systems – in which a very dense, very small white-dwarf star made of carbon and oxygen orbits a companion, from which it sweeps up additional matter. There's a specific limit to how massive the white dwarf can grow, equal to about 1.4 times the mass of our sun, before it can no longer support itself against gravitational collapse.

"As it approaches the limit, conditions are met in the center so that the white dwarf detonates in a colossal thermonuclear explosion, which converts the carbon and oxygen to heavier elements including nickel," says Nugent. "A shock wave rips through it and ejects the material in a bright expanding photosphere. Much of the brightness comes from the heat of the radioactive nickel as it decays to cobalt. Light also comes from ejecta being heated by the shock wave, and if this runs into the companion star it can be reheated, adding to the luminosity."
By examining how SN 2011fe's brightness evolved – its so-called early-time light curve – and the features of its early-time spectra, members of the PTF team were able to constrain how big the exploding star was, when it exploded, what might have happened during the explosion, and what kind of binary star system was involved.
The first observations of SN 2011fe were carried out at the Liverpool Telescope at La Palma in the Canary Islands, followed within hours by the Shane Telescope at Lick Observatory in California and the Keck I Telescope on Mauna Kea in Hawaii. These were shortly followed by NASA's orbiting Swift Observatory.

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This is the Pinwheel Galaxy before (left) and after (right) the supernova called SN2011fe happened. It's the brightest and closest stellar explosion seen in 25 years. Credit: BJ Fulton (Las Cumbres Observatory Global Telescope)/Palomar Transient Factory/Space Telescope Science Institute

Says Nugent, "We made an absurdly conservative assumption that the earliest luminosity was due entirely to the explosion itself and would increase over time in proportion to the size of the expanding fireball, which set an upper limit on the radius of the progenitor." Daniel Kasen, an assistant professor of astronomy and physics at the University of California at Berkeley and a faculty scientist in Berkeley Lab's Nuclear Science Division, explains that "it only takes a few seconds for the shock wave to tear apart the star, but the debris heated in the explosion will continue to glow for several hours. The bigger the star, the brighter this afterglow. Because we caught this supernova so early, and with such sensitive observations, we were able to directly constrain the size of the progenitor."
"Sure enough, it could only have been a white dwarf," says Nugent. "The spectra gave us the carbon and oxygen, so we knew we had the first direct evidence that a Type Ia supernova does indeed start with a carbon-oxygen white dwarf."
The expected and the unexpected
"The early-time light curve also constrained the radius of the binary system," says Nugent, "so we got rid of a whole bunch of models," ranging from old red giant stars to other white dwarfs in a so-called "double-degenerate" system.
Kasen explains that "if there was a giant companion star orbiting nearby, we should have seen some fireworks when the debris from the supernova crashed into it." A red giant would have made the supernova brighter by several orders of magnitude early on. "Because we didn't observe any bright flashes like that, we determined that the companion star could not have been much bigger than our sun."
Nor was there much chance the companion was another white dwarf in a double-degenerate system, unless it had somehow avoided being torn apart and littering the surroundings with debris. A shock wave plowing through that kind of rubble would have produced a burst of early light the observers couldn't have missed. So unless the companion was positioned almost exactly between the exploding star and the observers on Earth, closer to it than a 10th the diameter of our sun – an unlikely set of circumstances – the white dwarf's companion had to be a main-sequence star.
While these observations pointed to a "normal" SN Ia, the way the white dwarf exploded held surprises. Typical of what would be expected, early spectra obtained by the Lick three-meter telescope showed many intermediate-mass elements spewing out of the expanding fireball, including ionized oxygen, magnesium, silicon, calcium, and iron, traveling 16,000 kilometers a second – more than five percent of the speed of light. Yet some oxygen was traveling much faster, at over 20,000 kilometers a second.
"The high-velocity oxygen shows that the oxygen wasn't evenly distributed when the white dwarf blew up," Nugent says, "indicating unusual clumpiness in the way it was dispersed." But more interesting, he says, is that "whatever the mechanism of the explosion, it showed a tremendous amount of mixing, with some radioactive nickel mixed all the way to the photosphere. So the brightness followed the expanding surface almost exactly. This is not something any of us would have expected."
PTF team member Mark Sullivan of the University of Oxford says, "Understanding how these giant explosions create and mix materials is important because supernovae are where we get most of the elements that make up the Earth and even our own bodies – for instance, these supernovae are a major source of iron in the universe. So we are all made of bits of exploding stars."
"It is rare that you have eureka moments in science, but it happened four times on this supernova," says Andy Howell, coleader of PTF's SN Ia team: "The super-early discovery; the crazy first spectrum; when we figured out it had to be a white dwarf; and then, the Holy Grail, when we figured out details of the second star."
Howell adds, "We're like Captain Ahab … except our white whale is a white dwarf. We're obsessed with proving they cause supernovae, but the evidence has been eluding us for decades." This time, he says, "We got our whale … and we lived."
"This first close SN Ia in the era of modern instrumentation will undoubtedly become the best-studied thermonuclear supernova in history," the PTF team notes in their Nature paper, and "will form the new foundation upon which our knowledge of more distant Type Ia supernovae is built."
Two decades after the Berkeley-Lab-based Supernova Cosmology Project, led by 2011 Nobel Prize-winner in Physics Saul Perlmutter, proved that Type Ia supernovae could be used to measure the expansion history of the universe, Berkeley Lab astrophysicists and computer scientists have finally gotten a close-up look at what these remarkable cosmic mileposts really look like.
News source:physorg

Tinkering with evolution: Ecological implications of modular software networks

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Evolution of the modular structure of the network of dependencies between packages of the Debian GNU/Linux operating system. Packages are represented by nodes. A green arrow from package i to package j indicates that package i depends on package j, and a red arrow indicates that package i has a conflict with package j. Packages within a module (depicted by a big circle) have many dependencies between themselves and only a few with packages from other modules. During the growth of the operating system, the modular structure of the network of dependencies has increased: (I) The new packages added in successive releases depended mainly on previously existing packages within the same module, and hence, the size of the modules created in earlier releases increased over time; (ii) the number of modules also increased, although the new modules consisted only of a few new packages; and (iii) the relative number of dependencies between packages from different modules decreased. Moreover, the relative number of conflicts between packages from different modules decreased, whereas those within modules increased through the different releases of the operating system.

(PhysOrg.com) -- In the 1960s, Dr.Lawrence J. Fogel introduced what would come to be known as evolutionary programming to the nascentfield of Artificial Intelligence in an attempt to produce intelligent softwarewithout relying on neural networks modeled on the brain or human expert-based heuristicprogramming. Now, researchers in the Department of Ecology and EvolutionaryBiology at Princeton University haveshown the inverse – namely, that network theory, when applied to softwaresystems, provides surprising insights into biology, ecology and evolution. Specifically,they explored evolutionary behavior in complex systems by analyzing how theDebian GNU/Linux operating system utilizes modular code. The researchers foundthat how the network becomes more modular over time in various OS installationsoften parallels that of ecological relationships between interacting species.

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Lead researcher MiguelA. Fortuna, who worked with JuanA. Bonachela and Prof. Simon A.Levin, Director of Princeton’s Center for BioComplexity, describes the mainchallenges they encountered in designing and implementing the methods used toanalyze OS the evolution. “The main difficulty we had was getting, organizing,and storing the data,” says Fortuna. “Notice that the network of interdependentpackages of the last release analyzed was composed by more than 100,000dependencies. “This complexity required that they use structuring querylanguages (SQL) for managing databases. “We were very careful when identifyingsoftware packages through different release – sometimes there could bedifferent versions of the same package within the same release due to theimprovements made by developers.”
While Fortuna notes that quantifying the increase of the code’smodular structure time was the main insight of their study, he points out that reuseof code and software’s hierarchical structure were suggested by the pioneeringwork of Ricard V. Solé and Sergi Valverde in the early 2000s. “The interestthat our paper has drawn has helped us to discover work we did not know aboutsoftware systems. The idea of using the network of dependencies and conflictsof different releases of the Debian operating system as a case study hasfacilitated the understanding of how code development evolves over time withoutthe need to go deeper into the details of the code itself.”
Another key innovation cited by Fortuna was the team’s useof a very precise method to detect the modular structure of the operating system.“We borrowed an algorithm developed by physicists and widely used in ecologynowadays. In fact, this work has been constantly enriched by aninterdisciplinary mixture of ideas from biology and physics.”
The team already has its eye on ways of improving andextending the current experimental design. “The most important follow-up of ourstudy would be the exploration of proprietary software like the MicrosoftWindows operating system,” Fortuna comments. “Since Debian is the result of avolunteer effort to create a free operating system, you have the freedom todistribute copies, receive source code, modify the software or use pieces of itin new free programs. The question then becomes, what does the softwaredevelopment pattern looks like when the company developing code doesn't offerthis freedom to their users? A comparison of the structure of both developmentstrategies would be more than interesting.”

They are also developing a dynamical model to mimic thegrowth of Debian over time – an effort which, if successful, might let them predicthow many packages, dependencies, and conflicts will arise in the next releaseof the operating system. An interesting question would be,” he conjectures, “ifthere are limits to the number of packages that an operating system can offerto the users without jeopardizing its functionality and robustness. Followingour analogy with the biological evolution, we could ask if there is a limit tobiodiversity, that is, to the number of species that can coexist in our planet.”
Regarding potential analogies with evolution and ecology,Fortuna points to macroevolution – that is, speciation and extinction processes– that he sees as being in some ways equivalent to the creation of new packagesand the deprecation of those rendered obsolete from one release to the next. “Doesthe probability of a species becoming extinct depend on how long it’s been onthe planet? In other words, are the most ancient species, like crocodiles, theones with higher risk of extinction? We can formulate the question, which wasalready explored by Van Valen in the 1970's, by replacing species with software packages. Why do some packages not existafter a subsequent release? Does a new software package created in one of theearliest releases have a high probability to persist over time? What does itdepend on? We can calculate these probabilities following the identity of thepackages of the Debian operating system through time. The data to do it areavailable, and we therefore might learn something from software studies thathelp us answer the biological question – because evolution works as a tinkererin both cases.”
In relation to the ecological processes, Fortunaillustrates, “When an oceanic island is created colonization and extinction arethe main mechanisms that leads to the establishment of a stable community. Thiscommunity assembly would be equivalent to the package installation process in alocal computer. For example, dependencies and conflicts between packages mimicpredator-prey interactions and competitive exclusion relationships,respectively. A predator can colonize the island only if the prey it feeds onis already there.”
In Fortuna’s view, the same thing happens with softwarepackages. “A package can be installed in a computer only if the packages itdepends on are already installed. Ecologically similar prey species are goingto compete with each other in the island for light and nutrients so that thebest competitor is going to displace the others, which can then become extinct.Predators feeding on extinct prey are going to disappear as well. Conflictsbetween software packages have the same consequences: one package cannot beinstalled in the computer if it has a conflict with an already installed one,so that those packages depending on it cannot be installed either. Thisparallelism can help us understand the general principles operating on systemsof different nature.”
Reminiscent of AI-based evolutionary programming, Fortunaalso says that their work might well lead to improved in silico modelsof evolutionary biology and population ecology. “Charles Ofria and his lab atMichigan State University are studying evolution by using self-replicatingcomputer programs able to mutate and evolve over time.” The genome of theseprograms consists of a set of instructions that are executed by the centralprocessing unit (CPU). Some of the mutations imply the insertion of randominstructions into the genome. If the mutant program is able to reproduce fasterthan the others, its genome is going to persist through time.
“It could be interesting to explore to what extent newinstructions added to the genome interact with the preexisting ones – that is, whetheror not there is a reuse of the genome instructions of these digital organismsand its resemblance with a modular structural pattern,” Fortuna observes. “Theinterplay between ecology and computer science is much more evident if we takea look at the work developed by Luis Zaman, Ofria's graduate student, who isincorporating host-parasite interactions into these computer programs.”
Looking further afield, Fortuna describes how other modelsor applications might be targeted using the team’s findings. “The closest studywould be the comparison with the development pattern of other GNU/Linux distributions– openSuse, Fedora, Gentoo, and so on – as well as proprietary operatingsystems like Microsoft Windows and Apple OS X. The information needed toaccomplish this task would easily be compiled for the first ones – but it willbe much more difficult to get it for the last ones. The algorithms fordetecting modular structures are publicly available. There are also powerfulfree SQL relational database management systems like PostgreSQL and MySQL tostore, organize, and manage the information. So,’ he concludes, “the bottleneckis once again data availability.”
More information: Evolutionof a modular software network, Publishedonline before print November 21, 2011, PNAS December 13, 2011 vol. 108 no. 50 19985-19989, doi: 10.1073/pnas.1115960108
News source:physorg.com