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模仿植物光合作用 MIT開發高效率太陽能電池

十月 4, 2010
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模仿植物光合作用

 MIT開發高效率太陽能電池

上網時間: 2010年09月10日

佈滿磷脂碟狀物(phospholipid disks)的碳奈米管

能讓太能量採集具備自我修復(self-repairing)的功能,

就像是植物行光合作用

 

這種光電化學(photoelectrochemical)太陽能電池

是由美國麻省理工學院(MIT)的研究人員所開發,

其能源轉換效率號稱可達到目前效能最佳之固態太陽能光電板的兩倍。

 

以人工方式進行的太陽能轉換,以及自然界的太陽能轉換,兩者間的主要不同之處,在於工程師會為太陽能電池做防護,以避免固態無機材料的逐漸劣化;而自然界的太陽能轉換,是透過光合作用,來預防並修復不可避免的液態有機材料損壞。

在自然界,使用永續性太陽能的案例不勝枚舉;

舉例來說,能讓樹葉進行光合作用的有機化合物,經常會受到陽光的損壞,但樹葉有自我修復機制。透過對能夠不斷更新其太陽能轉換燃料機制的生物性光合作用過程之研究,科學家們現在已經有自信能製作出模仿該種自我修復能力的太陽能電池。

MIT的研究人員並沒有聲稱已經破解光合作用的秘密,但表示已能夠模仿植物的自我修復機制,不斷充實其能量採集技術。

光合作用過程包含一些內建的機制,植物內部以化學為基礎的動力引擎,會週期性地分解為基本的功能區塊(building blocks),然後那些更新過的元素會再重組成全新的引擎。根據MIT教授Michael Strano的說法,植物會每個小時執行以上的程序,更新並循環其基於蛋白質的光合作用功能,使其以最佳效率持續運作。

Strano所開發的方案,具備一種會模仿光合作用程序可逆性、叫做磷脂的合成性碟狀分子,該種分子每一個都具備能將光線轉換成電流的內部反應中心;當把該種分子與碳奈米管混合到溶液中,碟狀分子會圍繞著碳奈米管自我組裝。由於碳的導電性比金屬好,當曝露在陽光下時,奈米管會提高釋入碟狀分子的電子之傳輸率。

而在碟狀分子的內部,Strano的團隊利用了會自我組裝成光線採集器的、由七種不同元素組成的化合物,建立了類似光合作用的循環性機制。透過添加一類似除油劑的介面活性劑,所有化合物組合會裂解為原來的元素;若再用過濾器將溶液中的介面活性劑去除,那些原始元素又會再次自我組裝成太陽能電池。

與目前性能最佳的、能源轉換效率不到20%的固態太陽能電池相比,MIT研究人員開發出的液態光電化學電池,轉換效率號稱可達到40%;研究人員並表示,開發濃度更高的碳奈米管與碟狀分子組合,可望能將這種太陽能電池的效率進一步提高。

(參考原文: Self-repairing solar cell is bio-inspired ,by R. Colin Johnson)

http://www.eettaiwan.com/ART_8800620128_675763_NT_119685f1.HTM?8800059530&8800620128&click_from=8800059530,8723946550,2010-09-10,EETOL,ARTICLE_ALERT

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Multicore may not be so scary: Linux will keep up with addition of more processing units

十月 3, 2010
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Multicore may not be so scary: Linux will keep up with addition of more processing units

Computer chips have stopped getting faster.

To keep improving chips’ performance, manufacturers have turned to adding more "cores," or processing units, to each chip. In principle, a chip with two cores can run twice as fast as a chip with only one core, a chip with four cores four times as fast, and so on.

But breaking up computational tasks so that they run efficiently on multiple cores is a difficult task, and it only gets harder as the number of cores increases. So a number of ambitious research projects, including one at MIT, are reinventing computing, from chip architecture all the way up to the design of programming languages, to ensure that adding cores continues to translate to improved performance.

To managers of large office networks or Internet server farms, this is a daunting prospect. Is the computing landscape about to change completely? Will information-technology managers have to relearn their trade from scratch?

Probably not, say a group of MIT researchers. In a paper they’re presenting on Oct. 4 at the USENIX Symposium on Operating Systems Design and Implementation in Toronto, the researchers argue that, for at least the next few years, the Linux operating system should be able to keep pace with changes in chip design.

Linux is an open-source operating system, meaning that any programmer who chooses to may modify its code, adding new features or streamlining existing ones. By the same token, however, any public distribution of those modifications must be free of charge, which makes Linux popular among managers of large data centers. Programmers around the world have contributed thousands of hours of their time to the continuing improvement of Linux.

Clogged counter

To get a sense of how well Linux will run on the chips of the future, the MIT researchers built a system in which eight six-core chips simulated the performance of a 48-core chip. Then they tested a battery of applications that placed heavy demands on the operating system, activating the 48 cores one by one and observing the consequences.

At some point, the addition of extra cores began slowing the system down rather than speeding it up. But that performance drag had a surprisingly simple explanation. In a multicore system, multiple cores often perform calculations that involve the same chunk of data. As long as the data is still required by some core, it shouldn’t be deleted from memory. So when a core begins to work on the data, it ratchets up a counter stored at a central location, and when it finishes its task, it ratchets the counter down. The counter thus keeps a running tally of the total number of cores using the data. When the tally gets to zero, the operating system knows that it can erase the data, freeing up memory for other procedures.

As the number of cores increases, however, tasks that depend on the same data get split up into smaller and smaller chunks. The MIT researchers found that the separate cores were spending so much time ratcheting the counter up and down that they weren’t getting nearly enough work done. Slightly rewriting the Linux code so that each core kept a local count, which was only occasionally synchronized with those of the other cores, greatly improved the system’s overall performance.

On the job

“That basically tells you how scalable things already are,” says Frans Kaashoek, one of three MIT computer-science professors who, along with four students, conducted the research. “The fact that that is the major scalability problem suggests that a lot of things already have been fixed. You could imagine much more important things to be problems, and they’re not. You’re down to simple reference counts.” Nor, Kaashoek says, do Linux contributors need a trio of MIT professors looking over their shoulders. “Our claim is not that our fixes are the ones that are going to make Linux more scalable,” Kaashoek says. “The Linux community is completely capable of solving these problems, and they will solve them. That’s our hypothesis. In fact, we don’t have to do the work. They’ll do it.”

Kaashoek does say, however, that while the problem with the reference counter was easy to repair, it was not easy to identify. “There’s a bunch of interesting research to be done on building better tools to help programmers pinpoint where the problem is,” he says. “We have written a lot of little tools to help us figure out what’s going on, but we’d like to make that process much more automated.”

"The big question in the community is, as the number of cores on a processor goes up, will we have to completely rethink how we build operating systems," says Remzi Arpaci-Dusseau, a professor of computer science at the University of Wisconsin. "This paper is one of the first to systematically address that question."

Someday, Arpaci-Dusseau says, if the number of cores on a chip gets "significantly beyond 48," new architectures and operating systems may become necessary. But "for the next five, eight years," he says, "I think this paper answers pretty definitively that we probably don’t have to completely rethink things, which is great, because it really helps direct resources and research toward more relevant problems."

Arpaci-Dusseau points out, too, that the MIT researchers "showed that finding the problems is the hard part. What that hints at for the rest of the community is that building techniques — whether they’re software techniques or hardware techniques or both — that help to identify these problems is going to be a rich new area as we go off into this multicore world."


This story is republished courtesy of MIT News (http://web.mit.edu/newsoffice/), a popular site that covers news about MIT research, innovation and teaching.

Provided by Massachusetts Institute of Technology

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