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Mystery of high-performing solar cell materials revealed (cam.ac.uk)
98 points by rustoo 11 days ago | hide | past | favorite | 19 comments

Full text report: http://arxiv-export-lb.library.cornell.edu/pdf/2106.04942v1

The summary in the paper is perhaps clearer than the article about it:

> "Our study has significant implications for the fundamental understanding of defect tolerance in these materials and the design of halide perovskite solar cells, in particular for tandem cells. Using a novel suite of multimodal microscopy techniques, we unveil the remarkably complex energetic landscape that charge carriers must navigate in halide perovskites. We provide the first nanoscale picture of how this energetic landscape influences photodoping, carrier recombination and trapping."

> "We find that the pursuit of homogeneous chemical compositions is not necessarily the best way to maximize the performance of this family of semiconductors, at least while the material still possesses deep trap clusters that lower device performance from the radiative limits. The existence of mixed Br and I samples induces the formation of beneficial local heterostructures that confer enhanced defect tolerance to these materials. In these regions, charge-carrier photogeneration and radiative recombination occurs through a rapid wide-to-narrow bandgap funneling process, more efficient than in the chemically homogeneous counterparts."

What's really interesting is how these materials are heterogenous at the nanoscale, which is rather like how the biological light-harvesting protein complexes(LHC) operate, with ordered aligned arrays of chlorophyll molecules held in particular orientations within the protein structure that optimize funneling of photon energy into reaction centers (water-splitting for H2 production).

However, these materials may not ever be commercially successful, due to issues like lead pollution and the working lifetime of the materials (they degrade fairly rapidly in full sun). Regardless, this is still very useful and important basic research.

I know nothing about the manufacturing cost nor the lifespan of these materials, but I'm curious if it would be viable to have infrastructure for periodically replacing and recycling the panels. I.e., have regional facilities for receiving old panels, re-smelting the lead and other materials, and perhaps locally manufacture the replacements.

This approach might work in an industrial setting for photo-electrochemical applications but is highly unlikely for residential or commercial power generation. mono-Si panels last for decades with no need for maintenance other than regular surface cleaning and no lead issues.

However you could, in an industrial setting, do something like this:

"Integration of a Hydrogenase in a Lead Halide Perovskite Photoelectrode for Tandem Solar Water Splitting 2020"


Here you could use a catalyst regeneration strategy where you basically have a little production line onsite and as each unit wears out you just pop in a new one and send the old one to be regenerated, that's more plausible.

Materials cost should be significantly lower than Si or CdTe. The active layer of semiconductor is just 0.3-0.4 microns thick.


There will be no advantage of doing this locally.

There lifetime is too long to have enough locally and if we have 100% renewable, transport will be no ecological issue anymore.

> The lead salts used to make them are much more abundant [...] than crystalline silicon

This statement fragment makes no sense. Silicon is the second most abundant element in the Earth's crust, after oxygen. If it means the specific form in crystalline silicon, well that doesn't occur in nature, but then neither do these lead salts.

Lead salts also tend to be a lot more toxic than silicon. Putting that in something as plentiful and exposed as solar panels sounds like a big potential issue.

I think it would be fairly trivial to recoup the lead. Add a $500 deposits you get back when they are returned end of life cycle. Manufacturers should eat that initial cost with contract to return to them directly at end of life or they charge you the $500 as per contract if you fail to return them. If that doesn’t scale financially then I guess it’s a non starter. But something as big as a panel should be easy enough to recycle. Weather it is financially a viable business I don’t know the math of recycling one of these things to even get an idea if it is possible.

This isn't a glass bottle you return next week, if you buy the panels they'll last you 30 or 40 years. At that point it's completely likely that the company will no longer exist when you go back for your deposit lmao.

It's almost like we could create organizations that last longer than companies, and have the citizens' best interests at heart, to administer a deposit program like that. Perhaps these organizations could also govern other aspects of society instead of leaving those to corporations as well. Could we call them govern-ments?

Organizations that will be shut down the next time the opposing political party comes into power? Don't make me laugh.

"have the citizens' best interests at heart" - citation needed

There are also versions of this technology that use tin instead of lead.

>>> Combining a series of new microscopy techniques, the group present a complete picture of the nanoscale chemical, structural and optoelectronic landscape of these materials

It's not even relevant to call it "microscopy" anymore, we require a new term. It's a complete thin film atlas of all interacting forces of nature. Better data for the models, means higher fidelity simulations.

The question is can AI predict new materials? Can a simulation be sophisticated enough to predict say, high temperature superconductivity in rare earth cuprate perovskites?

I'm not sure if this is exactly what you're talking about, but I read something a while back about using AI to predict if certain metallic glass alloys will have useful properties: https://phys.org/news/2018-04-artificial-intelligence-discov...

If we are going to speculate, then the question is, why couldn't AI do it? What kind of fundamental limitation would it hit? Data? But we could get a ton of data from already existing software[^1]. It is slow, but I have the feeling it wouldn't require as much computing as GPT-3, and it would perhaps be enough to train more efficient neural networks that can do the actual search.

Because how important is for human life, a compiler industry that finds ways to translate complicated simulations to AI algorithms could be the next big thing.

[^1]: https://en.wikipedia.org/wiki/List_of_quantum_chemistry_and_...

I mean cheaper technology at the same efficiency of todays solar cells but available in the next decade. Interesting but not changing the game. Silicon Solar will keep downward pressure over that time anyways so it will need to get significantly better.

Lots of other options for viability im sure.

This technology will likely be rolled out as tandem cells with conventional Si cells underneath. So any improvements to Si cells will carry over to these, and there will always be an efficiency bump vs. just Si.

Could be - it's a decade away, lots can change. Hopeful for improvements but we've needed all this stuff like 2 decades ago.

Better late then never I guess.

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