by Riko Seibo
Tokyo, Japan (SPX) Apr 16, 2026
Inverted perovskite solar cells are widely considered the future of next-generation photovoltaics due to their high efficiency, low cost, and ease of manufacturing. A collaborative research team from the Southern University of Science and Technology (SUSTech) and The Hong Kong Polytechnic University (PolyU) has proposed a new approach to stabilizing the delicate interfaces inside these devices, achieving a power conversion efficiency of 26.54 percent with outstanding long-term durability.
To achieve record efficiencies, scientists typically use self-assembled monolayers, or SAMs, just one molecule thick to extract positive charges from the perovskite layer. However, these conventional ultra-thin interfaces are extremely fragile. They are prone to molecular disorder and weak bonding, leading to severe performance degradation under heat and operational stress.
The new strategy, published in Science Bulletin, introduces a concept the researchers call multidimensional spatial confinement. Rather than relying on the flexible alkyl linkers used in conventional SAM molecules, the team designed a custom molecule called MeO-PABDCB featuring a rigid phenylene backbone. This backbone promotes dense, ordered in-plane packing through pi-pi interactions. At the same time, the molecule forms strong multidentate chemical bonds with the underlying indium tin oxide electrode and establishes robust interactions with the overlying perovskite layer.
Together, these effects spatially confine the molecules both laterally and vertically, creating what the researchers describe as a molecular lock at the interface. This locked molecular architecture suppresses molecular desorption and disorder while also improving the quality of the perovskite film grown on top. Devices incorporating the spatially confined SAM exhibit reduced interfacial defects, lower residual strain in the perovskite layer, and more efficient hole extraction.
As a result, the inverted perovskite solar cells achieved a power conversion efficiency of 26.54 percent with a high fill factor of 86.4 percent. More importantly, the devices demonstrated outstanding durability, retaining approximately 90 percent of their initial efficiency after 1,000 hours of continuous operation and 250 thermal cycles between -40 and 85 degrees Celsius.
The study establishes spatial confinement as a general molecular design principle for stabilizing ultra-thin functional interfaces. By showing that structural robustness and electronic performance can be achieved simultaneously, the work provides a practical pathway toward more reliable perovskite-based optoelectronic devices.
Research Report:Strongly spatial-confined self-assembled monolayers for high-performance perovskite photovoltaics
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energy-tech
ED https://www.eurekalert.org/news-releases/1123902
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22-DEC-49
AI Model Projects Wind and Solar on Course for 2C Target but Short of 1.5C
AI Model Projects Wind and Solar on Course for 2C Target but Short of 1.5C
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Chalmers University of Technology
by Robert Schreiber
Berlin, Germany (SPX) Apr 16, 2026
Wind and solar power have grown faster than almost anyone predicted, but projecting their future expansion remains surprisingly difficult. Researchers at Chalmers University of Technology in Sweden have developed what they call a computational time machine – a model that outperforms existing projection methods by using AI techniques to analyse historical growth patterns across countries.
Their central projection shows that onshore wind is likely to supply around 25 percent of global electricity by 2050, with solar reaching about 20 percent. This is consistent with the 2 degrees Celsius climate target, but falls short of what is required for 1.5 degrees Celsius.
“Existing models are very good at identifying what needs to happen to reach climate targets, but they can’t tell us which developments are most likely. That’s the gap we wanted to fill,” said Jessica Jewell, Professor at Chalmers University of Technology.
Across more than 200 countries, the researchers identified a recurring pattern in how wind and solar power grow: long periods of relatively steady expansion punctuated by sudden growth spurts often triggered by policy shifts. “Most models assume a smooth S-shaped growth curve, but that’s not how it actually looks in the real world. Growth often comes in bursts, and if you ignore that, you can misjudge how fast technologies will expand,” said Avi Jakhmola, PhD Student at Chalmers and first author of the paper published in Nature Energy.
To improve projections, Jakhmola built a model on 13,000 virtual worlds in which solar and wind power develop in different ways – from the fastest possible expansion to the slowest and everything in between. A machine learning algorithm was then trained on all these worlds to learn to predict global outcomes from early national trends. “When we apply the model to real-world data, it can tell us what is the most probable outcome for the future – given what we have seen so far and given all the virtual worlds it has seen,” said Jakhmola.
By 2050, the model projects onshore wind reaching around 26 percent of global electricity with a central range of 20 to 34 percent, and solar around 21 percent with a range of 15 to 29 percent. This broadly aligns with 2 degrees Celsius-compatible pathways but falls short of what is needed for 1.5 degrees Celsius.
The projections also put the COP28 pledge to triple renewables capacity by 2030 in perspective. That pledge falls near the 95th percentile of the model’s outcomes, meaning it would require growth rates rarely observed. “The tripling of renewables pledge is not impossible, but it would require everything to go extremely well in all countries,” said Jewell.
The researchers also examined what would be required to reach the 1.5 degrees Celsius goal. “If we start now, the required growth rates are demanding but not unprecedented, comparable to what the EU targets for wind with REPowerEU and what India has planned for solar power,” said Jakhmola. “But if we delay until 2030, the acceleration needed becomes much steeper and much more abrupt. The window for ramping up closes quickly.”
To test the reliability of the model’s projections, the team used it to go back in time. By feeding the model only data from 2015, they found it correctly predicts what has happened since then. “This is what we mean by a computational time machine and it gives us real confidence in the projections going forward,” said Jakhmola. The study points toward a broader ambition to develop scientifically rigorous methods for projecting the most likely growth paths for other low-carbon technologies beyond wind and solar.
Research Report:Probabilistic projections of global wind and solar power growth based on historical national experience
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