Solar Energy

Toward new solar cells with active learning

Published

4 years ago

April 25, 2021

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Toward new solar cells with active learning

How can I prepare myself for something I do not yet know? Scientists from the Fritz Haber Institute in Berlin and from the Technical University of Munich have addressed this almost philosophical question in the context of machine learning. Learning is no more than drawing on prior experience. In order to deal with a new situation, one needs to have dealt with roughly similar situations before.

In machine learning, this correspondingly means that a learning algorithm needs to have been exposed to roughly similar data. But what can we do if there is a nearly infinite amount of possibilities so that it is simply impossible to generate data that covers all situations?

This problem comes up a lot when dealing with an endless number of possible candidate molecules. Organic semiconductors enable important future technologies such as portable solar cells or rollable displays.

For such applications, improved organic molecules – which make up these materials – need to be discovered. Tasks of this nature are increasingly using methods of machine learning, while training on data from computer simulations or experiments.

The number of potentially possible small organic molecules is, however, estimated to be on the order of 1033. This overwhelming number of possibilities makes it practically impossible to generate enough data to reflect such a large material diversity. In addition, many of those molecules are not even suitable for organic semiconductors. One is essentially looking for the proverbial needle in a haystack.

In their work published recently in Nature Communications the team around Prof. Karsten Reuter, Director of the Theory Department at the Fritz-Haber-Institute, addressed this problem using so-called active learning. Instead of learning from existing data, the machine learning algorithm iteratively decides for itself which data it actually needs to learn about the problem.

The scientists first carry out simulations on a few smaller molecules, and obtain data related to the molecules’ electrical conductivity – a measure of their usefulness when looking at possible solar cell materials. Based on this data, the algorithm decides if small modifications to these molecules could already lead to useful properties or whether it is uncertain due to a lack of similar data.

In both cases, it automatically requests new simulations, improves itself through the newly generated data, considers new molecules, and goes on to repeat this procedure.

In their work, the scientists show how new and promising molecules can efficiently be identified this way, while the algorithm continues its exploration into the vast molecular space, even now, at this very moment. Every week new molecules are being proposed that could usher in the next generation of solar cells and the algorithm just keeps getting better and better.

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Solar Energy

Finding better photovoltaic materials faster with AI

Published

23 hours ago

January 24, 2025

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Finding better photovoltaic materials faster with AI

by Robert Schreiber

Berlin, Germany (SPX) Jan 24, 2025

Researchers at the Karlsruhe Institute of Technology (KIT) and the Helmholtz Institute Erlangen-Nurnberg (HI ERN) have developed a novel AI-driven workflow that dramatically accelerates the discovery of high-efficiency materials for perovskite solar cells. By synthesizing and testing just 150 targeted molecules, the team achieved results that would typically require hundreds of thousands of experiments. “The workflow we have developed will open up new ways to quickly and economically discover high-performance materials for a wide range of applications,” said Professor Christoph Brabec of HI ERN. One of the newly identified materials enhanced the efficiency of a reference solar cell by approximately two percentage points, reaching 26.2 percent.

The research began with a database containing the structural formulas of about one million virtual molecules, each potentially synthesizable from commercially available compounds. From this pool, 13,000 molecules were randomly selected. KIT researchers applied advanced quantum mechanical methods to evaluate key properties such as energy levels, polarity, and molecular geometry.

Training AI with Data from 101 Molecules

Out of the 13,000 molecules, the team chose 101 with the most diverse properties for synthesis and testing at HI ERN’s robotic systems. These molecules were used to fabricate identical solar cells, enabling precise comparisons of their efficiency. “The ability to produce comparable samples through our highly automated synthesis platform was crucial to our strategy’s success,” Brabec explained.

The data obtained from these initial experiments were used to train an AI model. This model then identified 48 additional molecules for synthesis, focusing on those predicted to offer high efficiency or exhibit unique, unforeseen properties. “When the machine learning model is uncertain about a prediction, synthesizing and testing the molecule often leads to surprising results,” said Tenure-track Professor Pascal Friederich from KIT’s Institute of Nanotechnology.

The AI-guided workflow enabled the discovery of molecules capable of producing solar cells with above-average efficiencies, surpassing some of the most advanced materials currently in use. “We can’t be sure we’ve found the best molecule among a million, but we are certainly close to the optimum,” Friederich commented.

AI Versus Chemical Intuition

The researchers also gained valuable insights into the AI’s decision-making process. The AI identified chemical groups, such as amines, that are associated with high efficiency but had been overlooked by traditional chemical intuition. This capability underscores the potential of AI to uncover previously unrecognized opportunities in materials science.

The team believes their AI-driven strategy can be adapted for a wide range of applications beyond perovskite solar cells, including the optimization of entire device components. Their findings were achieved in collaboration with scientists from FAU Erlangen-Nurnberg, South Korea’s Ulsan National Institute of Science, and China’s Xiamen University and University of Electronic Science and Technology. The research was published in the journal Science.

Research Report:Inverse design of molecular hole-transporting semiconductors tailored for perovskite solar cells

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Solar Energy

Scale-up fabrication of perovskite quantum dots

Published

23 hours ago

January 24, 2025

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Scale-up fabrication of perovskite quantum dots

by Simon Mansfield

Sydney, Australia (SPX) Jan 24, 2025

Quantum dots, tiny semiconductor nanomaterials known for their color-tunable and highly efficient photoluminescence, have revolutionized display technologies such as liquid crystal displays (LCDs), organic light-emitting diodes (OLEDs), and micro light-emitting diodes (Micro-LEDs). In 2023, the Nobel Prize in Chemistry recognized the discovery and development of quantum dots, underscoring their significance in modern technology.

Perovskite quantum dots (PQDs) are a promising class of materials distinguished by their high absorption coefficient, cost-effectiveness, ease of processing, and reduced environmental impact. Their potential for display applications has attracted considerable interest. In 2015, Professor Zhong and his team introduced a groundbreaking method for in-situ fabrication of PQDs within a polymeric matrix. The subsequent establishment of Zhijing Technology (Beijing) Co., Ltd. in 2016 aimed to advance the scale-up production and application of PQDs in display technologies.

After extensive efforts, the company has developed several in-situ fabrication techniques to enable large-scale manufacturing. These methods include in-situ blade coating, spray drying, extrusion, inkjet printing, and lithography. Recently, the team resolved PQD stability challenges, leading to the integration of PQDs in Skyworth’s TV products. Unlike conventional quantum-dot light-emitting diode (QLED) TVs that utilize 630 nm emissive materials, these innovations introduced deep-red emissive PQDs at 650 nm, enhancing eye care capabilities.

In January 2025, the journal Engineering published a research article titled “Spray-Drying Fabrication of Perovskite Quantum-Dot-Embedded Polymer Microspheres for Display Applications.” This study highlighted the successful scale-up fabrication of PQDs, achieving a production capacity of 2000 kilograms annually. The research also demonstrated the use of PQDs in LCD backlight applications, where PQD-based optical films exhibited exceptional stability under challenging conditions. Aging tests showed brightness decay within 10% after 1000 hours at 60 C with 90% relative humidity and under 70 C conditions with 150 W/m2 455 nm blue light irradiation.

Furthermore, researchers showcased PQD-embedded polymer microspheres as efficient color converters in full-color Micro-LED displays with pixel sizes as small as 10 um. The spray-drying fabrication method provides a cost-effective solution for large-scale PQD production. These PQD-embedded polymer microspheres demonstrated remarkable long-term operational stability, making them highly competitive for use in advanced display technologies.

Research Report:Spray-Drying Fabrication of Perovskite Quantum-Dot-Embedded Polymer Microspheres for Display Applications

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Solar Energy

Solar power surpasses coal in EU for first time

Published

2 days ago

January 23, 2025

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Solar power surpasses coal in EU for first time

by AFP Staff Writers

Paris (AFP) Jan 23, 2025

Solar overtook coal in the European Union’s electricity production in 2024, with the share of renewables rising to almost half the bloc’s power sector, according to a report released Thursday.

Gas generation, meanwhile, declined for the fifth year in a row and fossil-fuelled power dipped to a “historic low”, climate think tank Ember said in its European Electricity Review 2025.

“The European Green Deal has delivered a deep and rapid transformation of the EU power sector,” the think tank said.

“Solar remained the EU’s fastest-growing power source in 2024, rising above coal for the first time. Wind power remained the EU’s second-largest power source, above gas and below nuclear.”

Overall, strong growth in solar and wind have boosted the share of renewables to 47 percent, up from 34 percent in 2019.

Fossil fuels have fallen from 39 to 29 percent.

“A surge in wind and solar generation is the main reason for declining fossil generation. Without wind and solar capacity added since 2019, the EU would have imported 92 billion cubic metres more of fossil gas and 55 million tonnes more of hard coal, costing EUR59 billion,” the report said.

According to Ember, these trends are widespread across Europe, with solar power progressing in all EU countries.

More than half have now either eliminated coal, the most polluting fossil fuel, or reduced its share to less than five percent of their energy mix.

“Fossil fuels are losing their grip on EU energy,” said Chris Rosslowe, lead author of the report.

“At the start of the European Green Deal in 2019, few thought the EU’s energy transition would be where it is today: wind and solar are relegating coal to the margins and pushing gas into decline.”

– Battery storage –

But Rosslowe cautioned much work remains.

“We need to accelerate our efforts, particularly in the wind power sector,” he said.

Europe’s electricity system will also need to increase its storage capacity to make the most of renewable energies, which are by definition intermittent, he added.

In 2024, plentiful solar energy helped drive down prices in the middle of the day, sometimes even resulting in “negative or zero price hours” due to an overabundance of supply compared to demand.

“A readily available solution is a battery co-located with a solar plant. This gives solar power producers more control over the prices they receive and helps them avoid selling for low prices in the middle of the day,” the report said.

The think tank suggested consumers could reduce their bills by shifting usage to periods of abundance (smart electrification), while battery operators could earn revenue from buying power when prices are low and selling it back when demand peaks.

Batteries have advanced significantly in recent years, with installed capacity across the EU doubling to 16 GW in 2023, compared with 8 GW in 2022, according to Ember.

But this capacity is concentrated in just a small number of countries: 70 percent of existing batteries were located in Germany and Italy at the end of 2023.

“More storage and demand flexibility is needed to sustain growth and for consumers to reap the full benefits of abundant solar,” Ember said.

“After a challenging few years for the wind power sector, additions are set to grow, but not by enough to hit EU targets. Closing this gap will require continued policy implementation and political support, such that the rate of additions between now and 2030 is more than double that of recent years.”

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