Solar Energy

Virtually unlimited solar cell experiments

Published

4 years ago

March 3, 2021

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Virtually unlimited solar cell experiments

Osaka University researchers employed machine learning to design new polymers for use in photovoltaic devices. After virtually screening over 200,000 candidate materials, they synthesized one of the most promising and found its properties were consistent with their predictions. This work may lead to a revolution in the way functional materials are discovered.

Machine learning is a powerful tool that allows computers to make predictions about even complex situations, as long as the algorithms are supplied with sufficient example data. This is especially useful for complicated problems in material science, such as designing molecules for organic solar cells, which can depend on a vast array of factors and unknown molecular structures.

It would take humans years to sift through the data to find the underlying patterns – and even longer to test all of the possible candidate combinations of donor polymers and acceptor molecules that make up an organic solar cell. Thus, progress in improving the efficiency of solar cells to be competitive in the renewable energy space has been slow.

Now, researchers at Osaka University used machine learning to screen hundreds of thousands of donor:acceptor pairs based on an algorithm trained with data from previously published experimental studies. Trying all possible combinations of 382 donor molecules and 526 acceptor molecules resulted in 200,932 pairs that were virtually tested by predicting their energy conversion efficiency.

“Basing the construction of our machine leaning model on an experimental dataset drastically improved the prediction accuracy,” first author Kakaraparthi Kranthiraja says.

To verify this method, one of the polymers predicted to have high efficiency was synthesized in the lab and tested. Its properties were found to conform with predictions, which gave the researchers more confidence in their approach.

“”This project may contribute not only to the development of highly efficient organic solar cells, but also can be adapted to material informatics of other functional materials,” senior author Akinori Saeki says.

We may see this type of machine learning, in which an algorithm can rapidly screen thousands or perhaps even millions of candidate molecules based on machine learning predictions, applied to other areas, such as catalysts and functional polymers.

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Solar Energy

Enhancing agrivoltaic synergies through optimized tracking strategies

Published

1 day ago

March 17, 2025

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Enhancing agrivoltaic synergies through optimized tracking strategies

by Robert Schreiber

Berlin, Germany (SPX) Mar 17, 2025

Agrivoltaic systems, which merge agricultural cultivation with solar power generation, represent a strategic solution to the dual challenge of meeting increasing global energy demands and ensuring food security. By situating solar panels directly above crops, these systems mitigate land use conflicts and deliver additional benefits, such as alleviating crop water stress and shielding plants from extreme weather conditions. They also foster ecological advantages, including creating habitats for pollinators and enhancing forage availability. In arid regions, agrivoltaics have shown to delay flowering and boost flower production, thereby supporting pollinators later in the season. Furthermore, the moderated microclimate beneath solar panels can enhance photovoltaic efficiency.

As their adoption expands, optimizing agrivoltaic systems through advanced tracking technologies becomes crucial. Horizontal single-axis tracker (HSAT) systems, which pivot solar panels to follow the sun’s path throughout the day, can significantly improve system performance. Strategically managing panel orientation can achieve a delicate balance between maximizing solar output and safeguarding crop yields. This balance is particularly important for securing subsidies, which often require agrivoltaic systems to remain within specified yield loss margins, thereby bolstering their financial feasibility.

A recent investigation published in the Journal of Photonics for Energy (JPE) sheds light on methodologies to fine-tune solar panel angles for optimal energy and agricultural results. The study, centered on apple orchards in southwestern Germany, introduces a novel technique to dynamically align panel positions with specific crop light requirements. Rather than relying on conventional shading guidelines or static structures like hail nets, this method leverages precise irradiation targets to fulfill the unique light needs of different crops. Researchers employed a bespoke simulation tool, APyV, to explore how variations in panel angles affect sunlight availability for crops.

The APyV platform applies sophisticated ray tracing algorithms to map solar radiation distribution, assessing its influence on both solar panels and crops. This tool streamlines agrivoltaic system design by integrating crop models and key performance metrics, enabling accurate calculations of light exposure and its impact on system performance.

Findings from the case study demonstrated that tailored panel control could deliver 91 percent of the annual light requirement for apple trees, while only slightly diminishing solar power output by 20 percent. Nonetheless, certain time periods revealed shortfalls in meeting crop light demands, highlighting the inherent challenge of achieving perfect alignment between agricultural and energy goals. Despite these constraints, the study establishes a strong platform for future research and refinement.

“Our study shows that the combination of solar energy and farming can be enhanced by smart PV-trackers that adjust the position of solar panels based on weather conditions, crop types, and their growth stages. This approach ensures an optimal balance between light available for photosynthesis and light available for electricity production,” explained corresponding author Maddelena Bruno, a doctoral researcher at Fraunhofer ISE.

Bruno further indicated that the proposed irradiation targets and tracking methodology are scheduled for field testing during the ongoing growing season in Nussbach. These trials aim to validate the simulation outcomes and broaden the understanding of how agrivoltaic systems influence crop growth and environmental conditions. The research is expected to inform future strategies for integrating agriculture and renewable energy, contributing to a more sustainable energy transition.

Research Report:Enhancing agrivoltaic synergies through optimized tracking strategies

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Solar Energy

Chinese battery behemoth CATL posts jump in annual profit

Published

1 day ago

March 17, 2025

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Chinese battery behemoth CATL posts jump in annual profit

by AFP Staff Writers

Beijing (AFP) Mar 14, 2025

Chinese battery giant CATL announced on Friday surging annual profits despite a decline in revenue, as slowing demand for electric vehicles drives down the price of lithium.

The firm produces more than a third of all electric vehicle (EV) batteries sold worldwide, cooperating with major brands including Tesla, Mercedes-Benz, BMW and Volkswagen.

CATL has been aided by robust financial support from Beijing, which has sought in recent years to shore up domestic strength in certain strategic high-tech sectors.

Net profits were up more than 15 percent in 2024 compared to 2023.

Last year, CATL achieved a profit of 50.74 billion yuan ($7.01 billion), a filing at the Shenzhen Stock Exchange showed Friday.

The figure came in below a Bloomberg forecast of 51.47 billion yuan.

Revenue, meanwhile, fell 9.7 percent year-on-year to 362 billion yuan in 2024, the filing showed.

CATL had warned in January that its slide in sales last year was likely due to a “decline in the prices of raw materials such as lithium carbonate”, which had forced the firm to adjust prices.

Last year saw lithium prices decline significantly, partly due to market oversupply and less fervent consumer demand for EVs.

– Overseas expansion –

Founded in 2011 in the eastern Chinese city of Ningde, Contemporary Amperex Technology Co., Limited (CATL) was initially propelled to success by rapid growth in the domestic market.

CATL’s shares are publicly traded in Shenzhen, though it is now planning to seek a secondary listing in Hong Kong.

Last month, the firm started a Hong Kong listing application process — a first step towards what analysts say could be a blockbuster initial public offering for the financial hub.

Funds raised from a secondary listing could be used to accelerate CATL’s overseas expansion, particularly in Europe.

The battery giant is building its second factory on the continent in Hungary after launching its first in Germany in January 2023.

In December, CATL announced that it would work with automotive giant Stellantis on a $4.3 billion factory to make EV batteries in Spain, with production slated to begin by the end of 2026.

The firm’s international push comes as challenges in the domestic market mount.

Following years of rapid growth, the world’s largest EV market has begun to show signs of flagging sales amid a broader slowdown in consumption.

The trends have fuelled a fierce price war in the country’s expansive EV sector, putting smaller firms under huge pressure to compete while remaining financially viable.

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Solar Energy

Artificial photosynthesis breakthrough replicates early plant processes

Published

1 day ago

March 17, 2025

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Artificial photosynthesis breakthrough replicates early plant processes

by Robert Schreiber

Berlin, Germany (SPX) Mar 17, 2025

Harnessing sunlight to convert carbon dioxide and water into sugars and oxygen is a remarkable feat of nature, accomplished through the intricate process of photosynthesis. This natural mechanism allows plants to derive energy from sunlight, fueling a sequence of reactions that sustain life on Earth.

Replicating photosynthesis in a laboratory setting promises significant benefits. Artificially harnessing solar energy could enable the conversion of atmospheric carbon dioxide into carbohydrates and other valuable compounds. Furthermore, as water splitting is part of photosynthesis, this approach holds potential for producing hydrogen fuel by isolating hydrogen and oxygen.

However, recreating this natural process is no simple task. Photosynthesis involves a series of complex reactions occurring in plant cells, mediated by a network of pigments, proteins, and molecules. Despite these challenges, research continues to make strides in mimicking nature’s design.

A notable advance has been achieved by Professor Frank Wurthner, a chemist at Julius-Maximilians-Universitat (JMU) Wurzburg in Bavaria, Germany. His team successfully replicated one of the initial phases of photosynthesis using an engineered array of artificial dyes and conducted an in-depth analysis of the system’s behavior.

This research, conducted in partnership with Professor Dongho Kim’s laboratory at Yonsei University in Seoul, Korea, was recently published in the journal Nature Chemistry.

The team developed a dye assembly that closely resembles plant cell light-harvesting complexes. The synthetic structure captures light at one terminus, facilitates charge separation, and then transfers electrons progressively through a series of steps to the opposite end. This assembly features four perylene bisimide dye molecules arranged in a vertical stack.

“We can specifically trigger the charge transport in this structure with light and have analysed it in detail. It is efficient and fast. This is an important step towards the development of artificial photosynthesis,” said JMU PhD student Leander Ernst, who was responsible for synthesising the stacked system.

Looking ahead, the JMU researchers plan to increase the number of dye components in their nanoscale stack to form a supramolecular wire. Such a structure would absorb sunlight and channel energy effectively across greater distances. Achieving this would mark significant progress toward new photofunctional materials that support artificial photosynthesis.

Research Report:Photoinduced stepwise charge hopping in p-stacked perylene bisimide donor-bridge-acceptor arrays.