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New calcium-doping strategy surpasses platinum catalysts in hydrogen fuel cells

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New calcium-doping strategy surpasses platinum catalysts in hydrogen fuel cells


New calcium-doping strategy surpasses platinum catalysts in hydrogen fuel cells

by Riko Seibo

Sendai, Japan (SPX) Feb 12, 2024






In an innovative stride towards enhancing the efficiency of hydrogen fuel cells, a research team has unveiled a novel method that significantly improves the electrochemical surface area (ECSA) of a calcium-doped perovskite, La0.6Ca0.4MnO3 (LCMO64). This development is poised to address a notable challenge in leveraging perovskite oxides as effective electrocatalysts in hydrogen fuel cells, a promising direction for sustainable energy technology.

Published in the journal Advanced Materials on November 29, 2023, the study delves into the intricacies of perovskite oxides, materials celebrated for their diverse and compelling properties. These oxides are particularly esteemed for their high intrinsic activities, positioning them as a viable alternative to the traditionally used noble metal catalysts in catalyzing the oxygen reduction reaction (ORR), a critical process in the operation of hydrogen fuel cells. Despite their potential, the practical application of perovskite oxides has been curtailed by their limited electrical conductivity and low specific surface area.



The breakthrough method, as elaborated by Hao Li, Associate Professor at Tohoku University’s Advanced Institute for Materials Research (WPI-AIMR) and the corresponding author of the study, involves an electrochemically induced calcium-leaching process. This process not only augments the ECSA in LCMO64 but also marks a significant improvement in the material’s electrocatalytic ORR performance. “The activated, calcium-deficient LCMO64 demonstrated an ECSA approximately 33.84% higher than that of unactivated materials, showcasing superior electrocatalytic ORR performance-surpassing the benchmark commercial Pt/C catalyst in an alkaline solution,” Li stated.



The research team’s approach included theoretical analysis, electrochemical surface state probing, and pH-dependent microkinetic modeling to establish the material’s benchmarks. The findings underscored that the catalyst reaches the Sabatier optimum for alkaline ORR, indicating an optimal balance between the adsorption and desorption of reactants and products on the catalyst’s surface, a crucial criterion for efficient catalysis.



This study is notable for being the first to utilize calcium (Ca) doping as a strategy to overcome the inherent limitations of low conductivity and surface area in perovskite oxides. The observed phenomenon of Ca leaching under ORR conditions leads to increased surface roughness and, consequently, an expanded available surface area for ORR, enhancing the catalyst’s overall performance.



Li further emphasized the broader impact of their work, stating, “Finding low-cost and effective electrocatalysts for the ORR in hydrogen fuel cells has been a significant challenge. Our work not only addresses this challenge but also offers a novel strategy for enhancing the electrocatalytic performance of perovskite oxides.” This advancement heralds a significant leap towards the widespread adoption of hydrogen fuel cell technology, promising a future where sustainable and efficient energy solutions are more accessible.



Research Report:Cation-Deficient Perovskites Greatly Enhance the Electrocatalytic Activity for Oxygen Reduction Reaction


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Rice Lab Reports Significant Advances in Perovskite Solar Cell Stability

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Rice Lab Reports Significant Advances in Perovskite Solar Cell Stability


Rice Lab Reports Significant Advances in Perovskite Solar Cell Stability

by Clarence Oxford

Los Angeles CA (SPX) Jun 18, 2024






Solar power is growing rapidly as an energy technology, recognized for its cost-effectiveness and its role in reducing greenhouse gas emissions.

A Rice University study published in Science details a method for synthesizing formamidinium lead iodide (FAPbI3) into stable, high-quality photovoltaic films. The efficiency of these FAPbI3 solar cells declined by less than 3% over more than 1,000 hours of operation at 85 degrees Celsius (185 Fahrenheit).



“Right now, we think that this is state of the art in terms of stability,” said Rice engineer Aditya Mohite. “Perovskite solar cells have the potential to revolutionize energy production, but achieving long-duration stability has been a significant challenge.”



This breakthrough represents a major step towards making perovskite photovoltaics commercially viable. The researchers added specially designed two-dimensional (2D) perovskites to the FAPbI3 precursor solution, which served as a template to enhance the stability of the crystal lattice structure.



“Perovskite crystals get broken in two ways: chemically – destroying the molecules that make up the crystal – and structurally – reordering the molecules to form a different crystal,” explained Isaac Metcalf, a Rice graduate student and a lead author on the study. “Of the various crystals that we use in solar cells, the most chemically stable are also the least structurally stable and vice versa. FAPbI3 is on the structurally unstable end of that spectrum.”



The researchers found that while 2D perovskites are more stable, they are less effective at harvesting light. By using 2D perovskites as templates, they improved the stability and efficiency of FAPbI3 films. The addition of well-matched 2D crystals facilitated the formation of high-quality FAPbI3 films, showing less internal disorder and better illumination response.



The study showed that solar cells with 2D templates retained their efficiency and durability significantly better than those without. Encapsulation layers further enhanced the stability of these solar cells, extending their operational life to timescales relevant for commercial applications.



“Perovskites are soluble in solution, so you can take an ink of a perovskite precursor and spread it across a piece of glass, then heat it up and you have the absorber layer for a solar cell,” Metcalf said. “Since you don’t need very high temperatures – perovskite films can be processed at temperatures below 150 Celsius (302 Fahrenheit) – in theory that also means perovskite solar panels can be made on plastic or even flexible substrates, which could further reduce costs.”



Silicon, the most commonly used semiconductor in photovoltaic cells, requires more resource-intensive manufacturing processes than perovskites, which have seen efficiency improvements from 3.9% in 2009 to over 26% currently.



“It should be much cheaper and less energy-intensive to make high-quality perovskite solar panels compared to high-quality silicon panels, because the processing is so much easier,” Metcalf said.



“We need to urgently transition our global energy system to an emissions-free alternative,” he added, referring to UN estimates that highlight the importance of solar energy in replacing fossil fuels.



Mohite emphasized that advancements in solar energy technologies are crucial for meeting the 2030 greenhouse gas emissions target and preventing a 1.5 degrees Celsius rise in global temperatures, essential for achieving net zero carbon emissions by 2050.



“If solar electricity doesn’t happen, none of the other processes that rely on green electrons from the grid, such as thermochemical or electrochemical processes for chemical manufacturing, will happen,” Mohite said. “Photovoltaics are absolutely critical.”



Mohite holds the title of William M. Rice Trustee Professor at Rice, is a professor of chemical and biomolecular engineering, and directs the Rice Engineering Initiative for Energy Transition and Sustainability. The study’s lead authors also include Siraj Sidhik, a Rice doctoral alumnus.



“I would like to give a lot of credit to Siraj, who started this project based on a theoretical idea by Professor Jacky Even at the University of Rennes,” Mohite said. “I would also like to thank our collaborators at the national labs and at several universities in the U.S. and abroad whose help was instrumental to this work.”



Research Report:Two-dimensional perovskite templates for durable, efficient formamidinium perovskite solar cells


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Sweeping review reveals impact of integrating AI into photovoltaics

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Sweeping review reveals impact of integrating AI into photovoltaics


Sweeping review reveals impact of integrating AI into photovoltaics

by Simon Mansfield

Sydney, Australia (SPX) Jun 13, 2024






Artificial intelligence is set to enhance photovoltaic systems by improving efficiency, reliability, and predictability of solar power generation.

In their paper published on May 8 in CAAI Artificial Intelligence Research, a research team from Chinese and Malaysian universities examined the impact of artificial intelligence (AI) technology on photovoltaic (PV) power generation systems and their applications globally.



“The overall message is an optimistic outlook on how AI can lead to more sustainable and efficient energy solutions,” said Xiaoyun Tian from Beijing University of Technology. “By improving the efficiency and deployment of renewable energy sources through AI, there is significant potential to reduce global carbon emissions and to make clean energy more accessible and reliable for a broader population.”



The team, which included researchers from Beijing University of Technology, Chinese Academy of Sciences, Hebei University, and the Universiti Tunku Abdul Rahman, focused their review on key applications of AI in maximum power point tracking, power forecasting, and fault detection within PV systems.



The maximum power point (MPP) refers to the specific operating point where a PV cell or an entire PV array yields its peak power output under prevailing illumination conditions. Tracking and exploiting the point of maximum power by adjusting the operating point of the PV array to maximize output power is a critical issue in solar PV systems. Traditional methods have defects, resulting in reduced efficiency, hardware wear, and suboptimal performance during sudden weather changes.



The researchers reviewed publications showing how AI techniques can achieve high performance in solving the MPP tracking problem. They compiled methods that presented both single and hybrid AI methods to solve the tracking problem, exploring the advantages and disadvantages of each approach.



The team reviewed publications that presented AI algorithms applied in PV power forecasting and defect detection technologies. Power forecasting, which predicts the production of PV power over a certain period, is crucial for PV grid integration as the share of solar energy in the mix increases annually. Fault detection in PV systems can identify various types of failures, such as environmental changes, panel damage, and wiring failures. For large-scale PV systems, traditional manual inspection is almost impossible. AI algorithms can identify deviations from normal operating conditions that may indicate faults or anomalies proactively.



The research team compared AI-driven techniques, exploring and presenting advantages and disadvantages of each approach.



While integrating AI technology optimizes PV systems’ operational efficiency, new challenges continue to arise. These challenges are driven by issues such as revised standards for achieving carbon neutrality, interdisciplinary cooperation, and emerging smart grids.



The researchers highlighted some emerging challenges and the need for advanced solutions in AI, such as transfer learning, few-shot learning, and edge computing.



According to the paper’s authors, the next steps should focus on further research directed towards advancing AI techniques that target the unique challenges of PV systems; practical implementation of AI solutions into existing PV infrastructure on a wider scale; scaling up successful AI integration; developing supportive policy frameworks that encourage the use of AI in renewable energy; increasing awareness about the benefits of AI in enhancing PV system efficiencies; and ultimately aligning these technological advancements with global sustainability targets.



“AI-driven techniques are essential for the future development and widespread adoption of solar-energy technologies globally,” Tian said.



The research was supported by the National Key R and D Program of China and Fundamental Research Grant Scheme of Malaysia. The grants are part of the China-Malaysia Intergovernmental Science, Technology and Innovation Cooperative Program 2023.



Other contributors include Jiaming Hu, Kang Wang, and Dachuan Xu from Beijing University of Technology; Boon-Han Lim from Universiti Tunku Abdul Rahman; Feng Zhang from Hebei University; and Yong Zhang from Shenzhen Institute of Advanced Technology, Chinese Academy of Science.



Research Report:A Comprehensive Review of Artificial Intelligence Applications in Photovoltaic Systems


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New approaches for perovskite-based ferroelectric ceramics in energy storage

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New approaches for perovskite-based ferroelectric ceramics in energy storage


New approaches for perovskite-based ferroelectric ceramics in energy storage

by Simon Mansfield

Sydney, Australia (SPX) Jun 13, 2024






With the increasing impacts of climate change and resource depletion, dielectric capacitors are becoming key candidates for high-performance energy storage devices. However, various dielectric ceramics, such as paraelectrics, ferroelectrics, and antiferroelectrics, face challenges due to their low polarizability, low breakdown strength, and large hysteresis loss. Therefore, synthesizing novel perovskite-based materials that offer high energy density, efficiency, and low loss is essential for improving energy storage performance.

A team of material scientists led by Bingcheng Luo from the Department of Applied Physics at China Agricultural University recently reviewed the state of perovskite-based ferroelectric ceramics for energy storage. These capacitors are noted for their stability, high energy and power density, conversion efficiency, wide operating temperature range, environmental friendliness, and cost-effectiveness, setting them apart from traditional electrochemical capacitors and batteries.



“In this review, we outlined the recent development of perovskite-based ferroelectric energy storage ceramics from the perspective of combinatorial optimization for tailoring ferroelectric hysteresis loops and comprehensively discussed the properties arising from the different combinations of components. Also, we provided the future guidelines in this realm and therefore, the combinatorial optimization strategy in this review will open up a practical route towards the application of new high-performance ferroelectric energy storage devices,” said Bingcheng Luo, senior author of the review paper, professor in the Department of Applied Physics at China Agricultural University, who received his PhD in 2018 in Tsinghua University and then worked as Research Associate at University of Cambridge.



Dielectric materials can be categorized into four types based on their hysteresis loops: paraelectric (PE), ferroelectric (FE), relaxor ferroelectric (RFE), and antiferroelectric (AFE), each with unique properties.



The research team highlights advancements in the energy storage performance of lead-free ferroelectric ceramics. “We classify the perovskites-based ferroelectric ceramics into seven types for tailoring ferroelectric hysteresis loops from the perspective of combinatorial optimization and comprehensively discuss the properties arising from the different combinations of components. The concept of combinatorial optimization is to maximize breakdown strength and maximum saturation polarization while slenderizing electric hysteresis loop, which bolsters the energy storage performance of perovskites-based ferroelectric ceramics,” Bingcheng Luo said.



The seven types of combinatorial optimization of perovskite-based ferroelectric ceramics discussed in the review include FE vs. PE, FE vs. FE, FE vs. AFE, AFE vs. PE, RFE vs. PE, RFE vs. FE, and RFE vs. AFE combinations. Luo explained, “As an example of combinatorial optimization strategies, ferroelectrics have higher maximum saturation polarization, and paraelectrics have higher breakdown strength, and the combination of the two creates an RFE that has the advantages of both materials and with a narrower hysteresis loop, the long-range ferroelectric order will become polar nanodomains, which will increase the energy storage density and efficiency of ceramics.”



The concept of combinatorial optimization aims to maximize the complementary advantages of each component. Generally, polarization and breakdown strength are mutually exclusive in dielectric materials. Increasing the content of one component alone does not achieve high breakdown strength or polarization. It is necessary to find the optimal balance between these factors and tailor more optimized hysteresis loops to improve energy storage performance.



The team anticipates that their review of combinatorial optimization strategies will not only aid in the design of future high-performance passive devices but also provide guidance for the practical utilization of ferroelectric ceramics.



Research Report:Combinatorial optimization of perovskites-based ferroelectric ceramics for energy storage applications


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