A molecular shield against light: Stabilizing perovskite solar cells at record efficiency

KeAi Communications Co., Ltd.

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Hindered amine stabilization suppresses light-induced degradation while enabling record-efficiency perovskite solar cells. Schematic illustration of the hindered amine stabilization strategy (HASS) and its impact on device performance. Under illumination and oxygen exposure, photoexcited electrons in the perovskite generate superoxide radicals (O₂•⁻), which trigger decomposition into MA/FA species, I₂, and PbI₂. Incorporation of a multifunctional hindered amine scavenges these reactive radicals while simultaneously coordinating with Pb²⁺ and iodine vacancy defects, thereby blocking degradation pathways and passivating trap states. The resulting inverted perovskite solar cell achieves a champion power conversion efficiency of 26.74% (certified 26.56%), demonstrating the synergistic role of radical suppression and defect passivation in enhancing both efficiency and light stability.

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Credit: Cong Chen

Perovskite solar cells have reached power conversion efficiencies comparable to established photovoltaic technologies, yet their vulnerability to light-induced degradation continues to hinder practical deployment. This study introduces a chemical stabilization strategy that suppresses the radical reactions responsible for photo-driven decomposition in perovskite materials. By integrating a multifunctional hindered amine into the perovskite layer, the approach simultaneously scavenges reactive oxygen species and passivates electronic defects. As a result, the solar cells achieve both exceptionally high efficiency and markedly improved operational durability under illumination. The work demonstrates that controlling light-activated chemical pathways at the molecular level can reconcile efficiency and stability—two long-standing, competing challenges in perovskite photovoltaics.

Metal-halide perovskite solar cells are attractive for next-generation photovoltaics due to their low fabrication cost and rapidly rising efficiencies. However, exposure to light and oxygen generates superoxide radicals that attack organic cations and disrupt the perovskite lattice, leading to rapid performance loss. While encapsulation and optical filtering can mitigate environmental damage, they do not address degradation originating inside the perovskite crystal or at defect-rich interfaces. Moreover, trap states at grain boundaries often accelerate radical formation and non-radiative recombination. Based on these challenges, there is a pressing need to develop strategies that directly suppress light-induced chemical degradation while simultaneously reducing defect density within perovskite films.

Researchers from Hebei University of Technology, Kunming University of Science and Technology, Macau University of Science and Technology, and Chimie ParisTech report a new stabilization approach for perovskite solar cells in eScience, published (DOI: 10.1016/j.esci.2025.100451) in January 2026. The team demonstrates that incorporating a hindered amine light stabilizer into inverted perovskite solar cells effectively blocks photo-induced decomposition pathways. The resulting devices deliver a certified power conversion efficiency above 26% while maintaining performance under prolonged light exposure, offering a promising route toward durable, high-performance perovskite photovoltaics.

The proposed hindered amine stabilization strategy operates through a dual mechanism. Under illumination, the hindered amine absorbs light energy and forms nitroxyl radicals that catalytically neutralize superoxide species generated within the perovskite layer. By removing these highly reactive radicals before they can attack organic cations or Pb–I bonds, the strategy suppresses the primary chemical trigger of light-induced degradation. Importantly, the radical-scavenging process is regenerative, allowing continuous protection during device operation.

In parallel, functional groups within the hindered amine molecule coordinate with under-coordinated lead ions and iodine vacancies at grain boundaries and surfaces. This chemical interaction passivates electronic trap states, enlarges perovskite grain size, smooths film morphology, and reduces non-radiative recombination. Spectroscopic and electrical analyses confirm lower trap densities, longer carrier lifetimes, and improved energy-level alignment at device interfaces.

Together, these effects enable inverted perovskite solar cells fabricated under ambient conditions to reach a champion efficiency of 26.74%. Unencapsulated devices retain over 95% of their initial efficiency after more than 1,000 hours of continuous light aging, demonstrating a rare combination of record efficiency and operational stability.

“This work shows that light instability in perovskite solar cells is not an unavoidable materials problem, but a chemically addressable one,” the researchers note. By targeting both reactive radicals and interfacial defects, the hindered amine approach offers a unified solution rather than a collection of incremental fixes. The authors emphasize that the strategy is compatible with existing device architectures and scalable fabrication methods, making it particularly relevant for translating laboratory advances into commercially viable photovoltaic technologies.

The demonstrated stabilization strategy could significantly accelerate the commercialization of perovskite solar cells, especially for applications requiring long-term exposure to sunlight, such as building-integrated photovoltaics and tandem solar modules. Beyond perovskites, the concept of combining radical scavenging with defect passivation may be applicable to other light-sensitive optoelectronic materials. By reframing stability as a controllable chemical process rather than a structural limitation, this work opens new pathways for designing durable, high-efficiency solar technologies that bridge the gap between laboratory performance and real-world deployment.

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Media contact

Name: Editorial Office of eScience

Email: eScience@nankai.edu.cn

eScience – a Diamond Open Access journal cooperated with KeAi and published online at ScienceDirect. eScience is founded by Nankai University (China) in 2021 and aims to publish high quality academic papers on the latest and finest scientific and technological research in interdisciplinary fields related to energy, electrochemistry, electronics, and environment. eScience provides insights, innovation and imagination for these fields by built consecutive discovery and invention. Now eScience has been indexed by SCIE, CAS, Scopus and DOAJ. Its  impact factor is 36.6, which is ranked first in the field of electrochemistry.

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Journal

eScience

DOI

10.1016/j.esci.2025.100451 

Article Title

Chemical inhibition of light-induced decomposition by hindered amine for efficient and stable perovskite solar cells

A two-layer strategy pushes perovskite solar cells toward long-term stability

KeAi Communications Co., Ltd.

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Mutual stabilization strategy enables efficient and durable perovskite solar cells. Schematic illustration and performance summary of a hybrid–inorganic bilayer perovskite architecture. An ultrathin cubic CsPbI₃ capping layer is deposited on black-phase FAPbI₃, where close lattice matching enables mutual phase stabilization and suppresses ion diffusion at the interface. Compared with conventional 3D and 3D/2D-treated devices, the bilayer structure delivers markedly higher power conversion efficiency and greatly enhanced operational stability, retaining over 94% of its initial efficiency after more than 1,100 hours of continuous operation at 85 °C under simulated sunlight.

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Credit: Xiong Li, et al.

A bilayer perovskite strategy improves long-term stability in solar cellsPerovskite solar cells have achieved remarkable efficiencies, yet their practical deployment remains limited by phase instability and ion migration under heat and illumination. This study introduces a bilayer perovskite design that combines a hybrid organic-inorganic absorber with an ultrathin inorganic capping layer to achieve mutual stabilization. By leveraging lattice matching between the two materials, the approach simultaneously preserves the photoactive crystal phase and suppresses detrimental ion diffusion across interfaces. As a result, the bilayer devices deliver record-level efficiency together with exceptional operational stability, demonstrating a viable pathway toward durable, high-performance perovskite photovoltaics.

Organic–inorganic halide perovskites are widely regarded as promising candidates for next-generation photovoltaics because of their tunable bandgaps and high absorption efficiency. Among them, formamidinium lead iodide (FAPbI3) has attracted particular interest due to its favorable optoelectronic properties. However, its photoactive black phase is thermodynamically unstable at room temperature and prone to transformation into non-functional phases under light, heat, or moisture. Existing stabilization strategies, including compositional mixing and surface passivation, often introduce new degradation pathways, including interfacial strain and accelerated ion migration. Based on these challenges, there is a clear need to develop advanced strategies that simultaneously stabilize crystal phases and suppress ion transport through deeper, interface-focused investigations.

Researchers from Huazhong University of Science and Technology, Hainan University, and collaborating institutions report a new perovskite stabilization strategy, published in eScience in 2026 (DOI: 10.1016/j.esci.2025.100449). The team developed a 3D/3D bilayer perovskite structure, in which an ultrathin (~5 nm) cesium lead iodide (CsPbI3) layer is deposited on top of a formamidinium-based perovskite absorber using a vapor-phase co-evaporation process. Unlike conventional low-dimensional surface treatments, both layers retain a three-dimensional perovskite framework, enabling robust structural coupling across the interface.

Structural analyses revealed that strong lattice matching at the interface favors the formation of a photoactive cubic phase in both layers, despite each material being individually metastable under ambient conditions. This interfacial coupling reduces strain, suppresses phase transitions during aging, and maintains structural integrity under prolonged thermal stress. Importantly, the inorganic capping layer also acts as an effective barrier against ion migration, blocking both intrinsic ions and ligand-derived species from diffusing across the interface, one of the primary causes of long-term degradation in perovskite devices.

When integrated into inverted perovskite solar cell devices, the bilayer design delivered a certified power conversion efficiency exceeding 27% for small-area cells, while large-area devices achieved efficiencies close to 25%. Operational stability tests demonstrated that the cells retained over 94% of their initial performance after more than 1,100 hours of continuous operation at elevated temperatures. These results place the devices among the most stable and efficient perovskite solar cells reported to date.

According to the researchers, the key advance is not a single material improvement but the cooperative behavior between two perovskite layers. By allowing the hybrid and inorganic components to stabilize each other through lattice matching, the design avoids many of the degradation pathways that typically limit perovskite devices. The team emphasizes that this approach shifts the focus from compositional complexity to interface control, offering a more universal and scalable route for improving both efficiency and durability in perovskite photovoltaics.

This bilayer stabilization strategy has broad implications for the commercialization of perovskite solar technologies. By addressing phase instability and ion migration simultaneously, the approach moves perovskite devices closer to meeting industrial reliability standards. Beyond single-junction solar cells, the design concept can be extended to tandem photovoltaics and other optoelectronic devices where interface stability is critical. Moreover, the use of vacuum-deposited inorganic layers is compatible with scalable manufacturing processes. Together, these advantages suggest that rationally engineered perovskite interfaces could play a central role in enabling durable, high-efficiency solar modules for real-world energy applications.

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Media contact

Name: Editorial Office of eScience

Email: eScience@nankai.edu.cn

eScience – a Diamond Open Access journal cooperated with KeAi and published online at ScienceDirect. eScience is founded by Nankai University (China) in 2021 and aims to publish high quality academic papers on the latest and finest scientific and technological research in interdisciplinary fields related to energy, electrochemistry, electronics, and environment. eScience provides insights, innovation and imagination for these fields by built consecutive discovery and invention. Now eScience has been indexed by SCIE, CAS, Scopus and DOAJ. Its  impact factor is 36.6, which is ranked first in the field of electrochemistry.

 

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Journal

eScience

DOI

10.1016/j.esci.2025.100449 

Article Title

Mutual stabilization of hybrid and inorganic perovskites for photovoltaics

 

AI meets electrocatalysis: Lessons from three decades and a roadmap ahead

KeAi Communications Co., Ltd.

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This schematic illustrates the major bottlenecks that have long constrained electrocatalysis research—including the scale gap of atomistic simulations, limited inverse catalyst design, poor physical consistency of data-driven models, inefficient human experimentation, and scarce high-quality datasets—and how recent AI advances are helping to overcome them. Emerging approaches such as machine-learning interatomic potentials (MLIPs), diffusion-based generative models, physics-informed machine learning (PIML), autonomous robotic electrochemists, and FAIR-compliant data infrastructures are converging to transform electrocatalysis from a trial-and-error discipline into a predictive, data-centric discovery pipeline.

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Credit: Richard G. Compton

Electrocatalysis sits at the heart of clean hydrogen production, fuel cells, and carbon dioxide conversion, yet progress toward scalable, high-performance catalysts has remained frustratingly slow. A growing body of research now suggests that artificial intelligence (AI) may be key to breaking this bottleneck—but only if it is used wisely. By reviewing three decades of AI applications in electrocatalysis, researchers reveal how the field has shifted from isolated data analysis toward end-to-end, data-driven discovery. The work highlights a critical turning point: AI is no longer just accelerating experiments, but beginning to reshape how electrocatalysts are designed, evaluated, and understood at a fundamental level.

Despite intense global investment in clean energy technologies, electrocatalyst development still struggles with deep-rooted challenges. Atomistic simulations rarely translate into device-scale performance, experimental workflows remain labor-intensive and difficult to reproduce, and most machine-learning models lack physical interpretability. At the same time, the demand for efficient catalysts in hydrogen production and carbon-neutral chemical manufacturing continues to rise. The rapid expansion of artificial intelligence (AI) capabilities—ranging from physics-informed models to autonomous experimentation—has opened new possibilities, but also exposed systemic weaknesses in data quality and integration. Based on these challenges, a comprehensive reassessment of how AI should be deployed in electrocatalysis has become urgently needed.

Addressing this need, a review published (DOI: 10.1016/j.esci.2025.100515) in December 2025 in eScience by an international team of researchers from the University of Michigan, Xiamen University, and the University of Oxford examines 30 years of AI-driven electrocatalysis research. rather than cataloging past successes, the authors identify why many AI approaches have failed to deliver real-world impact—and how recent advances in machine learning, data infrastructure, and laboratory automation may finally change that trajectory. the review positions the field at a decisive moment, where strategic choices could determine whether AI delivers genuine breakthroughs or remains largely incremental.

The authors identify five structural bottlenecks that have limited the effectiveness of AI in electrocatalysis: mismatches between atomic-scale models and macroscopic performance, the immaturity of inverse catalyst design, poor physical consistency of black-box algorithms, inefficient manual experimentation, and a shortage of reliable experimental data. To overcome these barriers, recent work has introduced machine-learning interatomic potentials capable of simulating dynamic catalyst restructuring at unprecedented scales, alongside generative AI models that propose new materials rather than merely screening known ones.

Equally transformative is the rise of physics-informed machine learning, which embeds electrochemical laws directly into neural networks, enabling models that are both predictive and interpretable. The review also highlights the emergence of autonomous “robotic electrochemists” that integrate AI decision-making with high-throughput synthesis and testing. Together, these developments suggest that electrocatalysis is shifting from a trial-and-error discipline toward a closed-loop, self-improving discovery system—provided that data quality and model transparency are treated as core scientific priorities.

Importantly, the authors caution against viewing AI as a universal solution. They emphasize that poorly curated data and physically inconsistent models risk amplifying errors rather than accelerating discovery. Instead, they argue that the most impactful advances will come from combining AI with electrochemical theory, standardized data practices, and interdisciplinary collaboration. In their view, the true value of AI lies not in replacing human expertise, but in enabling scientists to ask deeper questions and explore chemical spaces that were previously inaccessible.

If these challenges are addressed, AI-driven electrocatalysis could significantly accelerate the deployment of clean energy technologies, from large-scale hydrogen production to carbon-neutral fuel synthesis. The review suggests that the next breakthroughs will likely emerge where automated laboratories, physics-informed models, and open data infrastructures converge. Beyond energy applications, the lessons outlined may influence how AI is applied across chemistry and materials science more broadly. By reframing AI as an integrated scientific partner rather than a standalone tool, the work points toward a future in which catalyst discovery becomes faster, more reliable, and more directly connected to real-world impact.

###

Media contact

Name: Editorial Office of eScience

Email: eScience@nankai.edu.cn

eScience – a Diamond Open Access journal cooperated with KeAi and published online at ScienceDirect. eScience is founded by Nankai University (China) in 2021 and aims to publish high quality academic papers on the latest and finest scientific and technological research in interdisciplinary fields related to energy, electrochemistry, electronics, and environment. eScience provides insights, innovation and imagination for these fields by built consecutive discovery and invention. Now eScience has been indexed by SCIE, CAS, Scopus and DOAJ. Its first impact factor is 36.6, which is ranked first in the field of electrochemistry.

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Journal

eScience

DOI

10.1016/j.esci.2025.100515 

Article Title

30 years of AI for electrocatalysis: Where we are and what's next?

 

HKUST research reveals cost-effective food waste treatment through sewage systems

Cutting costs and greenhouse gas emissions by 11% and 47%

Hong Kong University of Science and Technology

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Prof. CHEN Guanghao (center, the corresponding author), Chair Professor of the Department of Civil and Environmental Engineering, and his research group members in the same department, postdoctoral fellow Dr. GUO Hongxiao (right, the corresponding author) and PhD student Mr. ZOU Xu (left, the first author).

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Credit: HKUST

A research team at The Hong Kong University of Science and Technology (HKUST) has developed an innovative urban food waste management framework by analyzing food waste data from 29 large cities worldwide, including Hong Kong, Beijing, and New York. The study shows that in cities with higher food waste moisture loads, such as Hong Kong, grinding food waste and diverting it into the sewage system is more effective than relying solely on landfilling. This approach can reduce overall greenhouse gas emissions by about 47% and lower total waste-management costs by about 11%. The research provides a new, quantitative basis for shaping food waste management strategies in cities around the globe.

The study was led by Prof. CHEN Guanghao, Chair Professor of the Department of Civil and Environmental Engineering at HKUST, together with Dr. GUO Hongxiao, Postdoctoral Fellow and PhD student Mr. ZOU Xu, in collaboration with researchers from Huazhong University of Science and Technology. The findings, titled “Redefining separate or integrated food waste and wastewater streams for 29 large cities”, were published in the international academic journal Nature Cities.

As urban populations continue to expand worldwide, food waste volumes are rising accordingly. Most cities still rely on landfilling or incineration to manage food waste, even though its high moisture content reduces processing efficiency and increases logistical burdens. For example, in the United States, food waste alone accounts for approximately 58% of methane emissions generated from landfills, making it one of the major pollution sources of greenhouse gas emissions.

The research team collected data on food waste composition, wastewater generation, energy consumption, and treatment costs from 29 large cities worldwide for analysis. They found that the key factor affecting food waste treatment efficiency is not the weight or type of food waste, but its moisture load. Higher moisture loads were linked to increased treatment costs and emissions.

The team developed the Urban Biowaste Flux (UBF) framework and identified a threshold of about 46.8kg per capita per year of food waste moisture load. Above this threshold, adopting an integrated system—diverting food waste into the sewage network and combining it with landfill or incineration—results in lower overall costs than maintaining separate systems. Cities such as Hong Kong, Beijing and Seoul, where fresh ingredients and soup‑based diets are common, tend to generate wetter food waste streams. The study shows that using food waste grinders to divert it into the sewage system can improve overall treatment efficiency in such cities. In Hong Kong, for example:

• Economic benefits: Under the integrated system, the annual operating costs for wastewater treatment and sludge treatment increase by US$5.63 million and US$22.51 million, respectively. However, landfill expenditure decreases by US$74 million, resulting in an 11.13% reduction in Hong Kong’s total waste‑management costs (including capital, operation, and grinder costs).

• Greenhouse gas emissions: Integrated treatment can reduce Hong Kong’s direct and indirect greenhouse‑gas emissions by a combined 46.61%.

Mr. Zou, HKUST PhD student, said, “Using Hong Kong as an example, our analysis of food waste and wastewater samples shows that food waste accounts for 57.78% of the total chemical oxygen demand entering the biowaste treatment system. This demonstrates why we must rethink how food waste is managed. The UBF model offers an effective analytical tool for cities with high food waste moisture loads like Hong Kong.”

Dr. Guo, HKUST Postdoctoral Fellow, said, “Compared with traditional separate collection and landfilling, integrated system can reduce greenhouse gas emissions by 24% to 88% across different cities. Around half of all food waste in the U.S. is already managed through this method, but it remains uncommon in Asia. The UBF model helps cities like Hong Kong identify more efficient and sustainable approaches to food waste management.”

Prof. Chen said, “Using wastewater systems to process wet food waste, together with anaerobic digestion, allows sludge to be used as fuel, and the heat generated during incineration can be recovered for electricity generation. Our study shows that among 29 cities worldwide, 27 would reduce per‑capita annual energy consumption by about 20.6%, and 26 would reduce per‑capita greenhouse‑gas emissions by about 22.6% if integrated treatment were adopted. Of course, cities differ, and not all will be suited to the same model. But for those with high food waste moisture load and high solid‑waste processing costs, integrated treatment is a practical path forward. We hope this research provides a scientific foundation for cities to formulate more appropriate strategies for food waste management.”

 

Ten years of research spanning lab-scale to pilot-scale studies, employing the UBF model to evaluate food waste integration potential in 29 global cities.

Credit

HKUST

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Journal

Nature Cities

DOI

10.1038/s44284-025-00341-8 

Method of Research

Data/statistical analysis

Subject of Research

Not applicable

Article Title

Redefining separate or integrated food waste and wastewater streams for 29 large cities