Results 111 to 120 of about 8,083 (249)

Amorphous π‐Conjugated Passivator Facilitates Widening Process Window for Reliable Perovskite Solar Modules

Advanced Energy Materials, EarlyView.
A wide process window is essential for the commercialization of perovskite photovoltaics. Here, we demonstrate an amorphous π‐conjugated passivator having an asymmetric mono‐iodine substituent on a carbazole moiety imparts a high dipole moment, desirable molecular energy levels, and high thickness tolerance, thereby enabling a wide process window in ...
Hyun Seo Kim, Young Yun Kim, Hyejin Na, You‐Hyun Seo, Sung Jae Na, Seulyi Lee, Mingi Kang, Jinuk Jang, Daehyeok Kim, Yeonkyeong Ju, So‐Min Yoo, Jae Yong Park, Bong Joo Kang, Geun Ho Gu, Tae Joo Shin, Jaemin Lee, Nam Joong Jeon, Eui Hyuk Jung   +17 more
wiley   +1 more source

Multiscale Perspectives on Perovskite Instability: From Atomistic Deformation to Device Degradation in Perovskite Solar Cells

Advanced Energy Materials, EarlyView.
Multiscale perspectives on how excess charges in soft lead halide perovskites induce operational instability in photovoltaic devices are presented. Localized carriers formed under thermodynamic non‐equilibrium states modify atomistic interactions and drive lattice distortions, accelerating device degradation.
Joo‐Hong Lee, Donghyeon Lee, Seoyoon Lee, Jin‐Wook Lee, Mansoo Choi, Min‐cheol Kim, Namyoung Ahn   +6 more
wiley   +1 more source

High‐Performance Noble‐Metal‐Free Perovskite Solar Cells Enabled by MoOX/Cr/Al Multilayer Electrodes

Advanced Energy Materials, EarlyView.
Cost‐effective perovskite solar cells (PSCs) are developed using a noble‐metal‐free MoOX/Cr/Al multilayer electrode. The devices achieve a power conversion efficiency (PCE) of 25.6%, competitive with that of Au‐based devices (26.3%), and a 25.5 cm2 mini‐module shows 21.3% PCE.
Wooyeon Kim, Soyeon Kim, In Choi, Seoyeong Lee, Subin Yu, Young Yun Kim, Bonkee Koo, Min Jae Ko   +7 more
wiley   +1 more source

Machine Learning Interatomic Potentials for Energy Materials: Architectures, Training Strategies, and Applications

Advanced Energy Materials, EarlyView.
Machine learning interatomic potentials bridge quantum accuracy and computational efficiency for materials discovery. Architectures from Gaussian process regression to equivariant graph neural networks, training strategies including active learning and foundation models, and applications in solid‐state electrolytes, batteries, electrocatalysts ...
In Kee Park, Saeed Pourasad, Jinhong Mun, Arunkumar Chitteth Rajan, Tae Hyeon Park, Anand Rohit, Mohammad Zafari, Tan‐Lien Pham, Eunjae Jung, Bonseung Koo, Miran Ha, Gi Beom Sim, Hyun Gyu Park, Won Woong Choi, Kwanghyeon Jo, Soohaeng Yoo Willow, David ChangMo Yang, Chang Woo Myung, Geunsik Lee, Kwang S. Kim   +19 more
wiley   +1 more source

Redefining Crystalline Silicon: Unlocking New Horizons in Transparent and Flexible Photovoltaics

Advanced Energy Materials, EarlyView.
Crystalline silicon is presented as a platform for transparent and flexible photovoltaics. This review article outlines design principles for optical strategies to fabricate transparent silicon solar cells, mechanical strategies that mitigate silicon brittleness, and emerging concepts such as singlet‐fission spectral conversion and tandem architectures,
Kangmin Lee
wiley   +1 more source

Experimental investigation on the effect of real environmental factors on photovoltaic module power output in Southern Algeria. [PDF]

Sci Rep
Rachedi MY, Slimani D, Rabehi A, Amiar A, Bechki D, Bouguettaia H, Alsabah YA, Bessous N, Chennana A.   +8 more
europepmc   +1 more source

A Kinetic–Energetic Bottleneck of Charge‐Transfer Injection Governs Energy Loss in Organic Solar Cells

Advanced Energy Materials, EarlyView.
Kinetic–energetic projection of time‐resolved photoluminescence reveals that charge‐transfer injection acts as a universal bottleneck in organic solar cells. A physics‐constrained Bayesian framework identifies an emergent effective CT injection rate governing the trade‐off between charge generation and nonradiative energy loss.
Rong Wang, Tobias Osterrieder, Atul Shukla, Christos L. Chochos, Vasilis G. Gregoriou, Yakun He, Hua Tang, Julian Matthias Haffner‐Schirmer, Karen Forberich, Ning Li, Thomas Heumueller, Frédéric Laquai, Jens Hauch, Safa Shoaee, Dieter Neher, Larry Lüer, Christoph J. Brabec   +16 more
wiley   +1 more source

Advanced metric for evaluating the performance of photovoltaic module enhancement techniques using a lifespan, cost and power-based approach. [PDF]

Sci Rep
Sultan SM, Tso CP, Abdullah MZ, Sopian K.   +3 more
europepmc   +1 more source

Verification and Mitigation of Proton‐Induced Non‐Ionizing Damage in Perovskite Solar Cells for Space Applications

Advanced Energy Materials, EarlyView.
Metal‐halide perovskite solar cells offer high‐efficiency power for orbital missions but suffer from permanent proton‐induced degradation. This work identifies non‐ionizing energy loss (NIEL) as the primary driver of irreversible failure, inducing atomic displacements and microcracks in the high‐fluence regime. Through energy‐tuned mapping and scalable
Jangwon Byun, Sung‐Pil Yoon, Beomjun Park, Sung‐Jun Park, Dong Hoe Kim, Sunwoo Kim, Jin‐Wook Lee, Sangwook Lee, Hyun Suk Jung, Nam‐Gyu Park, Man‐Jong Lee   +10 more
wiley   +1 more source

Model‐Based Bayesian Optimization for Organic Photovoltaics: Combining Bayesian Optimization With Physical Domain Knowledge

Advanced Energy Materials, EarlyView.
Integration of a physical solar cell model into Bayesian optimization is performed using the Knowledge Gradient acquisition function to balance exploration and exploitation. Experimental validation on the PTQ10:BTP‐eC9 material system and statistical validation on an OPV benchmark function show that the model‐based approach outperforms conventional ...
Leonard Christen, Thomas Kirchartz
wiley   +1 more source