Results 141 to 150 of about 1,085,425 (239)

Smart Exploration of Perovskite Photovoltaics: From AI Driven Discovery to Autonomous Laboratories

Advanced Energy Materials, EarlyView.
In this review, we summarize the fundamentals of AI in automated materials science, and review AI applications in perovskite solar cells. Then, we sum up recent progress in AI‐guided manufacturing optimization, and highlight AI‐driven high‐throughput and autonomous laboratories.
Wenning Chen, Zheyu Zhang, Kelvian T. Mularso, Bonghyun Jo, Hyun Suk Jung   +4 more
wiley   +1 more source

AI models of unstable flow exhibit hallucination. [PDF]

Sci Rep
Wibawa R, Jha B.
europepmc   +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

Medial prefrontal cortex encodes but is not required to generate goal-directed actions under threat. [PDF]

Elife
Sajid MS, Zhou J, Castro-Alamancos MA.
europepmc   +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

MXene‐Derived Highly Oriented TiN Enables Ta3N5 Photoanodes for Transmission‐Mode Bias‐Free Solar Water Splitting

Advanced Energy Materials, EarlyView.
This work reports 2D MXene‐derived TiN thin films with (111)‐preferred orientation for transparent Ta3N5 photoanodes, demonstrating effective electron transfer behavior. All‐nitride electron‐collection architecture based on MXene‐derived TiN and n‐GaN resolves a long‐standing materials bottleneck between photocarrier transport and light transmission in
Jin Wook Yang, Hee Ryeong Kwon, Young Seon Yoon, Sung Yeon Lim, Tae Hyung Lee, Jiwoo Lee, Sung Hyuk Park, Sohyeon Park, Jungwon Park, Jin Young Kim, Ho Won Jang   +10 more
wiley   +1 more source

Sub-6 GHz acoustic filters using laterally-excited bulk acoustic resonator with scattering vias in double-layer electrodes. [PDF]

Microsyst Nanoeng
Wen Z, Liu W, Zeng M, Liu J, Qu Y, Wang R, Liu Y, Cai Y, Sun C.   +8 more
europepmc   +1 more source

From Top to Bottom: Manufacturing Process‐Context Aware Resolution of Energy Device Electrodes Through a 3D Diffusion Generative Model

Advanced Energy Materials, EarlyView.
The application of a generative diffusion model, enhanced with a training data augmentation pipeline retaining the manufacturing process context of electrode microstructures, leads to improved fidelity of the through‐plane tortuosity factor in the AI generated samples.
Victor Ramirez‐Camacho, Siwar Ben Hadj Ali, Maxence Desnoyers, Francisco Fernandez, Nassima Benammar, Alejandro A. Franco   +5 more
wiley   +1 more source

Breaking the phase noise-mode purity trade-off in long-loop OEOs via cascaded zero-dispersion recirculating loops. [PDF]

Light Sci Appl
Wang Z, Bernal S, Plant DV, Chen LR.
europepmc   +1 more source

Differentiated Impacts of EU Rural Development Measures: A Finite Mixture Evaluation of Italian Olive Farms

Applied Economic Perspectives and Policy, EarlyView.
ABSTRACT This paper examines the relationship between participation in the EU Rural Development Program and the economic performance of Italian olive farms using a finite‐mixture model with inverse‐probability‐weighted regression adjustment. Based on 2010–2022 FADN panel data, it estimates heterogeneous treatment effects while correcting for selection ...
Francesco Caracciolo, Marilena Furno
wiley   +1 more source