Results 201 to 210 of about 1,480,294 (293)

Scalable Manufacturing of Roll‐to‐Roll Slot‐Die Coated Perovskite Solar Cells

open access: yesAdvanced Science, EarlyView.
Roll‐to‐roll (R2R) slot‐die coating is emerging as a scalable pathway for perovskite solar cells. This mini‐review summarizes advances in ink design, drying control, and electrode integration that enable high‐efficiency flexible devices and modules. Challenges in throughput, stability, and sustainable processing are outlined, guiding the translation of
Farshad Jafarzadeh   +5 more
wiley   +1 more source

Diffusion–Model–Driven Discovery of Ferroelectrics for Photocurrent Applications

open access: yesAdvanced Science, EarlyView.
We developed a diffusion model–based generative AI and high‐throughput screening framework that accelerates the discovery of photovoltaic ferroelectrics. By coupling AI driven crystal generation with machine learning and DFT screening, we identified Ca3P2 and LiCdP as new ferroelectric materials exhibiting strong polarization, feasible switching ...
Byung Chul Yeo   +3 more
wiley   +1 more source

Unveiling a Bulk WTaV Multicomponent Alloy With Superior Thermal Properties and Manufacturability

open access: yesAdvanced Science, EarlyView.
ABSTRACT Many tungsten (W)‐based medium and high entropy alloys (HEA) demonstrate superior microstructural stability and enhanced mechanical properties as compared to pure W, effectively rendering them as viable candidate materials for extreme environments such as nuclear fusion, aerospace applications, and so on.
Ishtiaque K. Robin   +11 more
wiley   +1 more source

The COLIEE 2025 Competition on Legal Information Extraction and Entailment: Overview, Discussion, and Dataset Expansion. [PDF]

open access: yesRev Socionetwork Strateg
Goebel R   +7 more
europepmc   +1 more source

Physics‐Embedded Neural Network: A Novel Approach to Design Polymeric Materials

open access: yesAdvanced Science, EarlyView.
Traditional black‐box models for polymer mechanics rely solely on data and lack physical interpretability. This work presents a physics‐embedded neural network (PENN) that integrates constitutive equations into machine learning. The approach ensures reliable stress predictions, provides interpretable parameters, and enables performance‐driven, inverse ...
Siqi Zhan   +8 more
wiley   +1 more source

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