Mathematics at the International Congress of Philosophy, Paris, 1900 [PDF]
Edgar Odell Lovett
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Recent Advances in Wide‐Bandgap Perovskite Solar Cells
Ubiquitous defects predominately account for photo‐instability and open‐circuit voltage losses in wide‐bandgap perovskite solar cells (WBG PSCs). This review comprehensively presents the underlying impact mechanisms, summarizes the advanced optimization strategies across various functional layers and their interfaces to develop efficient and stable WBG
Jianjun Mei, Feng Yan
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Spatial Reasoning and Its Contribution to Mathematical Performance Across Different Content Domains: Evidence from Chinese Students. [PDF]
Xu T, Sun S, Kong Q.
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Implantable devices rely on batteries that demand surgical replacement, posing risks, and financial burdens. Ultrasound energy transfer (US‐ET) offers a revolutionary wireless alternative but struggles with efficiency. The presented dielectric‐ferroelectric‐boosted US‐TENG (US‐TENGDF‐B) is thin, flexible, and biocompatible that provides high‐efficiency
Iman M. Imani+15 more
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Retraction Note: Partial differential equations of entropy analysis on ternary hybridity nanofluid flow model via rotating disk with hall current and electromagnetic radiative influences. [PDF]
Al Oweidi KF+6 more
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SOME APPLICATIONS OF MATHEMATICS TO BREEDING PROBLEMS [PDF]
Rainard B. Robbins
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Laser micropatterning is presented as a promising technology in the search for autonomous dew water harvesting materials. Laser‐grooved metallic surfaces achieve simultaneously high infrared emissivity and superhydrophilicity, which gives them self‐cooling properties under atmospheric radiative deficit and the ability to condense water in an efficient ...
Pablo Pou‐Álvarez+7 more
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The relationship between medical students' interest in learning and their ability to solve mathematical problems: the chain-mediating role of teacher-student relationship and self-efficacy. [PDF]
Yang L, Cui J, Zhang Y.
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Characterization and Inverse Design of Stochastic Mechanical Metamaterials Using Neural Operators
This study presents a DeepONet‐based machine learning framework for designing stochastic mechanical metamaterials with tailored nonlinear mechanical properties. By leveraging sparse but high‐quality experimental data from in situ micro‐mechanical tests, high predictive accuracy and enable efficient inverse design are achieved.
Hanxun Jin+7 more
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