Results 71 to 80 of about 434,301 (280)
This review highlights the role of self‐assembled monolayers (SAMs) in perovskite solar cells, covering molecular engineering, multifunctional interface regulation, machine learning (ML) accelerated discovery, advanced device architectures, and pathways toward scalable fabrication and commercialization for high‐efficiency and stable single‐junction and
Asmat Ullah, Ying Luo, Stefaan De Wolf
wiley +1 more source
Integration of Bayesian Methods in Machine Learning: A Theoretical and Empirical Review
Abstrak Studi ini merupakan sebuah tinjauan literatur sistematis yang mendalami integrasi metode Bayesian dalam pembelajaran mesin. Metode Bayesian telah terbukti memberikan keuntungan signifikan dalam menangani ketidakpastian dan variabilitas data ...
Syaharuddin Syaharuddin
doaj +1 more source
Superionic Amorphous Li2ZrCl6 and Li2HfCl6
Amorphous Li2HfCl6 and L2ZrCl6 are shown to be promising solid‐state electrolytes with predicted ionic conductivities >20 mS·cm−1. Molecular dynamics simulations with machine‐learning force fields reveal that anion vibrations and flexible MCl6 octahedra soften the Li coordination cage and enhance mobility. Correlation between Li‐ion diffusivity and the
Shukai Yao, De‐en Jiang
wiley +1 more source
A parsimonious model of subjective life expectancy [PDF]
This paper develops a theoretical model for the formation of subjective beliefs on individual survival expectations. Data from the Health and Retirement Study (HRS) indicate that, on average, young respondents underestimate their true survival ...
Alexander Ludwig, Alexander Zimper
core +4 more sources
An active learning framework, grounded in independently generated in‐house experimental data, enables reliable discovery of high‐performance interfacial materials for perovskite solar cells. Iterative model refinement autonomously converges toward structurally robust quaternary ammonium architectures, establishing a new design principle for interfacial
Jongbeom Kim +8 more
wiley +1 more source
Learning Bayesian Networks for Student Modeling [PDF]
In the last decade, there has been a growing interest in using Bayesian Networks (BN) in the student modelling problem. This increased interest is probably due to the fact that BNs provide a sound methodology for this difficult task. In order to develop a Bayesian student model, it is necessary to define the structure (nodes and links) and the ...
Millán-Valldeperas, Eva +3 more
openaire +2 more sources
The perspective presents an integrated view of neuromorphic technologies, from device physics to real‐time applicability, while highlighting the necessity of full‐stack co‐optimization. By outlining practical hardware‐level strategies to exploit device behavior and mitigate non‐idealities, it shows pathways for building efficient, scalable, and ...
Kapil Bhardwaj +8 more
wiley +1 more source
Nanomaterial Integration at Liquid–Liquid Interfaces for Green Catalysis
Functional nanomaterials assembled at liquid–liquid interfaces create dual‐role platforms serving as emulsion stabilizers and catalytic sites, offering enhanced reaction kinetics with improved catalyst recovery and recyclability. This review examines design strategies, structure‐performance relationships, and industrial implementation prospects of ...
Bokgi Seo +6 more
wiley +1 more source
Magnetic Textiles: A Review of Materials, Fabrication, Properties, and Applications
Magnetic textiles (M‐textiles) are emerging as a programmable materials platform that merges magnetic matter with hierarchical textile structures. This article consolidates magnetic material classes, textile architectures, and fabrication and magnetization strategies, revealing structure–property–function relationships that govern magneto‐mechanical ...
Li Ke +3 more
wiley +1 more source
This study shows that a lightweight blackbox neural network provides a practical, cost‐effective solution for bidirectional process prediction in laser‐induced graphene (LIG) fabrication. Achieving high predictive performance with minimal overhead, the approach democratizes machine learning (ML) for resource‐limited environments.
Maxim Polomoshnov +3 more
wiley +1 more source

