Results 141 to 150 of about 336,714 (315)

Methodology for stiffness prediction in structural timber using cross-validation RMSE analysis

Journal of Building Engineering
Peer ...
Antonio Villasante, Álvaro Fernández-Serrano, Carlos Osuna-Sequera, Eva Hermoso   +3 more
openaire   +2 more sources

High‐Throughput Screening and Interpretable Machine Learning for Rational Design of Bimetallic Catalysts for Methane Activation

Advanced Science, EarlyView.
ABSTRACT Methane's efficient catalytic removal is vital for sustainable development. Bimetallic catalysts, though promising for methane activation, pose a design challenge due to their complex compositional space. This work introduces an integrated framework that combines high‐throughput density functional theory (DFT) and interpretable machine ...
Mingzhang Pan, Tian Zhang, Jiawei Dong, Yubao Xie, Kaifeng Zhong, Wei Guan, Haiqiao Wei, Changcheng Fu, Yaqiong Su   +8 more
wiley   +1 more source

Artificial Intelligence Predictions in Huge Chemical Spaces: Chiroptical Properties of [6]‐helicene Family

Advanced Science, EarlyView.
This study shows that a local, data‐driven AI model can accurately predict diverse optical and chiroptical properties of [6]helicenes using information from close structural neighbours. Combined with genetic algorithms, it enables inverse design for tailored properties, establishing practical structure–property rules for efficient molecular discovery ...
Rafael G. Uceda, Sandra Míguez‐Lago, Carlos M. Cruz, Boris Pérez‐Cañedo, Alfonso Gijón, Luis Álvarez de Cienfuegos, Antonio J. Mota, Delia Miguel, Juan M. Cuerva   +8 more
wiley   +1 more source

Machine Learning for Designing Perovskites and Perovskite‐Inspired Solar Materials: Emerging Opportunities and Challenges

Advanced Science, EarlyView.
This review offers a comprehensive comparison between perovskites and perovskite‐inspired materials (PIMs), focusing on their crystal structures, electronic properties, and chemical compositions. It evaluates the applicability of machine learning (ML) descriptors and models across both material classes.
Yangfan Zhang, Yiming Xia, Ali Shakiba, Hongrui Zhang, Xiaojing Hao, Priyank V. Kumar, Mahesh P. Suryawanshi   +6 more
wiley   +1 more source

Enhancing Electrical Impedance Based Deformation Sensing with Dielectric Current Guide

Advanced Electronic Materials, EarlyView.
This work introduces a dielectric‐based field manipulation strategy for electrical impedance tomography in soft robotics. By using silicone as a passive electric field guide, improved deformation sensing accuracy and reduced interference are achieved without embedding conductive components.
Arsen Abdulali, David Hardman, Yue Xie, Fumiya Iida   +3 more
wiley   +1 more source

A DC Compact Model of an Organic Electrochemical Transistor Based on a Semiconductor Physics and Thermodynamic Approach

Advanced Electronic Materials, EarlyView.
This work presents a physics‐based DC compact model of an Organic Electrochemical Transistor (OECT) that takes into account the faradaic redox reaction in the above threshold regime and incorporates the diffusive current of the subthreshold regime based on semiconductor physics.
Ermias Telahun Teka, Yeohoon Yoon, Laura Teuerle, Tommy Meier, Hans Kleemann, Ghader Darbandy, Benjamin Iniguez   +6 more
wiley   +1 more source

Enhanced High Dimensionality and the Information Processing Capacity in Interfered Spin Wave‐Based Reservoir Computing, Achieved With Eight Detectors

Advanced Electronic Materials, EarlyView.
Physical reservoir computing (PRC) based on spin wave interference has demonstrated high computational performance, yet room for improvement remains. In this study, we fabricated this concept PRC with eight detectors and evaluated the impact of the number of detectors using a chaotic time series prediction task.
Sota Hikasa, Wataru Namiki, Daiki Nishioka, Maki Nishimura, Ryo Iguchi, Kazuya Terabe, Takashi Tsuchiya   +6 more
wiley   +1 more source

Correspondence among the Correlation, RMSE, and Heidke Forecast Verification Measures; Refinement of the Heidke Score [PDF]

, 1992
Anthony G. Barnston
openalex   +1 more source

Integrating Automated Electrochemistry and High‐Throughput Characterization with Machine Learning to Explore Si─Ge─Sn Thin‐Film Lithium Battery Anodes

Advanced Energy Materials, Volume 15, Issue 11, March 18, 2025.
A closed‐loop, data‐driven approach facilitates the exploration of high‐performance Si─Ge─Sn alloys as promising fast‐charging battery anodes. Autonomous electrochemical experimentation using a scanning droplet cell is combined with real‐time optimization to efficiently navigate composition space.
Alexey Sanin, Jackson K. Flowers, Tobias H. Piotrowiak, Frederic Felsen, Leon Merker, Alfred Ludwig, Dominic Bresser, Helge Sören Stein   +7 more
wiley   +1 more source

Root-mean-square error (RMSE) or mean absolute error (MAE): when to use them or not [PDF]

, 2022
Timothy Hodson
openalex   +1 more source