Results 81 to 90 of about 851,309 (264)

Bridging Theory and Experiment: Machine Learning Potential‐Driven Insights into pH‐Dependent CO₂ Reduction on Sn‐Based Catalysts

Advanced Functional Materials, EarlyView.
Machine learning potential (MLP) enables large‐scale molecular dynamics (MD) simulations, uncovering dynamic surface reconstruction of SnO₂ and SnS₂ under CO₂ reduction reaction condition. The negative dipole moments upon *OCHO adsorption are the primary factors driving the leftward shift of the volcano plot.
Yuhang Wang, Zelin Wu, Yingfang Jiang, Di Zhang, Qiang Wang, Congwei Wang, Huihui Li, Xue Jia, Jun Fan, Hao Li   +9 more
wiley   +1 more source

Publisher's Note: Machine learning Z2 quantum spin liquids with quasiparticle statistics [Phys. Rev. B 96 , 245119 (2017)] [PDF]

, 2018
Yi Zhang, Roger G. Melko, Eun-Ah Kim
openalex   +1 more source

Battery‐Free, Wireless Multi‐Sensing Platform for Comprehensive Management of Pressure Injury and Hygiene

Advanced Functional Materials, EarlyView.
A battery‐free, wireless device for real‐time monitoring of pressure injury and hygiene integrates pressure (≈10 kPa), temperature (≈40 °C), and NH3 gas sensing with antibacterial functionality. Enabled by near‐field communication, it ensures simultaneous, interference‐free mechanical and chemical monitoring, offering a practical solution for pressure ...
Myungwoo Choi, Sunwoo Lee, Sang Won Kim, Ji Yeon Lee, Younghan Kim, Jewook Kim, Gye Hyeon Lee, Saehan Choi, Seonggwang Yoo, Hak‐Young Ahn, Taehoon Kim, Je‐Sang Lee, Weon Gi Min, Inkyu Park, Young‐Seok Shim, Yoon Sung Nam, Seokwoo Jeon, Jeong‐O Lee, Yong Suk Oh, Donghwi Cho   +19 more
wiley   +1 more source

Quantum Dots and Perovskites‐Based Physically Unclonable Functions for Binary and Ternary Keys via Optical‐to‐Electrical Conversion

Advanced Functional Materials, EarlyView.
This study investigates optoelectronic PUFs that improve on traditional optical and electrical PUFs. The absorber materials are randomly coated through spray coating, ligand exchange, and dynamic spin coating. Incident light generates wavelength‐dependent binary multikey and enhances security ternary keys, approaching near‐ideal inter‐ and intra ...
Hanseok Seo, Taesung Park, Awais Ali, Byung Ku Jung, Young Kyun Choi, Junhyeok Park, Soong Ju Oh   +6 more
wiley   +1 more source

Use of machine learning to estimate statistics of the posterior distribution in probabilistic inverse problems - an application to airborne EM data.

, 2021
Thomas Mejer Hansen, Christopher C. Finlay   +1 more
openalex   +2 more sources

Evaluation metrics and statistical tests for machine learning

Scientific Reports
AbstractResearch on different machine learning (ML) has become incredibly popular during the past few decades. However, for some researchers not familiar with statistics, it might be difficult to understand how to evaluate the performance of ML models and compare them with each other.
Oona Rainio, Jarmo Teuho, Riku Klén
openaire   +3 more sources

Printing Nacre‐Mimetic MXene‐Based E‐Textile Devices for Sensing and Breathing‐Pattern Recognition Using Machine Learning

Advanced Functional Materials, EarlyView.
This study presents a Ti3C2Tx MXene/WPU nacre‐mimetic nanomaterial as a printable ink for direct‐write printing onto textiles‐based sensors. The resulting wearable device demonstrates high sensitivity, biocompatibility, and mechanical strength. Furthermore, NFC‐enabled humidity sensor produces time‐series data, which informs a machine learning ...
Lulu Xu, Wenqing Chen, Qian Li, Rohit Gupta, Biswajoy Bagchi, Laurence B. Lovat, Manish K. Tiwari   +6 more
wiley   +1 more source

Artificial Intelligence‐Driven Development in Rechargeable Battery Materials: Progress, Challenges, and Future Perspectives

Advanced Functional Materials, EarlyView.
AI is transforming the research paradigm of battery materials and reshaping the entire landscape of battery technology. This comprehensive review summarizes the cutting‐edge applications of AI in the advancement of battery materials, underscores the critical challenges faced in harnessing the full potential of AI, and proposes strategic guidance for ...
Qingyun Hu, Junyuan Lu, Jian Hui, Ziyuan Rao, Yang Ren, Hong Wang   +5 more
wiley   +1 more source

Experimentally Validated Design Principles of D‐Block Transition Metal Single‐Atom Non‐Dissociative Chemisorption Solid‐State Hydrogen Storage Materials

Advanced Functional Materials, EarlyView.
A novel descriptor and a bottom‐up design principle are established to enable the rational design of hydrogen storage materials based on d‐block transition metal single‐atom COFs. By modulating H₂ adsorption through d‐orbital tuning, this approach achieves both high storage capacity and fast kinetics, while revealing a volcano‐type relationship between
Qiuyan Yue, Chao Li, Yong Gao, Zhenglong Li, Wen‐Gang Cui, Xinqiang Wang, Guoquan Na, Xiaowei Wang, Yiyang Wan, Mingchang Zhang, Yanxia Liu, Fulai Qi, Chenchen Li, Xu Xue, Jian Miao, Jing Zhang, Xiao Han, Pan Wang, Chang Guo, Xiacui Liu, Mingxia Gao, Wenping Sun, Jian Chen, Zhenhai Xia, Hongge Pan   +24 more
wiley   +1 more source

Power quality daily predictions in smart off-grids using differential, deep and statistics machine learning models processing NWP-data

, 2023
Ladislav Zjavka
openalex   +1 more source