Results 181 to 190 of about 1,130,914 (300)

A Comprehensive Analysis of Artificial Intelligence, Machine Learning, Deep Learning and Computer Vision in Food Science

Premkumar Borugadda, Hemantha Kumar Kalluri   +1 more
openalex   +1 more source

Accelerated Discovery of High‐Performance PCFC Cathodes: Computational‐Experimental Optimization of Cobalt‐Substituted Ba0.95La0.05FeO3‐δ

Advanced Functional Materials, EarlyView.
An integrated computational–experimental strategy accelerates the discovery of high‐performance PCFC cathodes. Computational screening using machine learning interatomic potentials and targeted experiments identifies optimal cobalt substitution in Ba0.95La0.05FeO3‐δ, reducing area‐specific resistance by 58% at 500 °C.
Abdullah Tahir, Yuhao Wang, Jingwei Li, Yunfeng Tian, Francesco Ciucci   +4 more
wiley   +1 more source

Smartphone image dataset for machine learning-based monitoring and analysis of mango growth stages. [PDF]

Data Brief
Kabir S, Akon MFI, Rashid MRA, Islam M, Jabid T, Islam MM, Ali MS.   +6 more
europepmc   +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

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

Ripen banana dataset: A comprehensive resource for carbide detection and ripening stage analysis to enhance food quality and agricultural efficiency. [PDF]

Data Brief
Alam E, Islam MT, Raka IZ, Ritu OS, Hossain MS, Rahman W, Khan R.   +6 more
europepmc   +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

Advantages of two quantum programming platforms in quantum computing and quantum chemistry. [PDF]

J Cheminform
Wang PH, Wu WY, Lee CY, Hong JC, Tseng YJ.   +4 more
europepmc   +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

Soybeans tempeh image dataset for tempeh maturity detection. [PDF]

Data Brief
Riccosan, Yora S, Karim NA, Wibisana EFS.   +3 more
europepmc   +1 more source