Results 211 to 220 of about 1,295,192 (344)

Data‐Driven Design and Fabrication of Heat‐Resistant, Ultrastrong, Lightweight Aluminum‐Based Entropy Alloy by Additive Manufacturing

Advanced Science, EarlyView.
A data‐driven strategy integrating quantum machine learning (QML) and high‐throughput computing overcomes hot‐cracking limitation to design a novel lightweight aluminum‐based entropy alloy for additive manufacturing. The fabrication transforms brittle intermetallics into deformable hierarchical nanostructures, yielding ultrastrong strength (>1 GPa) and
Enmao Wang, Chao Ding, Danyang Zhou, Chenjin Xu, Swee Leong Sing, Jianzhong Jiang, Huibin Wu   +6 more
wiley   +1 more source

Additive and Partially Dominant Effects from Genomic Variation Contribute to Rice Heterosis

Advanced Science, EarlyView.
Additive and partially dominant effects, namely at mid‐parent levels or values between mid‐parent and parental levels, respectively, are the predominant inheritance patterns of heterosis‐associated molecules. These two genetic effects contribute to heterosis of agronomic traits in both rice and maize, as well as biomass heterosis in Arabidopsis ...
Zhiwu Dan, Yunping Chen, Wei Zhou, Yanghong Xu, Junran Huang, Yi Chen, Jizhou Meng, Guoxin Yao, Wenchao Huang   +8 more
wiley   +1 more source

"Radiological Grading" for Preoperative Assessment of Central Cartilaginous Tumors. [PDF]

Cancers (Basel)
Miwa S, Hayashi K, Higuchi T, Yonezawa H, Morinaga S, Asano Y, Demura S.   +6 more
europepmc   +1 more source

Electrochemical Nitrate Reduction Reaction to Ammonia at Industrial‐Level Current Densities

Advanced Science, EarlyView.
This review starts from the mechanism and theoretical basis of electrochemical nitrate reduction reaction (NO3−RR), and systematically summarizes and discusses the design strategies of industrial‐level current density catalysts. In addition, the progress of industrial‐level NO3−RR‐based electrolyzers, including flow reactor and membrane electrode ...
Zhijie Cui, Honghai Wang, Chunli Li, Wenchao Peng, Jiapeng Liu   +4 more
wiley   +1 more source

Machine learning prediction of bacterial optimal growth temperature from protein domain signatures reveals thermoadaptation mechanisms. [PDF]

BMC Genomics
Liu H, Zhu G, Chen L, Ye H, Zhang Y, Han G.   +5 more
europepmc   +1 more source

Redefining the Health Risk of Battery Materials Through a Biologically Transformed Metal Mixture

Advanced Science, EarlyView.
Inhaled NCM particles undergo lysosomal degradation, releasing complex ion mixtures that induce systemic impact. The impact is determined by a critical balance between antagonistic Ni‐Co interactions and synergistic Mn effects. To capture these complexities in risk assessment, we develop an IAI model, ensuring a more accurate quantitative risk ...
Ze Zhang, Gan Miao, Xueyu Zhang, Zhao Shu, Dawei Lu, Yujie Song, Shanfa Yu, Qian Liu, Yang Song, Rong Zhang, Xiaoting Jin, Yuxin Zheng   +11 more
wiley   +1 more source

ML Workflows for Screening Degradation‐Relevant Properties of Forever Chemicals

Advanced Science, EarlyView.
The environmental persistence of per‐ and polyfluoroalkyl substances (PFAS) necessitates efficient remediation strategies. This study presents physics‐informed machine learning workflows that accurately predict critical degradation properties, including bond dissociation energies and polarizability.
Pranoy Ray, Andrew R. Castillo, Manoj Kolel‐Veetil, Surya R. Kalidindi   +3 more
wiley   +1 more source

A meta-learning ensemble framework for robust and interpretable prediction of emergency medical services demand. [PDF]

Sci Rep
Garg T, Toshniwal D, Parida M.
europepmc   +1 more source

Customizing Tactile Sensors via Machine Learning‐Driven Inverse Design

Advanced Science, EarlyView.
ABSTRACT Replicating the sophisticated sense of touch in artificial systems requires tactile sensors with precisely tailored properties. However, manually navigating the complex microstructure‐property relationship results in inefficient and suboptimal designs.
Baocheng Wang, Depeng Kong, Zhiao He, Jikai Liang, Yuyao Lu, Zikang Deng, Honghe Li, Mengke Wang, M. Jamal Deen, Zhiqiu Ye, Shuyao Zhou, Huayong Yang, Honghao Lyu, Jun Chen, Kaichen Xu, Geng Yang   +15 more
wiley   +1 more source

Harnessing machine learning to predict antibiotic susceptibility in Pseudomonas aeruginosa biofilms. [PDF]

NPJ Biofilms Microbiomes
Vergauwe F, De Waele G, Sass A, Highmore C, Hanrahan N, Cook Y, Lichtenberg M, Cnockaert M, Vandamme P, Mahajan S, Webb JS, Van Nieuwerburgh F, Bjarnsholt T, Waegeman W, Coenye T.   +14 more
europepmc   +1 more source