Results 201 to 210 of about 3,920,725 (334)

An Integrated NLP‐ML Framework for Property Prediction and Design of Steels

Advanced Science, EarlyView.
This study presents a data‐driven framework that uses language‐processing techniques to interpret steel processing descriptions and machine‐learning models to predict mechanical properties. By organising complex process histories into meaningful groups and enabling rapid property forecasts, the work supports faster, more informed steel design through ...
Kiran Devraju, Adithya Umanath Rai, Jose Thomson, Marzie Ghorbani, Shujing Zhao, Nick Birbilis   +5 more
wiley   +1 more source

Moment-Equivalent Adhesion Statistics Inferred From Particle Resuspension Kinetics. [PDF]

Small Sci
Almog R, Klausner Z, Berkovich R.
europepmc   +1 more source

The Importance of Metal‐Organic Framework Linker Atoms for CO2 Reduction: A DFT Study

Advanced Science, EarlyView.
Using DFT, we examine the role of linker atoms in CO2 reduction on copper‐based metal organic frameworks (Cu MOFs). Our calculations reveal that linker atoms may serve as both CO2 and H‐shuttling sites and suggest linker electrostatics as a descriptor for linker activity. ABSTRACT Although the metal within the secondary building unit of a metal‐organic
Ugochukwu Nwosu, Samira Siahrostami
wiley   +1 more source

Inverse-Intensity-Weighted Generalized Estimating Equations With Irregularly Measured Longitudinal Data and Informative Dropout. [PDF]

Stat Med
Stefan G, Pullenayegum E.
europepmc   +1 more source

Physics‐Embedded Neural Network: A Novel Approach to Design Polymeric Materials

Advanced Science, EarlyView.
Traditional black‐box models for polymer mechanics rely solely on data and lack physical interpretability. This work presents a physics‐embedded neural network (PENN) that integrates constitutive equations into machine learning. The approach ensures reliable stress predictions, provides interpretable parameters, and enables performance‐driven, inverse ...
Siqi Zhan, Hengheng Zhao, Haotian Wang, Zhanjie Liu, Qian Li, Weifeng Zhang, Qingsong Zhao, Liqun Zhang, Jun Liu   +8 more
wiley   +1 more source

Early acquisition efficiency in visual-to-auditory sensory substitution: the role of structured learning. [PDF]

Front Psychol
Moon KD, Park YK, Kim MS, Jeong CY.
europepmc   +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 Cautionary Note for Plasmode Simulation Studies in the Setting of Causal Inference. [PDF]

Stat Med
Shaw PA, Gruber S, Williamson BD, Desai R, Shortreed SM, Krakauer C, Nelson JC, van der Laan MJ.   +7 more
europepmc   +1 more source

An Investigation of RSN Frequency Spectra Using Ultra-Fast Generalized Inverse Imaging. [PDF]

Front Hum Neurosci, 2013
Boyacioglu R, Beckmann CF, Barth M.
europepmc   +1 more source

Sustainable Materials Design With Multi‐Modal Artificial Intelligence

Advanced Science, EarlyView.
Critical mineral scarcity, high embodied carbon, and persistent pollution from materials processing intensify the need for sustainable materials design. This review frames the problem as multi‐objective optimization under heterogeneous, high‐dimensional evidence and highlights multi‐modal AI as an enabling pathway.
Tianyi Xu, Tianshuo Wei, Yan Ge, Bo Peng, Yue Li, Maolin Wang, Peng Wen, Chao Yang, Ye Wei   +8 more
wiley   +1 more source