Machine Learning Potential for Identifying and Forecasting Complex Environmental Drivers of <i>Vibrio vulnificus</i> Infections in the United States. [PDF]
Environ Health PerspectCampbell AM +4 more
europepmc +1 more source
A Knowledge‐Based Approach for Understanding and Managing Additive Manufacturing Data
Advanced Engineering Materials, EarlyView.Additive manufacturing processes generate a large amount of data. Effectively managing, understanding, and retrieving information from this data remains a major challenge. Therefore, we propose an ontology‐based approach to integrate heterogeneous data, enable semantic queries, and support decision‐making.
Mina Abd Nikooie Pour +5 more
wiley +1 more source
Unraveling individual differences in learning potential: A dynamic framework for the case of reading development. [PDF]
Dev Cogn NeurosciBonte M, Brem S.
europepmc +1 more source
Advanced Engineering Materials, EarlyView.A simplified thermoplastic pultrusion model is developed to predict thermal fields in glass fiber/polyethylene terephthalate (GF/PET) composites with reduced computational cost. By combining effective material homogenization, validation against literature data, and Gaussian‐process‐based optimization, the study reveals how heating limits, pulling speed,
Elder Soares +3 more
wiley +1 more source
Exploring the frontiers of condensed-phase chemistry with a general reactive machine learning potential. [PDF]
Nat ChemZhang S +10 more
europepmc +1 more source
Advanced Engineering Materials, EarlyView.Additive manufacturing provides precise control over the placement of continuous fibres within polymer matrices, enabling customised mechanical performance in composite components. This article explores processing strategies, mechanical testing, and modelling approaches for additive manufactured continuous fibre‐reinforced composites.
Cherian Thomas, Amir Hosein Sakhaei
wiley +1 more source
Effect of Interlayer Bonding on Superlubric Sliding of Graphene Contacts: A Machine-Learning Potential Study. [PDF]
ACS NanoYing P, Natan A, Hod O, Urbakh M.
europepmc +1 more source
Fostering Innovation: Streamlining Magnetocaloric Materials Research by Digitalization
Advanced Engineering Materials, EarlyView.Magnetocaloric cooling (MCE) is an environmentally friendly refrigeration method with great potential. Optimizing MCE materials involves the preparation and screening of large quantities of samples, which in turn generates a large amount of data. A digitalization approach is presented that uses ontologies, knowledge graphs, and digital workflows to ...
Simon Bekemeier +17 more
wiley +1 more source
Multimodal Data‐Driven Microstructure Characterization
Advanced Engineering Materials, EarlyView.A self‐consistent autonomous workflow for EBSP‐based microstructure segmentation by integrating PCA, GMM clustering, and cNMF with information‐theoretic parameter selection, requiring no user input. An optimal ROI size related to characteristic grain size is identified.
Qi Zhang +4 more
wiley +1 more source
Parameter-Free and Electron Counting Satisfied Material Representation for Machine Learning Potential Energy and Force Fields. [PDF]
J Phys Chem LettXi B +6 more
europepmc +1 more source