Results 221 to 230 of about 476,790 (313)

A Simplified Laminar Flow Model for the Pultrusion of Glass Fiber/Polyethylene Terephthalate Commingled Yarns

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, Nadège Bouchonneau, Christian Jochum, Donald Radford   +3 more
wiley   +1 more source

A deep representation learning model to predict response to vagus nerve stimulation. [PDF]

Nat Commun
Suresh H, Mithani K, Li V, Latypov TH, Warsi NM, Wong SM, Erdman L, Kang J, Germann J, Gouveia FV, Coleman SC, Berger A, Chau V, Weiss S, Gorodetsky C, Donner E, Weil AG, Tailor J, Abel TJ, Remick M, Akwayena E, Schrader D, Bollo RJ, Smyth MD, Aum D, Lew SM, Wang S, Niazi TN, Fallah A, Raskin JS, Weiner HL, Gadgil N, Albert GW, Hadjinicolaou A, Major P, Niazi F, Theaud G, Obaid S, Widjaja E, Ertl-Wagner B, Vidarsson L, Taylor MJ, Boutet A, Rutka JT, LoPresti MA, Jain P, Ibrahim GM.   +46 more
europepmc   +1 more source

Additive Manufacturing of Continuous Fibre Reinforced Composites: Process, Characterisation, Modelling, and Sustainability

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

CLOUD: A Scalable and Physics-Informed Foundation Model for Crystal Representation Learning. [PDF]

Nat Commun
Xu C, Zhu S, Viswanathan V.
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, Moritz Blum, Luana Caron, Alisa Chirkova, Philipp Cimiano, Basil Ell, Inga Ennen, Michael Feige, Maik Gaerner, Thomas Hilbig, Andreas Hütten, Günter Reiss, Tapas Samanta, Sonja Schöning, Christian Schröder, Lennart Schwan, Chris Taake, Martin Wortmann   +17 more
wiley   +1 more source

S3RL: Enhancing Spatial Single-Cell Transcriptomics With Separable Representation Learning. [PDF]

Adv Sci (Weinh)
Fu L, Wang P, Xu G, Lu J, Peng Q, Wu D, Sun H.   +6 more
europepmc   +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, Santiago Benito, Özge Özgün, Sebastian Weber, Markus Stricker   +4 more
wiley   +1 more source

A systematic review of molecular representation learning foundation models. [PDF]

Brief Bioinform
Song B, Zhang J, Liu Y, Liu Y, Jiang J, Yuan S, Zhen X, Liu Y.   +7 more
europepmc   +1 more source

Symbolic Regression and Multi‐Objective Optimization of the Flory–Huggins Interaction Parameter for Hydrogels

Advanced Engineering Materials, EarlyView.
We develop a data‐driven method to derive the mathematical expressions of the Flory–Huggins interaction parameter χ for the swelling behavior of temperature–responsive hydrogels. Starting from initial assumptions of χ, our workflow combines Bayesian optimization, Flory–Rehner theory, and symbolic regression to generate candidate χ expressions.
Yawen Wang, Adrian Ehrenhofer, Thomas Wallmersperger   +2 more
wiley   +1 more source

An equivariant pretrained transformer for unified 3D molecular representation learning. [PDF]

Nat Commun
Jiao R, Kong X, Zhang L, Yu Z, Ren F, Tan W, Huang W, Liu Y.   +7 more
europepmc   +1 more source