The MaterialDigital initiative drives the digital transformation of material science by promoting findable, accessible, interoperable, and reusable principles and enhancing data interoperability. This article explores the role of scientific workflows, highlights challenges in their adoption, and introduces the Workflow Store as a key tool for sharing ...
Simon Bekemeier+37 more
wiley +1 more source
Effect of Surface Treatment on Physical and Tensile Properties of Borassus Fruit Fibers. [PDF]
Boimau K+5 more
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In this study, the mechanical response of Y‐shaped core sandwich beams under compressive loading is investigated, using deep feed‐forward neural networks (DFNNs) for predictive modeling. The DFNN model accurately captures stress–strain behavior, influenced by design parameters and loading rates.
Ali Khalvandi+4 more
wiley +1 more source
Mechanical constitutive model of stand off damping composites layered rubber core under wide strain rates. [PDF]
Zhao Z+7 more
europepmc +1 more source
This study explores the energy conversion in powder bed fusion of polymers using laser beam for polyamide 12 and polypropylene powders. It combines material and process data, using dimensionless parameters and numerical models, to enable the prediction of suitable printing parameters.
Christian Schlör+9 more
wiley +1 more source
Smallholder farmers can achieve more sustainable wheat production through Consolidating Land for Uniform Practice. [PDF]
Ren T+10 more
europepmc +1 more source
Study on the Microstructure and Corrosion Behavior of Dissimilar Aluminum Alloy Welded Joints Formed Using Laser Welding. [PDF]
Zhang S+6 more
europepmc +1 more source
Impact of Mechanical and Manual Peeling on the Volatile Profile of White Pepper (Piper nigrum L.). [PDF]
Zhang Y+6 more
europepmc +1 more source
Study of the Effects on the Strengthening Mechanism and Wear Behavior of Wear-Resistant Steel of Temperature Controlling in Heat Treatment. [PDF]
Zhu X+7 more
europepmc +1 more source
A fault diagnosis method for rolling bearings in open-set domain adaptation with adversarial learning. [PDF]
Lei T, Pan F, Hu J, He X, Li B.
europepmc +1 more source