Results 151 to 160 of about 1,597,633 (258)
Uncertainty Quantification in Inverse Scattering Problems. [PDF]
Abugattas C, Carpio A, Cebrián E.
europepmc +1 more source
Gallium microalloying redirects interfacial reactions in low‐temperature Bi–Sn solders from Cu–Sn toward Cu–Ga intermetallic formation. The resulting Cu–Ga layer suppresses intermetallic growth during thermal aging, alters fracture pathways, and improves interfacial stability.
Iva Králová +6 more
wiley +1 more source
Uncertainty quantification of U-Net based segmentation tool using conformal prediction. [PDF]
Borden BJ +4 more
europepmc +1 more source
Morphology, Transport, and Dynamics of Protein Adsorption in Open‐Cell Metal Foam
Stainless steel (SS) open‐cell foams are shown to adsorb more protein per unit area than previously reported 316L SS and chromium oxide surfaces under static and flow conditions. An integrated approach combining 3D pore imaging, flow simulation, and protein adsorption experiments characterizes the foam’s performance.
Chinmaya Prerana Inguva +2 more
wiley +1 more source
Uncertainty Quantification for <i>In Silico</i> Chemistry. [PDF]
Frömbgen T +5 more
europepmc +1 more source
A Novel Approach to Estimate the Transition Temperature via Dynamic Nanoindentation
A new dynamic nanoindentation‐based method was developed that uses the stiffness ratio as an indicator of the elastic–plastic deformation contributions at different temperatures. The approach successfully identified transition temperatures in ferritic steel and distinguished them from continuously ductile austenitic steel.
Stefan Zeiler +4 more
wiley +1 more source
Correction: Gated recurrent unit model for forecasting greenhouse gas concentrations with uncertainty quantification. [PDF]
Kimei EH +3 more
europepmc +1 more source
This perspective reframes additive manufacturing for electrical machines as a qualification‐limited materials and architecture design problem. It links process–structure–property–performance relationships to magnetic, conducting, dielectric, and thermal property windows, highlighting where AM can enable segmented magnetic circuits, permanent magnet ...
Dénes Fodor, Loránd Szabó
wiley +1 more source
Decoding Uncertainty Quantification for Oncology-An Illustration Using Radiomics. [PDF]
van Daalen F +8 more
europepmc +1 more source
Supporting AI Readiness Through Digital Workflows in Materials Science
Digitalization drives innovation in materials science by connecting data silos and turning heterogeneous processes into reusable research pipelines. Across 13 MaterialDigital projects, digital workflows reveal complementary pathways toward AI‐ready materials research, founded on structured data, persistent artifacts, executable orchestration, and ...
Marian Bruns +67 more
wiley +1 more source

