Results 201 to 210 of about 1,214,867 (285)

Gallium Microalloying in Bi–Sn Solders: Interfacial Phase Formation, Wettability, and Long‐Term Shear Reliability Under Isothermal Aging

open access: yesAdvanced Engineering Materials, EarlyView.
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

X-CART: a multimodal real-world data pipeline for explainable AI-driven patient navigation in radiation oncology. [PDF]

open access: yesESMO Real World Data Digit Oncol
Zink JA   +11 more
europepmc   +1 more source

Toward Full Interoperability in Materials Science: Integrating Workflows With Knowledge Graphs

open access: yesAdvanced Engineering Materials, EarlyView.
The connection of conceptual workflow design, portable execution, and ontology‐based semantics leading to provenance‐rich knowledge graphs are main contributors to interoperability in materials science and a prerequisite to AI‐assisted orchestration and for interoperable Materials Acceleration Platforms.
Jan Janssen   +14 more
wiley   +1 more source

Supporting AI Readiness Through Digital Workflows in Materials Science

open access: yesAdvanced Engineering Materials, EarlyView.
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

All‐in‐One Analog AI Hardware: On‐Chip Training and Inference with Conductive‐Metal‐Oxide/HfOx ReRAM Devices

open access: yesAdvanced Functional Materials, EarlyView.
An all‐in‐one analog AI accelerator is presented, enabling on‐chip training, weight retention, and long‐term inference acceleration. It leverages a BEOL‐integrated CMO/HfOx ReRAM array with low‐voltage operation (<1.5 V), multi‐bit capability over 32 states, low programming noise (10 nS), and near‐ideal weight transfer.
Donato Francesco Falcone   +11 more
wiley   +1 more source

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