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
FastNano Liquid: An Automated Platform for Small‐Angle X‐ray Scattering‐Based Materials Discovery
We present FastNano Liquid, an automated small‐ and wide‐angle X‐ray scattering platform for the combined synthesis and characterization of (nano)materials. The platform is coupled to varied reactor workflows for both in situ studies of reaction kinetics and ex situ screening of synthesis conditions to support machine learning‐guided exploration ...
Pierre‐Baptiste Flandrin +16 more
wiley +1 more source
Cu and combined Cu–P microalloying refine the microstructure and enhance the nanoindentation‐derived fracture resistance of CoNiAlSi ferromagnetic shape memory alloys without suppressing the martensitic transformation. Comparative SEM, DSC, and nanoindentation results reveal that the CuP‐containing alloy provides the most balanced response, achieving ...
Mehmet Demir
wiley +1 more source
Statistics of the Compression Ratio of a Variable-to-Variable Code: Exact Moments and Asymptotic Behavior. [PDF]
Merhav N.
europepmc +1 more source
Rotary 3D Printing With Integrated Electroplating
A rotary material extrusion platform integrates localized copper electroplating with printing and encapsulation to fabricate cylindrical polymer–metal structures containing fully embedded, low‐resistance conductive pathways that enable internal Joule heating and thermally activated shape‐memory responses.
Antonio Zagaria +5 more
wiley +1 more source
An Automated Tool for Predicting Ion-Molecule Reaction Rates in CI-MS: Application to PCDDs and PCDFs. [PDF]
Bhatia M.
europepmc +1 more source
A Multi‐Scale Machine Learning Framework for the Inverse Design of High Entropy Alloys
High‐entropy alloys offer vast potential for various applications, including electrocatalysis; however, their compositional complexity challenges conventional screening. We introduce an inverse‐design framework combining two neural networks to determine optimal compositions and reconstruct nanoparticle geometry from targeted properties and conventional
Mikael Takoutsin +14 more
wiley +1 more source
Laser‐Induced Graphene from Waste Almond Shells
Almond shells, an abundant agricultural by‐product, are repurposed to create a fully bioderived almond shell/chitosan composite (ASC) degradable in soil. ASC is converted into laser‐induced graphene (LIG) by laser scribing and proposed as a substrate for transient electronics.
Yulia Steksova +9 more
wiley +1 more source
Equidispersion and moment conditions for count panel data model [PDF]
This paper proposes some new moment conditions under the assumption of the equidispersion in count panel data model. These are obtained by using the association between variances and covariances in the disturbance. Some Monte Carlo experiments configured
Yoshitsugu Kitazawa
core
Magnetically frustrated calcium-substituted SrMn<sub>2</sub>Fe<sub>4</sub>O<sub>11</sub> R-type hexaferrite nanoparticles for biomedical applications. [PDF]
Idrees M +9 more
europepmc +1 more source

