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
Development and validation of a sustainable spectrofluorimetric method for simultaneous quantification of amlodipine and aspirin using genetic algorithm-enhanced partial least squares regression. [PDF]
Alqahtani T, Alqahtani A, Almrasy AA.
europepmc +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
Evaluating permutation-based inference for partial least squares analysis of neuroimaging data. [PDF]
Danyluik M +8 more
europepmc +1 more source
To enhance through‐thickness conductivity without sacrificing impregnation, large spherical graphite particles are intentionally employed in a low‐viscosity resin. Unlike finer conductive fillers, these particles remain outside the fiber bundles and accumulate in resin‐rich interlaminar regions during molding.
Keito Hosoe +6 more
wiley +1 more source
Disentangling the Impacts of PAHs, Microplastics, and Sediment Resuspension on Algal Physiology: A Partial Least Squares Structural Equation Modeling Approach. [PDF]
Lo HS +5 more
europepmc +1 more source
Despite benefits to storage stability and handleability of aluminum scrap, octadecyl phosphonic acid (ODPA) SAMs reduce the tensile strength of wires produced using friction‐induced recycling. Etching and methyl diphosphonic acid (MDPA) coatings, however, have little effect.
Timothy D. Goller +3 more
wiley +1 more source
Implementing partial least squares and machine learning regressive models for prediction of drug release in targeted drug delivery application. [PDF]
Yadav A +8 more
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
Block selection in multiblock partial least squares for modeling genotype-phenotype relations in Saccharomyces. [PDF]
Tahir M +4 more
europepmc +1 more source

