Additive Gaussian Process Regression for Predictive Design of High‐Performance, Printable Silicones
A chemistry‐aware design framework for tuning printable polydimethylsiloxane (PDMS) for vat photopolymerization (VPP) is developed using additive Gaussian process (GP) modeling. Polymer network mechanics informs variable groupings, feasible formulation constraints, and interaction variables.
Roxana Carbonell +3 more
wiley +1 more source
Combinatorial optimization enhanced by shallow quantum circuits with 104 superconducting qubits. [PDF]
Zhu X +33 more
europepmc +1 more source
Time‐Dependent Oxidation and Scale Evolution of a Wrought Co/Ni‐Based Superalloy
This study shows how a new wrought Co/Ni‐based superalloy resists oxidation at 800 ∘$^\circ$C. The oxide scale changes from rough, fast‐growing spinel to a dense, protective chromia–alumina layer. Atom probe analysis reveals tiny refractory‐rich bubbles at the interface that mark the transition to long‐term, diffusion‐controlled protection ...
Cameron Crabb +6 more
wiley +1 more source
Colloquium on Combinatorial Methods in Probability Theory August 1-10,1962
Colloquium on Combinatorial Methods in Probability Theory 1962 Århus
core
Multiclass portfolio optimization via variational quantum Eigensolver with Dicke state ansatz. [PDF]
Scursulim JVS +3 more
europepmc +1 more source
Fostering Innovation: Streamlining Magnetocaloric Materials Research by Digitalization
Magnetocaloric cooling (MCE) is an environmentally friendly refrigeration method with great potential. Optimizing MCE materials involves the preparation and screening of large quantities of samples, which in turn generates a large amount of data. A digitalization approach is presented that uses ontologies, knowledge graphs, and digital workflows to ...
Simon Bekemeier +17 more
wiley +1 more source
Multi-State Probabilistic Computing Using Floating-Body MOSFETs Based on the Potts Model for Solving Complex Combinatorial Optimization Problems. [PDF]
Cheong S +9 more
europepmc +1 more source
Multimodal Data‐Driven Microstructure Characterization
A self‐consistent autonomous workflow for EBSP‐based microstructure segmentation by integrating PCA, GMM clustering, and cNMF with information‐theoretic parameter selection, requiring no user input. An optimal ROI size related to characteristic grain size is identified.
Qi Zhang +4 more
wiley +1 more source
Secure Cooperative Communications in 6G Networks: A Constrained Hierarchical Reinforcement Learning Framework with Hybrid Action Space. [PDF]
Tian X, Wang Z, Ni Y.
europepmc +1 more source

