Results 31 to 40 of about 835,490 (206)

Additive Gaussian Process Regression for Predictive Design of High‐Performance, Printable Silicones

open access: yesAdvanced Engineering Materials, EarlyView.
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

Evaluating Energy Absorption Performance of Filled Lattice Structures

open access: yesAdvanced Engineering Materials, EarlyView.
Maximum stress must be considered to robustly evaluate energy absorber designs. This approach was applied to compare all types of absorbers in a single Ashby diagram and determine the utility of filling lattice voids with a second material. High‐performance fillers can improve the performance of lattices that are limited by buckling or catastrophic ...
Christian Bonney   +2 more
wiley   +1 more source

Toward Low‐Consumable Anodes: Process Simulation and Prospective Life Cycle Assessment of NiFe2O4‐NiO‐Ni‐Cu vs. Prebaked Anodes for Aluminum Production with use of Molten Salt Electrolysis

open access: yesAdvanced Engineering Materials, EarlyView.
Low‐consumable nickel ferrite‐based anodes for the Hall–Héroult process are compared with conventional prebaked carbon anodes using thermodynamic simulation and prospective life cycle assessment under contrasting future electricity system pathways from 2025 to 2050.
Felipe Alejandro Garcia Paz   +6 more
wiley   +1 more source

Unraveling the Effect of Tramp Elements on Phase Transformations in Steels by Combining CALPHAD Modeling and Experiments

open access: yesAdvanced Engineering Materials, EarlyView.
This study investigates how tramp elements from increased scrap usage influence phase transformations in low‐alloyed steel. Combining dilatometry and microscopy reveal that tramp elements delay transformations, reduce critical cooling rates and increase hardenability.
Lukas Hatzenbichler   +5 more
wiley   +1 more source

Phase Field Failure Modeling: Brittle‐Ductile Dual‐Phase Microstructures under Compressive Loading

open access: yesAdvanced Engineering Materials, EarlyView.
The approach by Amor and the approach by Miehe and Zhang for asymmetric damage behavior in the phase field method for fracture are compared regarding their fitness for microcrack‐based failure modeling. The comparison is performed for the case of a dual‐phase microstructure with a brittle and a ductile constituent.
Jakob Huber, Jan Torgersen, Ewald Werner
wiley   +1 more source

Multimodal Data‐Driven Microstructure Characterization

open access: yesAdvanced Engineering Materials, EarlyView.
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

Self-organization of punishment in structured populations [PDF]

open access: yes, 2012
Cooperation is crucial for the remarkable evolutionary success of the human species. Not surprisingly, some individuals are willing to bare additional costs in order to punish defectors.
Attila Szolnoki   +9 more
core   +3 more sources

A Topology Optimization Framework for the Inverse Design of Nonlinear Mechanical Metamaterials

open access: yesAdvanced Engineering Materials, EarlyView.
This work uses topology optimization to design unit cells for mechanical metamaterials with a prescribed nonlinear stress–strain response. The framework adds contact and postbuckling modeling to synthesize microstructures for three highly nonlinear responses, including pseudoductile behavior, monostable with snap‐through buckling, and bistable ...
Charlie Aveline   +2 more
wiley   +1 more source

Punishment in Pre-Colonial Indigenous Societies in North America [chapter] [PDF]

open access: yes, 1991
This paper was originally presented at the Conference on Punishment of the Jean Bodin Society for the Comparative History of Institutions, Barcelona, Spain, May 1987.
Conn, Stephen
core  

Unleashing the Power of Machine Learning in Nanomedicine Formulation Development

open access: yesAdvanced Functional Materials, EarlyView.
A random forest machine learning model is able to make predictions on nanoparticle attributes of different nanomedicines (i.e. lipid nanoparticles, liposomes, or PLGA nanoparticles) based on microfluidic formulation parameters. Machine learning models are based on a database of nanoparticle formulations, and models are able to generate unique solutions
Thomas L. Moore   +7 more
wiley   +1 more source

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