Results 181 to 190 of about 6,121,974 (286)

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

Learning and Development [PDF]

open access: yesDevelopment and Learning in Organizations: An International Journal, 2007
openaire   +1 more source

Photoswitchable Conductive Metal–Organic Frameworks

open access: yesAdvanced Functional Materials, EarlyView.
A conductive material where the conductivity can be modulated remotely by irradiation with light is presented. It is based on films of conductive metal–organic framework type Cu3(HHTP)2 with embedded photochromic molecules such as azobenzene, diarylethene, spiropyran, and hexaarylbiimidazole in the pores.
Yidong Liu   +5 more
wiley   +1 more source

Transforming Education: Case-Based Integrated Learning Development and Implementation - A Mixed Methods Study at a Private Medical College. [PDF]

open access: yesJ Adv Med Educ Prof
Ali R   +9 more
europepmc   +1 more source

Advancing Electronic Application of Coordination Solids: Enhancing Electron Transport and Device Integration via Surface‐Mounted MOFs (SURMOFs)

open access: yesAdvanced Functional Materials, EarlyView.
The layer‐by‐layer (LbL) assembly of coordination solids, enabled by the surface‐mounted metal‐organic framework (SURMOF) platform, is on the cusp of generating the organic counterpart of the epitaxy of inorganics. The programmable and sequential SURMOF protocol, optimized by machine learning (ML), is suited for accessing high‐quality thin films of ...
Zhengtao Xu   +2 more
wiley   +1 more source

Novel application of an automated-machine learning development tool for predicting burn sepsis: proof of concept. [PDF]

open access: yesSci Rep, 2020
Tran NK   +7 more
europepmc   +1 more source

Home - About - Disclaimer - Privacy