C&EN

Leveraging Persistent Homology Features for Accurate Defect Formation Energy Predictions via Graph Neural Networks

Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. To evaluate the defect formation energies, first-principles ...
C&EN

Machine Learning with Enormous “Synthetic” Data Sets: Predicting Glass Transition Temperature of Polyimides Using Graph Convolutional Neural Networks

You are free to share (copy and redistribute) this article in any medium or format within the parameters below: Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must ...
Europe PMC

Apparent Young's Modulus of Epoxy Adhesives.

This article presents the results of a study of the properties of epoxy adhesives in an adhesive joint. The study analysed changes in Young's modulus values as a function of the rigidity of the ...
PNAS

Rigidity percolation in a random tensegrity via analytic graph theory

Mechanical structures combining rigid elements, like rods and bone, with flexible ones, like cables and membranes, are ubiquitous across a wide range of scales in natural and engineered systems. We ...
Europe PMC

Inactivation of Lrp5 in osteocytes reduces young's modulus and responsiveness to the mechanical loading.

Low-density-lipoprotein receptor-related protein 5 (Lrp5) is a co-receptor in Wnt signaling, which plays a critical role in development and maintenance of bone. Osteoporosis-pseudoglioma syndrome, for ...
Scientific Research Publishing

Prediction of Effective Elastic Modulus of Biphasic Composite Materials ()

Two semi-empirical approaches for prediction of elastic modulus of biphasic composites have been proposed. Developed relations are for pore free matrix and pore free filler and found to depend on ...