MD simulations with ML force fields reveal non-monotonic friction-load curves in MX2/metal heterostructures arising from coexistence of longitudinal, lateral-slip, and zig-zag sliding modes.
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Electrospinning-Data.org is a FAIR data platform that organizes electrospinning experiments into a structured, failure-inclusive corpus to enable predictive modeling and inverse design of nanofiber morphologies.
Proposes a regional data-centric materials science ecosystem for the Great Plains, identifying five barriers to data sharing and outlining a staged roadmap illustrated by a high-purity germanium pilot.
citing papers explorer
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Microscopic contributions to the deviation from Amontons friction law
MD simulations with ML force fields reveal non-monotonic friction-load curves in MX2/metal heterostructures arising from coexistence of longitudinal, lateral-slip, and zig-zag sliding modes.
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Electrospinning-Data.org: A FAIR, Structured Knowledge Resource for Nanofiber Fabrication
Electrospinning-Data.org is a FAIR data platform that organizes electrospinning experiments into a structured, failure-inclusive corpus to enable predictive modeling and inverse design of nanofiber morphologies.
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Building a Regional Data-Centric Materials Science Ecosystem for Processing-Rich Materials Innovation in the Great Plains
Proposes a regional data-centric materials science ecosystem for the Great Plains, identifying five barriers to data sharing and outlining a staged roadmap illustrated by a high-purity germanium pilot.