A differentiable contact mechanics engine embedded in a neural network and quadratic optimizer discovers axisymmetric asperity topographies that produce target nonlinear friction laws, validated against BEM simulations.
Inverse design and flexible parameterization of meta-optics using algorithmic differentiation
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PyMieDiff provides a new open-source PyTorch library for fully differentiable Mie scattering from layered spheres, with autograd support for efficiencies, angular patterns, and near-fields.
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Inverse Design of Metainterfaces for Static Friction Control: Beyond the Hertzian Limit
A differentiable contact mechanics engine embedded in a neural network and quadratic optimizer discovers axisymmetric asperity topographies that produce target nonlinear friction laws, validated against BEM simulations.
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PyMieDiff: A differentiable Mie scattering library
PyMieDiff provides a new open-source PyTorch library for fully differentiable Mie scattering from layered spheres, with autograd support for efficiencies, angular patterns, and near-fields.