#nematicity — Public Fediverse posts

https://phys.org/news/2023-09-ai-algorithm-microscopic-nematicity-moir.html

"…typically composed of stacks of #graphene layers with a relative twist…attracted immense attention from the #condensedmatter community…due to their high tunability and…make these systems a perfect playground for testing theories from #stronglycorrelatedphenomena…but directly obtaining these details from experimental data is often an ill-defined inverse problem…we trained a #convolutionalneuralnetwork…to recognize features of #nematicity from the data…"

https://phys.org/news/2023-09-ai-algorithm-microscopic-nematicity-moir.html

"…typically composed of stacks of #graphene layers with a relative twist…attracted immense attention from the #condensedmatter community…due to their high tunability and…make these systems a perfect playground for testing theories from #stronglycorrelatedphenomena…but directly obtaining these details from experimental data is often an ill-defined inverse problem…we trained a #convolutionalneuralnetwork…to recognize features of #nematicity from the data…"

https://phys.org/news/2023-09-ai-algorithm-microscopic-nematicity-moir.html

"…typically composed of stacks of #graphene layers with a relative twist…attracted immense attention from the #condensedmatter community…due to their high tunability and…make these systems a perfect playground for testing theories from #stronglycorrelatedphenomena…but directly obtaining these details from experimental data is often an ill-defined inverse problem…we trained a #convolutionalneuralnetwork…to recognize features of #nematicity from the data…"

https://phys.org/news/2023-09-ai-algorithm-microscopic-nematicity-moir.html

"…typically composed of stacks of #graphene layers with a relative twist…attracted immense attention from the #condensedmatter community…due to their high tunability and…make these systems a perfect playground for testing theories from #stronglycorrelatedphenomena…but directly obtaining these details from experimental data is often an ill-defined inverse problem…we trained a #convolutionalneuralnetwork…to recognize features of #nematicity from the data…"

https://phys.org/news/2023-09-ai-algorithm-microscopic-nematicity-moir.html

"…typically composed of stacks of #graphene layers with a relative twist…attracted immense attention from the #condensedmatter community…due to their high tunability and…make these systems a perfect playground for testing theories from #stronglycorrelatedphenomena…but directly obtaining these details from experimental data is often an ill-defined inverse problem…we trained a #convolutionalneuralnetwork…to recognize features of #nematicity from the data…"