Bidirectional Learning of Relationships between Atomic Environments and Electronic Band Dispersion in Semiconductor Heterostructures
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arXiv
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| Hauptverfasser: | , |
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| Format: | Preprint |
| Veröffentlicht: |
2023
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| _version_ | 1866917316296441856 |
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| author | Pimachev, Artem K Neogi, Sanghamitra |
| author_facet | Pimachev, Artem K Neogi, Sanghamitra |
| contents | Atomic-scale variations in semiconductor heterostructures, arising from strain, interfaces, and compositional modulation, strongly influence electronic band dispersion but remain difficult to probe and compare using first-principles methods alone. Here, we introduce a bidirectional learning approach that links local atomic environments to electronic band dispersion using atomically resolved spectral functions as information-dense representations. This formulation enables a forward model that predicts how atomic environments shape electronic bands, and a reverse model that infers atomic-environment descriptors directly from band dispersion images, including angle-resolved photoemission spectra. Applied to silicon/germanium superlattices and heterostructures, the approach reveals how inner and interfacial atomic environments give rise to distinct spectral signatures. The coupled forward-reverse framework enables self-consistent validation by reconstructing electronic band structures from inferred descriptors. By treating electronic bands as decomposable, learnable objects, this work provides a physics-informed route for interpreting spectroscopic data and for data-driven exploration of electronic properties in complex semiconductor heterostructures. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2302_00261 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Bidirectional Learning of Relationships between Atomic Environments and Electronic Band Dispersion in Semiconductor Heterostructures Pimachev, Artem K Neogi, Sanghamitra Materials Science Atomic-scale variations in semiconductor heterostructures, arising from strain, interfaces, and compositional modulation, strongly influence electronic band dispersion but remain difficult to probe and compare using first-principles methods alone. Here, we introduce a bidirectional learning approach that links local atomic environments to electronic band dispersion using atomically resolved spectral functions as information-dense representations. This formulation enables a forward model that predicts how atomic environments shape electronic bands, and a reverse model that infers atomic-environment descriptors directly from band dispersion images, including angle-resolved photoemission spectra. Applied to silicon/germanium superlattices and heterostructures, the approach reveals how inner and interfacial atomic environments give rise to distinct spectral signatures. The coupled forward-reverse framework enables self-consistent validation by reconstructing electronic band structures from inferred descriptors. By treating electronic bands as decomposable, learnable objects, this work provides a physics-informed route for interpreting spectroscopic data and for data-driven exploration of electronic properties in complex semiconductor heterostructures. |
| title | Bidirectional Learning of Relationships between Atomic Environments and Electronic Band Dispersion in Semiconductor Heterostructures |
| topic | Materials Science |
| url | https://arxiv.org/abs/2302.00261 |