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README.md

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+## Introduction
+An educational code for structural topology optimization based on automatic differentiation.<br />![SA2AD.jpg](https://cdn.nlark.com/yuque/0/2022/jpeg/2749792/1667552365458-e024f164-f9bf-4c88-9cf0-2d2238a5c9a0.jpeg#clientId=u190c3999-3642-4&crop=0&crop=0&crop=1&crop=1&from=ui&id=uaac0448a&margin=%5Bobject%20Object%5D&name=SA2AD.jpg&originHeight=693&originWidth=3579&originalType=binary&ratio=1&rotation=0&showTitle=false&size=669739&status=done&style=none&taskId=u8a57aeb2-e405-49da-afbd-9a637cc3207&title=)
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+## Running Requirement
+
+- Python
+- Jax
+- Jaxlib
+- Optax
+- Flax
+
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+## The verification of automatic differentiation accuracy
+
+
+
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+## Citation
+Feel free to cite this library.
+```markdown
+@article{Zhang_TONRExploration_2021,
+    title = {{{TONR}}: {{An}} Exploration for a Novel Way Combining Neural Network with Topology Optimization},
+    shorttitle = {{{TONR}}},
+    author = {Zhang, Zeyu and Li, Yu and Zhou, Weien and Chen, Xiaoqian and Yao, Wen and Zhao, Yong},
+    year = {2021},
+    month = dec,
+    journal = {Computer Methods in Applied Mechanics and Engineering},
+    volume = {386},
+    pages = {114083},
+    issn = {00457825},
+    doi = {10.1016/j.cma.2021.114083},
+    langid = {english},
+    }
+```
+