Update README.md

README.md

@@ -275,12 +275,30 @@ pretty_name: LeMatBulk
 
 **Motivation**: check out the blog post [https://huggingface.co/blog/lematerial](https://huggingface.co/blog/lematerial) to hear more about the motivation behind the creation of this dataset.
 
+## Changelog:
+2025.04.17 (hash: NOT YET  RELEASED):
+- We have changed the Yb default pseudopotential to Yb_3 from VASP, this is the same that Materials Project uses. In the previous version we had kept it as Yb, and Materials Project had to Yb-containing materials. Alexandria and OQMD uses Yb. As a result no Yb-containing materials are cross_compatible=True in the latest iteration.
+- We have filtered out high-force materials (norm of forces > 0.1eV/A). The criteria is still quite large. This mostly affect Materials Project materials.
+- We have pulled the latest materials from Alexandria and Materials Project, as a result there are more materials in LeMat-Bulk and LeMat-Bulk-Unique
+- We have added energy_corrected field for the PBE subset using the Materials Project 2020 compatibility scheme across the entire dataset
+- We have added the international spacegroup number using Optimade's space_group_it_number and computed using Moyopy
+- We have re-computed the hash using the BAWL fingerprint with the spacegroup processed by Moyopy and the entalpic_fingerprint has been changed to bawl_fingerprint. The fingerprint can be found in our newly released [lematerial-hasher libary](https://github.com/LeMaterial/lematerial-hasher)
+- We have added r2SCAN data from Materials Project
+- We used logic as defined in Materials Project's emmet package to select which MP task to include as the task representing the bulk material for MP materials.
+- We added certain validation tests, as defined in our newly released [lematerial-fetcher library](https://github.com/LeMaterial/lematerial-fetcher)
+
+Initial release, Dec 2024 (hash: 704b431aa574902f423b1c28f9b90c358d8cd1e1)
+
+
 ## Download and use within Python
 ```python
 from datasets import load_dataset
 
 dataset = load_dataset('LeMaterial/LeMat-Bulk', 'compatible_pbe')
 
+# to use a specific database revision, based on the commit hash:
+dataset = load_dataset('LeMaterial/LeMat-Bulk', 'compatible_pbe', revision='704b431aa574902f423b1c28f9b90c358d8cd1e1')
+
 # convert to Pandas, if you prefer working with this type of object:
 df = dataset['train'].to_pandas()
 ```