Develop (#268)

* Image augmentation. * Augment images. * Augment images. * Specie update. * Add Latt2D, STM image (b-1) fix, image augmentation fix. * Add Latt2D, STM image (b-1) fix, image augmentation fix. * Update conf.py * Update conf.py * Multi-output graph bacthing. * Add EDOS dataset. * Temp. * Add circuit maker. * Add circuit maker. * NELECT update. * Version update, more DBs added. * Fix CHGCAR vasp. * Added volumetric reshape for CHGCAR. * Tmp * Tershoff Hamman update, specie update. * Add crop from center in STM. * Add Fourier transfor in STM. * Update STM pytest. * Add DPI to STM. * Zeo++ added, Atoms cif update, STM update, random vacancy maker added. * Atoms tempfile fix, Potcar from atoms module added. * Test for docs. * C2DB link update, docs Atoms update. * C2DB link update, docs Atoms update. * Version update, COD DB, QM9 JCTC DB added. * Compostion bug fix, elemental descriptor added. * Develop (#186) * Update outputs.py I added the calculation of the Raman intensities inside parse_raman_dat * Update outputs.py * Update outputs.py * Update outputs.py * Update cfid.py * Delete __init__.py * stylecss added. * stylecss added. * Adding extra Makefile/ * Remove examples from docs. * Docs update. * Docs update. * Docs update. * Docs update. * Docs update. * Docs update. * Docs update. * Docs update. * Docs update. * Docs update. * Tutorials update. * Tutorials docs update. * Docs update,pdb reader updated. * Update action_build.yml * Update action_build.yml * Remove pytraj strong dependencies. * Update docs, Added PDBBind and HPOV datasets. * Docs update. * Add thcikness to surface builder. * Surface builder update, Chemical only magpie descriptors added, pdb_core dataset added, zeopp tempfile bugfix. * Typo fix. * Add names to chem descs. * Lessen hermsolver pytest. * Reduced pytest. * Reduced pytest. * Reduced pytest. * Reduced pytest. * Reduced pytest. * No DFT3D * Exclude dft_3d dataset for memory issue. * Update figshare test. * Update figshare test. * Exclude db from coverage. * Exclude db from coverage. * Add magpie.json. * Add magpie.json. * Wien2k bands bug fix. * Wien2k bands bug fix. * Update JARVIS-FF,Elastictensor,LAMMPS parse folder, VASP bandstructure plot code. * JFF update. * Add JQE_TB3 and hMOF dataset. * Update LAMMPS module. * Update LAMMPS module. * Fix elastic tensor module. * Figshare update, docs db name update. * Substitutions. * Update figshare dft_3d, cfid_3d. * Docs data update. * Generate substitutions. * Lint fix. * Update DOS. * Update DOS. * Adding folders for nexus setup. * Update QMOF and hMOF info. * Fixing auto klength error. * Adding zeopp surface area. * Vacancy bug fix, added hmof to docs. * vacancy update. * QE inputs update. * Pyhon 3.9 test, added QE el-ph, VASP XANES, modified hmof db details. * Update Contribution.rst * Minor lint fix. * Update action_build.yml * Update action_build.yml * Fix qiskit requirements. * Fix phonopy requirements. * Fix all requirements. * Fix phonopy requirements. * QE test. * QE test. * Update action_build. * Try other python versions. * Try other python versions. * README updates. * Adding nexus. (#197) * Develop (#196) * Image augmentation. * Augment images. * Augment images. * Specie update. * Add Latt2D, STM image (b-1) fix, image augmentation fix. * Add Latt2D, STM image (b-1) fix, image augmentation fix. * Update conf.py * Update conf.py * Multi-output graph bacthing. * Add EDOS dataset. * Temp. * Add circuit maker. * Add circuit maker. * NELECT update. * Version update, more DBs added. * Fix CHGCAR vasp. * Added volumetric reshape for CHGCAR. * Tmp * Tershoff Hamman update, specie update. * Add crop from center in STM. * Add Fourier transfor in STM. * Update STM pytest. * Add DPI to STM. * Zeo++ added, Atoms cif update, STM update, random vacancy maker added. * Atoms tempfile fix, Potcar from atoms module added. * Test for docs. * C2DB link update, docs Atoms update. * C2DB link update, docs Atoms update. * Version update, COD DB, QM9 JCTC DB added. * Compostion bug fix, elemental descriptor added. * Develop (#186) * Update outputs.py I added the calculation of the Raman intensities inside parse_raman_dat * Update outputs.py * Update outputs.py * Update outputs.py * Update cfid.py * Delete __init__.py * stylecss added. * stylecss added. * Adding extra Makefile/ * Remove examples from docs. * Docs update. * Docs update. * Docs update. * Docs update. * Docs update. * Docs update. * Docs update. * Docs update. * Docs update. * Docs update. * Tutorials update. * Tutorials docs update. * Docs update,pdb reader updated. * Update action_build.yml * Update action_build.yml * Remove pytraj strong dependencies. * Update docs, Added PDBBind and HPOV datasets. * Docs update. * Add thcikness to surface builder. * Surface builder update, Chemical only magpie descriptors added, pdb_core dataset added, zeopp tempfile bugfix. * Typo fix. * Add names to chem descs. * Lessen hermsolver pytest. * Reduced pytest. * Reduced pytest. * Reduced pytest. * Reduced pytest. * Reduced pytest. * No DFT3D * Exclude dft_3d dataset for memory issue. * Update figshare test. * Update figshare test. * Exclude db from coverage. * Exclude db from coverage. * Add magpie.json. * Add magpie.json. * Wien2k bands bug fix. * Wien2k bands bug fix. * Update JARVIS-FF,Elastictensor,LAMMPS parse folder, VASP bandstructure plot code. * JFF update. * Add JQE_TB3 and hMOF dataset. * Update LAMMPS module. * Update LAMMPS module. * Fix elastic tensor module. * Figshare update, docs db name update. * Substitutions. * Update figshare dft_3d, cfid_3d. * Docs data update. * Generate substitutions. * Lint fix. * Update DOS. * Update DOS. Co-authored-by: tavazza <tavazza@gmail.com> Co-authored-by: knc6 <kamal.choudhary@nist.gov> Co-authored-by: KAMAL CHOUDHARY <kamalch@login1.frontera.tacc.utexas.edu> * First input. * added black * Example folder. Co-authored-by: Kamal Choudhary <writetokamal.1989@gmail.com> Co-authored-by: tavazza <tavazza@gmail.com> Co-authored-by: knc6 <kamal.choudhary@nist.gov> Co-authored-by: KAMAL CHOUDHARY <kamalch@login1.frontera.tacc.utexas.edu> * Revert back. * Update .readthedocs.yaml * Update dev-requirements.txt * Docs requirements update. * Update .readthedocs.yaml * Update requirements.txt * Update .readthedocs.yaml * Update requirements.txt * Update .readthedocs.yaml * Update requirements.txt * Update requirements.txt * Update requirements.txt * Update requirements.txt * Update requirements.txt * Update atoms.py * Fixe pbc in ase_to_Atoms. * Add installation tests (#214) * QE inputs, XANES, GHAction updates. (#210) * Image augmentation. * Augment images. * Augment images. * Specie update. * Add Latt2D, STM image (b-1) fix, image augmentation fix. * Add Latt2D, STM image (b-1) fix, image augmentation fix. * Update conf.py * Update conf.py * Multi-output graph bacthing. * Add EDOS dataset. * Temp. * Add circuit maker. * Add circuit maker. * NELECT update. * Version update, more DBs added. * Fix CHGCAR vasp. * Added volumetric reshape for CHGCAR. * Tmp * Tershoff Hamman update, specie update. * Add crop from center in STM. * Add Fourier transfor in STM. * Update STM pytest. * Add DPI to STM. * Zeo++ added, Atoms cif update, STM update, random vacancy maker added. * Atoms tempfile fix, Potcar from atoms module added. * Test for docs. * C2DB link update, docs Atoms update. * C2DB link update, docs Atoms update. * Version update, COD DB, QM9 JCTC DB added. * Compostion bug fix, elemental descriptor added. * Develop (#186) * Update outputs.py I added the calculation of the Raman intensities inside parse_raman_dat * Update outputs.py * Update outputs.py * Update outputs.py * Update cfid.py * Delete __init__.py * stylecss added. * stylecss added. * Adding extra Makefile/ * Remove examples from docs. * Docs update. * Docs update. * Docs update. * Docs update. * Docs update. * Docs update. * Docs update. * Docs update. * Docs update. * Docs update. * Tutorials update. * Tutorials docs update. * Docs update,pdb reader updated. * Update action_build.yml * Update action_build.yml * Remove pytraj strong dependencies. * Update docs, Added PDBBind and HPOV datasets. * Docs update. * Add thcikness to surface builder. * Surface builder update, Chemical only magpie descriptors added, pdb_core dataset added, zeopp tempfile bugfix. * Typo fix. * Add names to chem descs. * Lessen hermsolver pytest. * Reduced pytest. * Reduced pytest. * Reduced pytest. * Reduced pytest. * Reduced pytest. * No DFT3D * Exclude dft_3d dataset for memory issue. * Update figshare test. * Update figshare test. * Exclude db from coverage. * Exclude db from coverage. * Add magpie.json. * Add magpie.json. * Wien2k bands bug fix. * Wien2k bands bug fix. * Update JARVIS-FF,Elastictensor,LAMMPS parse folder, VASP bandstructure plot code. * JFF update. * Add JQE_TB3 and hMOF dataset. * Update LAMMPS module. * Update LAMMPS module. * Fix elastic tensor module. * Figshare update, docs db name update. * Substitutions. * Update figshare dft_3d, cfid_3d. * Docs data update. * Generate substitutions. * Lint fix. * Update DOS. * Update DOS. * Adding folders for nexus setup. * Update QMOF and hMOF info. * Fixing auto klength error. * Adding zeopp surface area. * Vacancy bug fix, added hmof to docs. * vacancy update. * QE inputs update. * Pyhon 3.9 test, added QE el-ph, VASP XANES, modified hmof db details. * Update Contribution.rst * Minor lint fix. * Update action_build.yml * Update action_build.yml * Fix qiskit requirements. * Fix phonopy requirements. * Fix all requirements. * Fix phonopy requirements. * QE test. * QE test. * Update action_build. * Try other python versions. * Try other python versions. * README updates. * Adding nexus. (#197) * Develop (#196) * Image augmentation. * Augment images. * Augment images. * Specie update. * Add Latt2D, STM image (b-1) fix, image augmentation fix. * Add Latt2D, STM image (b-1) fix, image augmentation fix. * Update conf.py * Update conf.py * Multi-output graph bacthing. * Add EDOS dataset. * Temp. * Add circuit maker. * Add circuit maker. * NELECT update. * Version update, more DBs added. * Fix CHGCAR vasp. * Added volumetric reshape for CHGCAR. * Tmp * Tershoff Hamman update, specie update. * Add crop from center in STM. * Add Fourier transfor in STM. * Update STM pytest. * Add DPI to STM. * Zeo++ added, Atoms cif update, STM update, random vacancy maker added. * Atoms tempfile fix, Potcar from atoms module added. * Test for docs. * C2DB link update, docs Atoms update. * C2DB link update, docs Atoms update. * Version update, COD DB, QM9 JCTC DB added. * Compostion bug fix, elemental descriptor added. * Develop (#186) * Update outputs.py I added the calculation of the Raman intensities inside parse_raman_dat * Update outputs.py * Update outputs.py * Update outputs.py * Update cfid.py * Delete __init__.py * stylecss added. * stylecss added. * Adding extra Makefile/ * Remove examples from docs. * Docs update. * Docs update. * Docs update. * Docs update. * Docs update. * Docs update. * Docs update. * Docs update. * Docs update. * Docs update. * Tutorials update. * Tutorials docs update. * Docs update,pdb reader updated. * Update action_build.yml * Update action_build.yml * Remove pytraj strong dependencies. * Update docs, Added PDBBind and HPOV datasets. * Docs update. * Add thcikness to surface builder. * Surface builder update, Chemical only magpie descriptors added, pdb_core dataset added, zeopp tempfile bugfix. * Typo fix. * Add names to chem descs. * Lessen hermsolver pytest. * Reduced pytest. * Reduced pytest. * Reduced pytest. * Reduced pytest. * Reduced pytest. * No DFT3D * Exclude dft_3d dataset for memory issue. * Update figshare test. * Update figshare test. * Exclude db from coverage. * Exclude db from coverage. * Add magpie.json. * Add magpie.json. * Wien2k bands bug fix. * Wien2k bands bug fix. * Update JARVIS-FF,Elastictensor,LAMMPS parse folder, VASP bandstructure plot code. * JFF update. * Add JQE_TB3 and hMOF dataset. * Update LAMMPS module. * Update LAMMPS module. * Fix elastic tensor module. * Figshare update, docs db name update. * Substitutions. * Update figshare dft_3d, cfid_3d. * Docs data update. * Generate substitutions. * Lint fix. * Update DOS. * Update DOS. Co-authored-by: tavazza <tavazza@gmail.com> Co-authored-by: knc6 <kamal.choudhary@nist.gov> Co-authored-by: KAMAL CHOUDHARY <kamalch@login1.frontera.tacc.utexas.edu> * First input. * added black * Example folder. Co-authored-by: Kamal Choudhary <writetokamal.1989@gmail.com> Co-authored-by: tavazza <tavazza@gmail.com> Co-authored-by: knc6 <kamal.choudhary@nist.gov> Co-authored-by: KAMAL CHOUDHARY <kamalch@login1.frontera.tacc.utexas.edu> * Revert back. * Update .readthedocs.yaml * Update dev-requirements.txt * Docs requirements update. * Update .readthedocs.yaml * Update requirements.txt * Update .readthedocs.yaml * Update requirements.txt * Update .readthedocs.yaml * Update requirements.txt * Update requirements.txt * Update requirements.txt * Update requirements.txt * Update requirements.txt * Update atoms.py * Fixe pbc in ase_to_Atoms. Co-authored-by: tavazza <tavazza@gmail.com> Co-authored-by: knc6 <kamal.choudhary@nist.gov> Co-authored-by: KAMAL CHOUDHARY <kamalch@login1.frontera.tacc.utexas.edu> Co-authored-by: wines1 <74620550+wines1@users.noreply.github.com> * Add installation tests * Fix codestyle * Fix codestyle with black * Add docstrings * Fix pydocstyle error * Update __init__.py * Update __init__.py Co-authored-by: Kamal Choudhary <writetokamal.1989@gmail.com> Co-authored-by: tavazza <tavazza@gmail.com> Co-authored-by: knc6 <kamal.choudhary@nist.gov> Co-authored-by: KAMAL CHOUDHARY <kamalch@login1.frontera.tacc.utexas.edu> Co-authored-by: wines1 <74620550+wines1@users.noreply.github.com> * Adding QE super. * Minor changes to QE module, atoms xyz fix. * Adding qe_tb info, and version update. * Update __init__.py * WIP super QE. * Working version of ScSi. * QE inputs and task update. * Add master super. * Add master super. * Lint fix. * Lint fix. * Minor fix. * ET update. * Fix ET test. * Update sanitize atoms. * Additonal checks on supercond. * Debye bug fix. * Pressure in QE Super. * Version fix, publication update, supercond workflow update. * Lint fix. * Tensorboard fix. * Tensorboard fix. * Tensorboard fix. * Melting temp fix. * Update vasp.py (#234) * Local tetra tmp. * Version update. * Lint fix. * HSE06 * Tmp. * Vacancy update, Optimade structureand other minor lint updates. * STEM pytest fix. * Minor lint fix. * Fixed selectrive dynamics issue in Poscar, force reading for single atom system in Vasprun, np.array in core.graps, num_atoms for single atom systems in core.Atoms * Lint fix. * Added phononDos class. * fix pytorch UserWarning in build_undirected_edgedata() (#243) site-packages/jarvis/core/graphs.py:158: UserWarning: Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. r = torch.tensor(r).type(torch.get_default_dtype()) * Add PhaseDiagram. * Add PhaseDiagram. * PhaseDiagram update. * STM image pytest increase, requirements upgrade. * STM image pytest increase, requirements upgrade. * STM image pytest increase, requirements upgrade. * Compare atoms, get spg info directly from atoms. * Flake8 fix. * Update publications.rst * Update qiskit. * Update qiskit. * Update test_hermsolver.py * FIix qiskit DOS. * Update test_hermsolver.py * Fix linting. * Develop og (#257) * Added isotope scattering rate to phonon DOS analysis script. * Linting fix. * Linting fix. * Linting fix. * Add QE convergence. * Update converg.py. * Nexus. * Super with converg. * Super with converg. * SuperCon QE update. * Figshare DB update. * Figshare DB update. * Update alignn ff link. * Lint fix. * DB docs update. Co-authored-by: tavazza <tavazza@gmail.com> Co-authored-by: knc6 <kamal.choudhary@nist.gov> Co-authored-by: KAMAL CHOUDHARY <kamalch@login1.frontera.tacc.utexas.edu> Co-authored-by: wines1 <74620550+wines1@users.noreply.github.com> Co-authored-by: Saurav Maheshkar <sauravvmaheshkar@gmail.com> Co-authored-by: Janosh Riebesell <janosh.riebesell@gmail.com> Co-authored-by: Ramya Gurunathan <ramya1006@gmail.com>
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diff --git a/docs/source/databases.rst b/docs/source/databases.rst
@@ -20,6 +20,8 @@ Database name            Number of data-points       Description
                                                      (Keyword:FD-ELAST)
 ``jff``                  2538                        Various 3D materials properties in JARVIS-FF database   
                                                      computed with several force-fields                     
+``alignn_ff_db``         307113                      Energy per atom, forces and stresses for ALIGNN-FF 
+                                                     trainig for 75k materials.
 ``edos_pdos``            48469                       Normalized electron and phonon density of states with 
                                                      interpolated values and fixed number of bins
 ``megnet``               69239                       Formation energy and bandgaps of 3D materials properties

diff --git a/docs/source/publications.rst b/docs/source/publications.rst
@@ -38,51 +38,61 @@ JARVIS-DFT related
 
 [14. Density functional theory-based electric field gradient database, Sci. Data](https://www.nature.com/articles/s41597-020-00707-8)
 
+[15. High-throughput DFT-based discovery of next generation two-dimensional (2D) superconductors](https://arxiv.org/abs/2211.05254)
+
+[16. A systematic DFT+U and Quantum Monte Carlo benchmark of magnetic two-dimensional (2D) CrX (X = I, Br, Cl, F)](https://arxiv.org/abs/2209.10379)
+
 JARVIS-ML related
 -----------------------------------------------------
-[15. Machine learning with force-field inspired descriptors for materials: fast screening and mapping energy landscape, Phys. Rev. Mat., 2, 083801 (2018).](https://journals.aps.org/prmaterials/abstract/10.1103/PhysRevMaterials.2.083801)
+[17. Machine learning with force-field inspired descriptors for materials: fast screening and mapping energy landscape, Phys. Rev. Mat., 2, 083801 (2018).](https://journals.aps.org/prmaterials/abstract/10.1103/PhysRevMaterials.2.083801)
+
+[18. Convergence and machine learning predictions of Monkhorst-Pack k-points and plane-wave cut-off in high-throughput DFT calculations, Comp. Mat. Sci. 161, 300 (2019).](https://www.sciencedirect.com/science/article/pii/S0927025619300813?via%3Dihub)
+
+[19. Materials science in the artificial intelligence age: high-throughput library generation, machine learning, and a pathway from correlations to the underpinning physics, MRS Comm., 1-18, 2019.](https://doi.org/10.1557/mrc.2019.95)
+
+[20. Enhancing materials property prediction by leveraging computational and experimental data using deep transfer learning, Nature Comm., 10, 1, (2019).](https://www.nature.com/articles/s41467-019-13297-w)
 
-[16. Convergence and machine learning predictions of Monkhorst-Pack k-points and plane-wave cut-off in high-throughput DFT calculations, Comp. Mat. Sci. 161, 300 (2019).](https://www.sciencedirect.com/science/article/pii/S0927025619300813?via%3Dihub)
+[21. Accelerated Discovery of Efficient Solar-cell Materials using Quantum and Machine-learning Methods, Chem. Mater., 31, 5900 (2019).](https://pubs.acs.org/doi/10.1021/acs.chemmater.9b02166)
 
-[17. Materials science in the artificial intelligence age: high-throughput library generation, machine learning, and a pathway from correlations to the underpinning physics, MRS Comm., 1-18, 2019.](https://doi.org/10.1557/mrc.2019.95)
+[22. High-throughput Density Functional Perturbation Theory and Machine Learning Predictions of Infrared, Piezoelectric and Dielectric Responses, npj Computational Materials 6, 64 (2020).](https://www.nature.com/articles/s41524-020-0337-2)
 
-[18. Enhancing materials property prediction by leveraging computational and experimental data using deep transfer learning, Nature Comm., 10, 1, (2019).](https://www.nature.com/articles/s41467-019-13297-w)
+[23. Data-driven Discovery of 3D and 2D Thermoelectric Materials, J. Phys.: Cond. Matt.](https://iopscience.iop.org/article/10.1088/1361-648X/aba06b/meta)
 
-[19. Accelerated Discovery of Efficient Solar-cell Materials using Quantum and Machine-learning Methods, Chem. Mater., 31, 5900 (2019).](https://pubs.acs.org/doi/10.1021/acs.chemmater.9b02166)
+[24. Efficient Computational Design of 2D van der Waals Heterostructures: Band-Alignment, Lattice-Mismatch, Web-app Generation and Machine-learning.](https://arxiv.org/abs/2004.03025)
 
-[20. High-throughput Density Functional Perturbation Theory and Machine Learning Predictions of Infrared, Piezoelectric and Dielectric Responses, npj Computational Materials 6, 64 (2020).](https://www.nature.com/articles/s41524-020-0337-2)
+[25. Enhancing materials property prediction by leveraging computational and experimental data using deep transfer learning, Nature Commun.](https://www.nature.com/articles/s41467-019-13297-w)
 
-[21. Data-driven Discovery of 3D and 2D Thermoelectric Materials, J. Phys.: Cond. Matt.](https://iopscience.iop.org/article/10.1088/1361-648X/aba06b/meta)
+[26. Atomistic Line Graph Neural Network for Improved Materials Property Predictions, npj Computational Materials 7, 1 (2021)](https://www.nature.com/articles/s41524-021-00650-1)
 
-[22. Efficient Computational Design of 2D van der Waals Heterostructures: Band-Alignment, Lattice-Mismatch, Web-app Generation and Machine-learning.](https://arxiv.org/abs/2004.03025)
+[27. Recent advances and applications of deep learning methods in materials science, npj Computational Materials 8, 1 (2022)](https://www.nature.com/articles/s41524-022-00734-6)
 
-[23. Enhancing materials property prediction by leveraging computational and experimental data using deep transfer learning, Nature Commun.](https://www.nature.com/articles/s41467-019-13297-w)
+[28. Graph neural network predictions of metal organic framework CO2 adsorption properties, Comp. Mat. Sci., 210, 111388 (2022)](https://www.sciencedirect.com/science/article/pii/S092702562200163X)
 
-[24. Atomistic Line Graph Neural Network for Improved Materials Property Predictions, npj Computational Materials 7, 1 (2021)](https://www.nature.com/articles/s41524-021-00650-1)
+[29. Data-Driven Multi-Scale Modeling and Optimization for Elastic Properties of Cubic Microstructures](https://link.springer.com/article/10.1007/s40192-022-00258-3)
 
-[25. Recent advances and applications of deep learning methods in materials science, npj Computational Materials 8, 1 (2022)](https://www.nature.com/articles/s41524-022-00734-6)
+[30. Uncertainty Prediction for Machine Learning Models of Material Properties](https://pubs.acs.org/doi/abs/10.1021/acsomega.1c03752)
 
-[26. Graph neural network predictions of metal organic framework CO2 adsorption properties, Comp. Mat. Sci., 210, 111388 (2022)](https://www.sciencedirect.com/science/article/pii/S092702562200163X)
+[31. Cross-property deep transfer learning framework for enhanced predictive analytics on small materials data](https://www.nature.com/articles/s41467-021-26921-5)
 
-[27. Data-Driven Multi-Scale Modeling and Optimization for Elastic Properties of Cubic Microstructures](https://link.springer.com/article/10.1007/s40192-022-00258-3)
+[32. Prediction of the Electron Density of States for Crystalline Compounds with Atomistic Line Graph Neural Networks (ALIGNN)](https://link.springer.com/article/10.1007/s11837-022-05199-y)
 
-[28. Uncertainty Prediction for Machine Learning Models of Material Properties](https://pubs.acs.org/doi/abs/10.1021/acsomega.1c03752)
+[33. Designing High-Tc Superconductors with BCS-inspired Screening, Density Functional Theory and Deep-learning](https://arxiv.org/abs/2205.00060)
 
-[29. Cross-property deep transfer learning framework for enhanced predictive analytics on small materials data](https://www.nature.com/articles/s41467-021-26921-5)
+[34. Rapid Prediction of Phonon Structure and Properties using an Atomistic Line Graph Neural Network (ALIGNN)](https://arxiv.org/abs/2207.12510)
 
-[30. Prediction of the Electron Density of States for Crystalline Compounds with Atomistic Line Graph Neural Networks (ALIGNN)](https://link.springer.com/article/10.1007/s11837-022-05199-y)
+[35. Unified Graph Neural Network Force-field for the Periodic Table](https://arxiv.org/abs/2209.05554)
 
-[31. Designing High-Tc Superconductors with BCS-inspired Screening, Density Functional Theory and Deep-learning](https://arxiv.org/abs/2205.00060)
+[36. AtomVision: A machine vision library for atomistic images](https://arxiv.org/abs/2212.02586)
 
-[32. Rapid Prediction of Phonon Structure and Properties using an Atomistic Line Graph Neural Network (ALIGNN)](https://arxiv.org/abs/2207.12510)
+[37. ChemNLP: A Natural Language Processing based Library for Materials Chemistry Text Data](https://arxiv.org/abs/2209.08203)
 
-[33. Unified Graph Neural Network Force-field for the Periodic Table](https://arxiv.org/abs/2209.05554)
+[38. A critical examination of robustness and generalizability of machine learning prediction of materials properties](https://arxiv.org/abs/2210.13597)
 
 JARVIS-QC related
 -----------------------------------------------------
-[34. Quantum Computation for Predicting Electron and Phonon Properties of Solids., J. Phys.: Cond. Matt.](https://iopscience.iop.org/article/10.1088/1361-648X/ac1154)
+[39. Quantum Computation for Predicting Electron and Phonon Properties of Solids., J. Phys.: Cond. Matt.](https://iopscience.iop.org/article/10.1088/1361-648X/ac1154)
 
 
 JARVIS-QETB related
 -----------------------------------------------------
-[35. Fast and Accurate Prediction of Material Properties with Three-Body Tight-Binding Model for the Periodic Table](https://arxiv.org/abs/2112.11585)
+[40. Fast and Accurate Prediction of Material Properties with Three-Body Tight-Binding Model for the Periodic Table](https://arxiv.org/abs/2112.11585)
diff --git a/jarvis/__init__.py b/jarvis/__init__.py
@@ -1,5 +1,5 @@
 """Version number."""
-__version__ = "2022.09.16"
+__version__ = "2022.12.11"
 
 import os
 

diff --git a/jarvis/analysis/phonon/dos.py b/jarvis/analysis/phonon/dos.py
@@ -1,8 +1,11 @@
 """Module to analyze phonon dos."""
 
 import numpy as np
+from phonopy.structure.atoms import isotope_data
+from math import pi as pi
 
 icm_to_eV = 1.23981e-4
+icm_to_thz = 2.99792458e-2
 hbar = 6.582119569e-16  # eV*s
 kB = 8.617333262145e-5  # eV/K
 e = 1.60217662e-19
@@ -42,12 +45,8 @@ def heat_capacity(self, temperature=300):
         # Eq. 1
         dos = np.array(self.phonon_dos) / icm_to_eV
         x = (omega) / (kB * temperature)
-        Cp = (
-            kB
-            * x[1:] ** 2
-            * (np.exp(x[1:]) / (np.exp(x[1:]) - 1) ** 2)
-            * dos[1:]
-        )
+        prefix = kB * x[1:] ** 2 * (np.exp(x[1:]) / (np.exp(x[1:]) - 1) ** 2)
+        Cp = prefix * dos[1:]
         Cp = np.insert(Cp, 0, 0)
         return np.trapz(Cp, omega) * e * Na
 
@@ -60,3 +59,50 @@ def vibrational_entropy(self, temperature=300):
         S_vib = kB * ((n + 1) * np.log(n + 1) + n * np.log(n)) * dos[1:]
         S_vib = np.insert(S_vib, 0, S_vib[0])
         return S_vib
+
+    def phonon_isotope_scattering(self, atoms=None):
+        """
+        Get phonon-isotope scattering rate at natural isotopic abundance.
+        Returns scattering rate in units of Hz.
+        """
+        omega = np.array(self.phonon_freq_cm)
+        dos = np.array(self.phonon_dos)
+
+        def isotopic_gamma(atoms):
+            formula = atoms.composition.reduce()
+            natoms = sum([v for v in formula[0].values()])
+            ave_m = 0
+            gamma = 0
+            for k, v in formula[0].items():
+                iso_list = isotope_data[k]
+                ave_m_n = sum([iso[2] * iso[1] for iso in iso_list])
+                g = [iso[2] * (iso[1] - ave_m_n) ** 2 for iso in iso_list]
+                gamma_n = sum(g)
+                ave_m += ave_m_n * (v / natoms)
+                gamma += gamma_n * (v / natoms)
+            return gamma / (ave_m ** 2)
+
+        gamma = isotopic_gamma(atoms)
+        atmV = (atoms.volume / atoms.num_atoms) * 1e-30
+        omega = omega * icm_to_thz
+        dos = dos / icm_to_thz / (atmV * atoms.num_atoms)
+        tau = (pi / 6) * (atmV * gamma * omega ** 2) * dos
+        return np.trapz(tau, omega) * 1e12
+
+
+if __name__ == "__main__":
+    from jarvis.core.atoms import Atoms
+    from jarvis.db.figshare import get_jid_data
+
+    dos_entry = get_jid_data(jid="JVASP-1459", dataset="edos_pdos")
+    dft3d_entry = get_jid_data(jid="JVASP-1459", dataset="dft_3d")
+    ph_dos = dos_entry["pdos_elast"]
+    ph_freq = np.arange(0, 1000, 5)
+    atoms = Atoms.from_dict(dft3d_entry["atoms"])
+
+    ph = PhononDos(phonon_dos=ph_dos, phonon_freq_cm=ph_freq)
+    debye_temp = ph.debye_temperature(atoms)
+    iso_scatt = ph.phonon_isotope_scattering(atoms)
+
+    print("Debye temperature:", debye_temp)
+    print("Isotope scattering rate:", iso_scatt)
diff --git a/jarvis/db/figshare.py b/jarvis/db/figshare.py
@@ -28,24 +28,27 @@ def get_db_info():
     db_info = {
         # https://doi.org/10.6084/m9.figshare.6815705
         "dft_2d": [
-            "https://ndownloader.figshare.com/files/26808917",
-            "d2-3-12-2021.json",
+            "https://ndownloader.figshare.com/files/38521268",
+            "d2-12-12-2022.json",
             "Obtaining 2D dataset 1.1k ...",
-            "https://www.nature.com/articles/s41524-020-00440-1",
+            "https://www.nature.com/articles/s41524-020-00440-1"
+            + "\nOther versions:https://doi.org/10.6084/m9.figshare.6815705",
         ],
         # https://doi.org/10.6084/m9.figshare.6815699
         "dft_3d": [
-            "https://ndownloader.figshare.com/files/29204826",
-            "jdft_3d-8-18-2021.json",
-            "Obtaining 3D dataset 55k ...",
-            "https://www.nature.com/articles/s41524-020-00440-1",
+            "https://ndownloader.figshare.com/files/38521619",
+            "jdft_3d-12-12-2022.json",
+            "Obtaining 3D dataset 76k ...",
+            "https://www.nature.com/articles/s41524-020-00440-1"
+            + "\nOther versions:https://doi.org/10.6084/m9.figshare.6815699",
         ],
         # https://doi.org/10.6084/m9.figshare.6815699
         "cfid_3d": [
             "https://ndownloader.figshare.com/files/29205201",
             "cfid_3d-8-18-2021.json",
             "Obtaining 3D dataset 55k ...",
-            "https://www.nature.com/articles/s41524-020-00440-1",
+            "https://www.nature.com/articles/s41524-020-00440-1"
+            + "\nOther versions:https://doi.org/10.6084/m9.figshare.6815699",
         ],
         # https://doi.org/10.6084/m9.figshare.14213522
         "jff": [
@@ -56,6 +59,14 @@ def get_db_info():
             "Obtaining JARVIS-FF 2k ...",
             "https://www.nature.com/articles/s41524-020-00440-1",
         ],
+        # https://doi.org/10.6084/m9.figshare.21667874
+        "alignn_ff_db": [
+            "https://ndownloader.figshare.com/files/38522315",
+            # "https://ndownloader.figshare.com/files/26809760",
+            "id_prop.json",
+            "Obtaining ALIGNN-FF training DB 300k ...",
+            "https://arxiv.org/abs/2209.05554",
+        ],
         "mp_3d_2020": [
             "https://ndownloader.figshare.com/files/26791259",
             "all_mp.json",
@@ -203,6 +214,13 @@ def get_db_info():
             "Obtaining PDBBind dataset 11k...",
             "https://doi.org/10.1093/bioinformatics/btu626",
         ],
+        # https://doi.org/10.6084/m9.figshare.21713885
+        "snumat": [
+            "https://ndownloader.figshare.com/files/38521736",
+            "snumat.json",
+            "Obtaining SNUMAT Hybrid functional dataset 10k...",
+            "https://www.nature.com/articles/s41597-020-00723-8",
+        ],
         # https://doi.org/10.6084/m9.figshare.13215308
         "aflow2": [
             "https://ndownloader.figshare.com/files/25453265",