H2 in a Pd crystal¶
Set up environment (optional)¶
These steps are required for Google Colab, but may work on other systems too:
[1]:
#import locale
#locale.getpreferredencoding = lambda: "UTF-8"
#!python3 -m pip install pack-mm data-tutorials weas-widget
Let us start by creating a Pd supercell, 4,4,4.
[2]:
from weas_widget import WeasWidget
from ase.build import bulk
Pd = bulk('Pd', 'fcc', a=3.89, cubic=True)*(4,4,4)
viewer=WeasWidget()
viewer.from_ase(Pd)
viewer.avr.model_style = 1
viewer
[2]:
now insert 32 H2 molecules anywhere.
[3]:
from pack_mm.core.core import pack_molecules
e, final = pack_molecules(
system=Pd,
molecule="H2",
nmols=32,
arch="mace_mp",
model="small-0b2",
device="cpu",
where="anywhere",
seed=2025,
temperature=300,
ntries=20,
geometry=True,
threshold=0.1,
)
Inserting 32 H2 molecules in Pd256+.
Using mace_mp model small-0b2 on cpu.
Insert in anywhere.
/home/runner/work/pack-mm/pack-mm/.venv/lib/python3.12/site-packages/e3nn/o3/_wigner.py:10: UserWarning: Environment variable TORCH_FORCE_NO_WEIGHTS_ONLY_LOAD detected, since the`weights_only` argument was not explicitly passed to `torch.load`, forcing weights_only=False.
_Jd, _W3j_flat, _W3j_indices = torch.load(os.path.join(os.path.dirname(__file__), 'constants.pt'))
/home/runner/work/pack-mm/pack-mm/.venv/lib/python3.12/site-packages/torch/jit/_script.py:1491: FutureWarning: `torch.jit.script` is deprecated. Please switch to `torch.compile` or `torch.export`.
warnings.warn(
/home/runner/work/pack-mm/pack-mm/.venv/lib/python3.12/site-packages/torch/jit/_script.py:1491: FutureWarning: `torch.jit.script` is deprecated. Please switch to `torch.compile` or `torch.export`.
warnings.warn(
cuequivariance or cuequivariance_torch is not available. Cuequivariance acceleration will be disabled.
/home/runner/work/pack-mm/pack-mm/.venv/lib/python3.12/site-packages/torch/jit/_script.py:1491: FutureWarning: `torch.jit.script` is deprecated. Please switch to `torch.compile` or `torch.export`.
warnings.warn(
/home/runner/work/pack-mm/pack-mm/.venv/lib/python3.12/site-packages/mace/calculators/mace.py:226: UserWarning: Environment variable TORCH_FORCE_NO_WEIGHTS_ONLY_LOAD detected, since the`weights_only` argument was not explicitly passed to `torch.load`, forcing weights_only=False.
torch.load(f=model_path, map_location=device)
/home/runner/work/pack-mm/pack-mm/.venv/lib/python3.12/site-packages/torch/jit/_serialization.py:176: FutureWarning: `torch.jit.load` is deprecated. Please switch to `torch.export`.
warnings.warn(
/home/runner/work/pack-mm/pack-mm/.venv/lib/python3.12/site-packages/torch/jit/_serialization.py:176: FutureWarning: `torch.jit.load` is deprecated. Please switch to `torch.export`.
warnings.warn(
/home/runner/work/pack-mm/pack-mm/.venv/lib/python3.12/site-packages/torch/jit/_serialization.py:176: FutureWarning: `torch.jit.load` is deprecated. Please switch to `torch.export`.
warnings.warn(
Using Materials Project MACE for MACECalculator with /home/runner/.cache/mace/macesmalldensityagnesistressmodel
Using float64 for MACECalculator, which is slower but more accurate. Recommended for geometry optimization.
Old energy=-1325.366945117035, new energy=-1322.5699942667352, de=2.7969508502997087, acc=np.float64(1.0310453840561145e-47), random=0.6573675854710377
Old energy=-1325.366945117035, new energy=-1289.0048635228052, de=36.36208159422972, acc=np.float64(0.0), random=0.7694578719378116
Old energy=-1325.366945117035, new energy=-1328.4408765925366, de=-3.073931475501695, acc=np.float64(4.363083313285293e+51), random=0.6663921049033288
Inserted particle 1
Old energy=-1328.4408765925366, new energy=-1333.0390689301964, de=-4.598192337659839, acc=np.float64(1.7630217505784013e+77), random=0.5196536887579605
Inserted particle 2
Old energy=-1333.0390689301964, new energy=-1322.2310047512287, de=10.808064178967697, acc=np.float64(2.7067706295888987e-182), random=0.06739574665921966
Old energy=-1333.0390689301964, new energy=-1275.7930886766396, de=57.24598025355681, acc=np.float64(0.0), random=0.49961201043327175
Old energy=-1333.0390689301964, new energy=-1326.5620351072955, de=6.477033822900921, acc=np.float64(1.550900179972136e-109), random=0.1050746012583641
Old energy=-1333.0390689301964, new energy=-1104.082050865744, de=228.95701806445254, acc=np.float64(0.0), random=0.9378701885604214
Old energy=-1333.0390689301964, new energy=-1335.5031370958882, de=-2.4640681656917423, acc=np.float64(2.4804892300827883e+41), random=0.3762683149324123
Inserted particle 3
Old energy=-1335.5031370958882, new energy=-1338.2138858026012, de=-2.710748706713048, acc=np.float64(3.4561250697525016e+45), random=0.6727933834766038
Inserted particle 4
Old energy=-1338.2138858026012, new energy=-1336.2273636085183, de=1.9865221940829088, acc=np.float64(4.245067607808471e-34), random=0.09706066849775918
Old energy=-1338.2138858026012, new energy=-1341.8665407867893, de=-3.652654984188075, acc=np.float64(2.3010383344976876e+61), random=0.47590567428965436
Inserted particle 5
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Old energy=-1341.8665407867893, new energy=-1340.5306018779777, de=1.3359389088116131, acc=np.float64(3.6075011965686785e-23), random=0.6096984257895941
Old energy=-1341.8665407867893, new energy=-1345.6117737192783, de=-3.745232932488989, acc=np.float64(8.263527234886871e+62), random=0.10084644599814097
Inserted particle 6
Old energy=-1345.6117737192783, new energy=-1344.6906176577675, de=0.9211560615108283, acc=np.float64(3.351614036192865e-16), random=0.8475810108898351
Old energy=-1345.6117737192783, new energy=-1319.5104323228657, de=26.101341396412636, acc=np.float64(0.0), random=0.9573928760728474
Old energy=-1345.6117737192783, new energy=-1347.8575142194134, de=-2.2457405001350708, acc=np.float64(5.330804394402069e+37), random=0.3273810695294246
Inserted particle 7
Old energy=-1347.8575142194134, new energy=-1349.9317818843642, de=-2.0742676649508667, acc=np.float64(7.017378827145788e+34), random=0.06247404096988407
Inserted particle 8
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Inserted particle 9
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Old energy=-1353.2420040066086, new energy=-1319.990867943644, de=33.25113606296463, acc=np.float64(0.0), random=0.1776678297264329
Old energy=-1353.2420040066086, new energy=-1334.424355736004, de=18.81764827060465, acc=np.float64(7.5390253e-317), random=0.6002380235886438
Old energy=-1353.2420040066086, new energy=-1354.073713097733, de=-0.8317090911243668, acc=np.float64(93778336017388.1), random=0.868138468423006
Inserted particle 10
Old energy=-1354.073713097733, new energy=-1358.167184359781, de=-4.0934712620480695, acc=np.float64(5.852129175127933e+68), random=0.657014836768514
Inserted particle 11
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Old energy=-1358.167184359781, new energy=-1203.3813645746689, de=154.78581978511215, acc=np.float64(0.0), random=0.9616436876719956
Old energy=-1358.167184359781, new energy=-1344.3048613336314, de=13.862323026149625, acc=np.float64(1.3278336545565518e-233), random=0.21200357006485315
Old energy=-1358.167184359781, new energy=-1350.3053362233882, de=7.861848136392837, acc=np.float64(8.44732863821161e-133), random=0.4817459907937399
Old energy=-1358.167184359781, new energy=-1350.584568516109, de=7.582615843672102, acc=np.float64(4.1458829922465735e-128), random=0.7175118692379753
Old energy=-1358.167184359781, new energy=-1361.323826568625, de=-3.156642208844005, acc=np.float64(1.0697274564096792e+53), random=0.4094954707153864
Inserted particle 12
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Old energy=-1361.323826568625, new energy=-1356.8185790361829, de=4.505247532442127, acc=np.float64(2.0660787247987283e-76), random=0.2593074228409512
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Old energy=-1361.323826568625, new energy=-1357.0463431259209, de=4.277483442704124, acc=np.float64(1.3848937880513224e-72), random=0.29948735641057544
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Old energy=-1361.323826568625, new energy=-1357.3412860897224, de=3.9825404789025924, acc=np.float64(1.2480783948791801e-67), random=0.853089891818317
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Old energy=-1361.323826568625, new energy=-1358.8264767835904, de=2.4973497850346575, acc=np.float64(1.1126430701539585e-42), random=0.7007421832233066
Old energy=-1361.323826568625, new energy=-1337.5852789056596, de=23.738547662965402, acc=np.float64(0.0), random=0.37954479237838723
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Old energy=-1361.323826568625, new energy=-1357.5889194234474, de=3.734907145177658, acc=np.float64(1.804264433654222e-63), random=0.38377598684075986
Old energy=-1361.323826568625, new energy=-1355.1118640736672, de=6.211962494957788, acc=np.float64(4.4013679660101056e-105), random=0.31636591169966843
Old energy=-1361.323826568625, new energy=-1339.8411025567043, de=21.48272401192071, acc=np.float64(0.0), random=0.6241331880244465
Old energy=-1361.323826568625, new energy=-1360.9612151677447, de=0.3626114008802688, acc=np.float64(8.098312025636141e-07), random=0.855239859074447
Old energy=-1361.323826568625, new energy=-1340.4864821529916, de=20.837344415633424, acc=np.float64(0.0), random=0.7155485138915397
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Old energy=-1361.323826568625, new energy=2855.7009921173935, de=4217.024818686019, acc=np.float64(0.0), random=0.021804557066307906
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Old energy=-1361.323826568625, new energy=-1338.575020211771, de=22.748806356853947, acc=np.float64(0.0), random=0.5470521216019214
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Inserted particle 14
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Inserted particle 15
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Inserted particle 16
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Inserted particle 17
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Inserted particle 18
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Inserted particle 19
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Inserted particle 20
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Inserted particle 21
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Inserted particle 22
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Inserted particle 23
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Inserted particle 24
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Old energy=-1394.7505435138107, new energy=-1395.7319047973247, de=-0.9813612835139338, acc=np.float64(3.0630180618932732e+16), random=0.09093121853013819
Inserted particle 25
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Inserted particle 26
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Inserted particle 27
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Inserted particle 28
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Old energy=-1404.2584989902962, new energy=-1406.8553279671473, de=-2.5968289768511568, acc=np.float64(4.2152328416048044e+43), random=0.8459407917027165
Inserted particle 29
Old energy=-1406.8553279671473, new energy=-1411.727536011097, de=-4.87220804394974, acc=np.float64(7.071645737554182e+81), random=0.3418441442059098
Inserted particle 30
Old energy=-1411.727536011097, new energy=-1416.124212058878, de=-4.396676047780829, acc=np.float64(7.259920229705699e+73), random=0.07064721496219473
Inserted particle 31
Old energy=-1416.124212058878, new energy=-1416.0898197386298, de=0.03439232024811645, acc=np.float64(0.2643834422690635), random=0.8740430055123146
Old energy=-1416.124212058878, new energy=-1405.088227917805, de=11.035984141072959, acc=np.float64(4.013870090847984e-186), random=0.5749522470905434
Old energy=-1416.124212058878, new energy=-1420.9478059302646, de=-4.82359387138672, acc=np.float64(1.078544489448318e+81), random=0.5984262838675192
Inserted particle 32
Using Materials Project MACE for MACECalculator with /home/runner/.cache/mace/macesmalldensityagnesistressmodel
Using float64 for MACECalculator, which is slower but more accurate. Recommended for geometry optimization.
/home/runner/work/pack-mm/pack-mm/.venv/lib/python3.12/site-packages/mace/calculators/mace.py:226: UserWarning: Environment variable TORCH_FORCE_NO_WEIGHTS_ONLY_LOAD detected, since the`weights_only` argument was not explicitly passed to `torch.load`, forcing weights_only=False.
torch.load(f=model_path, map_location=device)
/home/runner/work/pack-mm/pack-mm/.venv/lib/python3.12/site-packages/torch/jit/_serialization.py:176: FutureWarning: `torch.jit.load` is deprecated. Please switch to `torch.export`.
warnings.warn(
/home/runner/work/pack-mm/pack-mm/.venv/lib/python3.12/site-packages/torch/jit/_serialization.py:176: FutureWarning: `torch.jit.load` is deprecated. Please switch to `torch.export`.
warnings.warn(
Step Time Energy fmax
LBFGS: 0 07:07:58 -1420.947806 26.370228
LBFGS: 1 07:08:00 -1473.887774 6.297223
LBFGS: 2 07:08:01 -1495.307868 2.796887
LBFGS: 3 07:08:02 -1502.332220 1.798741
LBFGS: 4 07:08:04 -1505.853797 1.582420
LBFGS: 5 07:08:05 -1509.296897 1.542127
LBFGS: 6 07:08:07 -1512.257467 1.562981
LBFGS: 7 07:08:08 -1514.483556 1.497180
LBFGS: 8 07:08:09 -1517.104044 1.469545
LBFGS: 9 07:08:11 -1519.965651 1.434309
LBFGS: 10 07:08:12 -1522.113028 1.474840
LBFGS: 11 07:08:13 -1524.514389 1.368891
LBFGS: 12 07:08:15 -1526.827230 1.330121
LBFGS: 13 07:08:16 -1528.856271 1.291945
LBFGS: 14 07:08:17 -1530.627965 1.255548
LBFGS: 15 07:08:19 -1532.280445 1.220374
LBFGS: 16 07:08:20 -1533.921235 1.185527
LBFGS: 17 07:08:21 -1535.543146 1.151275
LBFGS: 18 07:08:23 -1536.867973 1.123256
LBFGS: 19 07:08:24 -1537.952482 1.099096
LBFGS: 20 07:08:25 -1539.076696 1.070046
LBFGS: 21 07:08:27 -1540.149636 1.036044
LBFGS: 22 07:08:28 -1541.019422 1.002921
LBFGS: 23 07:08:29 -1541.773165 0.970869
LBFGS: 24 07:08:31 -1542.488318 0.939566
LBFGS: 25 07:08:32 -1543.191376 0.908760
LBFGS: 26 07:08:33 -1543.874490 0.878487
LBFGS: 27 07:08:35 -1544.521649 0.848930
LBFGS: 28 07:08:36 -1545.122647 0.820246
LBFGS: 29 07:08:38 -1545.680023 0.792370
LBFGS: 30 07:08:39 -1546.209666 0.764963
LBFGS: 31 07:08:40 -1546.728923 0.737616
LBFGS: 32 07:08:41 -1547.244346 0.710104
LBFGS: 33 07:08:43 -1547.750498 0.682408
LBFGS: 34 07:08:44 -1548.235853 0.654641
LBFGS: 35 07:08:45 -1548.690588 0.626941
LBFGS: 36 07:08:47 -1549.111381 0.599398
LBFGS: 37 07:08:48 -1549.501326 0.572041
LBFGS: 38 07:08:49 -1549.866939 0.567489
LBFGS: 39 07:08:50 -1550.215864 0.570581
LBFGS: 40 07:08:52 -1550.554783 0.596167
LBFGS: 41 07:08:53 -1550.888161 0.597413
LBFGS: 42 07:08:54 -1551.217564 0.593959
LBFGS: 43 07:08:56 -1551.541543 0.645698
LBFGS: 44 07:08:57 -1551.856336 0.653548
LBFGS: 45 07:08:58 -1552.157888 0.625679
LBFGS: 46 07:09:00 -1552.443428 0.667565
LBFGS: 47 07:09:01 -1552.712544 0.691129
LBFGS: 48 07:09:02 -1552.967449 0.698551
LBFGS: 49 07:09:04 -1553.212700 0.693215
LBFGS: 50 07:09:05 -1553.454352 0.678287
LBFGS: 51 07:09:06 -1553.698167 0.655633
LBFGS: 52 07:09:08 -1553.947195 0.625211
LBFGS: 53 07:09:09 -1554.200379 0.615232
LBFGS: 54 07:09:10 -1554.455187 0.645703
LBFGS: 55 07:09:11 -1554.713487 0.627031
LBFGS: 56 07:09:13 -1554.972323 0.615182
LBFGS: 57 07:09:14 -1555.201216 0.664478
LBFGS: 58 07:09:15 -1555.430339 0.691248
LBFGS: 59 07:09:17 -1555.631542 0.681272
LBFGS: 60 07:09:18 -1555.836538 0.671091
LBFGS: 61 07:09:19 -1556.017928 0.656332
LBFGS: 62 07:09:20 -1556.179708 0.602136
LBFGS: 63 07:09:22 -1556.321602 0.520276
LBFGS: 64 07:09:23 -1556.442875 0.425343
LBFGS: 65 07:09:24 -1556.540089 0.337738
LBFGS: 66 07:09:26 -1556.611803 0.267273
LBFGS: 67 07:09:27 -1556.664937 0.214949
LBFGS: 68 07:09:28 -1556.707092 0.194480
LBFGS: 69 07:09:30 -1556.742671 0.173977
LBFGS: 70 07:09:31 -1556.772797 0.156386
LBFGS: 71 07:09:32 -1556.796046 0.143284
LBFGS: 72 07:09:33 -1556.812889 0.133453
LBFGS: 73 07:09:35 -1556.826297 0.123209
LBFGS: 74 07:09:36 -1556.838132 0.109470
LBFGS: 75 07:09:37 -1556.848042 0.092456
[4]:
viewer2=WeasWidget()
viewer2.from_ase(final)
viewer2.avr.model_style = 1
viewer2
[4]:
[ ]: