AlphaNet-v1-OAM

Version: v1 Added: 2025-05-12 Published: 2025-05-12 4.65M parameters
Repo Paper Docs DOI Files PR Checkpoint
Predictions
DiscoveryGeometry OptimizationDiatomicsMolecular DynamicsκSRME
Leaderboard ranks CPS #23 /41Discovery F1 #14 /52Geo Opt RMSD #27 /42Phonons κSRME #33 /41MD CMDS #13 /34Diatomics CDS #6 /33

Discovery: energy and convex hull diagnostics

Missing preds: 0

Per-element convex hull distance errors

1 H 0.13
2 He Helium
3 Li 0.03
4 Be 0.04
5 B 0.06
6 C 0.05
7 N 0.09
8 O 0.15
9 F 0.11
10 Ne Neon
11 Na 0.03
12 Mg 0.04
13 Al 0.05
14 Si 0.06
15 P 0.06
16 S 0.08
17 Cl 0.10
18 Ar Argon
19 K 0.04
20 Ca 0.04
21 Sc 0.04
22 Ti 0.04
23 V 0.06
24 Cr 0.09
25 Mn 0.11
26 Fe 0.09
27 Co 0.04
28 Ni 0.04
29 Cu 0.04
30 Zn 0.04
31 Ga 0.04
32 Ge 0.05
33 As 0.06
34 Se 0.09
35 Br 0.08
36 Kr Krypton
37 Rb 0.04
38 Sr 0.04
39 Y 0.04
40 Zr 0.04
41 Nb 0.06
42 Mo 0.05
43 Tc 0.04
44 Ru 0.05
45 Rh 0.05
46 Pd 0.05
47 Ag 0.04
48 Cd 0.03
49 In 0.05
50 Sn 0.05
51 Sb 0.06
52 Te 0.12
53 I 0.07
54 Xe 0.05
55 Cs 0.04
56 Ba 0.04
57 La 0.04
58 Ce 0.04
59 Pr 0.03
60 Nd 0.03
61 Pm 0.03
62 Sm 0.03
63 Eu 0.06
64 Gd 0.04
65 Tb 0.03
66 Dy 0.04
67 Ho 0.03
68 Er 0.03
69 Tm 0.03
70 Yb 0.04
71 Lu 0.03
72 Hf 0.04
73 Ta 0.08
74 W 0.06
75 Re 0.04
76 Os 0.05
77 Ir 0.07
78 Pt 0.06
79 Au 0.06
80 Hg 0.03
81 Tl 0.03
82 Pb 0.06
83 Bi 0.04
84 Po Polonium
85 At Astatine
86 Rn Radon
87 Fr Francium
88 Ra Radium
89 Ac 0.03
90 Th 0.05
91 Pa 0.05
92 U 0.06
93 Np 0.09
94 Pu 0.20
95 Am Americium
96 Cm Curium
97 Bk Berkelium
98 Cf Californium
99 Es Einsteinium
100 Fm Fermium
101 Md Mendelevium
102 No Nobelium
103 Lr Lawrencium
104 Rf Rutherfordium
105 Db Dubnium
106 Sg Seaborgium
107 Bh Bohrium
108 Hs Hassium
109 Mt Meitnerium
110 Ds Darmstadtium
111 Rg Roentgenium
112 Cn Copernicum
113 Nh Nihonium
114 Fl Flerovium
115 Mc Moscovium
116 Lv Livermorium
117 Ts Tennessine
118 Og Oganesson
57-71 La-Lu Lanthanides
89-103 Ac-Lr Actinides

ML vs DFT Lattice Thermal Conductivity

Model Authors

  1. Bangchen Yin  Tsinghua University  
  2. Jiaao Wang  University of Texas at Austin  
  3. Weitao Du  DAMO Academy, Alibaba Inc  
  4. Yuanqi Du  Cornell University  
  5. Chenru Duan  Deep Principle, Inc  
  6. Carla P. Gomes  Cornell University  
  7. Graeme Henkelman  The University of Texas at Austin  
  8. Hai Xiao  Tsinghua University  

Trained By

  1. Bangchen Yin  Tsinghua University  

Model Info

  • Version v1
  • Role Interatomic potential
  • Architecture gnn
  • Targets EFSG
  • Openness OSOD
  • Discovery Train Task S2EFS
  • Discovery Test Task IS2RE-SR

Training Set

MPtrj: 1.58M structures from 146k materials

OMat24: 101M structures from 3.23M materials

Subsampled Alexandria: 10.4M structures from 3.23M materials

description

AlphaNet is a local frame-based equivariant model designed to tackle the challenges of achieving both accurate and efficient simulations for atomistic systems. AlphaNet enhances computational efficiency and accuracy by leveraging the local geometric structures of atomic environments through the construction of equivariant local frames and learnable frame transitions.

Hyperparams

  • evaluation: {"max_force":0.03,"max_steps":500,"ase_optimizer":"FIRE","cell_filter":"FrechetCellFilter","kappa":{"protocol":"phonondb-v1","displacement_distance":0.03}}
  • architecture: {"n_layers":4,"graph_construction_radius":5,"max_neighbors":50}
  • training: {"batch_size":256,"initial_learning_rate":0.0002,"epochs":4,"optimizer":"Adam"}
  • upstream_config: {"loss":"MAE","loss_weights":{"energy":4,"force":100,"stress":10},"learning_rate_schedule":"StepLR(decay_steps=10000, decay_ratio = 0.93)","n_hidden_channels":176,"n_bessel_basis":8,"n_heads":24}

Dependencies