4.1. Mg-Y alloy system
4.1.1. Introduction
We will briefly analyze the candidate configurational space of a metallic system by taking Mg-based Mg-Y binary alloy as an example. In atomistic simulations on metallic materials, defects (point defects, dislocations, grain boundaries, etc.) are usually concerned. In order to meet the requirements in these simulations, the potential should have correct descriptions on:
Non-defective Mg and Mg-Y solid solutions with HCP, BCC, and FCC structures, and Mg-Y compounds (Mg24Y5, Mg2Y, MgY). For example, lattice parameters, cohesive energy, elastic properties. Since we are concerned with Mg-based alloys, the concentrations of Y in solid solutions are limited to be lower than 20 at. % (the highest solid solution concentration of Y in Mg is 3.75 at. %, as shown in the Mg-Y phase diagram). However, the local concentration of Y may be higher due to segregation, e.g. around dislocations or grain boundaries. 20 at. % of Y is close to the first stable Mg24Y5 compound in the Mg-rich end in Mg-Y phase diagram. NO NEED to explore the full concentration. This will save lots of time and money.
Typical defects in Mg-Y system, including, vancancies, intersititials, dislocations, twins, stacking faults, grain boundaries, and surfaces. For example, the formation energies of defects, the interaction between solid solutes and defects.
Armophous structures. Even though we are not concerned with Mg-Y melts, local high-energy regions in simulations may exhibit amorphous-like structures, e.g. high-energy grain boundaries at high temperatures.
In our work, we are concerned with the interaction between the solute atom Y and dislocations, grain boundaries, and evaluating the solute segregation effects on properties of these defects. Therefore, our final DP model should meet all the requirements listed above. In addition, the DP should also be stable to achieve long-time simulation at large scales, since the simulation time is as long as tens of nanoseconds in systems with tens of thousands of atoms. Thus, the DP should be stable enough to do the simulation.
Therefore, we divided the task into the following steps during the DP-GEN process:
Only perfect crystals of Mg, Y, Mg-Y solid solutes (HCP, BCC, and FCC) and Mg-Y compounds (Mg24Y5, Mg2Y, MgY) were considered. During this stage, hybrid MC/MD simulations with npt-iso, npt-aniso or npt-tri ensemble will be used to sample both changes in local chemical configurational space and in local spacial configurational space (vibrations of atoms from their equilibrium positions).
Defective structures, including interstitials, vacancies, stacking faults, and surfaces, were constructed and sampled with similar strategies as those in the first stage. The defective structures were only constructed for pure Mg and Mg-Y solid solutions. Usually, a dislocation model is too large to be calculated by DFT with high precision. Therefore, dislocations are not explicitly included. During this stage, the temperatures were limited to a value that was not too high, e.g. 0.5Tm (Tm is the melting point of Mg). For surface models, nvt ensembles were preferred. Therefore, artificial deformations can be applied to the simulation cells .
Amorphous (liquid) structures with different densities and Y concentrations were considered, which are obtained by burning the above structures to high temperatures at different pressures (to change their density). During this stage, hybrid MC/MD simulations with npt-iso ensemble will be used to ensure that the shape of a simulation cell is reasonable, since the cell shape of an amorphous may change to an unreasonable one in npt-aniso or npt-tri ensemble. Alternatively, hybrid MC/MD simulations with nvt ensemble can also be adopted, if amorphous structures can be well constructed.
4.1.2. Folder Structure
A typical folder structure of DP-GEN process can be set as following:
Mg-Y (The name of your project)
|—-pseudopotentials (pseudopotentials for elements, e.g. Mg: PAW_PBE, Y: PAW_PBE_sv)
|—-input_fp (input files of the DFT calculations, including single-point calculation, relaxation and MD simulation)
|—-init (generating initial data by DP-GEN “init_bulk” or “init_surf”, other initial DFT data generated by yourself or downloaded from the DP library )
|—-run (auto iteration folder for DP-GEN run)
|—-train_test (training and testing DP models after finished DP-GEN)
|—-autotest (test properties by DP-GEN autotest)
4.1.3. Preparing Files
By checking the DP library, we can find that there are some data for Mg substance. Therefore, these data are downloaded and taken as part of the inital data.
The examplory files are attached: init_bulk param.json, run param.json. machine-alo.json
{
"stages" : [1,2,3,4],
"elements": ["Mg","Y"],
"cell_type": "bcc",
"latt": 5.160,
"super_cell": [2, 2, 2],
"from_poscar": true,
"from_poscar_path": "./POSCAR",
"potcars": ["/data/wangyinan/wangyinan/Mg-Y/files/POTCAR_Mg","/data/wangyinan/wangyinan/Mg-Y/files/POTCAR_Y"],
"relax_incar": "/data/wangyinan/wangyinan/Mg-Y/files/INCAR_rlx",
"md_incar" : "/data/wangyinan/wangyinan/Mg-Y/files/INCAR_md",
"skip_relax": true,
"scale": [0.97, 1.00, 1.03],
"pert_numb": 20,
"md_nstep" : 5,
"pert_box": 0.03,
"pert_atom": 0.01,
"coll_ndata": 5000,
"type_map" : ["Mg","Y"],
"_comment": "that's all"
}
{
"type_map": ["Mg","Y"],
"mass_map": [24.3,89],
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"training_reuse_old_ratio": 0.9,
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"neuron": [25,50,100],
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"disp_file": "lcurve.out",
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"load_ckpt": "model.ckpt",
"disp_training": true,
"time_training": true,
"profiling": false,
"profiling_file": "timeline.json",
"_comment": "that's all"
}
},
"_comment": " 01.model_devi ",
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"model_devi_skip": 0,
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},
{
"_idx": 45,
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}
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"fp_accurate_threshold": 0.9995,
"fp_pp_path": "/data/wangyinan/wangyinan/Mg-Y/files/",
"fp_pp_files": [
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],
"fp_incar": "./INCAR_scf",
"fp_params": {},
"_comment": " that's all "
}
{
"train": [
{
"machine": {
"batch": "shell",
"hostname": "",
"password": "",
"port": 22,
"username": "root",
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"cloud_resources": {
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"AccessKey_ID":"",
"AccessKey_Secret":"",
"regionID": "cn-shanghai",
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"img_name": "kit-1.2.0",
"address": "public",
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],
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}
},
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},
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{
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"password": "",
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"instance_name": "MgY_modevi_yinan",
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}
},
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},
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{
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"password": "",
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],
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}
},
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"source_list": ["/opt/intel/parallel_studio_xe_2018/psxevars.sh"],
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},
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}
]
}