NIMS-OS: an automation software to implement a closed loop between artificial intelligence and robotic experiments in materials science

Figures & data

Figure 1. Image of the combinations of AI algorithms and robotic systems via NIMS-OS.

Figure 2. Procedures in NIMS-OS and roles of each Python scripts.

Figure 3. (Top panels) Examples of the candidates files of the initial stage and that after some experiments. Here, an example for the case that $N=9$ is shown. (Bottom panels) Examples for the list of descriptors depending on the types of search space. If the continuous parameter space is considered, $D=\{{\mathbf{x}}_i{\}}_{i=1,\dots ,N}$ is the discretized parameters. When the combination of materials is the search space, the bit strings where the material used is represented by 1 and the material not used is represented by 0 are prepared in $D=\{{\mathbf{x}}_i{\}}_{i=1,\dots ,N}$. Furthermore, materials descriptors from compositions obtained by such as magpie [36,37] and fingerprint of molecules obtained by such as RDKit [38] would be used as $D=\{{\mathbf{x}}_i{\}}_{i=1,\dots ,N}$.

Figure 4. Operation screen of the NIMS-OS GUI version.

Table 1. List of 16 types of additives used in an automated exploration for new electrolytes using the NAREE system. For all additives, the solvent is fixed as TEGDME.

ID	Additive	Concentration
1	lithium bis(pentafluoroethanesulfonyl)imide (LiBETI)	100 mM
2	LiPF6	100 mM
3	LiBF4	100 mM
4	lithium bis(trifluoro methanesulfonyl)imide (LiTFSI)	100 mM
5	LiTfO	100 mM
6	LiClO4	100 mM
7	lithium bis(oxalate)borate (LiBOB)	10 mM
8	LiAsF6	10 mM
9	LiF	10 mM
10	N-methyl-2-pyrrodione (NMP)	2 vol.%
11	sulfolane	2 vol.%
12	dimethyl sulfoxide (DMSO)	2 vol.%
13	propylene carbonate (PC)	2 vol.%
14	ethylene carbonate (EC)	2 vol.%
15	fluoroethylene carbonate (FEC)	2 vol.%
16	vinylene carbonate (VC)	2 vol.%

Figure 5. Output results from NIMS-OS for automated exploration for electrolytes using the NAREE system: (a) history_step.png and (b) history_best.png by nimsos.Visualization.plot_history and (c) distribution.png by nimsos.Visualization.plot_distribution.plot. The target property is the discharge time and its unit is seconds. In the first cycle, RE is used to generate initial states. After the second cycle, PHYSBO is used.

Table 2. Top 10 compositions that enhanced the discharge time. The found cycle number is also shown.

Ranking	Additive 1	Additive 2	Additive 3	Additive 4	Additive 5	Discharge time	Found cycle
1	100 mM LiPF6	100 mM LiTFSI	2 vol.% PC	2 vol.% FEC	2 vol.% VC	1439.09 s	7th
2	100 mM LiBETI	100 mM LiTfO	10 mM LiBOB	2 vol.% EC	2 vol.% FEC	1401.97 s	12th
3	2 vol.% NMP	2 vol.% sulfolane	2 vol.% DMSO	2 vol.% PC	2 vol.% FEC	1374.86 s	9th
4	100 mM LiBF4	100 mM LiTFSI	100 mM LiTfO	10 mM LiF	2 vol.% FEC	1365.57 s	9th
5	100 mM LiBETI	100 mM LiBF4	10 mM LiBOB	2 vol.% PC	2 vol.% FEC	1364.32 s	12th
6	100 mM LiTFSI	100 mM LiTfO	10 mM LiAsF6	2 vol.% FEC	2 vol.% VC	1358.99 s	10th
7	100 mM LiBETI	10 mM LiBOB	10 mM LiF	2 vol.% EC	2 vol.% VC	1357.43 s	10th
8	100 mM LiBETI	100 mM LiTFSI	10 mM LiBOB	10 mM LiF	2 vol.% FEC	1356.39 s	9th
9	100 mM LiBF4	100 mM LiTFSI	100 mM LiClO4	2 vol.% sulfolane	2 vol.% VC	1347.23 s	11th
10	100 mM LiPF6	100 mM LiTfO	10 mM LiAsF6	10 mM LiF	2 vol.% EC	1346.72 s	7th

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