Battery Simulation for Materials Design

<p>Synopsys QuantumATK atomistic simulation software is used to design novel battery materials for cathodes and anodes, liquid and solid electrolytes, additives, solid electrolyte interphases (SEI) for denser and safer batteries for automotive and other industrial applications. It enables systematic selection of materials and performance optimization through co-design of structure and chemistry, shortening battery development time and reducing costs.</p>

Synopsys QuantumATK atomistic simulation software is used to design novel battery materials for cathodes and anodes, liquid and solid electrolytes, additives, solid electrolyte interphases (SEI) for denser and safer batteries for automotive and other industrial applications. It enables systematic selection of materials and performance optimization through co-design of structure and chemistry, shortening battery development time and reducing costs.

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Atomistic simulations with QuantumATK accelerate the battery research into new materials for cathode, anode, electrolytes, additives, and SEI to reach higher Li-ion diffusivity, electrochemical stability, higher capacity, lower cost, thermal stability, mechanical properties, etc. In addition to the leading Li-ion technology, use QuantumATK to investigate other novel technologies, including solid state batteries, Li-S, Li-metal, Li-air batteries and alternative ions to Li, such as Na or Mg. QuantumATK team provides customized and novel solutions, expertise and support during your entire battery material design journey. 

Also, discover Synopsys Simpleware solution  for optimizing battery performance with 3D imaging and simulation.

Battery Material Design Directions


  • Higher capacity and longer cycle life
  • Electrochemical stability (surface, bulk)
  • Lower scarce and expensive element, e.g., Co, content
  • Higher ion diffusivity


  • Suppressed dendrite formation
  • Mechanical properties (suppressed swelling, crack formation)
  • Electrochemical stability (SEI)
  • Graphite, Silicon and Li-metal anodes


  • Higher ion diffusivity at a wide range of temperatures
  • Electrochemical stability
  • Non-flammable  

Interfaces between materials

Addressing Alternative Technologies

  • Solid state batteries
  • Solid / Polymer electrolytes
  • Alternatives to Li-ion (Na, Mg, etc.)
  • Li-S batteries
  • Li-metal batteries
  • Li-air batteries

Battery Design Challenges for Cathode and Solid Electrolyte Materials

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QuantumATK Battery Simulation Application Examples

Li-ion Diffusivity in Cathode Under Electric Field

Gain deep understanding of Li-ion diffusion paths and mechanisms and screen materials with high Li-ion diffusivity and stable structures. In this example, Li-ion diffusivity (slope) is calculated in the LiFePO4 cathode material using molecular dynamics (MD) with an external electric field which drives the diffusion at different temperatures and different electric field strengths. Benefit from the multi-model approach, that combines classical Force Fields (FF) with DFT, the latter to include the effect of the field and of time-dependent charge fluctuations.

Case Study
Modules Used: DFT, Force Fields, MD, NanoLab GUI

Open-Circuit Voltage Profiles

Obtain a profile of open circuit voltage (OCV) that indicates lithiation of a cathode during battery charge /discharge processes using molecular dynamics (MD) tools. Optimize these processes by screening cathode materials for morphological evolution, degradation, and failure. This example shows a calculated open-circuit voltage profile of a Li-S battery.

Modules Used: Force Fields (ReaxFF), MD, NanoLab GUI

Li-ion Solvation in Liquid Electrolytes

Study Li-ion solvation in various liquid electrolytes (pure, binary or ternary mixtures) to find optimal electrolyte composition for high Li-ion diffusivity at a wide range of temperatures. In this example, Li-ion solvation, transference number, coordination number and diffusivity  are calculated in pure EC (ethylene carbonate), binary mixture of EC and DMC (dimethyl carbonate), ternary mixture adding PC (propylene carbonate) using molecular dynamics (MD) tools.

Modules Used: Force Fields (OPLS-AA), MD, NanoLab GUI

Li-ion Transport in SEI and Electrolytes

Predict Li-ion transport mechanisms (ballistic, trapping, diffusive) in solid electrolyte interphases (SEI) and electrolytes to screen materials (e.g., additives for SEI) with smaller trapping regions for faster charging of Li-ion batteries. In this example, Li-ion transport mechanisms are investigated in Li2EDC - dominant component of SEI, and EC electrolyte using long 10ns molecular dynamics (MD) simulations.

Modules Used: Force Fields (OPLS-AA), MD, NanoLab GUI

Formation of SEI at Anode Surfaces

Understand SEI formation mechanisms at anode surfaces to screen electrolytes and additives that help forming an initial SEI layer. This example shows how fluoroethylene carbonate (FEC) additive adsorbs on a lithiated Si anode surface and decomposes into different compounds depending on lithiated Si concentration and surface structure. Get insight into reaction paths and dominated interactions on realistic semi-infinite surfaces using the Surface NEGF method.

Modules Used: Surface NEGFNEBNanoLab GUI

Degradation Mechanisms at Cathode Surfaces

Investigate mechanism of cathode surface degradation due to chemical and electrochemical reactions with electrolytes and additives. Screen different electrolytes and investigate how to modify a cathode surface in order to suppress degradation and improve the surface chemical and electrochemical stability. This example investigates reaction paths and barriers for the LiNiO2 (104) cathode surface degradation due to reactions with ethylene carbonate (EC) electrolyte molecules under electric field using the Nudged Elastic Band (NEB) methodology. Benefit from the Surface NEGF method for studying realistic complex surfaces without artificial finite size effects of the slab model.

Modules Used: DFT, Surface NEGF, NEB, NanoLab GUI

Interface Band Engineering

Calculate interface band offsets and band diagrams to screen interface materials for target interface electron conductivities for optimal battery performance. This example investigates if ultra-thin films, such as LaAlO3, can be used for increasing electron conductivity at the cathode (Li0.9CoO2)/current collector (SrTiO3) interface to improve the battery performance of the solid-state battery. Also, simulate the effect of thin films between anode and electrolytes to decrease electron conductivity for suppressing dendrite formation. Benefit from running DFT-LCAO calculations on large interface structures at a low computational cost.

Modules Used: DFTNanoLab GUI, Interface Builder

Electron Transport at Cathode/Electrolyte Interfaces

Simulate electron transport at cathode/electrolyte interfaces to screen materials for good interface electron conductivity. This example investigates Li2O2/Li2CO3 interfaces in a Li-air battery, showing that the presence of Li2O2/Li2CO3 interfaces and Li vacancies in Li2O2 has a substantial negative effect on the coherent electron transport/conductivity in a Li-air battery. Benefit from the NEGF-DFT method to simulate electron transport.

Modules Used: DFT, NEGF (electron transport), NanoLab GUI

Polymer Electrolyte Membranes

Investigate structural and electronic properties of polymer electrolytes. This example shows simulation of structure and electronic properties of poly(ethyleneoxide) (PEO) polymer. Benefit from automatic workflows for generating polymers and adding external ions or particles. Also, benefit from running DFT-LCAO calculations on large polymer structures (3500+ atoms), even with hybrid functionals such as HSE.

Polymer Simulation Webpage
Modules Used: ForceFields, DFT (HSE-LCAO), NanoLab GUI, Polymer Builder

Article on Making Batteries Safer and Denser

Learn about the role of atomistic simulations of materials on making batteries denser and safer.

"When there are so many more elements involved, the complexity simply scales out of hand for you to do experimental work on all conditions. This is a place where atomistic simulations could accelerate the battery research into new materials".

Semiconductor Engineering Article

Key Advantages of QuantumATK for Battery Simulation

Why QuantumATK (Video)

Realistic Physics of Complex Materials

  • DFT-LCAO to simulate large systems at low computational cost
  • Hybrid DFT functionals (HSE06, B3LYP, PBE0) for accurate formation energies and electronic structure
  • Machine-Learning Force Fields for Li-diffusion in cathode and solid electrolytes. Automatic generation of training data, active learning, Moment Tensor Potentials

Synergistic Solution

  • Multi-level simulations to combine different engines in one workflow (e.g., combine Force Field and DFT)
  • Ionic transport using advanced molecular dynamics (MD) framework with hook functions and analysis tools (e.g., for applying electric field during an MD simulation)
  • Electron transport at interfaces with the NEGF-DFT method
  • Surface NEGF for studying realistic complex surfaces without artificial finite size effects of the slab model

Effective Tools

  • Workflows for generating complex structures, e.g., amorphous structures, nanostructures, interfaces, polymers, liquids, etc. with GUI support
  • Tools for materials screening
  • Convenient analysis tools in GUI to extract the relevant quantities
  • Convenient access to databases containing novel battery material structures (e.g., Materials Project)

Highlighted QuantumATK Papers on Battery Simulation

[1] S. Jamil, A. B. Yousaf, S. H. Yoon, D. S. Han, L. Yang, P. Kasak, X. Wang,  “Dual cationic modified high Ni-low co layered oxide cathode with a heteroepitaxial interface for high energy-density lithium-ion batteries”, Chem. Engin. J. 416, 129118 (2021).

[2] H. Dua, J. Deb, D. Paul, and U- Sarkar, “Twin-graphene as a promising anode material for Na-ion rechargeable batteries”, ASC Appl. Nano Mater. 2, 4, 4912 (2021).

[3] S. Xu, Y. Yin, H. Niu, X. Wang, C. Shao, K. Xi, Z. Zhang, Y. Guo, “Adsorption and diffusion of alkali atoms on FeX2 (X=Se, S) surfaces for potassium-ion battery applications”, Appl. Surf. Sci. 536, 14774 (2021).

[4] D. Bauer, and M. Luisier, “Influence  of disorder and surface roughness on the electrical and thermal properties of lithiated silicon nanowires”, J. Appl. Phys. 127, 135101 (2020).

[5] C. Yang, X. Zhang, J. Li, J. Ma, L. Xu, J. Yang, S. Liu, S. Fang, Y. Li, X. Sun, X. Yang, F. Pan, J. Lu. D. Yu, “Holey graphite: A promising anode material with ultrahigh storage for lithium-ion battery”, Electroch. Acta 346, 136244 (2020).

[6] S. Upadhyay, P. Srivastava, “Modelling of antimonene as an anode material in sodium-ion battery: A first-principles study”, Mat. Chem. Phys. 241, 122381 (2020).

[7] T. Wang, C. Li, C. Xia, L. Yin, Y. An, S. Wei, X. Dai, “Silicene/BN vdW heterostructure as an ultrafast ion diffusion anode material for Na-ion battery”, Physica E 122, 114146 (2020).  

[8] X. Zhang, S. Li, J. Li, M. Ye, Z. Song, S. Jin, B. Shi, Y. Pan, J. Yan, Y. Wang, J. Zheng, F. Pan, J. Liu, “Absorption and diffusion of lithium on layered InSe”, Comp. Cond. Matt. 21 (2019).

[9] Y. Yu, D. Chen, S. Gao, J. Huang, S. Hu, H. Yang, and G. Jin, “The surface passivation of Ge(100) and Ge(111) anodes in Ge-air batteries with different doping types and concentrations”, RSC Adv. 9. 39582 (2019).

[10] Y. S. Mekonnen, J. M. Garcia-Lastra, J. S. Hummelshøj, C. Jin, and T. Vegge, “Role of Li2O2@Li2Co3 interfaces on charge transport in nonaqueous Li-Air Batteries”, J. Phys. Chem. C 119, 18066 (2015).

Learn more about QuantumATK products

Interested in applying QuantumATK software to your research? Test our software or contact us at to get more information on QuantumATK platform for atomic-scale modeling.