Battery materials involve complex material structure, electronic state properties and ion dynamics processes. Computational calculation and simulation can predict and guide the experimental research of related battery electrode materials effectively, helping to improve the energy storage density and life of the battery.
Energy storage technology plays a vital role in promoting energy production and consumption, energy revolution and the development of new energy formats. As one of the commonly used theoretical tools, molecular dynamics (MD) simulation has indispensable value in exploring the energy storage mechanism of energy storage materials, and can provide theoretical guidance and experimental basis for the design of energy storage devices with high-performance.
Alfa Chemistry employs theoretical calculation methods in MD simulation to effectively obtain the atomic level local information between the electrode/electrolyte interface, and provide mechanism explanations for some novel experimental discoveries that cannot be directly observed through experimental methods.
Figure 1. Schematics of molecular simulations of MOF-based supercapacitors. (Baskin, A.; Prendergast, D. 2017)
At Alfa Chemistry, we apply MD simulation to study the microscopic mechanism and dynamics of energy storage from the atomic level. Our fast and high-quality services include the following:
MD Simulation of Battery
- Cathode material
Construct a crystal structure
Study the energy and density of ion occupancy and vacancy, and predict battery voltage
- Anode material
Study the lithium ion intercalation and lithiation process
Estimate the volume expansion and structural stability of the material
- Lithium ion migration
Calculate ion mobility
Estimate the ionic resistance of a material
- Material interface
Study interface electronic properties (band structure, density of states) and ion properties (ion migration)
- Mechanism of new lithium battery
MD Simulation of Energy Storage Materials
- Constant potential and constant charge calculations
We can simulate the dynamic charging/discharging process by applying an external bias voltage to the double-layer calculation model through the constant potential method or constant charge method calculation method.
- Energy storage mechanism study
Our experts apply MD simulation method to investigate the charge storage mechanism of energy storage materials in confined environments, which is helpful for the design of supercapacitors with high energy density and high power density.
- Ion dynamics study
Ion kinetics and adsorption kinetics are another key factor that affects energy storage characteristics, which directly affect the power density of energy storage devices. Alfa Chemistry can also use molecular dynamics to simulate the charging power.
- Ion arrangement and kinetics study
Our Capabilities
- Construct and study the geometric structure and electronic state properties of the interface
- Study the battery system and simulate the charging and discharging process
- Modeling of various grain boundaries and interfaces of energy storage materials
- Use DFT and ForceField approaches to study ion diffusion kinetics. At Alfa Chemistry, the introduction of DFT self-consistent calculation can used to compensate for the charge change of ions during the diffusion process, which can reflect the diffusion process under the electric field.
- Support density functional tight-binding (DFTB) molecular dynamics simulation method
Our molecular dynamics simulation of battery and energy storage materials services remarkably reduce the cost, promote further experiments, and enhance the understanding of chemical process for customers worldwide. Our personalized and all-around services will satisfy your innovative study demands. If you are interested in our services, please don't hesitate to contact us. We are glad to cooperate with you and witness your success!
Reference
- Baskin, A.; Prendergast, D. Improving Continuum Models to Define Practical Limits for Molecular Models of Electrified Interfaces. Journal of The Electrochemical Society. 2017, 164(11): 3438-3447.