At present, a common problem in the research and development of new materials worldwide is: The time span for new materials from research and development to market application is very long. With the rapid development of computer technology, computational simulation has become one of the important tools for studying the structure and properties of functional materials. The simulation and calculation of material properties makes the research and development of materials more directional and forward-looking, which plays a crucial role in innovation research, and can greatly improve research efficiency. Algorithms based on machine learning can achieve efficient screening of functional materials through the simulation of material properties. Based on this, scientists have combined machine learning and density functional theory high-throughput calculations to propose single-target/multi-target property-oriented functional materials screening methods. At Alfa Chemistry, our functional material properties simulation platform can be used to calculate various properties of materials, in which different simulation methods are implemented based on the type of material. We can explore the relationship between structure and properties of functional materials using research methods that combine computational simulation, experiment and theoretical analysis. We have established an efficient and integrated simulation technology with high-throughput computing mode, aiming to provide useful guidance for the development of new functional materials.
Application of Functional Materials Properties Simulation
- Provide property parameters for many material manufacturing processes
- Assist in material design
- Assist in material design technology (such as casting, forging, extrusion, etc.)
- Save a lot of project time and experiment costs
- Provide references for basic research such as thermodynamic calculations
Figure 1. Hierarchical structures of complex materials. (Goodwin, A. L. 2019)
Our Simulation Services
With the deepening of quantum chemistry research and the improvement of computing software, they play an important role in the process of scientific research and chemistry teaching. We apply multiple quantum chemistry computing software to provide functional materials properties simulation services in a competitive fashion. We have prepared the most convenient services for you.
- Adsorption Energy Calculation
- Computation of Coefficient of Thermal Expansion
- Computation of HOMO/LUMO-level, EA, IP, Redox Potential, Electrical Conductivity
- Computation of Phase Interactions
- Determination of Dynamics and Stability of Particles
- Determination of Melting-, Boiling-, Glass Transition Temperatures
Adsorption energy calculation plays an important role in the exploration of the adsorption mechanism and the chemical engineering properties study. At Alfa Chemistry, we have established a modified process for calculating the adsorption energy using various calculation methods such as density functional theory (DFT), cluster model and molecular simulation methods.
Different forms of objects including solids, liquids, and gases have thermal expansion process in which an object or body expands on the application of heat. Our teams mainly apply ab-initio density functional theory calculations and electron localized function to calculate the coefficient of thermal expansion, helping to measure the thermal stability of the material effectively.
At Alfa Chemistry, our scientists apply self-consistent field calculation using Hartree Fock approximation to perform HOMO/LUMO-level calculation. A DFT method has been established to calculate the electron affinity and ionization potential. In terms of the calculation of redox potentials of metal complexes, we support a DFT-based molecular dynamics protocol. Moreover, our teams have developed a neural network computation, ab-initio molecular dynamics and DFT to estimate electrical conductivity of the metal.
In general, composite materials are composed of two phases and there is an interface between the two phases. We offer a diversity of models for computing the phase interactions between two phases. The particle pinning model, the solute drag model and faceted anisotropy are available for the description of the grain boundary migration.
We investigate the dynamics of particle motion and bodies in rigid planar motion from two aspects: kinematics and kinetics. Our teams are capable of using a DFT method, bivariate dynamic model, Derjaguin-Landau-Verwey-Overbeek method and gravitational search algorithm to study the dynamics and stability of particles.
In order to measure the relationship between the physical properties of substances and temperature, our scientific staffs conduct thermal analysis to simulate and determine the melting temperature, boiling temperature and glass transition temperature using molecular dynamic (MD) simulation.
Figure 2. Simulation workflow from material selection to macroscopic property prediction. (Zhao, H.; et al. 2016)
- Determination of Morphology of Big Material Systems
- Key Property Prediction of Organic Electronic Materials
- Molecular Dynamics Simulation of Battery and Energy Storage Materials
- Molecular Modeling of Polymers
- Prediction of Assembly and Stability of Emulsions
- Simulation of Key Mechanical, Electronic, Magnetic and Dielectric Properties
Computational simulation is a powerful tool to study the relationship between material structure and material properties by reproducing the morphology of material. We use DFT calculation, MD simulation, phase field method simulation and Monte Carlo method to predict the structure and properties of some big material systems, thereby accelerating the development of new materials.
At Alfa Chemistry, we are capable of using ab initio method, molecular dynamics simulation and artificial intelligence technologies to perform accurate property prediction of organic electronic materials, helping to accelerate the design and optimization of novel organic electrical materials.
Nowadays, MD simulation has proven an effective technique to obtain the atomic level local information between the electrode/electrolyte interface. We have abilities in using MD method to to study the microscopic mechanism and dynamics of energy storage from the atomic level, as well as provide mechanism explanations for some novel experimental discoveries that cannot be directly observed through experimental methods.
The modeling of polymer materials, and the simulation of thermo-mechanics and other properties of polymer have always been a challenge for scientists. Alfa Chemistry provides various simulation methods, advanced techniques and automated amorphous polymer modeling tools to support the construction of multiple polymer models.
The self-assembly process of emulsion system and emulsion stability have always been the focus and challenges of emulsion research. Multiscale molecular dynamics simulation methods are applied to the prediction of assembly of emulsions by investigating assembly mechanism of emulsion systems. In addition, we perform MD simulations to reveal the characterization of the interactions and microstructures in the emulsion, helping to study the stabilization mechanism of the oil-water interface.
At Alfa Chemistry, our experienced experts have created a hybrid discrete-continual model to describe the mechanical properties for various levels of deformations. A semi-empirical quantum mechanics program based on tight-binding density functional (DFTB) method is available to simulate the electronic properties of materials. We introduce the magnetic anisotropy energy (MAE) simulation to study the magnetic properties of a material. In addition, our experts propose a technique combining molecular dynamics and DFT to determine the frequency-dependent dielectric properties of materials.
- Flexible and advanced computational methods
- personalized and customized innovative scientific research services
- Cost-efficient and time-saving
Our functional materials properties simulation services remarkably reduce the cost, promote further experiments, and enhance the understanding of catalytic reactions 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!
- Goodwin, A. L. Opportunities and challenges in understanding complex functional materials. Nature Communications. 2019, 10(1).
- Zhao, H.; et al. Perspective: NanoMine: A material genome approach for polymer nanocomposites analysis and design. Apl Materials. 2016, 4, 053204.