Project Overview
In some of the more complex molecular simulation scenarios, or where compromise modeling is necessary, it is often difficult to directly logically match simulation results to experimental data. At this point, we need to correct these deviations through simple or in-depth mathematical modeling to ensure that the simulation results logically correspond to the experimental parameters to the greatest extent possible. Our team has experts in mathematics and physics who will apply their expertise and innovative thinking to solve these problems for you. By combining accurate molecular simulation with corresponding mathematical model formulas, we can ensure the scientificity and credibility of simulation results, making them closer to experimental observations.
Core advantage
Our mathematical modeling team, with a background in molecular simulation, has a deeper understanding and detailed insight into chemical and physical processes. We have a team of experienced Mathematica and MATLAB engineers who are skilled at scripting and solving complex mathematical models with ease. This comprehensive expertise enables us to provide efficient and accurate mathematical modeling services to our clients, ensuring that every challenge is effectively solved.
We are equipped with powerful computational resources and a wealth of software tools to support our team of engineers who are experienced in mathematical modeling and solving partial differential equations. This allows them to build models quickly and explore solutions efficiently. Relying on our powerful computing power, we are also able to quickly respond to and solve challenges in complex scenarios, ensuring timely and accurate service for customers.
Classic case
We use mathematical modeling method and molecular simulation to model and solve the diffusion process of drug molecules in crystals, and successfully calculate the key parameters such as diffusion coefficient. In this process, we pay special attention to the estimation of the deviation of theoretical predictions, and use high-performance computing resources to achieve this goal. By accurately calculating and taking into account deviations from predicted values, we ensure the stability and reliability of the final results. This approach not only improves the accuracy of the results, but also provides more reliable data support for our partners.