This inventor holds 1 USPTO granted patent and 2 published patent applications. Top assignee: Shenzhen Jingtai Technology Co., Ltd.. Active years: 2021.
Company Filing History:
Years Active: 2021
Title: Yingdi Jin - Innovator in Computational Chemistry
Introduction
Yingdi Jin is a prominent inventor based in Guangdong, China. He has made significant contributions to the field of computational chemistry, particularly in the area of fitting repulsive potentials through Density Functional Tight Binding (DFTB) methods. His innovative approach has the potential to enhance the efficiency and accuracy of molecular simulations.
Latest Patents
Yingdi Jin holds a patent titled "Method for automatically and efficiently fitting repulsive potentials through DFTB." This method involves several key steps, including optimizing a molecule containing an atomic pair and performing a spacing scan on the atomic pair according to an acting interval of repulsive potentials. The process includes high-accuracy energy calculations, difference calculations to obtain second-order derivatives of force and energy, and saving the results into a database. The method ultimately transforms target values of repulsive potentials into splines and constructs a training set for fitting the repulsive potentials through singular value decomposition. He has 1 patent to his name.
Career Highlights
Yingdi Jin is currently employed at Shenzhen Jingtai Technology Co., Ltd. His work at the company focuses on advancing computational methods that can be applied in various scientific and industrial contexts. His innovative contributions have positioned him as a valuable asset in the field of computational chemistry.
Collaborations
Yingdi Jin collaborates with talented individuals such as Qun Zeng and Peiyu Zhang. Their combined expertise fosters a productive environment for innovation and research.
Conclusion
Yingdi Jin's work in developing efficient methods for fitting repulsive potentials showcases his dedication to advancing computational chemistry. His contributions are paving the way for more accurate molecular simulations and enhancing the understanding of molecular interactions.