I-Ta Hsieh is a Ph.D. student in Materials Science at Brown University. His research specializes in Computational Materials Science, with a focus on atomistic simulations (MD, DFT), multi-scale modeling, and developing machine learning-based (PINNs) interatomic potentials. The overarching aim of his work is to uncover the underlying physical and chemical principles of materials to expedite the creation of innovative technologies.
DFT calculations were performed to confirmed the representing structure of Ni-rich NMC, elucidated the sequence of electron loss during charging, and provided a general relationship for the oxidation state change on each transition metal, offering a theoretical approach to get insights into the defects and oxidation in NMC cathodes.
Reconstruct and model the interlayer interactions of the Heterostructure and investigate the strain distribution using DFT and MD simulations.
The construction of a computationally efficient potential model for atomistic simulations of chemically complex materials with high fidelity to ab initio calculations is not a trivial task. An artificial neural network (ANN) model was demonstrated to be employed for efficient and accurate potential energy and forces evaluation of those chemically complex materials. My research focuses on enhancing the training efficiency and evaluation accuracy of ANN interatomic potential in the use of TensorFlow and LAMMPS.
A Monte-Carlo (MC) simulation is used to predict the evolution of hybrid organic−inorganic perovskite (MAFAPbIBr) microstructure, however, the acceptance rate of atom swapping is very low. Hence, we aim at creating a reinforcement learning agency to predict swapping policy that improves accepted probabilities of swapping in the Metropolis-Hastings algorithm and thus accelerates the simulation.
Bismuth telluride (Bi2Te3) is known as the best thermoelectric (TE) material at room temperature, having a zT value of about 1. To further increase the zT value, crystal defects, grain boundaries, and nanostructures have been fabricated on purpose to reduce the lattice thermal conductivity and possibly create the electron filtering phenomenon. We explore the influence of twin boundaries on the heat transfer capacity of twinned Bi2Te3 because of its great potential to have large zT values. The thermal boundary resistances (TBRs) of twin boundaries occurring at three different atomic layers (Te1, Bi, and Te2) of Bi2Te3 are investigated in the use of the non-equilibrium molecular dynamics (NEMD) simulation method.
We design a vehicle with a steering system made of two independently rotatable wheels on the front and quantify the effectiveness of the steering system in the mobility and maneuverability of the vehicle running in a box containing a layer of ping-pong balls with a packing density 0.8, below the random close packing value 0.84 in 2D. The steering system can reduce the resistance exerted by the jammed balls formed ahead of the fast-moving vehicle.
• IT Hsieh, Y Wu, B Li, Y Qi (2024). First-principles study of the structures and redox mechanisms of Ni-rich lithium nickel manganese cobalt oxides. Solid State Ionics 411 (2024) 116556
• YH Wang, CH Yeh, IT Hsieh, PY Yang, YW Hsiao, HT Wu, CW Pao, CF Shih (2024). Comparative Study of the Orientation and Order Effects on the Thermoelectric Performance of 2D and 3D Perovskites. Nanomaterials 2024, 14, 446.
• BH Lin, YC Chao, IT Hsieh, CP Chuu, CJ Lee, FH Chu, LS Lu, WT Hsu, CW Pao, CK Shih, JJ Su, and WH Chang (2023). Remarkably Deep Moiré Potential for Intralayer Excitons in MoSe2/MoS2 Twisted Heterobilayers. Nano Letters 2023 23 (4), 1306-1312
• IT Hsieh & MJ Huang (2019). An investigation into the thermal boundary resistance associated with the twin boundary in bismuth telluride. Nanoscale and Microscale Thermophysical Engineering, 23(1), 36–47.
• PY Lee, MC Tsai, IT Hsieh, PJ Tseng, GJJ Gao (2017). A vehicle with a two-wheel steering system mobile in shallow dense granular media. arXiv:1707.08716
• IT Hsieh & MJ Huang (2017, December 1–2). An investigation of the thermal boundary resistance associated with the twin boundary in bismuth telluride [Presentation]. 34th Annual CSME Conference, NCUT, Taichung, Taiwan.
• CP Huang & IT Hsieh (2020). Digital data anti-counterfeiting device and method. T.W. Patent Number I693816. Taiwan: Intellectual Property Office, MOEA(Taiwan).
• Machine learning and data science techniques for identifying descriptors of structure-property relationships in chemically complex materials
• Development of new simulation methods for computing structural, mechanical, thermal, and transport properties of materials based on the fundamental interactions of molecules
• Multi-scale modeling: ab Initio calculation, molecular dynamics simulation, Monte Carlo simulation.
• Information security for web server.
• High performance computation: parallel computing, quantum computing algorithm.