Expanding the horizons of machine learning in nanomaterials to chiral nanostructures
Abstract Machine learning holds significant research potential in the field of nanotechnology,
enabling nanomaterial structure and property predictions, facilitating materials design and …
enabling nanomaterial structure and property predictions, facilitating materials design and …
AI-driven inverse design of materials: Past, present and future
XQ Han, XD Wang, MY Xu, Z Feng, BW Yao… - Chinese Physics …, 2024 - iopscience.iop.org
The discovery of advanced materials is the cornerstone of human technological
development and progress. The structures of materials and their corresponding properties …
development and progress. The structures of materials and their corresponding properties …
Optical Properties Prediction for Red and Near‐Infrared Emitting Carbon Dots Using Machine Learning
Functional nanostructures build up a basis for the future materials and devices, providing a
wide variety of functionalities, a possibility of designing bio‐compatible nanoprobes, etc …
wide variety of functionalities, a possibility of designing bio‐compatible nanoprobes, etc …
AI-driven inverse design of materials: Past, present and future
H **ao-Qi, X Meng-Yuan, F Zhen, Y Bo-Wen… - Chin. Phys. Lett …, 2025 - cpl.iphy.ac.cn
The discovery of advanced materials is the cornerstone of human technological
development and progress. The structures of materials and their corresponding properties …
development and progress. The structures of materials and their corresponding properties …
[HTML][HTML] Fundamental Aspects and Advances in Thermoelectric Materials for Power Generation: A Numerical Simulation Case Study
BIA Ismail, JHI Abed - New Materials and Devices for …, 2023 - intechopen.com
Power generation using thermoelectric generator technology is becoming increasingly
attractive solution due to the ongoing substantial improvements in material engineering …
attractive solution due to the ongoing substantial improvements in material engineering …