Skip To Main Content
Yingguang Li on Muck Rack

Yingguang Li

As seen in: Nature, Wiley Online Library, MDPI
Is this you? As a journalist, you can create a free Muck Rack account to customize your profile, list your contact preferences, and upload a portfolio of your best work. Claim your profile

Get in touch with Yingguang

Contact Yingguang, search articles and posts on X, monitor coverage, and track replies from one place.

Learn more about Muck Rack

Actions

Share this page

Is this you?

As a journalist, you can create a free Muck Rack account to customize your profile, list your contact preferences, and upload a portfolio of your best work.
Claim your profile

Articles

Negative temperature coefficient metamaterial absorber for uniform microwave heating

|
By Jing Zhou, Di Li, Lingfeng Xia, Shuting Liu, Guido Link, James Gao, Xiaozhong Hao, Lei Zhou, Yingguang Li, Xicheng Heng
| Nature Verified
Abstract Microwave heating is widely used in daily applications but is fundamentally limited by non-uniform temperature distribution. Despite extensive efforts to manipulate energy distribution around materials, achieving uniform heating remains elusive due to the intrinsic inhomogeneity of electromagnetic fields. Here, we report a self-regulating solution that adaptively modulates the absorbance distribution using a Negative Temperature Coefficient (NTC) Metamaterial Absorber (MA).
Open in Who Shared Issue with article?

[2509.12237] Neural Diffeomorphic-Neural Operator for Residual Stress-Induced Deformation Prediction

|
By Kaining Dai, Zhiwei Zhao, Tianyi Wu, Yingguang Li
| arXiv
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.
Open in Who Shared View Duplicates (404) Issue with article?

Diffeomorphism neural operator for various domains and parameters of partial differential equations - Communications Physics

|
By Yingguang Li
| Nature Verified
Abstract Solving partial differential equations (PDEs) across varying geometric domains and parameters represents a significant challenge in fields such as materials science, engineering, design and medical imaging, primarily due to the high computing cost associated with recomputing the solution for every change in geometry or parameters. This paper presents a neural operator learning framework for solving PDEs with various domains and parameters, named diffeomorphism neural operator (DNO).
Open in Who Shared Issue with article?
See all 7 articles