I am a computational physicist with a strong interest in turning physical models into practical
simulation workflows. My work spans first-principles calculations, computational electromagnetics,
and multiphysics structural modeling for heterogeneous and multiscale systems.
I am particularly interested in combining analytical modeling, numerical simulation,
and experimental measurements to relate material-level mechanisms to measurable device and structural behavior.
"Density Functional Theory Simulation in Material Science," Invited Talk, Summer Lecture, National Taipei University of Technology, July, 2019
"Use of Density Functional Theory in the Design and Fabrication of Materials," Invited Talk, PhD Seminar, Khalifa University, December, 2018
"In Depth Wettability Nano Scale Investigation: Interesting Carbonate Case Study in Society of Petroleum Engineers," Invited Talk, ESG monthly meeting, December 2017
Selected Research Areas
These selected research areas highlight the physical problems, modeling approaches, and representative systems
that connect my work in first-principles simulation, multiscale materials modeling, optics, and multiphysics analysis.
2D Materials Studies
This work combines local probe measurements and first-principles analysis to study graphene-coated interfaces and other low-dimensional material systems. The emphasis is on how interfacial structure and surface energetics influence measurable behavior, which is directly relevant to functional heterostructures, surface engineering, and materials characterization. The related work has been published in Nanoscale, which could be accessed here.
The figure below compares local surface-energy behavior for graphene-coated substrates prepared by different routes.
Surface Wettability Studies
This research develops first-principles routes for predicting wettability, adhesion, and interfacial energetics in solid–liquid and multiphase systems. It connects atomistic calculations to engineering observables such as contact angle and spreading behavior, and is relevant to surface design, interfacial materials, and physics-based materials screening. The related work has been published in Journal of Physical Chemistry Letters, which could be accessed here.
The figure below illustrates an atomistic workflow for predicting macroscopic wetting behavior from surface-specific calculations.
Interfacial Solar Vapor Generators
This work combines device design, thermal transport analysis, and multiphysics simulation to understand interfacial solar vapor generation under realistic operating conditions. It reflects a broader interest in linking material properties, heat transfer, and system-level performance in engineered energy devices. The related work has been published in Joule, which could be accessed here.
The figure below compares measured and simulated temperature fields for the vapor generator under different illumination conditions.
Plasmonic Nanocomposite Solar Absorbers
This research uses electromagnetic simulation, nanocomposite design, and experiment to develop broadband optical absorbers with scalable thin-film architectures. The work sits at the interface of photonic materials engineering and structure–property design, and is closely aligned with computationally guided materials discovery for functional coatings and optical materials. The related work has been published in Advanced Optical Materials, which could be accessed here.
The figure below shows how embedded metallic nanoparticles strengthen light–matter interaction in nanocomposite absorber films.
Plasmon-Enhanced Nanoporous Absorbers
This work focuses on wave-based design of ultrathin absorbing structures by combining thin-film interference with localized plasmonic effects. It highlights a physics-driven route for engineering optical response through geometry, materials selection, and simulation, which aligns well with advanced materials design and device-oriented computational research. The related work has been published in Advanced Optical Materials, which could be accessed here.
The figure below illustrates an ultrathin broadband absorber in which pore-shaped metallic features activate localized plasmonic enhancement.
B. Alfakes, J. E. Villegas, H. Apostoleris, R. S. Devarapalli, S. R. Tamalampudi, J.-Y. Lu, J. Viegas, I. Almansouri, and M. Chiesa,
"Optoelectronic Tunability of Hf Doped ZnO for Photovoltaic Applications,"
Journal of Physical Chemistry C, vol. 123, no. 24, pp. 15258-15266, May 2019
J.-Y. Lu, A. Raza, N. X. Fang, G. Chen, and T. J. Zhang,
"Optical Characterizations of Plasmonic Nanocomposites,"
The 8th Annual International Workshop on Advanced Materials, Feb. 21-23, 2016, Ras Al Khamiah, UAE
S. Noorulla, J.-Y. Lu, S. H. Nam, N. X. Fang, and T. J. Zhang,
"Plasmon-Enhanced Solar Absorbers,"
The 8th Annual International Workshop on Advanced Materials, Feb. 21-23, 2016, Ras Al Khamiah, UAE
J.-Y. Lu, and Y. H. Chang,
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The 14th International Conference on Modulated Semiconductor structures (MSS-14), 2011, Florida, USA
J.-Y. Lu, H. Y. Chou, J. C. Wu, S. Y. Wei, and Y. H. Chang,
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The 16th International Conference on Superlattices, Nanostructures and Nanodevices, 2010, Beijing, China
J.-Y. Lu and Y. H. Chang,
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The 9th International Conference on Physics of Light-Matter Coupling in Nanostructures, 2009, Leece, Italy
Research Notes
These notes sit between the publication list and the teaching modules. They emphasize how physical models are formulated,
validated, and translated into defensible computational workflows for materials, devices, and engineered structures.
Effective Medium Theory and Composite Response
Notes on homogenization, Maxwell–Garnett theory, Bergman spectral representation, and the interpretation of microstructure-dependent effective response in heterogeneous media.
This stream also includes revisiting classical formulations beyond the basic dipolar Maxwell–Garnett limit, including PRB 1992-type treatments of interaction effects, spectral response, and the physically meaningful reconstruction of published composite-medium results.
First-Principles Modeling and Materials Discovery
Notes on DFT-based workflows, descriptor selection, structure–property mapping, and physically grounded strategies for computational materials screening and accelerated materials discovery.
Physics-Guided AI and Inverse Design
Methodological notes on combining simulation, optimization, and machine-learning-assisted search for functional materials and engineered structures, with emphasis on interpretable design logic rather than black-box prediction alone.
Multiphysics Modeling for Functional Materials and Structures
Notes linking analytical models, finite element simulation, and engineering observables across structural, thermal, electromagnetic, and heterogeneous material systems, with attention to scale bridging and physically meaningful performance metrics.
Validation, Benchmarking, and Physical Interpretation
Notes on model validation, convergence assessment, analytical benchmarking, code verification, and physics-based interpretation across electromagnetic, mechanical, and atomistic simulation workflows.
FDTD-Ready Optical Material Fitting Database
This section provides access to a searchable database of compact optical material models for time-domain electromagnetic simulation.
The current release contains precomputed rational-pole (RP) and critical-point (CP) dielectric-function fits to experimental optical-constant records.
The models are generated through an automated fitting procedure and are reported with explicit passivity, stability, and fitting-quality information.
The exported model files are provided in the Tidy3D PoleResidue JSON format for practical FDTD workflows.
Recommended models are selected from candidates that pass the database production gates, including passivity screening and a final time-domain amplification-matrix stability audit.
These checks are intended to avoid nonphysical gain and unstable dispersive updates within the fitted wavelength range.
Database Scope
The current release contains 60 material labels and 405 source-specific optical-constant records. Each record is converted into its own fitting grid and treated independently, so data from different literature sources are not mixed.
Model Families
The workflow uses two pole-based representations: RP models and CP models. Automated fitting and refinement are performed over N = 1–5 pole pairs, giving 6075 candidate model rows in the current release.
FDTD Readiness
The current database contains 3991 exported model files. Final recommendations are available for 402 of 405 source-specific records after passivity, export, and time-domain stability checks.
Current record-specific visible–near-IR release
Materials60
Source-specific records405
Candidate model rows6075
Exported model files3991
Recommended records402 / 405
Materials with recommendation60 / 60
Full 0.3–1.1 µm records274 / 405
Partial-window records131 / 405
How ε-RMS is computed.
For each source-specific record, the experimental optical constants are first converted to a complex dielectric function,
εexp(λ) = [n(λ) + i k(λ)]2. The fitted model gives εfit(λ) on the same fitting grid.
The reported dimensionless error is
ε-RMS = sqrt(mean(|εfit − εexp|2 / (|εexp|2 + 10−12))).
This is a relative RMS error of the complex dielectric function, not a direct RMS of n or k alone.
Recommended ε-RMS ≤ 10−3
56 / 402
Recommended ε-RMS ≤ 5×10−3
241 / 402
Recommended ε-RMS ≤ 10−2
283 / 402
Recommended ε-RMS > 5×10−2
37 / 402
The RMS statistics above use the final recommended model for each source-specific record, so the denominator is 402 rather than the 3991 exported model files.
A value of ε-RMS ≤ 10−2 means that the fitted complex dielectric function has an average relative RMS error below approximately 1% on the fitting grid.
This usually indicates that the fitted dielectric response is visually close to the experimental ε(λ) over the fitted wavelength range, but it does not imply that the maximum pointwise error is below 1% at every wavelength.
Records with sharp interband features, metallic free-carrier response, narrow wavelength coverage, or strong source-specific structure should still be checked in the online plots before use.
The wavelength window is record-specific. Of the 405 source-specific records, 274 cover approximately the full 0.3–1.1 µm visible–near-IR window, while 131 cover only the available subset of that range.
Three records have no recommended exported model in the current release.
For questions, corrections, or suggestions, please contact
jinyoulu@ntu.edu.tw.
Current release: precomputed RP/CP optical material fits with record-specific visible–near-IR wavelength coverage. Last updated: May 2026.
THANK YOU ALL!
My beloved family
Thank you for all the supports during my postdoc career:
Prof. TieJun Zhang, Khalifa University
Prof. Daniel Choi, Khalifa University
Prof. Matteo Chiesa, Khalifa University
Prof. Ibraheem Almansouri, Abu Dhabi Future Energy Company
Prof. Nicholas Xuanlai Fang, MIT
Prof. Gang Chen, MIT
Prof. Thomas C.-K, Yang, National Taipei University of Technology
Prof. Weilin Yang, Jiangnan University
Dr. Aikifa Raza, Khalifa University
Dr. Hongxia Li, Khalifa University
Dr. Srinivasa Reddy Tamalampudi, Khalifa University
Dr. Nitul S Rajput, Khalifa University
Dr. Shih-Wen Chen, National Taipei University of Technology
Mr. Boulos Fakes, Khalifa University
Mr. Abdulrahman Al-Hagri, Khalifa University
Ms Chia-Yun Lai, Khalifa University
Ms Mariam Ali Almahri, Khalifa University
Mr. Harry Apostoleris, Khalifa University
Mr. Yu-Cheng Chiou, UiT
Mr. Cheng-Hsiang Chiu, UiT
Ms Shabnam Ranny, Aspen Heights School
Thank you for the supports during my PhD:
Prof. Yuan-Huei Chang, my PhD advisor
Prof. Chi-Te Liang, Nationa Taiwan University
Prof. Yang-Fang Chen, National Taiwan University
Prof. Kuo-PIn Chiu, CYCU
Prof. Chih-Ming Wang, NCU
Prof. Din-Pin Tsai, Academia Sinica
Prof. Wei Chih Liu, NTNU
Dr. Husan-Yi Chao, SCIENTEK
Dr. Hung-Ji Huang, Instrument Technology Research Center
Dr. Ryan Cheng, senior member at my lab
Thank you for the supports during my career at TSMC:
Dr. Lu-Hsing Tsai, TSMC
Dr. Chung-Liang Cheng, TSMC
Mr. Wilson Liu, ASML
Ms. Ya-Ling Huang, TSMC
Mr. Che-Chih Hsu, TSMC
Dr. San-Yi Huang, TSMC
Dr. Ju-Ying Chen, TSMC
Teaching & Technical Tutorials
This section collects selected teaching modules and technical tutorials in computational mechanics,
computational electromagnetics, scientific computing, and materials modeling.