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Photonics
Special Issues
Optical Displays: Materials, Devices and Systems
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Optical Displays: Materials, Devices and Systems

A special issue of Photonics (ISSN 2304-6732). This special issue belongs to the section "Optoelectronics and Optical Materials".

Deadline for manuscript submissions: 31 October 2026 | Viewed by 399

Special Issue Editors

Dr. Haiyan Bai

E-Mail Website
Guest Editor
School of Artificial Intelligence Optics and Electronics (iOPEN), Northwestern Polytechnical University, Xi’an 710072, China
Interests: CDs; fluorescence; LED; wavelength regulation; QY; materials genome engineering
Dr. Liu Ding

E-Mail Website
Guest Editor
School of Material Science and Engineering, Shaanxi University of Technology, Hanzhong 723000, China
Interests: carbon dots; aggregation-induced emission; room-temperature phosphorescence; thermally activated delayed fluorescence; advanced dynamic anti-counterfeiting encryption; luminescence mechanisms
Prof. Dr. In-Hwan Lee

E-Mail Website
Guest Editor
Department of Materials Science and Engineering, Korea University, Seoul 02841, Republic of Korea
Interests: photocatalysis; water splitting; display; micro-/nano-LED; exploration of novel properties from optoelectronic materials by using nanotechnology
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Optical Displays aims to provide a premier interdisciplinary platform for showing cutting-edge research and comprehensive reviews in the rapidly evolving field of optical display technology. We seek to bridge the gap between fundamental material innovation, device engineering and full-system integration, fostering dialogue that accelerates the development of next-generation displays for applications ranging from consumer electronics to healthcare and beyond.

 This Special Issue on ‘Optical Displays: Materials, Devices and Systems’ will welcome contributions covering the entire spectrum of display technology. Topics of interest include, but are not limited to:

  • Novel luminescent materials (e.g., Quantum Dots, perovskites, OLED/QLED emitters, phosphors, fluorescent carbon dots).
  • Advanced liquid crystals (e.g., blue-phase, ferroelectric and liquid crystal-based devices) and electro-optic materials.
  • Emerging display concepts (Micro-LED, AR/VR near-eye displays, holographic displays, flexible and transparent displays).
  • Device physics, fabrication processes and performance optimization (efficiency, longevity, colour gamut).
  • System integration, driving schemes, human-factor engineering and novel applications.

We invite researchers, engineers and industry leaders to submit original work and join us in shaping the future of visual technology. Share your insights and be a part of this dynamic discourse.

Dr. Haiyan Bai
Dr. Liu Ding
Prof. Dr. In-Hwan Lee
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Photonics is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • display technologies
  • luminescent materials
  • quantum dots
  • OLED
  • micro-LED
  • liquid crystals
  • AR/VR
  • device engineering
  • human–computer interactions
  • solid-state lighting

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Published Papers (1 paper)

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Research

20 pages, 18964 KB  
Article
Reliability Prediction of TFT-LCD Modules in Harsh Environments Using Physics-Guided Machine Learning
by Rui Zhou, Han Li, Xiaoqin Wei, Haitao Zhu, Xu Zhou, Xiaojie Li, Rihui Yao, Wei Xu, Honglong Ning and Junbiao Peng
Photonics 2026, 13(6), 568; https://doi.org/10.3390/photonics13060568 - 10 Jun 2026
Viewed by 123
Abstract
Accurate Remaining Useful Life (RUL) prediction of TFT-LCD modules is critical for industrial predictive maintenance, yet it remains heavily challenged by complex degradation mechanisms in different climates. Traditional purely data-driven models (SVR, LSTM) often lack physical interpretability, struggling to filter out environmental noise [...] Read more.
Accurate Remaining Useful Life (RUL) prediction of TFT-LCD modules is critical for industrial predictive maintenance, yet it remains heavily challenged by complex degradation mechanisms in different climates. Traditional purely data-driven models (SVR, LSTM) often lack physical interpretability, struggling to filter out environmental noise or predict irreversible failures. To address this, we propose a highly reliable prognostic tool based on a Physics-Informed Gaussian Process Regression (PI-GPR) framework, by embedding cumulative thermal load and thermo-mechanical stress into the model’s prior function. Evaluated using one-year field exposure data, the physical constraints empower the model to accurately predict device lifetime under highly variable environments, including luminance fluctuations in tropical hygrothermal conditions and device failures in cold environments. Quantitative results demonstrate that the unified PI-GPR framework achieves an outstanding coefficient of determination (R2 = 0.93) and reduces the RUL prediction error to merely 7.5 days, significantly outperforming conventional shallow learning, deep sequence, and standard probabilistic baselines. Ultimately, this study provides a robust, physically grounded methodology for the health monitoring and life cycle management of display modules in practical industrial applications. Full article
(This article belongs to the Special Issue Optical Displays: Materials, Devices and Systems)
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